repo
stringlengths 8
116
| tasks
stringlengths 8
117
| titles
stringlengths 17
302
| dependencies
stringlengths 5
372k
| readme
stringlengths 5
4.26k
| __index_level_0__
int64 0
4.36k
|
|---|---|---|---|---|---|
philip-mueller/equivariant-deep-dmri | ['lesion segmentation'] | ['Rotation-Equivariant Deep Learning for Diffusion MRI'] | equideepdmri/layers/layer_builders.py equideepdmri/layers/filter/angular_basis_filters.py equideepdmri/layers/BatchNormalization.py equideepdmri/layers/filter/radial_basis_functions.py equideepdmri/layers/filter/radial_basis_filters.py equideepdmri/layers/EquivariantPQLayer.py equideepdmri/layers/Recomputeable.py equideepdmri/layers/filter/filter_kernel.py equideepdmri/layers/filter/utils.py equideepdmri/layers/QLengthWeightedPool.py equideepdmri/utils/q_space.py example/utils.py setup.py equideepdmri/utils/spherical_tensor.py equideepdmri/layers/filter/kernel_builders.py equideepdmri/network/VoxelWiseSegmentationNetwork.py equideepdmri/layers/filter/combined_filter_kernels.py BatchNorm EquivariantPQLayer EquivariantPLayer build_q_reduction_layer build_pq_layer build_p_layer GatedBlockNonLin build_non_linearity QLengthWeightedAvgPool Recomputable recompute SH_Q_AngularKernelConstructor TP_AngularKernel SH_PQDiff_AngularKernelConstructor SH_P_AngularKernel AngularKernelBasis TP_AngularKernelConstructor compute_Q_diff_vectors SH_PQDiff_AngularKernel SH_Q_AngularKernel SH_P_AngularKernelConstructor SumKernel ConcatKernel Kernel compute_TP_mixing_matrix_for_filter mul_scalar_angular_kernel find_filter_type build_q_space_kernel build_q_radial_basis_constructor build_tp_kernel _is_sum_kernel_definition build_kernel_from_definition_name SumKernelDefinition _prepare_sub_kernel_selection_rule build_concat_kernel KernelDefinition build_p_radial_basis_constructor _is_concat_kernel_definition build_p_space_kernel build_sum_kernel build_kernel ConcatKernelDefinition build_diff_kernel RadialKernelBasis LengthQIn_RadialKernelBasis CombinedRadialKernelBasis LengthQOut_RadialKernelBasis LengthPDiff_ScalarKernelConstructor LengthPDiff_RadialKernelBasis LengthQOut_ScalarKernelConstructor CombinedScalarKernelConstructor Constant_RadialKernelBasis LengthQIn_ScalarKernelConstructor Cosine_RadialBasis FiniteElement_RadialBasis Cosine_RadialBasisConstructor build_radial_basis_constructor RadialBasis gaussian_basis_fn cosine_basis_fn Bessel_RadialBasisConstructor Gaussian_RadialBasisConstructor Bessel_RadialBasis FC Gaussian_RadialBasis compute_channel_mapping_matrix compute_angular_mapping_tensor selection_rule predefined_selection_rule tensor_product_in_out eye_3d predefined_selection_rule_out selection_rule_out normalized_sh normalize_sh selection_rule_out_fn get_scalar_non_linearity selection_rule_fn tensor_product_out VoxelWiseSegmentationNetwork checkpoint Q_SamplingSchema SphericalTensorType SphericalTensor compute_binary_label_weights RandomDMriSegmentationDataset from_multiplicities_or_type EquivariantPQLayer Rs build_non_linearity BatchNorm pop from_multiplicities_or_type GatedBlockNonLin Rs from_multiplicities_or_type get_scalar_non_linearity isinstance kernel_fn_2 reshape size kernel_fn_1 kernel_mask check_validity from_ls dim tensor_product_out einsum norm reshape size expand normalized_sh dim norm view reshape size normalized_sh compute_Q_diff_vectors dim norm view size normalized_sh compute_Q_diff_vectors unsqueeze q_vectors normalize size new_empty view append selection_rule Rs T selection_rule SparseTensor reshape sort Rs t C_l sparse_reshape repeat simplify dim append wigner_3j SH_PQDiff_AngularKernelConstructor LengthQIn_ScalarKernelConstructor CombinedScalarKernelConstructor LengthQOut_ScalarKernelConstructor build_q_radial_basis_constructor LengthPDiff_ScalarKernelConstructor build_p_radial_basis_constructor SH_Q_AngularKernelConstructor TP_AngularKernelConstructor _prepare_sub_kernel_selection_rule LengthQIn_ScalarKernelConstructor CombinedScalarKernelConstructor LengthQOut_ScalarKernelConstructor build_q_radial_basis_constructor LengthPDiff_ScalarKernelConstructor build_p_radial_basis_constructor SH_P_AngularKernelConstructor selection_rule_out predefined_selection_rule_out all isinstance LengthPDiff_ScalarKernelConstructor build_p_radial_basis_constructor SH_P_AngularKernelConstructor SH_Q_AngularKernelConstructor CombinedScalarKernelConstructor LengthQOut_ScalarKernelConstructor build_q_radial_basis_constructor LengthQIn_ScalarKernelConstructor selection_rule predefined_selection_rule all isinstance KernelDefinition split list map iter append split _is_sum_kernel_definition _is_concat_kernel_definition isinstance build_radial_basis_constructor build_radial_basis_constructor partial linspace get_scalar_non_linearity partial linspace get_scalar_non_linearity tensor_product from_Rs reshape Rs dim tensor_product selection_rule defaultdict Rs add set iter from_ls multiplicities C zeros dim range enumerate multiplicities eye_3d from_multiplicities zip zeros dim range enumerate ones pi sqrt dim diag cat ls size from_ls sh list min filter abs range min max pop list all ones tuple bool enumerate | # Rotation-Equivariant Deep Learning for Diffusion MRI [[arXiv:2102.06942 - Rotation-Equivariant Deep Learning for Diffusion MRI](https://arxiv.org/abs/2102.06942)] Rotationally and translationally equivariant layers and networks for deep learning on diffusion MRI (dMRI) scans. In this paper we showed that adding rotational equivariance to CNNs can improve the performance on prediction tasks on dMRI scans. By publishing our code, we want to enable anyone to profit from the benefits of equivariance as our layers can be used off the shelf without understanding the mathematical background. So feel free to try our layers as a drop-in replacement of 3D CNN layers in any CNN architecture for dMRI. Note that you should not use common nonlinearities (like ReLU) in combination with them, but use the provided nonlinearities (i.e. gated nonlinearities). It might also hurt the performance to mix our roto-translationally equivariant layers with normal 3D CNN layers. If you plan to mix them, we propose to use our equivariant layers (with gated nonlinearities) as the first | 3,300 |
philippe554/MANN | ['one shot learning'] | ['One-shot Learning with Memory-Augmented Neural Networks'] | src/MANN/Head/DNCHead.py src/DataGen/VertexCover.py src/GraphPlot.py src/RNN/LSTMCell.py src/MANN/Head/LRUAHead.py src/MANN/Memory/ASymZeroMemory.py src/DataGen/MinPath.py src/MANN/Memory/WeightMemory.py src/MANN/Memory/ZeroMemory.py src/DataGen/Data.py src/DataGen/DataGenBase.py src/MANN/Head/HeadBase.py src/mann.py src/MANN/MANNUnit.py src/RNN/FFCell.py src/helper.py src/DataGen/Copy.py src/Logging/epochLogger.py src/RNN/RNNBase.py src/RNN/GRUCell.py src/main.py src/MANN/Head/NTMHead.py src/MANN/Memory/MemoryBase.py genGraph check map strfixedFloat printStats getBatchWeight progress strfixed Copy Data DataGenBase MinPath getPathLength genGraph VertexCover epochLogger MANNUnit DNCHead HeadBase LRUAHead NTMHead ASymZeroMemory MemoryBase WeightMemory ZeroMemory FFCell GRUCell LSTMCell RNNBase append randint list range check tile get_variable expand_dims len print get_shape name str enumerate int write float round flush str format append pop len | # Memory Augmented Neural Network This package allows you to make a custom Memory Augmented Neural Network (MANN) by combining different architectures proposed by different papers. It is fully modular, and can be added to any other RNN in Tensorflow. ## Features * 3 types of contollers * 2 types of heads * modular * compatible with batch training * generate random toy data to train a model ## Getting Started Packages needed: | 3,301 |
phizaz/cprop | ['stochastic optimization'] | ['CProp: Adaptive Learning Rate Scaling from Past Gradient Conformity'] | cprop/cprop_lib.py tf/cprop_tf/cprop_common.py tf/cprop_tf/cprop.py tf/setup.py cprop/__init__.py tf/cprop_tf/cprop_tf1.py setup.py cprop/cprop_adam.py cprop/cprop_universal.py cprop/test/test_update_avg.py cprop/cprop_sgd.py update CPropAdam cprop_scale_bfo cprop_scale_bft _cprop_scale cprop_se _update_avg_x best_fit_two cprop_scale_normal cprop_scale_logistic _update_avg_sq best_fit_one logistic_cdf normal_cdf cprop CPropSGD CProp scale_update CProp best_fit_one best_fit_two normal_cdf cprop CProp cprop_scale_bfo cprop_scale_bft zeros_like _update_avg_x cprop_scale_normal _update_avg_sq cprop_scale_logistic Normal sqrt mul pi sqrt normal_cdf cprop_se best_fit_two cprop_se best_fit_one cprop_se logistic_cdf cprop_se dtype best_fit_two maximum sqrt assign cast clip_by_value abs normal_cdf best_fit_one | # CProp: Adaptive Learning Rate Scaling from Past Gradient Conformity Implementation of CProp in Pytorch. [Looking for Tensorflow version?](https://github.com/phizaz/cprop/tree/master/tf) A preprint Arxiv version can be found at https://arxiv.org/abs/1912.11493. Paper is being reviewed. ## Installation Requires Python with type-hint support (I guess 3.6+). It seems to require Pytorch 1.2 due to its use of JIT. ``` # clone | 3,302 |
phuccuongngo99/Fence_GAN | ['anomaly detection'] | ['Fence GAN: Towards Better Anomaly Detection'] | utils/data.py utils/visualize.py 2D_experiment/custom_losses.py utils/model.py utils/custom_losses.py 2D_experiment/2D_fgan.py main.py fgan_train.py noise_data pretrain training_pipeline D_data set_trainability train noise_data animate real_data get_generative pretrain D_loss get_discriminative data_G data_D set_trainability train make_gan com com_conv get_cifar10 preprocess load_data get_mnist load_model D_loss get_mnist_model set_trainability get_cifar10_model compute_au show_images histogram deprocess layers noise_data list ones sample zeros range predict format batch_size print latent_dim range batch_size compute_au ano_class save dataset round open noise_data OrderedDict v_freq range predict format close latent_dim listdir show_images print makedirs write histogram evaluation epochs len seed load_model pretrain set_random_seed load_data train str T int xlabel reshape close ylabel colorbar ylim scatter contourf figure linspace title meshgrid savefig xlim predict noise_data real_data ones zeros predict noise_data zeros binary_crossentropy Model Input Model Input compile G D Model set_trainability Input compile train_on_batch set_value data_D set_trainability append sum len train_on_batch set_value animate data_G data_D set_trainability append sum float64 clip concatenate print reshape delete preprocess load_data append enumerate int asarray concatenate choice preprocess load_data array G Adam D Model set_trainability Input compile G random_normal_initializer variable Adam D Model set_trainability Input compile uint8 clip subplot format squeeze len close tight_layout imshow savefig figure deprocess xticks range yticks squeeze roc_curve precision_recall_curve predict auc normal format xlabel squeeze close ylabel title hist savefig figure legend predict | # Fence GAN: Towards Better Anomaly Detection This is the official implementation of the paper: Fence GAN: Towards Better Anomaly Detection [(link)](https://arxiv.org/abs/1904.01209). ## Prerequisites 1. Linux OS 2. Python 3 3. CUDA 4. Tensorflow Version 1.12 (Tested on this version) ## Installation 1. Clone repository ``` | 3,303 |
piazzesiNiccolo/myLbc | ['autonomous driving'] | ['Learning by Cheating'] | bird_view/models/roaming.py bird_view/scripts/parse_runs.py bird_view/utils/train_utils.py misc/no_rendering_mode.py PythonAPI/agents/tools/misc.py PythonAPI/agents/navigation/controller.py bird_view/models/image.py benchmark/base_suite.py bird_view/augmenter.py bird_view/models/birdview.py data_collector.py bird_view/models/controller.py training/train_birdview.py bird_view/utils/bz_utils/gif_maker.py view_benchmark_results.py PythonAPI/agents/navigation/agent.py bird_view/models/factory.py misc/dynamic_weather.py bird_view/models/baseline.py misc/find_traffic_violations.py benchmark/goal_suite.py bird_view/utils/image_utils.py PythonAPI/agents/navigation/global_route_planner.py training/train_image_phase0.py training/train_image_phase1.py misc/manual_control.py bird_view/utils/bz_utils/test.py benchmark/run_benchmark.py PythonAPI/agents/navigation/global_route_planner_dao.py bird_view/models/common.py training/phase2_utils.py bird_view/utils/logger.py bird_view/scripts/tune_pid.py bird_view/utils/bz_utils/optimizer.py PythonAPI/agents/navigation/test_global_route_planner.py misc/tutorial.py bird_view/utils/bz_utils/__init__.py bird_view/utils/bz_utils/plotter.py bird_view/utils/bz_utils/saver.py bird_view/utils/datasets/birdview_lmdb.py PythonAPI/agents/navigation/roaming_agent.py bird_view/utils/carla_utils.py bird_view/utils/datasets/image_lmdb.py misc/spawn_npc.py bird_view/utils/datasets/__init__.py bird_view/utils/map_utils.py bird_view/utils/no_rendering_mode.py misc/automatic_control.py benchmark_agent.py bird_view/models/resnet.py misc/vehicle_gallery.py benchmark/__init__.py PythonAPI/agents/navigation/local_planner.py training/train_image_phase2.py bird_view/models/attack.py bird_view/utils/bz_utils/video_maker.py misc/synchronous_mode.py bird_view/models/agent.py __init__.py PythonAPI/agents/navigation/basic_agent.py _debug main NoisyAgent get_episode main BaseSuite PointGoalSuite from_file run_single run_benchmark _paint _add make_suite get_suites soft medium soft_harder super_hard high medium_harder custom Agent load_model load_spatial load_hopskip load_bim load_attack load_newton BaselineAgent BaselineBranch Baseline regression_base BirdViewAgent BirdViewPolicyModelSS spatial_softmax_base ResnetBase NormalizeV2 select_branch make_arc SpatialSoftmaxBZ SpatialSoftmax project_point_to_circle signed_angle Normalize crop_birdview ls_circle CustomController PIDController get_model ImageAgent ImagePolicyModelSS conv1x1 ResNet Bottleneck conv3x3 get_resnet BasicBlock RoamingAgentMine main world_loop TrafficTracker set_sync_mode carla_img_to_np PedestrianTracker visualize_birdview is_within_distance_ahead get_birdview process CarlaWrapper visualize_predicted_birdview draw_msra_gaussian gaussian_radius Wrapper _preprocess_image _format MapImage get_actor_display_name ModuleHUD TrafficLightSurfaces ModuleManager ModuleWorld FadingText HelpText Wrapper ModuleInput Util MapImage get_actor_display_name ModuleHUD TrafficLightSurfaces ModuleManager ModuleWorld FadingText HelpText Wrapper ModuleInput Util SummaryWriter one_hot viz_birdview_pred viz_image_pred UnNormalize Dummy Experiment _preprocess_image _format show _create_writer Dummy load_json BirdViewDataset Wrap world_to_pixel BiasedBirdViewDataset _dataloader load_birdview_data get_birdview get_image project_to_image Wrap load_image_data world_to_pixel _dataloader ImageDataset FadingText LaneInvasionSensor game_loop find_weather_presets get_actor_display_name CollisionSensor main CameraManager HUD KeyboardControl HelpText World Weather clamp Sun main Storm parse get_town Vector2 get_collision main FadingText LaneInvasionSensor GnssSensor game_loop find_weather_presets get_actor_display_name CollisionSensor main CameraManager HUD KeyboardControl HelpText World MapImage game_loop get_actor_display_name ModuleHUD TrafficLightSurfaces ModuleManager ModuleWorld exit_game FadingText main HelpText ModuleInput Util main main should_quit get_font draw_image main main get_transform Agent AgentState BasicAgent PIDLateralController PIDLongitudinalController VehiclePIDController GlobalRoutePlanner GlobalRoutePlannerDAO _retrieve_options LocalPlanner RoadOption LocalPlannerNew LocalPlannerOld _compute_connection RoamingAgent suite Test_GlobalRoutePlanner vector distance_vehicle compute_yaw_difference get_speed draw_waypoints is_within_distance_ahead compute_magnitude_angle weighted_random_choice load_image_model ReplayBuffer get_weight CoordConverter repeat _log_visuals LocationLoss load_birdview_model get_optimizer train _log_visuals LocationLoss train_or_eval train_or_eval CoordConverter _log_visuals LocationLoss train train_or_eval CoordConverter _log_visuals LocationLoss repeat train get_control _train rollout crop_birdview train get join int norm _dot _write _stick_together copy visualize_birdview dot show_image crop_birdview process array set_route run_step frame_skip frames_per_episode tick list location append process range update _debug debug close get_observations init tqdm apply_control NoisyAgent list n_episodes print tqdm dataset_path mkdir Path range items sorted table name glob search group dict DoubleTable zip append array read_csv parent split get int norm _write brake _stick_together add_to_video copy visualize_birdview steer throttle dot show_image crop_birdview array _tick visualize_predicted_birdview set_route total_lights run_step _paint _tick tick list location append agent_maker debug get_observations init pop total_lights_ran collided is_success _player apply_control str list run_single print to_csv tqdm all_tasks init_video mkdir append DataFrame read_csv len Sequential float min float Sequential float Sequential float Sequential float Sequential Sequential float min float Sequential load join model_class Adam parameters load_state_dict PyTorchClassifier ImagePolicyModelSS load_json CrossEntropyLoss size stack enumerate dot norm acos norm arctan2 cos project_point_to_circle linspace sin solve mean sqrt sum array len print ResNet load_url load_state_dict seed pop plot len world_loop uniform savefig ion cla norm acos degrees dot array get_settings apply_settings get_world reshape convert raw_data Raw frombuffer concatenate dict float32 copy concatenate zeros range len int exp arange maximum float32 sqrt requires_grad make_grid isinstance unsqueeze Tensor numpy detach append items list isinstance join scatter_ clamp zero_ FloatTensor int unnormalizer clone enumerate int enumerate dict transpose imshow waitKey cvtColor COLOR_BGR2RGB dataset_cls make_dataset tan projectPoints pi zeros array clip ImageDataset make_dataset compile get_world port run_step set_destination KeyboardControl host HWSURFACE tick render width DOUBLEBUF set_mode World height Client Clock init RoamingAgent BasicAgent flip vehicle apply_control parse_events HUD set_timeout basicConfig add_argument game_loop port ArgumentParser info host parse_args Weather str get_weather weather get_world set_weather speed write Client set_timeout wait_for_tick flush tick cross show list plot debug Vector2 get_collision append array range len append list array split parse iterrows parent get_town to_csv sum tick_busy_loop autopilot filter start_modules set_caption ModuleHUD blit description register_module Font get_default_font ModuleWorld ModuleInput get_rect clear_modules exit quit description number_of_vehicles sleep get_spawn_points shuffle safe choice delay filter try_spawn_random_vehicle_at reshape raw_data make_surface blit swapaxes frombuffer match_font get listen Transform get_blueprint_library get_waypoint put apply_settings location get_font render next get frame_count get_settings Clock Queue init Location set_transform transform Rotation get_fps set_simulate_physics get_map spawn_actor find try_spawn_actor get_location set_location recommended_values set_autopilot type_id LogarithmicDepth set_attribute radians Location cos sin get_spectator get_transform append _compute_connection yaw addTest TestSuite Test_GlobalRoutePlanner radians draw_arrow location yaw transform Location get_velocity acos degrees dot array clip norm acos degrees dot array location y x norm y x z LongTensor size dim is_cuda cat mean device to sum max cumsum sum Adam load to load_state_dict get list _dot _write min copy visualize_birdview item append sum range load to load_state_dict time criterion backward to zero_grad close tqdm mean dict eval _log_visuals image item train step net scalar enumerate LocationLoss Path save str list train_or_eval end_epoch Adam load_state_dict to range state_dict save_config glob init load print tqdm parameters load_data _img_size coord_converter load_config eval CoordConverter Normal tensor view size clamp repeat list add_data tqdm keys array range len get_weight zero_grad Normal DataLoader _log_visuals image normalize_weights save Path tensor str view end_epoch Adam update_weights range init_new_weights state_dict size chunk mean eval stack _img_size item float net enumerate criterion backward print clamp coord_converter get_highest_k dict parameters repeat train step scalar load_image_model ReplayBuffer _train rollout log load_birdview_model | # Learning by Cheating and Adversarial Robustness Toolbox This repo is a custom version of the [LearningByCheating](https://github.com/dianchen96/LearningByCheating) autonomous driving agent and related suite, which has been integrated with the IBM Adversarial Robustness Toolbox ([ART](https://adversarial-robustness-toolbox.readthedocs.io/en/latest/)) for the injection of 4 attacks on the RGB camera: • Spatial Transformation ([STA](https://adversarial-robustness-toolbox.readthedocs.io/en/latest/modules/attacks/evasion.html#spatial-transformations-attack)), • HopSkipJump ([HSJ](https://adversarial-robustness-toolbox.readthedocs.io/en/latest/modules/attacks/evasion.html#hopskipjump-attack)), • Basic Iterative Method ([BIM](https://adversarial-robustness-toolbox.readthedocs.io/en/latest/modules/attacks/evasion.html#basic-iterative-method-bim)), • NewtonFool ([NF](https://adversarial-robustness-toolbox.readthedocs.io/en/latest/modules/attacks/evasion.html#newtonfool)). # Summary For my Bachelor Thesis in Computer Science at the University of Florence, I injected some adversarial attacks inside the images extracted by the RGB camera, before these are fed to the Learning By Cheating trained agent. The objective is to visualize theeffects of these attacks on the trained agents. The attacks injected were provided by the Adversarial Robustness Toolbox ([ART](https://adversarial-robustness-toolbox.readthedocs.io/en/latest/)) library (version 1.2.0). This repo contains the modified LbC agent that I used to test the attacks. You can see the tests results and the videos recorded for the various runs [here](https://drive.google.com/drive/folders/1tTEAQSK2XAK_sdmuWo80Bd-58_pkiK3h?usp=sharing). The following table summarizes results recorded in the regular suite | 3,304 |
pillowlab/gaudy-images | ['active learning'] | ['High-contrast “gaudy” images improve the training of deep neural network models of visual cortex'] | fig2/3layerconvnet_relu/class_model.py fig3/class_features.py fig2/3layerconvnet_sigmoid/class_random_selection.py fig4/class_largebank_normal_only.py fig1/script_train_models.py fig1/class_images.py fig2/3layerconvnet_sigmoid/script_train_model.py fig4/class_model_ensemble.py fig5/class_data.py fig1/class_sigmoid_model.py fig2/3layerconvnet_sigmoid/class_model.py fig1/class_gaudi_images.py fig2/3layerconvnet_relu/class_features.py fig2/3layer_convnet_linear/class_gaudi.py fig2/identify_100_neurons_each_pretrained_cnn/class_features.py fig2/3layerconvnet_relu/class_gaudi.py fig3/class_images.py fig3/class_model.py fig3/script_smoothe_after_gaudi.py fig4/class_synthetic_normal.py fig4/script_num_ensemble_networks.py fig4/script_test_AL_algorithm_long_run.py fig2/3layerconvnet_relu/class_images.py fig2/3layer_convnet_linear/get_figs.py fig1/class_gabor_responses.py fig2/3layerconvnet_sigmoid/class_gaudi.py fig2/3layerconvnet_sigmoid/get_figs.py fig1/class_relu_model.py fig4/class_surrogate_responses.py fig4/script_test_AL_algorithms.py fig5/class_images.py fig2/3layer_convnet_linear/script_train_model.py fig2/3layer_convnet_linear/class_random_selection.py fig1/script_obj_function_normal_vs_gaudy.py fig4/class_synthetic_gaudi.py fig5/class_features.py fig2/identify_100_neurons_each_pretrained_cnn/script_variance_all_neurons.py fig2/3layerconvnet_relu/class_surrogate_responses.py fig4/class_features.py fig3/script_change_pixels_far_from_edges.py fig3/script_smoothe_before_gaudi.py fig2/3layerconvnet_relu/class_random_selection.py fig2/3layer_convnet_linear/class_images.py fig2/3layerconvnet_relu/get_figs.py fig1/class_random_selection.py fig5/script_partition_gaudylike_images.py fig2/3layer_convnet_linear/class_features.py fig1/get_figs.py fig2/identify_100_neurons_each_pretrained_cnn/script_save_models_with_100neurons_output.py fig3/script_change_pixels_near_edges.py fig2/3layerconvnet_relu/script_train_model.py fig3/script_pca_on_vgg_responses.py fig5/class_model_archived.py fig5/script_train_model.py fig3/class_surrogate_responses.py fig2/3layerconvnet_sigmoid/class_images.py fig4/class_images.py fig1/class_linear_model.py fig2/3layer_convnet_linear/class_model.py fig2/3layerconvnet_sigmoid/class_surrogate_responses.py fig4/class_coreset_normal.py fig2/identify_100_neurons_each_pretrained_cnn/class_images.py fig4/class_largebank_gaudi_and_normal.py fig2/3layerconvnet_sigmoid/class_features.py fig2/3layer_convnet_linear/class_surrogate_responses.py fig4/class_coreset_gaudy.py fig4/class_largebank_gaudi_only.py fig4/class_random_selection.py fig4/get_figs.py fig4/class_gaudi.py fig3/class_model_sigmoid.py fig3/class_random_selection.py fig3/class_gaudi.py GaborResponsesClass GaudiImageClass ImageClass LinearModel RandomSelectionClass ReluModel SigmoidModel get_test_set run_model ResnetFeaturesClass GaudiSelectionClass ImageClass ModelEnsembleClass RandomSelection SurrogateResponsesClass get_initial_train_set plot_images get_test_set run_model plot_pcs plot_errornorm_histograms ResnetFeaturesClass GaudiSelectionClass ImageClass ModelEnsembleClass RandomSelection SurrogateResponsesClass get_initial_train_set plot_images get_test_set run_model plot_pcs plot_errornorm_histograms ResnetFeaturesClass GaudiSelectionClass ImageClass ModelEnsembleClass RandomSelection SurrogateResponsesClass get_initial_train_set plot_images get_test_set run_model plot_pcs plot_errornorm_histograms FeaturesClass ImageClass ResnetFeaturesClass GaudiSelectionClass ImageClass ModelEnsembleClass ModelEnsembleClass RandomSelection SurrogateResponsesClass get_test_set transform_image_to_far_from_edges run_model get_test_set transform_image_to_near_edges run_model get_test_set run_model transform_image_to_smoothe_after get_test_set transform_image_to_smoothe_before run_model CoresetGaudyClass CoresetNormalClass ResnetFeaturesClass GaudiSelectionClass ImageClass LargebankGaudiNormalClass LargebankGaudiOnlyClass LargebankNormalOnlyClass ModelEnsembleClass RandomSelection SurrogateResponsesClass SyntheticGaudiClass SyntheticNormalClass get_test_set get_initial_train_set run_model get_test_set get_initial_train_set run_model get_test_set get_initial_train_set run_model DataClass ResnetFeaturesClass ImageClass ModelClass get_inds_normal get_gaudy_metrics get_random_natural_images get_responses_from_imgs train_model str get_responses_from_imgs format asarray print compute_frac_var save get_images_to_show range append get_features_from_imgs get_random_natural_images get_responses_from_imgs get_features_from_imgs subplot str format axis argsort imshow title savefig figure subplot T str plot xlabel explained_variance_ PCA ylabel title savefig figure legend fit str xlabel ylabel hist savefig figure legend plot_images get_features_from_imgs close sqrt get_predicted_ensemble_responses plot_pcs sum train_models plot_errornorm_histograms compute_corr get_images_to_show_far_from_edges sum print size copy range mean quantile hypot sobel clip gaussian_filter get_images_to_show_near_edges sum print size copy range mean quantile hypot sobel clip gaussian_filter get_images_to_show_smoothing_after_gaudi int mean gaussian_filter copy get_images_to_show_smoothing_before_gaudi mean gaussian_filter copy save_models axis subplot imshow savefig astype figure mean range append copy permutation | # gaudy-images This is the repository code for "High-contrast 'gaudy' images improve the training of deep neural network models of visual cortex" by Cowley and Pillow, NeurIPS 2020. Link to paper: <a href="https://proceedings.neurips.cc//paper/2020/hash/f610a13de080fb8df6cf972fc01ad93f-Abstract.html" target="_blank">NeurIPS abstract</a> * We want to predict neural responses of higher-order visual cortex (e.g., V4, IT) from natural images. * We use a deep neural network to make this prediction, which require a *lot* of data to train accurately---data we don't have in neuroscience. * We reduce the amount of training data required by using high-contrast, binarized *gaudy images*. * Training on *gaudy images* yields better DNN prediction than training on the same number of normal images. * In our paper, we find this is because gaudy images overemphasize edges in the image. # gaudy transformation To transform a normal, colorful image into its gaudy version: | 3,305 |
pimdh/causal-confusion | ['imitation learning'] | ['Causal Confusion in Imitation Learning'] | ccil/environments/mountain_car.py ccil/imitate.py ccil/utils/policy_runner.py ccil/utils/models.py ccil/gen_data.py ccil/utils/utils.py ccil/utils/data.py ccil/intervention_policy_execution.py main gen_data run_uniform run_simple inference_step train_step print_metrics imitate main linear_regression intervention_policy_execution SoftQAlgo sample main MountainExpertCarStateEncoder MCRichDenseEnv MountainCarStateEncoder MCRichEnv MountainCarExpert random_split batch_cat TransitionDataset Batch Trajectory Subset DataLoaderRepeater GrowingArray SimplePolicy UniformMaskPolicy MLP hard_discrete_action sample_discrete_action PolicyRunner FixedMaskPolicyAgent run_fixed_mask RandomMaskPolicyAgent random_mask_from_state test_mask_to_mask_idx mask_idx_to_mask test_mask_idx_to_mask mask_to_mask_idx num_steps make MountainExpertCarStateEncoder save_path print run_num_steps from_trajectories PolicyRunner Path mkdir save MountainCarExpert parse_args add_argument gen_data ArgumentParser random_mask_from_state criterion backward step zero_grad forward forward random_mask_from_state print make print PolicyRunner run_num_episodes RandomMaskPolicyAgent make print tolist PolicyRunner FixedMaskPolicyAgent run_num_episodes mask_idx_to_mask range COMPLETED save device run list Adam to partial data_seed add_event_handler mkdir attach load items random_split run_fn print Engine DataLoaderRepeater parameters MountainCarStateEncoder imitate fit load make sorted glob print MountainCarStateEncoder iter run_fixed_mask policy_name next run intervention_policy_execution seed permutation get_state set_state tensor sum len Batch any append zeros sum cat PolicyRunner FixedMaskPolicyAgent run_num_episodes asarray arange asarray | # Causal Confusion in Imitation Learning This is the code accompanying the paper: "[Causal Confusion in Imitation Learning](https://arxiv.org/abs/1905.11979)" by Pim de Haan, Dinesh Jayaraman and Sergey Levine, published at NeurIPS 2019. See the [website](https://sites.google.com/view/causal-confusion) for a video presentation of the work. This simplified code implements the graph conditioned policy learning and intervention by policy execution for the MountainCar environment. Code for the other environments and intervention modes may be published at a later stage. For questions or comments, feel free to submit an issue. ## Dependencies Assumes machines with CUDA 10. For machine without GPU or different CUDA versions, you may need to tweak the pytorch and tensorflow dependency. | 3,306 |
piroLight/unity-ml-agent | ['unity'] | ['Unity: A General Platform for Intelligent Agents'] | ml-agents/mlagents/trainers/components/reward_signals/curiosity/model.py ml-agents-envs/mlagents_envs/communicator_objects/command_pb2.py ml-agents-envs/mlagents_envs/mock_communicator.py ml-agents-envs/mlagents_envs/communicator_objects/unity_to_external_pb2.py ml-agents-envs/mlagents_envs/communicator.py gym-unity/gym_unity/envs/__init__.py ml-agents-envs/mlagents_envs/communicator_objects/brain_parameters_pb2.py ml-agents/mlagents/trainers/learn.py ml-agents/mlagents/trainers/tests/test_sampler_class.py ml-agents/mlagents/trainers/meta_curriculum.py ml-agents/mlagents/trainers/tests/test_barracuda_converter.py ml-agents/mlagents/trainers/ppo/models.py ml-agents-envs/mlagents_envs/side_channel/raw_bytes_channel.py gym-unity/gym_unity/__init__.py utils/validate_meta_files.py ml-agents/mlagents/trainers/trainer_controller.py ml-agents/mlagents/trainers/components/bc/model.py ml-agents/mlagents/trainers/tests/test_curriculum.py ml-agents/mlagents/trainers/action_info.py ml-agents/mlagents/trainers/tests/test_ppo.py ml-agents/mlagents/tf_utils/__init__.py ml-agents/mlagents/trainers/components/reward_signals/__init__.py ml-agents-envs/setup.py ml-agents-envs/mlagents_envs/side_channel/engine_configuration_channel.py ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_output_pb2.py ml-agents/mlagents/trainers/tests/mock_brain.py ml-agents/mlagents/trainers/tests/test_bcmodule.py ml-agents/mlagents/trainers/tests/test_trainer_controller.py ml-agents/mlagents/trainers/components/reward_signals/reward_signal_factory.py ml-agents-envs/mlagents_envs/rpc_utils.py ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_initialization_output_pb2.py ml-agents/setup.py ml-agents/mlagents/trainers/barracuda.py ml-agents/mlagents/trainers/env_manager.py ml-agents/mlagents/trainers/sac/policy.py ml-agents/mlagents/trainers/ppo/trainer.py ml-agents-envs/mlagents_envs/communicator_objects/agent_action_pb2.py ml-agents-envs/mlagents_envs/tests/test_rpc_communicator.py ml-agents-envs/mlagents_envs/tests/test_envs.py ml-agents/mlagents/trainers/brain.py ml-agents-envs/mlagents_envs/side_channel/float_properties_channel.py ml-agents/mlagents/trainers/tests/test_meta_curriculum.py ml-agents/mlagents/trainers/components/reward_signals/curiosity/signal.py ml-agents/mlagents/trainers/simple_env_manager.py ml-agents-envs/mlagents_envs/exception.py ml-agents/mlagents/trainers/curriculum.py ml-agents/mlagents/trainers/tests/test_policy.py ml-agents/mlagents/trainers/ppo/policy.py ml-agents-envs/mlagents_envs/communicator_objects/unity_message_pb2.py ml-agents/mlagents/trainers/tests/test_learn.py ml-agents-envs/mlagents_envs/communicator_objects/agent_info_pb2.py ml-agents/mlagents/trainers/tests/test_demo_loader.py ml-agents-envs/mlagents_envs/communicator_objects/observation_pb2.py utils/validate_versions.py ml-agents-envs/mlagents_envs/tests/test_rpc_utils.py ml-agents/mlagents/trainers/models.py ml-agents-envs/mlagents_envs/tests/test_timers.py ml-agents/mlagents/trainers/__init__.py ml-agents-envs/mlagents_envs/communicator_objects/custom_reset_parameters_pb2.py ml-agents-envs/mlagents_envs/communicator_objects/agent_info_action_pair_pb2.py ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_input_pb2.py ml-agents-envs/mlagents_envs/timers.py ml-agents/mlagents/trainers/tests/test_simple_rl.py ml-agents/mlagents/trainers/exception.py gym-unity/gym_unity/tests/test_gym.py ml-agents/mlagents/tf_utils/tf.py ml-agents/mlagents/trainers/buffer.py ml-agents-envs/mlagents_envs/side_channel/side_channel.py ml-agents/mlagents/trainers/tests/test_subprocess_env_manager.py ml-agents/mlagents/trainers/subprocess_env_manager.py ml-agents/mlagents/trainers/tensorflow_to_barracuda.py ml-agents/mlagents/trainers/agent_processor.py ml-agents/mlagents/trainers/policy.py ml-agents-envs/mlagents_envs/communicator_objects/engine_configuration_pb2.py ml-agents/mlagents/trainers/tests/test_rl_trainer.py ml-agents-envs/mlagents_envs/rpc_communicator.py ml-agents-envs/mlagents_envs/communicator_objects/demonstration_meta_pb2.py ml-agents-envs/mlagents_envs/__init__.py gym-unity/setup.py ml-agents/mlagents/trainers/tests/__init__.py ml-agents-envs/mlagents_envs/communicator_objects/unity_output_pb2.py ml-agents-envs/mlagents_envs/communicator_objects/space_type_pb2.py ml-agents/mlagents/trainers/trainer_util.py ml-agents/mlagents/trainers/tests/test_trainer_util.py ml-agents/mlagents/trainers/components/reward_signals/extrinsic/signal.py ml-agents/mlagents/trainers/sac/trainer.py ml-agents/mlagents/trainers/sampler_class.py ml-agents/mlagents/trainers/tests/test_sac.py ml-agents/mlagents/trainers/trajectory.py ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_initialization_input_pb2.py ml-agents-envs/mlagents_envs/base_env.py ml-agents-envs/mlagents_envs/communicator_objects/header_pb2.py ml-agents/mlagents/trainers/sac/models.py ml-agents/mlagents/trainers/tests/test_stats.py ml-agents/mlagents/trainers/components/reward_signals/gail/model.py ml-agents/mlagents/trainers/rl_trainer.py ml-agents/mlagents/trainers/tests/test_reward_signals.py ml-agents/mlagents/trainers/components/reward_signals/gail/signal.py ml-agents-envs/mlagents_envs/tests/test_side_channel.py ml-agents/mlagents/trainers/ppo/multi_gpu_policy.py ml-agents/mlagents/trainers/tests/test_multigpu.py ml-agents-envs/mlagents_envs/environment.py ml-agents/mlagents/trainers/demo_loader.py ml-agents/mlagents/trainers/components/bc/module.py ml-agents-envs/mlagents_envs/communicator_objects/unity_input_pb2.py ml-agents/mlagents/trainers/tests/test_buffer.py ml-agents/mlagents/trainers/trainer.py ml-agents/mlagents/trainers/tests/test_agent_processor.py ml-agents-envs/mlagents_envs/communicator_objects/unity_to_external_pb2_grpc.py ml-agents/mlagents/trainers/brain_conversion_utils.py ml-agents/mlagents/trainers/stats.py ml-agents/mlagents/trainers/tf_policy.py ml-agents/mlagents/trainers/tests/test_trajectory.py VerifyVersionCommand UnityGymException ActionFlattener UnityEnv test_gym_wrapper test_multi_agent create_mock_group_spec test_branched_flatten setup_mock_unityenvironment test_gym_wrapper_visual create_mock_vector_step_result VerifyVersionCommand set_warnings_enabled ActionInfo AgentProcessor BarracudaWriter fuse print_known_operations compress Build sort lstm write fuse_batchnorm_weights trim mean gru Model summary Struct parse_args to_json rnn BrainInfo BrainParameters CameraResolution group_spec_to_brain_parameters step_result_to_brain_info BufferException AgentBuffer Curriculum make_demo_buffer load_demonstration demo_to_buffer EnvManager EnvironmentStep SamplerException TrainerConfigError CurriculumError TrainerError MetaCurriculumError CurriculumLoadingError CurriculumConfigError create_environment_factory CommandLineOptions create_sampler_manager parse_command_line run_training prepare_for_docker_run try_create_meta_curriculum main get_version_string MetaCurriculum EncoderType LearningModel LearningRateSchedule Policy RLTrainer MultiRangeUniformSampler UniformSampler SamplerFactory SamplerManager GaussianSampler Sampler SimpleEnvManager StatsWriter StatsSummary StatsReporter TensorboardWriter CSVWriter worker EnvironmentResponse UnityEnvWorker StepResponse SubprocessEnvManager EnvironmentCommand get_layer_shape pool_to_HW flatten sqr_diff process_layer process_model get_layer_rank slow_but_stable_topological_sort get_attr basic_lstm ModelBuilderContext order_by get_epsilon get_tensor_dtype replace_strings_in_list debug embody by_op get_tensor_dims strided_slice remove_duplicates_from_list axis_to_barracuda by_name locate_actual_output_node convert strides_to_HW get_tensor_data very_slow_but_stable_topological_sort gru TFPolicy UnityPolicyException UnityTrainerException Trainer TrainerController AgentManager TrainerFactory initialize_trainer load_config _load_config AgentExperience Trajectory SplitObservations BCModel BCModule create_reward_signal RewardSignal CuriosityModel CuriosityRewardSignal ExtrinsicRewardSignal GAILModel GAILRewardSignal PPOModel get_devices MultiGpuPPOPolicy PPOPolicy PPOTrainer get_gae discount_rewards SACPolicyNetwork SACTargetNetwork SACNetwork SACModel SACPolicy SACTrainer create_mock_pushblock_brain create_buffer simulate_rollout create_mock_3dball_brain make_brain_parameters create_mock_banana_brain setup_mock_unityenvironment create_mock_braininfo create_mock_brainparams setup_mock_env_and_brains test_agentprocessor create_mock_policy create_mock_brain test_barracuda_converter sac_dummy_config test_bcmodule_rnn_update test_bcmodule_update ppo_dummy_config test_bcmodule_constant_lr_update create_policy_with_bc_mock test_bcmodule_dc_visual_update test_bcmodule_defaults test_bcmodule_rnn_dc_update test_buffer_sample construct_fake_buffer test_num_experiences assert_array fakerandint test_buffer test_buffer_truncate test_curriculum_load_invalid_json location default_reset_parameters test_init_curriculum_bad_curriculum_raises_error test_curriculum_load_missing_file test_init_curriculum_happy_path test_increment_lesson test_curriculum_load_good test_get_config test_load_demo test_load_demo_dir basic_options test_docker_target_path test_run_training test_env_args test_commandline_args test_init_meta_curriculum_happy_path test_increment_lessons_with_reward_buff_sizes default_reset_parameters MetaCurriculumTest test_increment_lessons measure_vals reward_buff_sizes test_set_all_curriculums_to_lesson_num test_get_config test_set_lesson_nums test_init_meta_curriculum_bad_curriculum_folder_raises_error test_simple_metacurriculum more_reset_parameters test_create_model dummy_config test_average_gradients test_update basic_mock_brain test_take_action_returns_action_info_when_available basic_params test_take_action_returns_nones_on_missing_values test_take_action_returns_empty_with_no_agents test_trainer_increment_step test_trainer_update_policy test_min_visual_size test_process_trajectory test_rl_functions test_ppo_model_dc_vector_rnn test_ppo_model_cc_vector_rnn test_ppo_policy_evaluate test_ppo_model_cc_visual dummy_config test_ppo_model_dc_vector test_ppo_model_dc_visual test_ppo_get_value_estimates test_normalization test_ppo_model_cc_vector test_gail_dc_visual sac_dummy_config reward_signal_update reward_signal_eval test_extrinsic test_curiosity_cc test_gail_rnn test_gail_cc ppo_dummy_config create_policy_mock test_curiosity_dc curiosity_dummy_config test_curiosity_visual test_curiosity_rnn gail_dummy_config create_mock_all_brain_info create_rl_trainer test_clear_update_buffer dummy_config test_rl_trainer create_mock_brain create_mock_policy test_sac_update_reward_signals create_sac_policy_mock test_process_trajectory test_sac_model_dc_visual test_sac_cc_policy test_sac_visual_policy test_sac_model_cc_vector_rnn test_sac_model_dc_vector test_sac_model_cc_vector dummy_config test_sac_model_dc_vector_rnn test_sac_model_cc_visual test_sac_rnn_policy test_sac_save_load_buffer test_sac_dc_policy test_empty_samplers sampler_config_1 check_value_in_intervals incorrect_uniform_sampler test_incorrect_sampler test_sampler_config_1 sampler_config_2 incorrect_sampler_config test_incorrect_uniform_sampler test_sampler_config_2 test_simple_sac clamp test_simple_ppo Simple1DEnvironment _check_environment_trains test_tensorboard_writer test_stat_reporter_text test_stat_reporter_add_summary_write test_csv_writer mock_env_factory SubprocessEnvManagerTest MockEnvWorker test_initialization_seed test_take_step_if_not_training test_start_learning_trains_until_max_steps_then_saves basic_trainer_controller test_take_step_adds_experiences_to_trainer_and_trains trainer_controller_with_take_step_mocks trainer_controller_with_start_learning_mocks test_start_learning_trains_forever_if_no_train_model test_initialize_ppo_trainer test_handles_no_default_section test_load_config_invalid_yaml test_initialize_invalid_trainer_raises_exception dummy_bad_config dummy_config test_load_config_missing_file test_load_config_valid_yaml test_initialize_trainer_parameters_override_defaults test_raise_if_no_config_for_brain dummy_config_with_override make_fake_trajectory test_trajectory_to_agentbuffer test_split_obs np_zeros_no_float64 np_array_no_float64 _check_no_float64 np_ones_no_float64 VerifyVersionCommand StepResult ActionType AgentGroupSpec BatchedStepResult BaseEnv Communicator UnityEnvironment UnityWorkerInUseException UnityException UnityTimeOutException UnityCommunicationException UnityEnvironmentException UnityActionException MockCommunicator RpcCommunicator UnityToExternalServicerImplementation agent_group_spec_from_proto _generate_split_indices process_pixels batched_step_result_from_proto _process_vector_observation _process_visual_observation TimerNode hierarchical_timer get_timer_root get_timer_tree reset_timers set_gauge timed GaugeNode TimerStack UnityToExternalProtoServicer add_UnityToExternalProtoServicer_to_server UnityToExternalProtoStub EngineConfigurationChannel EngineConfig FloatPropertiesChannel RawBytesChannel SideChannelType SideChannel test_initialization test_reset test_returncode_to_signal_name test_close test_step test_handles_bad_filename test_rpc_communicator_checks_port_on_create test_rpc_communicator_create_multiple_workers test_rpc_communicator_close test_batched_step_result_from_proto generate_compressed_proto_obs test_agent_group_spec_from_proto test_vector_observation test_action_masking_continuous test_process_visual_observation test_action_masking_discrete_1 test_process_pixels test_action_masking_discrete test_action_masking_discrete_2 generate_compressed_data test_process_pixels_gray generate_list_agent_proto test_raw_bytes test_int_channel test_float_properties IntChannel test_timers decorated_func main set_version extract_version_string check_versions sample UnityEnv create_mock_group_spec create_mock_vector_step_result setup_mock_unityenvironment step UnityEnv create_mock_group_spec create_mock_vector_step_result setup_mock_unityenvironment step setup_mock_unityenvironment UnityEnv create_mock_group_spec create_mock_vector_step_result sample UnityEnv create_mock_group_spec create_mock_vector_step_result setup_mock_unityenvironment step tuple CONTINUOUS range DISCRETE list array range set_verbosity join isdir print replaceFilenameExtension add_argument exit verbose source_file ArgumentParser target_file sqrt topologicalSort list hasattr layers addEdge Graph print inputs set len list hasattr layers print filter match trim_model compile data layers print tensors float16 replace layers dumps data dtype layers isinstance print name tensors inputs outputs shape zip array_without_brackets to_json globals Build array_equal pool reduce Build tanh mad tanh mul Build concat add sigmoid sub mad _ tanh mul Build concat add sigmoid mad print sorted keys obs concatenate ones n_agents append zeros is_action_discrete action_mask enumerate is_action_discrete sum resequence_and_append from_agent_proto number_visual_observations vector_actions AgentBuffer append reset_agent array range enumerate make_demo_buffer load_demonstration join suffix isdir endswith isfile append listdir add_argument_group parse_args add_argument ArgumentParser start_learning target_frame_rate create_sampler_manager sampler_file_path put EngineConfig lesson load_config keep_checkpoints str docker_target_name load_model multi_gpu TrainerController save_freq trainer_config_path width quality_level run_id CSVWriter num_envs format create_environment_factory height no_graphics try_create_meta_curriculum add_writer curriculum_folder base_port env_args TrainerFactory time_scale SubprocessEnvManager train_model TensorboardWriter env_path pop SamplerManager load_config set_all_curriculums_to_lesson_num MetaCurriculum chmod format basename isdir glob copyfile copytree prepare_for_docker_run replace getLogger set_warnings_enabled setLevel seed Process append range parse_command_line debug run_training start Queue info get_version_string join print cpu randint num_runs FloatPropertiesChannel get_property_dict_copy get_timer_root reset_timers put _send_response StepResponse list set_actions _generate_all_brain_info set_property action set_configuration EngineConfigurationChannel external_brains payload items EnvironmentResponse reset step endswith len print HasField hasattr get_attr isinstance get_attr tensor_shape ndarray isinstance shape int_val bool_val float_val ListFields name ndarray isinstance str tensor_content ndarray product isinstance get_tensor_dtype print get_tensor_dims unpack int_val bool_val array float_val enter append add set Build mul sub insert Build tolist append range len locate_actual_output_node name find_tensor_by_name split locate_actual_output_node name lstm find_tensor_by_name find_forget_bias split get_layer_shape id Struct tensor get_layer_rank layer_ranks hasattr name patch_data rank input_shapes out_shapes input get_attr append replace_strings_in_list tensors embody astype op inputs zip enumerate print float32 patch_data_fn model_tensors map_ignored_layer_to_its_input co_argcount len items list hasattr get_tensors name print process_layer eval slow_but_stable_topological_sort ModelBuilderContext sort assign_ids pop range insert len layers verbose Struct process_model open print_known_operations fuse compress node GraphDef Model dims_to_barracuda_shape insert get_tensor_dims inputs MessageToJson ParseFromString cleanup_layers read memories print sort write trim summary print_supported_ops update str min_lesson_length format SACTrainer PPOTrainer copy warning brain_name get check_config rcls list_local_devices list zeros_like size reversed range append discount_rewards Mock CameraResolution Mock list ones array range brain_name pop create_buffer brain sequence_length append range vector_action_space_size resequence_and_append ones number_visual_observations shape AgentBuffer append zeros sum range enumerate len setup_mock_unityenvironment mock_env create_mock_braininfo create_mock_brainparams create_mock_brainparams create_mock_brainparams create_mock_brainparams create_mock_brainparams zeros Mock Mock create_mock_braininfo AgentProcessor range create_mock_policy add_experiences join remove _get_candidate_names convert _get_default_tempdir dirname abspath isfile next mock_env dirname abspath setup_mock_unityenvironment create_mock_braininfo create_policy_with_bc_mock close ppo_dummy_config create_mock_3dball_brain update items list close create_policy_with_bc_mock create_mock_3dball_brain update items list create_policy_with_bc_mock current_lr create_mock_3dball_brain update items list close create_policy_with_bc_mock create_mock_3dball_brain update items list close create_mock_banana_brain create_policy_with_bc_mock update items list close create_mock_banana_brain create_policy_with_bc_mock flatten list range len append range AgentBuffer resequence_and_append get_batch construct_fake_buffer assert_array make_mini_batch AgentBuffer reset_agent array resequence_and_append sample_mini_batch construct_fake_buffer AgentBuffer resequence_and_append construct_fake_buffer AgentBuffer truncate resequence_and_append construct_fake_buffer AgentBuffer Curriculum Curriculum Curriculum dumps StringIO StringIO load_demonstration demo_to_buffer dirname abspath load_demonstration demo_to_buffer dirname abspath MagicMock basic_options MagicMock parse_command_line parse_command_line MetaCurriculum assert_has_calls MetaCurriculumTest increment_lessons assert_called_with MetaCurriculumTest increment_lessons assert_called_with assert_not_called MetaCurriculumTest set_all_curriculums_to_lesson_num MetaCurriculumTest dict update MetaCurriculumTest MetaCurriculumTest Simple1DEnvironment _check_environment_trains reset_default_graph MultiGpuPPOPolicy create_mock_brainparams reset_default_graph create_mock_brainparams update Mock reset_default_graph MultiGpuPPOPolicy create_mock_brainparams MagicMock TFPolicy basic_mock_brain basic_params BrainInfo get_action MagicMock TFPolicy basic_mock_brain basic_params BrainInfo get_action MagicMock TFPolicy basic_mock_brain ActionInfo basic_params BrainInfo get_action evaluate group_spec_to_brain_parameters close get_agent_group_spec reset get_step_result MockCommunicator PPOPolicy reset_default_graph step_result_to_brain_info UnityEnvironment get_value_estimates items list next_obs to_agentbuffer make_fake_trajectory BrainParameters PPOPolicy reset_default_graph values get_batched_value_estimates reset_default_graph reset_default_graph reset_default_graph reset_default_graph reset_default_graph reset_default_graph assert_array_almost_equal array discount_rewards Mock increment_step BrainParameters assert_called_with PPOTrainer simulate_rollout update_policy policy PPOTrainer setup_mock_env_and_brains list PPOTrainer make_fake_trajectory BrainParameters process_trajectory values process_trajectory make_fake_trajectory BrainParameters zeros PPOTrainer range run update SACPolicy PPOPolicy setup_mock_env_and_brains ones reset evaluate model simulate_rollout _execute_model prepare_update update_dict make_mini_batch create_policy_mock reward_signal_update reward_signal_eval reward_signal_update reward_signal_eval create_policy_mock dirname abspath create_policy_mock reward_signal_update reward_signal_eval create_policy_mock reward_signal_update reward_signal_eval create_policy_mock reward_signal_update reward_signal_eval create_policy_mock reward_signal_update reward_signal_eval create_policy_mock reward_signal_update reward_signal_eval create_policy_mock reward_signal_update reward_signal_eval RLTrainer dummy_config create_mock_brain list create_rl_trainer end_episode episode_steps values items list construct_fake_buffer create_rl_trainer clear_update_buffer SACPolicy setup_mock_env_and_brains update evaluate create_sac_policy_mock simulate_rollout close reset reset_default_graph create_sac_policy_mock simulate_rollout close update_reward_signals reset_default_graph update evaluate create_sac_policy_mock simulate_rollout close reset reset_default_graph update evaluate create_sac_policy_mock simulate_rollout reset reset_default_graph update evaluate create_sac_policy_mock simulate_rollout close reset reset_default_graph reset_default_graph reset_default_graph reset_default_graph reset_default_graph reset_default_graph reset_default_graph str Mock SACTrainer save_model simulate_rollout num_experiences policy setup_mock_env_and_brains SACTrainer make_brain_parameters SamplerManager sample_all sampler_config_1 sampler_config_2 SamplerManager SamplerManager sample_all incorrect_uniform_sampler incorrect_sampler_config Simple1DEnvironment _check_environment_trains Simple1DEnvironment _check_environment_trains clear assert_called_once_with Mock get_stats_summaries add_stat add_writer StatsReporter float range write_stats clear Mock write_text add_writer StatsReporter assert_called_once_with TrainerController assert_called_with MagicMock start_learning assert_called_once MagicMock assert_not_called start_learning assert_called_once MagicMock MagicMock assert_called_once MagicMock EnvironmentStep advance outputs processor assert_not_called assert_called_once_with assert_called_once MagicMock EnvironmentStep advance outputs processor assert_not_called assert_called_once_with BrainParametersMock BrainParametersMock TrainerFactory BrainParameters generate TrainerFactory BrainParameters _load_config StringIO ones AgentExperience append zeros range append from_observations range ones items list to_agentbuffer add set make_fake_trajectory extract_stack filename get __old_np_array _check_no_float64 get _check_no_float64 __old_np_zeros get __old_np_ones _check_no_float64 tuple vector_action_size mean reshape array mean nan_to_num isnan warning array sum _generate_split_indices ones discrete_action_branches len astype dot isnan nan_to_num any cast warning split bool is_action_discrete array observation_shapes enumerate range len perf_counter push reset method_handlers_generic_handler add_generic_rpc_handlers UnityEnvironment close MockCommunicator obs n_agents close get_agent_group_spec get_step_result reset MockCommunicator zip UnityEnvironment observation_shapes obs zip ones n_agents step close get_agent_group_spec get_step_result MockCommunicator set_actions zeros UnityEnvironment observation_shapes UnityEnvironment close MockCommunicator close RpcCommunicator close RpcCommunicator close RpcCommunicator list extend ObservationProto AgentInfoProto append prod range len fromarray uint8 BytesIO astype save ObservationProto generate_compressed_data extend shape generate_compressed_data process_pixels rand generate_compressed_data process_pixels rand _process_vector_observation generate_list_agent_proto enumerate generate_compressed_proto_obs rand extend AgentInfoProto _process_visual_observation AgentGroupSpec CONTINUOUS batched_step_result_from_proto generate_list_agent_proto range AgentGroupSpec batched_step_result_from_proto DISCRETE generate_list_agent_proto action_mask AgentGroupSpec batched_step_result_from_proto DISCRETE generate_list_agent_proto action_mask AgentGroupSpec batched_step_result_from_proto DISCRETE generate_list_agent_proto action_mask AgentGroupSpec CONTINUOUS batched_step_result_from_proto generate_list_agent_proto action_mask BrainParametersProto agent_group_spec_from_proto extend _parse_side_channel_message _generate_side_channel_data send_int IntChannel FloatPropertiesChannel _parse_side_channel_message _generate_side_channel_data get_property set_property _parse_side_channel_message _generate_side_channel_data RawBytesChannel encode send_raw_data get_and_clear_received_messages set_gauge replace endswith add set walk join print extract_version_string set values print join | <img src="docs/images/unity-wide.png" align="middle" width="3000"/> <img src="docs/images/image-banner.png" align="middle" width="3000"/> # Unity ML-Agents Toolkit (Beta) [](docs/Readme.md) [](LICENSE) ([latest release](https://github.com/Unity-Technologies/ml-agents/releases/tag/latest_release)) ([all releases](https://github.com/Unity-Technologies/ml-agents/releases)) **The Unity Machine Learning Agents Toolkit** (ML-Agents) is an open-source Unity plugin that enables games and simulations to serve as environments for training intelligent agents. Agents can be trained using reinforcement learning, | 3,307 |
pitrack/monolign | ['machine translation'] | ['Deriving Consensus for Multi-Parallel Corpora: an English Bible Study'] | structures.py analysis/freq.py inferer.py analysis/POS.py analysis/HEAD.py parser.py relation.py aligner.py monolign.py analysis/pp.py analysis/pred.py analysis/pp2.py passesSimilarity collapseRules Aligner lowQuality Inferer saturate processFile Parser Relation Structure gen collect collect gen gen Predicate read_d_list expand wordify collapse POSify add set passesSimilarity range len read time parse format createDir print size alignWith infer extractRules extend loadAlignments range update writePairAlignments time format list writePOSHeads print processFile size writeProgress shuffle writeCommonAlignments numFiles clean sum collapseRules range split append list values Predicate prep dobj nsubj comp expand append append eval split | # monolign _probably better named multilign, but too late now_ Repository for the IJCNLP paper "Deriving Consensus for Multi-Parallel Corpora: an English Bible Study" [[pdf](http://cs.jhu.edu/~paxia/papers/ijcnlp17-paper.pdf)][[slides](http://cs.jhu.edu/~paxia/papers/ijcnlp17-slides.pdf)] # Execution To run, run ``` python monolign.py DATA_DIR ALIGNER ``` where DATA_DIR consists of n texts where the ith line of each document are parallel. ALIGNER in this case is the location of `fast_align`, and `aligner.py` would need to be modified for other aligners. # Analysis | 3,308 |
pixar0407/depth_map | ['depth estimation', 'monocular depth estimation', 'superpixels'] | ['Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-Scale Convolutional Architecture'] | extras/median-filter.py model_utils.py extras/gaussian-filter.py custom_transforms.py plot_utils.py error.py dataset.py nn_model.py ImgAndDepthToTensor NormalizeImg RandomHorizontalFlip UnNormalizeImgBatch ResizeImgAndDepth NYUDataset print_training_loss_summary apply_sobel_operator_on_sample_ds_image depth_loss err_rms_log get_unnormalized_ds_item im_gradient_loss unfreeze_all_layers freeze_all_layers err_abs_rel err_psnr get_model_predictions_on_a_sample_batch err_sql_rel err_rms_linear Scale3 Scale2 Net Scale1_Linear Flatten hide_subplot_axes plot_image plot_depth_tensor_in_subplot plot_image_tensor_in_subplot plot_model_predictions_on_sample_batch MedianPool2d unnormalize parameters parameters eval pow Tensor to unsqueeze_ im_gradient_loss log sum sum view print pow sqrt abs unsqueeze_ pow sqrt sum log unsqueeze_ abs sum pow unsqueeze_ abs sum view abs pow log10 sum print format view convert conv2d sqrt pow Tensor unnormalize hide_subplot_axes subplots tight_layout plot_depth_tensor_in_subplot plot_image_tensor_in_subplot flat enumerate set_visible imshow transpose imshow numpy hide_subplot_axes subplots tight_layout plot_depth_tensor_in_subplot plot_image_tensor_in_subplot range | # Depth-Map-Prediction-from-a-Single-Image-using-a-Multi-Scale-Deep-Network PyTorch implementation from the papers: https://cs.nyu.edu/~deigen/depth/depth_nips14.pdf https://arxiv.org/pdf/1411.4734v4.pdf Extended model architecture and loss fn to the newer paper. Model Results: (image, ground truth depth, model prediction)  Model Arch: <img src="https://raw.githubusercontent.com/DhruvJawalkar/Depth-Map-Prediction-from-a-Single-Image-using-a-Multi-Scale-Deep-Network/master/results/network-architecture.png" align="center" width="600"/> | 3,309 |
pldelisle/deepNormalize | ['semantic segmentation'] | ['Realistic Image Normalization for Multi-Domain Segmentation'] | DeepNormalize/blocks/ResNet/bottleneck.py DeepNormalize/model/DeepNormalize/deepNormalize.py DeepNormalize/blocks/UNet/unet_block.py DeepNormalize/model/UNet/unet.py DeepNormalize/io/dataset.py DeepNormalize/libs/utils.py DeepNormalize/layers/UNet/downsample.py DeepNormalize/blocks/ResNet/basic.py generate_tfrecords_multi_dataset.py DeepNormalize/layers/tversky_loss.py DeepNormalize/old/utils.py DeepNormalize/preprocessing/MRBrainS_preprocessor.py DeepNormalize/training/train.py DeepNormalize/io/data_provider.py DeepNormalize/layers/loss.py preprocess.py generate_tfrecords_BraTS.py DeepNormalize/old/preprocessing.py DeepNormalize/layers/UNet/convolution.py main.py DeepNormalize/old/sampler_deprecate.py DeepNormalize/utils/utils.py DeepNormalize/io/histogram.py DeepNormalize/preprocessing/iSEG_preprocessor.py DeepNormalize/io/transforms.py DeepNormalize/layers/UNet/elementwise.py DeepNormalize/model/GAN/gan.py DeepNormalize/model/ResNet/ResNet.py DeepNormalize/utils/cuda.py DeepNormalize/layers/layer_util.py write_training_examples _int_feature construct_weights_and_mask write_lists _bytes_feature write_testing_examples _float_feature generate_ROI main get_subjects_and_segmentations write_training_examples _int_feature construct_weights_and_mask write_lists _bytes_feature write_testing_examples _float_feature main get_subjects_and_segmentations main main show_slices BasicBlock Bottleneck UNetBlock MultimodalNiftiDataset NiftiDataset MultimodalDataset MultimodalImageDataset DataProvider get_histogram RandomFlip AddChannel RandomNoise ToPILImage RandomBlock get_transforms ToTensor FixIntensityRange Digitize ToFastaiImage RandomSlice RandomCrop RandomCrop2D RandomAffine CropBase Normalize RandomGamma RandomCrop3D check_spatial_dims trivial_kernel check_divisible_channels expand_spatial_params infer_spatial_rank weighted_cross_entropy dice_coefficient_loss generalised_dice_loss dice_coefficient labels_to_one_hot tversky cross_entropy TverskyLoss DiceLoss Convolution3D Deconvolution3D DownSample ElementWise recompose3D_overlap read_data preprocess_dynamic_lab get_filename extract_patches read_vol get_patches_lab DeepNormalize Discriminator ResNet UNet preprocess_images crop get_slices get_patches Sampler find_segmentations load_image_obj pad_image_and_center _get_file_paths load_dataset find_files iSEGPreprocessor MRBrainSPreprocessor Trainer Cuda split_filename glob_imgs get_MRBrainS_subjects export_inputs get_iSEG_subjects generate_ROI save_nifti_image zeros where shape exp find_boundaries sort size distance_transform_edt zeros sum enumerate bitwise_xor str list TFRecordWriter print astype write construct_weights_and_mask SerializeToString dict Example int64 close zip expand_dims preprocess_images range len str list replace print TFRecordWriter astype write SerializeToString close dict Example int64 get_patches zip expand_dims preprocess_images range len join list remove sort append walk str write_training_examples extraction_step print data_dir len makedirs write_lists write_testing_examples output_dir zip train_test_split get_subjects_and_segmentations correct_class_ids_iSEG get_MRBrainS_subjects data_mrbrains get_iSEG_subjects data_iseg train Cuda Trainer verbose summary device to DataProvider show T subplots imshow enumerate len mrbrains_data_dir iSEGPreprocessor MRBrainSPreprocessor mrbrains_output_dir iseg_output_dir preprocess iseg_data_dir astype float32 flatten hist savefig RandomFlip RandomNoise isinstance ToPILImage RandomBlock ToTensor RandomGamma RandomAffine Normalize append as_list shape with_rank_at_least all shape with_rank_at_least zeros reshape int float tolist int constant isinstance to_int64 to_int32 concat reshape shape stack sparse_reshape int32 Tensor range SparseTensor zeros_like reduce_max where reciprocal multiply reduce_sum cast is_inf expand_dims ones_like value square tile sparse_reduce_sum is_nan reshape float32 maximum labels_to_one_hot flatten reduce_sum weighted_cross_entropy_with_logits reduce_sum maximum sparse_softmax_cross_entropy_with_logits to_float value reshape reduce_sum labels_to_one_hot to_dense tile expand_dims read_data zeros range print extract_patches where vstack zeros range len print read_vol get_patches_lab empty range str print around zeros range crop dict items list get_slices minimum max min maximum where logical_or any array items list reshape extract_patches dict zeros abs floor int load int64 astype append join list walk list search lower filter _get_file_paths compile list search filter _get_file_paths compile append list load_image_obj basename dirname splitext glob join sorted list search dict filter append walk list search dict filter append walk join str save makedirs asarray join str astype imshow savefig int32 range enumerate makedirs | # <img src="/icons/chip.png" width="60" vertical-align="bottom"> Adversarial normalization network for multi-task segmentation > This project aims to develop a convolutionnal neural network (CNN) that automatically and intelligently normalize 3D medical images for maximizing segmentation while preserving the medical plausibility of the image all along the segmentation pipeline. ## Using `python deepNormalize_main.py --data-dir=/path/to/tfrecords/folder/ --job-dir=./logs/` List of arguments of this script : * --data-dir: String. The directory where the deepNormalize input data is stored * --job-dir: String. The directory where the model will be stored. | 3,310 |
pln-fing-udelar/pghumor | ['humor detection'] | ['Is This a Joke? Detecting Humor in Spanish Tweets'] | clasificador/features/primerapersona.py clasificador/features/feature.py clasificador/test/testpreprocesamiento.py clasificador/herramientas/chistesdotcom.py clasificador/features/preguntasrespuestas.py clasificador/config/__init__.py clasificador/test/testoov.py clasificador/features/antonimos.py clasificador/herramientas/utilclasificacion.py clasificador/features/features.py clasificador/features/negacion.py clasificador/features/hashtags.py clasificador/features/oovfreelingwiktionary.py clasificador/features/exclamacion.py bootstraping/bootstrappingsexo.py clasificador/features/palabrasclave.py clasificador/realidad/tweet.py clasificador/test/testantonimos.py clasificador/config/environment.py clasificador/test/testhashtags.py clasificador/test/testutilreflection.py clasificador/features/oovfreeling.py clasificador/herramientas/wikicorpus.py clasificador/features/npersona.py clasificador/herramientas/mayoria.py clasificador/main.py clasificador/test/testpalabrasmayusculas.py clasificador/herramientas/tokenizacion.py clasificador/test/testguionesdialogo.py experimentos/mainchistesdotcom.py clasificador/test/testwiktionary.py clasificador/test/testgoogle.py clasificador/herramientas/freeling.py clasificador/features/dialogo.py clasificador/realidad/chiste.py experimentos/sample_verbs_in_humor.py clasificador/features/distanciacategoria.py clasificador/test/testfreeling.py clasificador/test/testpreguntasrespuestas.py clasificador/features/presenciaanimales.py clasificador/herramientas/tweetstofeatures.py clasificador/herramientas/wiktionary.py clasificador/herramientas/utils.py experimentos/performanceshell.py clasificador/features/jergasexual.py clasificador/features/links.py clasificador/herramientas/define.py clasificador/herramientas/google.py clasificador/test/testwordnet.py experimentos/tweetsenvivo.py clasificador/herramientas/tweettotext.py clasificador/features/palabrasmayusculas.py clasificador/test/testcorpus.py clasificador/herramientas/reflection.py clasificador/features/oov.py clasificador/features/palabrasnoespanolas.py clasificador/features/segundapersona.py clasificador/herramientas/utilanalisis.py clasificador/herramientas/persistencia.py clasificador/features/oovwiktionary.py guardar_dicc_para_feature imprimir_top clasificar cargar_diccionario pulcrar guardar_diccionario bootstrapping Antonimos guiones_dialogo Dialogo DistanciaCategoria Exclamacion Feature Features Hashtags JergaSexual Links Negacion esta_en_persona NPersona OOV OOVFreeling OOV OOVWiktionary PalabrasClave PalabrasMayusculas contiene_caracteres_no_espanoles OOV cantidad_de_capturas_no_solapadas PreguntasRespuestas guion_dialogo_re PresenciaAnimales PrimeraPersona SegundaPersona obtener_chistes_categoria cargar_chistes_pagina open_db obtener_categorias AnalyzerClient TokenFL Freeling Google Mayoria guardar_features open_db cargar_parecidos_con_distinto_humor guardar_parecidos_con_distinto_humor cargar_tweets cargar_modulos_vecinos subclases paquete modulos_vecinos archivos_python_vecinos tokenizar TweetsToFeatures TweetToText tweets_parecidos_con_distinto_humor f_score_feature_selection mismas_features_distinto_humor imprimir_importancias tree_based_feature_selection chi2_feature_selection cross_validation_y_reportar calcular_medidas get_clases mostrar_medidas_ponderadas imprimir_matriz_de_confucion calcular_verdaderos_falsos_positivos_negativos train_test_split_pro get_features metricas_ponderadas_segun_concordancia matriz_de_confusion_y_reportar metricas_ponderadas_segun_humor imprimir_matriz_metricas distancia_edicion get_stop_words ejecutar_comando entropia obtener_diccionario filtrar_segun_votacion eliminar_underscores read_wiki_corpus obtener_sample_wikicorpus Wiktionary Chiste remover_hashtags Tweet remover_retweet_si_hay remover_usuarios remover_links remover_espacios_multiples_y_strip TestAntonimos TestCorpus open_db TestFreeling TestGoogle TestGuionesDialogo TestHashtags TestOOV TestPalabrasMayusculas TestPreguntasRespuestas TestPreprocesamiento TestUtilReflection TestWiktionary TestWordNet SalidaEstandarListener colorear_texto OAuthHandler tokenizar defaultdict print text search API resource_filename obtener_diccionario set_access_token print nlargest print readline sorted append cursor open_db Chiste execute append cursor open_db Chiste execute append execute cursor open_db append obtener_diccionario resource_filename str int cursor format open_db IncrementalBar Tweet strip close finish execute next append pop items list cursor commit open_db IncrementalBar close finish execute next modulos_vecinos paquete import_module sorted format print range len ExtraTreesClassifier print feature_importances_ imprimir_importancias fit print chi2 imprimir_importancias print f_classif imprimir_importancias tokens id finish es_chiste round list defaultdict procesar_texto IncrementalBar add guardar_parecidos_con_distinto_humor append chain next range texto_original set cargar_parecidos_con_distinto_humor es_humor int print len print IncrementalBar texto id finish append next pop int list sample range len append array_features len print format items list defaultdict format std IncrementalBar StratifiedKFold print flatten mean sqrt imprimir_matriz_metricas finish append next array predict fit sum sum len format imprimir_matriz_de_confucion print calcular_verdaderos_falsos_positivos_negativos metricas_ponderadas_segun_humor format calcular_medidas imprimir_matriz_de_confucion print calcular_verdaderos_falsos_positivos_negativos metricas_ponderadas_segun_concordancia len print format wait Popen add set votos_humor votos float es_humor list min append range enumerate len glob resource_filename parse resource_filename obtener_diccionario resource_filename sub | # pgHumor: Humor detection in Spanish tweets This thesis is about deciding if a tweet written in Spanish is humorous or not, applying Supervised Machine Learning. It was carried out by [Matías Cubero](https://github.com/matu1104) and [Santiago Castro](https://github.com/bryant1410), and supervised by [Guillermo Moncecchi](https://github.com/gmonce) and Diego Garat. For detailed information, see [the final report](InformeV3.4.pdf). ## Abstract Looking at this tweet: > — Yesterday, when leaving work I ran over a unicorn. > > — No way, you got job? which is the translated version of this one: > — Ayer, al salir del trabajo atropellé a un unicornio. > | 3,311 |
pmeletis/IV2018-hierarchical-semantic-segmentation-for-heterogeneous-datasets | ['semantic segmentation'] | ['Training of Convolutional Networks on Multiple Heterogeneous Datasets for Street Scene Semantic Segmentation'] | hierarchical-semantic-segmentation/input_cityscapes_mapillary_gtsdb/input_pipeline.py hierarchical-semantic-segmentation/estimator/define_losses.py hierarchical-semantic-segmentation/train_cityscapes_mapillary_gtsdb.py hierarchical-semantic-segmentation/system_factory.py hierarchical-semantic-segmentation/train.py hierarchical-semantic-segmentation/utils/util_problem_def.py hierarchical-semantic-segmentation/utils/utils.py hierarchical-semantic-segmentation/evaluate_cityscapes_mapillary_gtsdb.py hierarchical-semantic-segmentation/estimator/define_custom_metrics.py hierarchical-semantic-segmentation/estimator/define_savers.py hierarchical-semantic-segmentation/estimator/define_initializers.py hierarchical-semantic-segmentation/input_cityscapes_mapillary_gtsdb/preprocess_augmentation_1.py hierarchical-semantic-segmentation/model/model.py hierarchical-semantic-segmentation/predict.py datasets/cityscapes_extended/v1/annotation_tool/annotate.py hierarchical-semantic-segmentation/utils/__init__.py hierarchical-semantic-segmentation/estimator/define_estimator.py hierarchical-semantic-segmentation/estimator/__init__.py hierarchical-semantic-segmentation/model/feature_extractor.py datasets/labels.py hierarchical-semantic-segmentation/input_cityscapes_mapillary_gtsdb/input_pipeline_test.py hierarchical-semantic-segmentation/utils/util_zip.py assureSingleInstanceName Loader App save_annotations save_no_annotations split_path myPushButton get_image_and_label_fpaths CurrentPacket Packet main _add_extra_args main _add_extra_args SemanticSegmentation _validate_settings main _add_extra_args main _add_extra_args confusion_matrices_for_classes_and_subclasses mean_iou train_init define_losses evaluate_saver train_saver evaluate_parse_prepare_preprocess_gtsdb train_parse_prepare_preprocess_cityscapes evaluate_parse_prepare_preprocess_cityscapes_extended evaluate_parse_prepare_preprocess_mapillary predict_input predict_image_generator evaluate_input_mapillary train_input evaluate_parse_prepare_preprocess_cityscapes evaluate_input_cityscapes train_parse_prepare_preprocess_mapillary _concatenate_datasets _replacevoids evaluate_input_cityscapes_extended evaluate_input_gtsdb predict_prepare_and_preprocess create_dataset train_parse_prepare_preprocess_gtsdb main train_input_test random_color preprocess_predict random_blur preprocess_train distort_blur preprocess_evaluate distort_color feature_extractor _create_upsampler model get_unique_variable_by_name_without_creating safe_div almost_equal print_metrics_from_confusion_matrix split_path print_tensor_info get_unique_tensor_by_name_without_creating _replacevoids _validate_problem_config cids2lids get_saveable_objects_list count_non_i SemanticSegmentationArguments ids2image zipit _zippy list replace print astype logical_or int32 save array exists makedirs replace print astype int32 save exists makedirs sorted list replace glob print set splitext split items sorted SemanticSegmentation join evaluate print _add_extra_args OrderedDict eval_res_dir add_evaluate_arguments SemanticSegmentationArguments parse_args int height_feature_extractor height_network num_examples Neval num_batches_per_epoch Nb width_network width_feature_extractor add_subplot save str imshow results_dir range predict export_color_images add_predict_arguments export_lids_images tight_layout flush plotting set_axis_off write now waitforbuttonpress figure array makedirs add_train_arguments train print Ntrain Ne append log_dir zipit Nb_mapil Ntrain_mapil ones_like logical_and where cast int32 top_k assert_has_rank argmax equal _streaming_confusion_matrix float32 confusion_matrix reduce_sum diag_part reduce_mean div cast get_regularization_losses lamda add_n get_total_loss init_ckpt_path random_crop training_lids2cids_mapil uint8 reduce_any print to_int32 concat less tuple float32 convert_image_dtype cast cond parse_single_example gather decode_png decode_jpeg resize_images uint8 random_crop print to_int32 concat tuple float32 preprocess_train convert_image_dtype cast parse_single_example gather training_lids2cids_citys decode_png training_lids2cids_gtsdb resize_images random_crop uint16 print to_int32 concat tuple float32 preprocess_train convert_image_dtype cast parse_single_example gather decode_png TFRecordDataset partial map shuffle repeat batch map zip Nb_citys Nb_gtsdb print tfrecords_path_mapil make_one_shot_iterator _concatenate_datasets Nb_mapil get_next create_dataset tfrecords_path_gtsdb tfrecords_path_citys max resize_images print to_int32 convert_image_dtype _replacevoids cast int32 parse_single_example gather decode_png decode_jpeg TFRecordDataset partial map shuffle make_one_shot_iterator get_next set_shape Nb batch tfrecords_path resize_images print to_int32 convert_image_dtype _replacevoids cast int32 parse_single_example gather decode_png TFRecordDataset partial map shuffle make_one_shot_iterator get_next set_shape Nb batch tfrecords_path resize_images print to_int32 convert_image_dtype _replacevoids cast int32 parse_single_example gather decode_png TFRecordDataset partial map shuffle make_one_shot_iterator get_next set_shape Nb batch tfrecords_path resize_images print to_int32 convert_image_dtype _replacevoids cast int32 parse_single_example gather decode_png TFRecordDataset partial map shuffle make_one_shot_iterator get_next set_shape Nb batch tfrecords_path join predict_dir glob extend open resize_images print float32 convert_image_dtype set_shape map make_one_shot_iterator get_next from_generator prefetch Nb batch Nb_citys print now shape Ntrain_citys range InteractiveSession run train_input_test random_color expand_dims random_blur convert_image_dtype resize_images float32 stack random_uniform stack random_uniform get_shape set_shape float32 py_func feature_extractor array print items ones_like print astype write where logical_not isnan shape mean trace int32 diagonal sum list max map enumerate _zippy isdir print ZIP_DEFLATED write close split ZipFile makedirs join isdir relpath write listdir | # Training of Convolutional Networks on Multiple Heterogeneous Datasets for Street Scene Semantic Segmentation (IV 2018) Code for reproducing results for IV2018 paper "Training of Convolutional Networks on Multiple Heterogeneous Datasets for Street Scene Semantic Segmentation". __Panagiotis Meletis and Gijs Dubbelman (2018)__ _Training of convolutional networks on multiple heterogeneous datasets for street scene semantic segmentation._ The 29th IEEE Intelligent Vehicles Symposiom (IV 2018), [full paper on arXiv](https://arxiv.org/abs/1803.05675). If you find our work useful for your research, please cite the following paper: ``` @inproceedings{heterogeneous2018, title={Training of Convolutional Networks on Multiple Heterogeneous Datasets for Street Scene Semantic Segmentation}, author={Panagiotis Meletis and Gijs Dubbelman}, booktitle={2018 IEEE Intelligent Vehicles Symposium (IV)}, year={2018} | 3,312 |
pmorenoz/RecyclableGP | ['gaussian processes'] | ['Recyclable Gaussian Processes'] | kernels/kernel.py experiments/parallel.py algebra.py likelihoods/bernoulli.py experiments/banana.py util.py kernels/rbf.py kernels/stationary.py setup.py models/svgp.py likelihoods/gaussian.py likelihoods/likelihood.py optimization/algorithms.py models/ensemblegp.py cholesky_inverse inverse jit_op cholesky lt_log_determinant trtrs true_function smooth_function_bias squared_distance smooth_function Kernel RBF Stationary Bernoulli Gaussian Likelihood EnsembleGP SVGP ensemble_vem_infographic vem_algorithm_infographic AlgorithmVEM vem_algorithm ensemble_vem ensemble_vem_parallel GPR_Optimizer mean range eye cos pi sin cos pi sin cos pi sin t sum str print step parameters LBFGS empty range show str plot model print backward xlabel step zero_grad SGD named_parameters parameters title LBFGS figure empty range show str plot model backward print xlabel step zero_grad SGD parameters title figure empty range show str plot model backward print xlabel zero_grad SGD parameters title figure zeros step range str model backward print step zero_grad SGD parameters empty range str model backward print zero_grad SGD parameters zeros step range | # Recyclable Gaussian Processes This repository contains the Pytorch implementation of Recyclable Gaussian Processes. We provide a detailed code for single-output GP regression and GP classification with both synthetic and real-world data. Please, if you use this code, cite the following [preprint](https://arxiv.org/abs/2010.02554): ``` @article{MorenoArtesAlvarez20, title = {Recyclable Gaussian Processes}, author = {Moreno-Mu\~noz, Pablo and Art\'es-Rodr\'iguez, Antonio and \'Alvarez, Mauricio A}, journal = {arXiv preprint arXiv:2010.02554}, year = {2020} } | 3,313 |
pmorerio/admd | ['action recognition'] | ['Learning with privileged information via adversarial discriminative modality distillation'] | ActionRecogDatasets/twostream_hall_rgb.py ActionRecogDatasets/s1_train_stream.py NYUD/model.py ActionRecogDatasets/s2_gan_hall.py ActionRecogDatasets/codebase/restorers.py ActionRecogDatasets/codebase/parsers.py ActionRecogDatasets/nets/resnet_v1_two_stream.py ActionRecogDatasets/twostream_depth_rgb.py NYUD/codebase_rename_ckpt.py ActionRecogDatasets/codebase/utils.py NYUD/convert_NYUD_with_FCRN.py NYUD/solver.py NYUD/main.py ActionRecogDatasets/nets/resnet_utils.py ActionRecogDatasets/codebase/rename_ckpt.py mask_random sample_mask_uniform _parse_fun_2stream sample_mask _parse_fun_one_mod main rename restore_weights_s2_5_gan_depth restore_weights_s1 restore_weights_hall_rgb restore_weights_s2 restore_weights_s1_continue correct_pred loss_hall_rect get_tfrecords_ntu double_log get_tfrecords get_tfrecords_uwa3dii_noval load_files_paths get_n_classes accuracy get_tfrecords_nwucla_noval get_temporal_order_onehot create_folders get_arguments Block conv2d_same subsample resnet_arg_scope conv_temp2 stack_blocks_dense lrelu resnet_one_stream_main resnet_one_stream feature_discriminator bottleneck_normal resnet_v1_50 resnet_v1_block main rename main MultiModal Solver greater sample_mask_uniform cond random_uniform to_float ones subtract to_int32 scatter_nd linspace expand_dims equal ones concat zeros equal random_shuffle ConfigProto print rename getopt exit append restore get_variables_to_restore Saver call restore get_variables_to_restore Saver call restore get_variables_to_restore Saver restore get_variables_to_restore Saver call restore get_variables_to_restore Saver parse_args add_argument ArgumentParser join strftime makedirs seed join list sort shuffle append listdir seed list sort shuffle listdir seed int list sort len extend shuffle choice append listdir range enumerate print rstrip write flush one_hot range tile pad value reshape conv3d stack constant_initializer zeros resnet_v1_50 resnet_one_stream concat train_eccv finetune_hallucination test_ensemble_baseline train_hallucination test_disc train_double_stream train_autoencoder test_double_stream_with_ae MultiModal test_moddrop train_single_stream test_hallucination test_autoencoder test_double_stream test_single_stream Solver | ## Code for the paper 'Learning with privileged information via adversarial discriminative modality distillation' [arXiv](https://arxiv.org/abs/1810.08437) [IEEEXplore](https://ieeexplore.ieee.org/document/8764498) Clone recursively to get also FCRN depth prediction code. ``` git clone --recursive https://github.com/pmorerio/admd.git ``` If you use this code as part of your research please cite ``` @article{garcia2020admd, title={Learning with privileged information via adversarial discriminative modality distillation}, | 3,314 |
pmorerio/dl-uncertainty | ['depth estimation', 'semantic segmentation'] | ['What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?'] | epistemic-uncertainty/solver.py combined/solver.py epistemic-uncertainty/main.py combined/main.py combined/model.py aleatoric-uncertainty/model.py aleatoric-uncertainty/solver.py epistemic-uncertainty/model.py prepro.py aleatoric-uncertainty/main.py main resize_images save_pickle fromarray asarray astype resize zeros enumerate read_data_sets save_pickle | ## Uncertainty in Deep Learning Some code (TensorFlow) based on the paper: A Kendall, Y Gal, “**What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?**”, NIPS 2017 [arXiv](https://arxiv.org/abs/1703.04977) __DISCLAIMER:__ This is __NOT__ the official repo. It is just based on my understanding of the paper. **Any feedback is welcome.** I am training a simple autoencoder (regression) to reconstruct MNIST digits. ### Getting MNIST Download MNIST: ` ./download.sh ` | 3,315 |
podgorskiy/GPND | ['one class classifier'] | ['Generative Probabilistic Novelty Detection with Adversarial Autoencoders'] | partition_mnist.py novelty_detector.py defaults.py evaluation.py save_to_csv.py schedule.py utils/multiprocessing.py utils/threshold_search.py dataloading.py utils/save_plot.py net.py train_AAE.py utils/tracker.py utils/jacobian.py create_set_with_outlier_percentage Dataset make_datasets make_dataloader get_cfg_defaults get_f1 evaluate Generator ZDiscriminator_mergebatch Encoder Discriminator normal_init ZDiscriminator r_pdf main extract_statistics partition get_mnist save_results f train compute_jacobian_autograd compute_jacobian_using_finite_differences_v2 compute_jacobian_using_finite_differences compute_jacobian_using_finite_differences_v3 map _f _get_gpu_count get_gpu_count _init set_numpy_treads save_plot find_maximum RunningMean RunningMeanTorch LossTracker TOTAL_CLASS_COUNT append range Dataset FOLDS_COUNT batch_provider BatchCollator seed int shuffle increase_length Dataset len minimum greater_equal arange abs float min logical_and greater logical_not info less get_f1 sum max roc_auc_score len normal_ zero_ digitize INPUT_IMAGE_SIZE flatten OUTPUT_FOLDER view BATCH_SIZE squeeze append current_device range save_plot plot concatenate join norm G LATENT_SIZE MAKE_PLOTS hist histogram make_dataloader zeros numpy E fit INPUT_IMAGE_SIZE getLogger save_image OUTPUT_FOLDER compute_threshold view Generator load_state_dict to current_device shuffle Encoder PERCENTAGES test eval set_default_tensor_type load join INPUT_IMAGE_CHANNELS print LATENT_SIZE make_datasets extract_statistics figure cpu len items mnist asarray imresize append seed items list join dump print close shuffle get_mnist open info append PATH range FOLDS_COUNT len writer list print writerow tuple close mean append keys open main train INPUT_IMAGE_SIZE getLogger binary_cross_entropy zero_grad LossTracker EPOCH_COUNT save BASE_LEARNING_RATE save_image OUTPUT_FOLDER BCE_loss ZDiscriminator str list BATCH_SIZE view ones Generator squeeze ZDiscriminator_mergebatch Adam register_means Discriminator current_device range cat detach update state_dict Z_DISCRIMINATOR_CROSS_BATCH plot shuffle Encoder weight_init requires_grad_ info BCELoss join time G INPUT_IMAGE_CHANNELS backward print LATENT_SIZE Variable makedirs make_datasets dict parameters make_dataloader cpu zeros step E len data backward zero_ zeros range cuda is_cuda zero_gradients device_count close send Process recv join start Pipe str cpu_count max int get print set_device current_device set_default_tensor_type put Manager Queue Pool range xlabel grid close ylabel tight_layout cla title clf savefig xticks yticks f binary_search | # Generative Probabilistic Novelty Detection with Adversarial Autoencoders **Stanislav Pidhorskyi, Ranya Almohsen, Donald A Adjeroh, Gianfranco Doretto** Lane Department of Computer Science and Electrical Engineering, West Virginia University\ Morgantown, WV 26508\ {stpidhorskyi, ralmohse, daadjeroh, gidoretto} @mix.wvu.edu [The e-preprint of the article on arxiv](https://arxiv.org/abs/1807.02588). [NeurIPS Proceedings](https://papers.nips.cc/paper/7915-generative-probabilistic-novelty-detection-with-adversarial-autoencoders). @inproceedings{pidhorskyi2018generative, | 3,316 |
poke1024/bbz-segment | ['optical character recognition'] | ['An Evaluation of DNN Architectures for Page Segmentation of Historical Newspapers'] | 02_preprocessing/preprocessing/gt.py 03_training/03_batch_grid/gridmate.py 02_preprocessing/preprocessing/zucker_warp.py 03_training/01_preprocessing/make_dhsegment_training_data.py 02_preprocessing/preprocessing/blocks.py 03_training/04_batch_production/grid.py 02_preprocessing/main.py 04_evaluation/grid/make_grid_table.py 03_training/01_preprocessing/make_training_data.py 02_preprocessing/preprocessing/segments.py 04_evaluation/dhsegment/gen_slurm.py 04_evaluation/folds/make_folds_table.py 02_preprocessing/preprocessing/utils/__init__.py 02_preprocessing/preprocessing/utils/transform.py 03_training/03_batch_grid/status.py 04_evaluation/partial/eval_partial.py 02_preprocessing/preprocessing/lines.py 02_preprocessing/preprocessing/__init__.py 02_preprocessing/preprocessing/bnet.py 05_prediction/src/main.py 03_training/02_train/train.py 02_preprocessing/preprocessing/labels.py 04_evaluation/dhsegment/eval_dh_segment.py 05_prediction/src/predict.py 02_preprocessing/preprocessing/pages.py 04_evaluation/grid/total-runtime.py 02_preprocessing/preprocessing/utils/mat2x3.py 02_preprocessing/preprocessing/utils/geometry.py WarpAugmentation TrainingImageGenerator Generator PixelLabelGenerator tiles LabelsGenerator tiles_1 Converter build_binarized Preprocessor Target RegionLabelGenerator Block Cell Row Table BNet acc_layout acc_text_2 acc_text_1 GroundTruth Loader collect_ground_truth GroundTruthRef Label _gen_pts _estimate_skew Merger _regions_to_convex_hull HMerger Regions Morpholizer Annotations HTextMerger _merge_convex_all _add_hull AnnotationsGenerator PolygonV Line Baseline best_split SplitNode Page Layout pick_first _polygons centroid_coordinate LeafNode LayoutNode Segment JoinResult warp_images convex_contours Simplifier estimate_angle contours convex_hull mul p inv to_shapely v Rotate Transform _transform_labels _white Resize Remap _n_channels binarized polygon_mask mask_to_polyline mask_to_contours mask_to_polygons mask_to_polyline_robust mask_to_polyline_hq smoothened_at _normalized _running_mean fast_snake extract_polygon_mask colorized polygons_to_mask gen_dhs_data find_tile_suffixes validation_set_for_tiles Generator _rnn_l2regs denormalize _get_layer_l2regs _compute_eta_t get_validation_augmentation visualize _cell_l2regs run _apply_lr_multiplier _check_args Dataloader K_eval warn_str _apply_weight_decays get_training_augmentation log_std_metrics get_weight_decays LogMetricsToSacred lsd_metrics colorize round_clip_0_1 get_tmp_model_path LsdMetrics cfg get_preprocessing fill_dict_in_order AdamW log_custom_metric reset_seeds EvaluateMoreMetrics Dataset GridMate OrigamiGridMate _determine_task_gpu _config_logging _patch_configuration gather_status load_document load_documents Tile parse_layout_name evaluate TileLoader Tiles by_backbone build_tables tiling_latex tiling_pixels by_model gather_data DataPoint Measurement layout_name gather_data load Tile colorize VotingPredictor _majority_vote Page Prediction Predictor category_colors NetPredictor Tiles int range invert parent stem convert nlbin mkdir save open dict Loader GroundTruthRef iter_int_dir gather_files is_dir append any endpoints enumerate length estimate_angle any coords dict any mask_to_polygons pop list insert bounds len intersects delete dict intersection append range Index convex_hull enumerate list argmin append defaultdict disjoint xpath seed slice shape uniform Warper digest array reshape convexHull Polygon ransac asin LineModelND degrees pi predict_y atan2 array sin flip zeros grayscale tuple astype float32 empty range len _n_channels fromarray zeros putpalette enumerate astype float32 logical_not cls uint8 line zip bounds reshape findContours tuple astype area array tile convexHull simplify zeros coords append int list bounds astype array int32 coords polygon_mask cumsum insert T zip tuple min gaussian convert astype circle active_contour flip argwhere skeletonize linspace int32 median array approximate_polygon enumerate flatten simplify abs max LineString watershed list transpose shape skeletonize append range astype reversed _normalized zip flip zeros enumerate print min extend argwhere int32 median fast_snake DIST_L2 flatten linspace simplify abs max LineString fitLine list transpose logical_and ceil append astype zip flip T float32 _running_mean median array min copy _running_mean array len stem group add set match iterdir compile suffix print stem find_tile_suffixes set add any Path append iterdir validation_set_for_tiles save getpalette open fromarray str list name stem shape putpalette append group mkdir fill empty keys compile enumerate print reshape index dict match iterdir array _check_array list range update format layers print _get_layer_l2regs keys enumerate append getattr layer hasattr name getattr append enumerate format batch_size print name total_iterations_wd sqrt K_eval cast eta_t eta_max t_cur cos cast total_iterations eta_min print K_eval name format print warn_str clear_session seed set_seed print set_random_seed reset_default_graph parent exists flatten zeros fromarray putpalette subplot uint8 items colorize len astype imshow title figure xticks enumerate yticks percentile clip clip get float log_scalar log_scalar mkdir multi_gpu_model plot_loss loads Path DiceLoss add_artifact str list defaultdict len exit Dataloader array savefig getattr append expand_dims range predict LRFinder CategoricalCELoss lsd_metrics astype get_tmp_model_path fit_generator mean zip get_preprocessing float compile join read uint8 items print AdamW log_scalar dict ModelCheckpoint Lookahead Dataset find stdout setFormatter getLogger addHandler StreamHandler Formatter DEBUG setLevel INFO list parse zip total_seconds stem now naturaldelta Status dict is_dir OrderedDict append iterdir exists len write_inner tuple reversed load_tile zeros tiles_gen list compile group match Tiles load_document items parse_layout_name defaultdict stem group tqdm match append compile load_documents save reset_default_graph defaultdict denominator LoadedModel precision_score getattr append TileLoader lsd_metrics recall_score close mkdir numerator InteractiveSession jaccard_score matthews_corrcoef namedtuple print reshape tqdm Decimal _fields len append tile_size get int str list items print add_sample dict is_dir match Tiling array Configuration startswith argmax iterdir exists items list defaultdict sorted select_best dict append values items list defaultdict sorted select_best dict enumerate full_size get items list defaultdict value sorted endswith dict Configuration append float layout_name max enumerate float colors category_colors max dict c tqdm dtype take_along_axis astype dstack logical_not argsort shape array zeros max range | # bbz-segment This repository contains code and data for the paper <a href="http://arxiv.org/abs/2004.07317">An Evaluation of DNN Architectures for Page Segmentation of Historical Newspapers</a>: * `00_demo_data` gives sample data that can be used to run the script in `02_preprocessing`. Our full annotated data that was used in the paper can be found on <a href="https://www.dropbox.com/sh/4b1ub2bmmgmbprp/AAC88d8h8oZVgt-4WC5_uNloa?dl=0">Dropbox</a>. * `01_selection` contains a random page selection script. * `02_preprocessing` contains the full pipeline used to postprocess the ground truth (before DNN training). * `03_training` contains the code used to train the DNN networks. Note that `train.py` contains AdamW optimizer code copied from https://github.com/OverLordGoldDragon/keras-adamw. * `04_evaluation` contains various scripts for evaluating performance, as well as our raw data (as <a href="https://github.com/IDSIA/sacred">sacred</a> runs, see `04_evaluation/data`). * `05_prediction` gives scripts for running our final models for prediction (see graphics below for the demo result). To run it yourself on on this or other document images, first download the models from <a href="https://www.dropbox.com/sh/7tph1tzscw3cb8r/AAA9WxhqoKJu9jLfVU5GqgkFa?dl=0">Dropbox</a> and move them to `05_prediction/data/models`. Then run `05_prediction/src/main.py` to predict the files in `05_prediction/data/pages`. Note that you need to have numpy, tensorflow and <a href="https://github.com/qubvel/segmentation_models">segmentation_models</a> installed. ## Demo Page  | 3,317 |
polarisZhao/mtcnn-pytorch | ['face detection', 'face alignment'] | ['Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks'] | test.py src/box_utils.py src/model.py src/utils.py src/detector.py main calibrate_box nms correct_bboxes convert_to_square _preprocess get_image_boxes detect_faces run_first_stage _generate_bboxes RNet ONet Flatten PNet calibrate_box nms correct_bboxes convert_to_square show_bboxes _preprocess IoU get_image_boxes show detect_faces show_bboxes open append maximum minimum maximum zeros_like expand_dims hstack fromarray correct_bboxes asarray _preprocess size BILINEAR resize zeros range len expand_dims transpose calibrate_box nms run_first_stage convert_to_square FloatTensor reshape size min rnet onet expand_dims eval numpy vstack append get_image_boxes round nms asarray FloatTensor _preprocess size _generate_bboxes BILINEAR resize numpy net vstack array where minimum maximum ellipse Draw copy rectangle range | # mtcnn-pytorch pytorch implementation of face detection algorithm MTCNN ### Usage MTCNN Just download the repository and then do this ``` from src.detector import detect_faces from src.utils import show_bboxes from PIL import Image image = Image.open('images/test3.jpg') bounding_boxes, landmarks = detect_faces(image) | 3,318 |
polm/fugashi | ['multilingual nlp'] | ['fugashi, a Tool for Tokenizing Japanese in Python'] | fugashi/cli.py fugashi/__init__.py fugashi_util.py setup.py fugashi/tests/test_basic.py fugashi/tests/test_ipadic.py mecab_config_windows mecab_config_cygwin mecab_config check_libmecab main build_dict info test_nbest test_pos test_wakati test_clobber test_invalid_args test_accent test_tokens test_wakati check_output decode chdir startswith run chdir getcwd config makedirs join parse print strip GenericTagger input join print dictionary_info GenericTagger split print join build_dictionary Tagger Tagger Tagger Tagger Tagger tagger skip Tagger tagger GenericTagger MECAB_ARGS | [](https://share.streamlit.io/polm/fugashi-streamlit-demo/main/demo.py) [](https://pypi.org/project/fugashi/)  [](https://pypi.org/project/fugashi/)  # fugashi <img src="https://github.com/polm/fugashi/raw/master/fugashi.png" width=125 height=125 alt="fugashi by Irasutoya" /> fugashi is a Cython wrapper for [MeCab](https://taku910.github.io/mecab/), a Japanese tokenizer and morphological analysis tool. Wheels are provided for Linux, OSX, and Win64, and UniDic is [easy to install](#installing-a-dictionary). | 3,319 |
polmonroig/style_transfer | ['style transfer'] | ['A Neural Algorithm of Artistic Style'] | main.py art_net.py file_manager.py ContentLoss StyleLoss ArtNet Normalization FileManager main join read_images print Experiment log_parameters FileManager clone device is_available train log_image ArtNet save_image | ### Image style transfer ### This repository contains the implementation of the Neural Style Transfer(https://arxiv.org/abs/1508.06576).<br> The following is a combined image from a Barcelona landscape with style image "style_00.jpg"  ### Who do I talk to? ### Pol Monroig | 3,320 |
pooja290992/ConFuse | ['time series analysis', 'time series'] | ['ConFuse: Convolutional Transform Learning Fusion Framework For Multi-Channel Data Analysis'] | Codes/data_processing.py Codes/utils.py Codes/ConFuse.py train_model train_on_batch Transform Network clfRF plotGraph ridge_regressor checkClassImbal calOutShape getFeatWiseData RegFinancialData getWindowedDataReg FinancialData splitData getData toFloatTensor labelData getPrevDayFeatures getStocksList compAnnualReturns saveResults plotPrecisionRecall plotROC computeMetrics computeConfMatrix int time format X_step model print backward zero_grad Z_step item train step enumerate computeLoss seed train_model str print Variable Adam RegFinancialData parameters DataLoader eval numpy shape manual_seed append float range Network yscale plot xlabel ylabel title savefig figure legend columns print size shape DataFrame RandomForestClassifier predict_proba predict fit Ridge predict fit print head read_csv DataFrame where int len groupby list asarray reset_index get_group reshape tolist extend copy shape append sort_values keys range list asarray dstack append keys range len append asarray show xlabel confusion_matrix ylabel ravel set title DataFrame heatmap show plot xlabel roc_curve set_edgecolor ylabel title legend auc show plot xlabel set_edgecolor ylabel average_precision_score precision_recall_curve title legend print savetxt groupby reset_index print tolist rename exp print log shape getWindowedDataReg round date DataFrame range days | pooja290992/ConFuse | 3,321 |
porouspaper/games-test | ['unity'] | ['Unity: A General Platform for Intelligent Agents'] | ml-agents-envs/mlagents_envs/communicator_objects/capabilities_pb2.py ml-agents/mlagents/trainers/tests/test_tf_policy.py ml-agents/mlagents/trainers/environment_parameter_manager.py ml-agents/mlagents/trainers/cli_utils.py ml-agents/mlagents/trainers/run_experiment.py ml-agents/mlagents/trainers/components/reward_signals/curiosity/model.py ml-agents-envs/mlagents_envs/communicator_objects/command_pb2.py ml-agents-envs/mlagents_envs/mock_communicator.py ml-agents/mlagents/trainers/policy/__init__.py ml-agents-envs/mlagents_envs/communicator_objects/unity_to_external_pb2.py ml-agents-envs/mlagents_envs/communicator.py gym-unity/gym_unity/envs/__init__.py ml-agents-envs/mlagents_envs/communicator_objects/brain_parameters_pb2.py ml-agents/mlagents/trainers/learn.py ml-agents/mlagents/trainers/tests/test_barracuda_converter.py ml-agents-envs/mlagents_envs/side_channel/raw_bytes_channel.py ml-agents/mlagents/trainers/trainer/trainer.py gym-unity/gym_unity/__init__.py ml-agents-envs/mlagents_envs/side_channel/__init__.py utils/validate_meta_files.py ml-agents/mlagents/trainers/trainer_controller.py ml-agents/mlagents/trainers/components/bc/model.py ml-agents/mlagents/trainers/action_info.py ml-agents/mlagents/trainers/tests/test_ppo.py ml-agents/mlagents/tf_utils/__init__.py ml-agents/mlagents/trainers/components/reward_signals/__init__.py ml-agents-envs/setup.py ml-agents-envs/mlagents_envs/side_channel/engine_configuration_channel.py ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_output_pb2.py ml-agents/mlagents/trainers/tests/mock_brain.py ml-agents/mlagents/trainers/policy/checkpoint_manager.py ml-agents/mlagents/trainers/tests/test_bcmodule.py ml-agents/mlagents/trainers/tests/test_models.py ml-agents/mlagents/trainers/tests/test_trainer_controller.py ml-agents-envs/mlagents_envs/side_channel/incoming_message.py ml-agents/mlagents/trainers/components/reward_signals/reward_signal_factory.py ml-agents-envs/mlagents_envs/rpc_utils.py ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_initialization_output_pb2.py ml-agents/setup.py ml-agents/tests/yamato/setup_venv.py ml-agents/mlagents/trainers/barracuda.py ml-agents/mlagents/trainers/optimizer/tf_optimizer.py utils/run_markdown_link_check.py ml-agents/mlagents/trainers/env_manager.py ml-agents/mlagents/trainers/ppo/trainer.py ml-agents/mlagents/trainers/policy/policy.py ml-agents-envs/mlagents_envs/communicator_objects/agent_action_pb2.py ml-agents/mlagents/model_serialization.py ml-agents-envs/mlagents_envs/tests/test_rpc_communicator.py ml-agents-envs/mlagents_envs/tests/test_envs.py utils/validate_inits.py ml-agents-envs/mlagents_envs/side_channel/float_properties_channel.py ml-agents/mlagents/trainers/components/reward_signals/curiosity/signal.py ml-agents/mlagents/trainers/simple_env_manager.py ml-agents/mlagents/trainers/tf/tensorflow_to_barracuda.py ml-agents-envs/mlagents_envs/side_channel/outgoing_message.py ml-agents-envs/mlagents_envs/exception.py ml-agents-envs/mlagents_envs/registry/remote_registry_entry.py ml-agents/mlagents/trainers/trainer/__init__.py ml-agents/mlagents/trainers/upgrade_config.py ml-agents-envs/mlagents_envs/communicator_objects/unity_message_pb2.py ml-agents/mlagents/trainers/tests/test_learn.py ml-agents/tests/yamato/scripts/run_gym.py utils/validate_release_links.py ml-agents-envs/mlagents_envs/communicator_objects/agent_info_pb2.py ml-agents/mlagents/trainers/tests/test_demo_loader.py ml-agents-envs/mlagents_envs/communicator_objects/observation_pb2.py utils/validate_versions.py ml-agents-envs/mlagents_envs/tests/test_rpc_utils.py ml-agents-envs/mlagents_envs/tests/test_timers.py ml-agents/mlagents/trainers/__init__.py ml-agents-envs/mlagents_envs/communicator_objects/custom_reset_parameters_pb2.py ml-agents/mlagents/trainers/tests/test_env_param_manager.py ml-agents-envs/mlagents_envs/tests/test_registry.py ml-agents-envs/mlagents_envs/communicator_objects/agent_info_action_pair_pb2.py ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_input_pb2.py ml-agents/mlagents/trainers/tests/test_nn_policy.py ml-agents-envs/mlagents_envs/timers.py ml-agents/tests/yamato/check_coverage_percent.py ml-agents/mlagents/trainers/tests/test_simple_rl.py ml-agents/mlagents/trainers/exception.py ml-agents/mlagents/trainers/tests/test_distributions.py gym-unity/gym_unity/tests/test_gym.py utils/make_readme_table.py ml-agents/mlagents/tf_utils/tf.py ml-agents/mlagents/trainers/tests/test_ghost.py ml-agents/mlagents/trainers/buffer.py ml-agents-envs/mlagents_envs/side_channel/side_channel.py ml-agents-envs/mlagents_envs/side_channel/environment_parameters_channel.py ml-agents/mlagents/trainers/tests/test_subprocess_env_manager.py ml-agents/mlagents/trainers/subprocess_env_manager.py ml-agents/mlagents/trainers/agent_processor.py ml-agents-envs/mlagents_envs/communicator_objects/engine_configuration_pb2.py ml-agents-envs/mlagents_envs/tests/test_env_utils.py ml-agents/mlagents/trainers/tests/test_rl_trainer.py ml-agents-envs/mlagents_envs/rpc_communicator.py ml-agents/mlagents/trainers/training_status.py ml-agents-envs/mlagents_envs/communicator_objects/demonstration_meta_pb2.py ml-agents-envs/mlagents_envs/__init__.py gym-unity/setup.py ml-agents/mlagents/trainers/behavior_id_utils.py ml-agents/mlagents/trainers/tests/test_config_conversion.py ml-agents/mlagents/trainers/sac/network.py ml-agents/mlagents/trainers/policy/tf_policy.py ml-agents/mlagents/trainers/optimizer/__init__.py ml-agents-envs/mlagents_envs/registry/__init__.py ml-agents/mlagents/trainers/tests/simple_test_envs.py ml-agents/mlagents/trainers/tests/__init__.py ml-agents-envs/mlagents_envs/communicator_objects/unity_output_pb2.py ml-agents-envs/mlagents_envs/env_utils.py ml-agents-envs/mlagents_envs/communicator_objects/space_type_pb2.py ml-agents/mlagents/trainers/trainer_util.py ml-agents/mlagents/trainers/tests/test_trainer_util.py ml-agents-envs/mlagents_envs/logging_util.py ml-agents/mlagents/trainers/components/reward_signals/extrinsic/signal.py ml-agents/mlagents/trainers/sac/trainer.py ml-agents-envs/mlagents_envs/side_channel/side_channel_manager.py ml-agents/tests/yamato/training_int_tests.py ml-agents/mlagents/trainers/tests/test_sac.py ml-agents/mlagents/trainers/trajectory.py ml-agents/mlagents/trainers/settings.py ml-agents/mlagents/trainers/ppo/optimizer.py ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_initialization_input_pb2.py ml-agents-envs/mlagents_envs/base_env.py ml-agents-envs/mlagents_envs/communicator_objects/header_pb2.py ml-agents/mlagents/trainers/tests/test_stats.py ml-agents/mlagents/trainers/components/reward_signals/gail/model.py ml-agents/mlagents/trainers/tests/test_reward_signals.py ml-agents-envs/mlagents_envs/side_channel/stats_side_channel.py ml-agents/mlagents/trainers/components/reward_signals/gail/signal.py ml-agents-envs/mlagents_envs/tests/test_side_channel.py ml-agents/mlagents/trainers/tf/models.py ml-agents/mlagents/trainers/tf/distributions.py ml-agents-envs/mlagents_envs/registry/base_registry_entry.py ml-agents/mlagents/trainers/ghost/controller.py ml-agents/mlagents/trainers/sac/optimizer.py ml-agents/tests/yamato/standalone_build_tests.py ml-agents-envs/mlagents_envs/environment.py ml-agents/mlagents/trainers/tests/test_training_status.py ml-agents/mlagents/trainers/demo_loader.py ml-agents/mlagents/trainers/ghost/trainer.py ml-agents-envs/mlagents_envs/registry/binary_utils.py ml-agents/tests/yamato/editmode_tests.py ml-agents/mlagents/trainers/tests/test_settings.py ml-agents/mlagents/trainers/components/bc/module.py ml-agents-envs/mlagents_envs/communicator_objects/unity_input_pb2.py ml-agents-envs/mlagents_envs/tests/test_steps.py ml-agents/mlagents/trainers/tests/test_buffer.py ml-agents/mlagents/trainers/trainer/rl_trainer.py ml-agents/mlagents/trainers/tests/test_agent_processor.py ml-agents-envs/mlagents_envs/communicator_objects/unity_to_external_pb2_grpc.py ml-agents/tests/yamato/yamato_utils.py ml-agents/tests/yamato/scripts/run_llapi.py ml-agents/mlagents/trainers/stats.py ml-agents-envs/mlagents_envs/registry/unity_env_registry.py ml-agents/mlagents/trainers/tests/test_trajectory.py ml-agents/mlagents/trainers/optimizer/optimizer.py VerifyVersionCommand UnityGymException ActionFlattener UnityToGymWrapper create_mock_vector_steps test_gym_wrapper_multi_visual_and_vector test_gym_wrapper create_mock_group_spec test_branched_flatten setup_mock_unityenvironment test_gym_wrapper_visual test_gym_wrapper_single_visual_and_vector VerifyVersionCommand _get_frozen_graph_node_names export_policy_model _make_frozen_graph _get_output_node_names _get_input_node_names convert_frozen_to_onnx _enforce_onnx_conversion SerializationSettings _process_graph set_warnings_enabled generate_session_config ActionInfo AgentManager AgentProcessor AgentManagerQueue BarracudaWriter fuse print_known_operations compress Build sort lstm write fuse_batchnorm_weights trim mean gru Model summary Struct parse_args to_json rnn BehaviorIdentifiers get_global_agent_id create_name_behavior_id BufferException AgentBuffer StoreConfigFile _load_config DetectDefaultStoreTrue DetectDefault load_config _create_parser make_demo_buffer write_demo get_demo_files load_demonstration write_delimited demo_to_buffer EnvironmentParameterManager EnvManager EnvironmentStep SamplerException TrainerConfigError CurriculumError TrainerError MetaCurriculumError CurriculumLoadingError UnityTrainerException CurriculumConfigError write_timing_tree create_environment_factory write_run_options parse_command_line run_training write_training_status main run_cli get_version_string main parse_command_line ScheduleType TrainerSettings PPOSettings ConstantSettings GaussianSettings strict_to_cls RewardSignalSettings EnvironmentSettings ParameterRandomizationType EnvironmentParameterSettings check_and_structure RewardSignalType TrainerType MultiRangeUniformSettings HyperparamSettings NetworkSettings SACSettings UniformSettings SelfPlaySettings Lesson EngineSettings EncoderType RunOptions GAILSettings CheckpointSettings BehavioralCloningSettings ParameterRandomizationSettings ExportableSettings CompletionCriteriaSettings defaultdict_to_dict CuriositySettings SimpleEnvManager StatsWriter StatsSummary ConsoleWriter StatsReporter GaugeWriter TensorboardWriter StatsPropertyType CSVWriter worker EnvironmentResponse EnvironmentRequest UnityEnvWorker StepResponse SubprocessEnvManager EnvironmentCommand TrainerController TrainerFactory initialize_trainer handle_existing_directories StatusMetaData StatusType GlobalTrainingStatus AgentExperience Trajectory SplitObservations parse_args write_to_yaml_file convert convert_behaviors main remove_nones convert_samplers_and_curriculum convert_samplers BCModel BCModule create_reward_signal RewardSignal CuriosityModel CuriosityRewardSignal ExtrinsicRewardSignal GAILModel GAILRewardSignal GhostController GhostTrainer Optimizer TFOptimizer NNCheckpointManager NNCheckpoint Policy UnityPolicyException TFPolicy UnityPolicyException PPOOptimizer PPOTrainer get_gae discount_rewards SACPolicyNetwork SACTargetNetwork SACNetwork SACOptimizer SACTrainer simulate_rollout create_mock_pushblock_behavior_specs create_mock_banana_behavior_specs setup_test_behavior_specs create_steps_from_behavior_spec create_mock_3dball_behavior_specs make_fake_trajectory create_mock_steps RecordEnvironment clamp SimpleEnvironment MemoryEnvironment test_end_episode test_agent_deletion test_agent_manager_queue test_agentprocessor test_agent_manager test_agent_manager_stats create_mock_policy test_barracuda_converter test_policy_conversion test_bcmodule_rnn_update test_bcmodule_update test_bcmodule_constant_lr_update test_bcmodule_dc_visual_update create_bc_module test_bcmodule_defaults test_bcmodule_rnn_dc_update test_buffer_sample construct_fake_buffer test_num_experiences assert_array fakerandint test_buffer test_buffer_truncate test_convert test_convert_behaviors test_remove_nones test_unsupported_version_raises_error test_load_demo test_demo_mismatch test_edge_cases test_load_demo_dir test_multicategorical_distribution test_tanh_distribution test_gaussian_distribution test_sampler_conversion test_sampler_and_constant_conversion test_create_manager test_curriculum_raises_no_completion_criteria_conversion test_curriculum_conversion test_load_and_set dummy_config test_publish_queue test_process_trajectory basic_options test_run_training test_yaml_args test_bad_env_path test_commandline_args test_env_args test_create_input_placeholders create_behavior_spec test_min_visual_size test_load_save create_policy_mock test_normalization ModelVersionTest test_policy_evaluate _compare_two_policies test_trainer_increment_step test_trainer_update_policy test_ppo_optimizer_update test_ppo_optimizer_update_curiosity test_process_trajectory test_rl_functions test_add_get_policy _create_ppo_optimizer_ops_mock dummy_config test_ppo_optimizer_update_gail test_ppo_get_value_estimates test_gail_dc_visual sac_dummy_config reward_signal_update reward_signal_eval test_extrinsic extrinsic_dummy_config test_gail_rnn test_curiosity_cc test_gail_cc ppo_dummy_config test_curiosity_dc curiosity_dummy_config test_curiosity_visual test_curiosity_rnn create_optimizer_mock gail_dummy_config FakeTrainer create_rl_trainer test_rl_trainer test_summary_checkpoint test_advance test_clear_update_buffer test_sac_update_reward_signals test_add_get_policy create_sac_optimizer_mock test_sac_optimizer_update dummy_config test_advance test_sac_save_load_buffer check_dict_is_at_least test_environment_settings test_strict_to_cls test_memory_settings_validation check_if_different test_is_new_instance test_no_configuration test_env_parameter_structure test_exportable_settings test_trainersettings_structure test_reward_signal_structure test_simple_ghost_fails test_gail test_visual_advanced_sac _check_environment_trains test_visual_sac test_2d_ppo test_simple_sac test_simple_ghost default_reward_processor test_simple_asymm_ghost test_gail_visual_ppo test_simple_ppo test_gail_visual_sac test_recurrent_ppo DebugWriter test_recurrent_sac test_simple_asymm_ghost_fails test_visual_advanced_ppo test_visual_ppo test_2d_sac simple_record test_tensorboard_writer test_stat_reporter_add_summary_write test_tensorboard_writer_clear test_gauge_stat_writer_sanitize ConsoleWriterTest test_csv_writer test_stat_reporter_property MockEnvWorker mock_env_factory SubprocessEnvManagerTest test_subprocess_env_raises_errors create_worker_mock test_subprocess_env_endtoend basic_mock_brain test_take_action_returns_action_info_when_available test_convert_version_string test_checkpoint_writes_tf_and_nn_checkpoints test_take_action_returns_nones_on_missing_values test_take_action_returns_empty_with_no_agents FakePolicy test_initialization_seed test_start_learning_trains_until_max_steps_then_saves basic_trainer_controller trainer_controller_with_take_step_mocks test_advance_adds_experiences_to_trainer_and_trains trainer_controller_with_start_learning_mocks test_start_learning_trains_forever_if_no_train_model test_initialize_ppo_trainer test_load_config_invalid_yaml test_load_config_missing_file test_handles_no_config_provided dummy_config test_load_config_valid_yaml test_existing_directories test_globaltrainingstatus test_model_management StatsMetaDataTest test_trajectory_to_agentbuffer test_split_obs np_zeros_no_float64 np_array_no_float64 _check_no_float64 np_ones_no_float64 OutputDistribution DiscreteOutputDistribution MultiCategoricalDistribution GaussianDistribution ModelUtils Tensor3DShape NormalizerTensors get_layer_shape pool_to_HW flatten sqr_diff process_layer process_model get_layer_rank slow_but_stable_topological_sort get_attr basic_lstm ModelBuilderContext order_by get_epsilon get_tensor_dtype replace_strings_in_list debug embody by_op get_tensor_dims strided_slice remove_duplicates_from_list axis_to_barracuda by_name locate_actual_output_node convert strides_to_HW get_tensor_data very_slow_but_stable_topological_sort gru RLTrainer Trainer main check_coverage main clean_previous_results TestResults parse_results main main main run_training run_inference find_executables override_config_file init_venv get_unity_executable_path override_legacy_config_file get_base_path run_standalone_build checkout_csharp_version _override_config_dict undo_git_checkout get_base_output_path test_closing test_run_environment test_closing test_run_environment VerifyVersionCommand ActionType BehaviorMapping TerminalStep DecisionSteps BehaviorSpec TerminalSteps BaseEnv DecisionStep Communicator UnityEnvironment validate_environment_path launch_executable get_platform UnityCommunicatorStoppedException UnityObservationException UnityWorkerInUseException UnityException UnityCommunicationException UnityTimeOutException UnitySideChannelException UnityEnvironmentException UnityActionException get_logger set_log_level MockCommunicator RpcCommunicator UnityToExternalServicerImplementation _generate_split_indices process_pixels behavior_spec_from_proto _raise_on_nan_and_inf observation_to_np_array steps_from_proto _process_vector_observation _process_visual_observation _get_thread_timer TimerNode merge_gauges hierarchical_timer add_metadata get_timer_tree get_timer_root reset_timers get_timer_stack_for_thread set_gauge timed GaugeNode TimerStack UnityToExternalProtoServicer add_UnityToExternalProtoServicer_to_server UnityToExternalProtoStub BaseRegistryEntry ZipFileWithProgress get_tmp_dir get_local_binary_path_if_exists get_local_binary_path load_local_manifest load_remote_manifest download_and_extract_zip print_progress RemoteRegistryEntry UnityEnvRegistry EngineConfigurationChannel EngineConfig EnvironmentParametersChannel FloatPropertiesChannel IncomingMessage OutgoingMessage RawBytesChannel SideChannel SideChannelManager StatsAggregationMethod StatsSideChannel test_initialization test_reset test_returncode_to_signal_name test_log_file_path_is_set test_close test_step test_port_defaults test_handles_bad_filename test_check_communication_compatibility test_set_logging_level test_validate_path mock_glob_method test_launch_executable test_validate_path_empty create_registry test_basic_in_registry delete_binaries test_rpc_communicator_checks_port_on_create test_rpc_communicator_create_multiple_workers test_rpc_communicator_close test_batched_step_result_from_proto_raises_on_nan test_process_pixels test_process_visual_observation_bad_shape test_agent_behavior_spec_from_proto proto_from_steps_and_action test_batched_step_result_from_proto test_action_masking_continuous test_action_masking_discrete_1 generate_list_agent_proto generate_uncompressed_proto_obs test_batched_step_result_from_proto_raises_on_infinite generate_compressed_proto_obs test_vector_observation proto_from_steps test_action_masking_discrete generate_compressed_data test_action_masking_discrete_2 test_process_pixels_gray test_process_visual_observation test_raw_bytes test_int_channel test_message_float_list IntChannel test_engine_configuration test_message_bool test_message_string test_float_properties test_environment_parameters test_message_int32 test_stats_channel test_message_float32 test_decision_steps test_specs test_terminal_steps test_empty_terminal_steps test_action_generator test_empty_decision_steps test_timers decorated_func table_line ReleaseInfo validate_packages main NonTrivialPEP420PackageFinder main get_release_tag check_file test_pattern main check_all_files git_ls_files set_academy_version_string _escape_non_none extract_version_string print_release_tag_commands check_versions set_package_version set_version set_extension_package_version MagicMock create_mock_vector_steps UnityToGymWrapper sample create_mock_group_spec setup_mock_unityenvironment step MagicMock create_mock_vector_steps UnityToGymWrapper create_mock_group_spec setup_mock_unityenvironment MagicMock create_mock_vector_steps UnityToGymWrapper sample create_mock_group_spec setup_mock_unityenvironment step MagicMock create_mock_vector_steps UnityToGymWrapper sample reset create_mock_group_spec setup_mock_unityenvironment step MagicMock create_mock_vector_steps UnityToGymWrapper sample reset create_mock_group_spec setup_mock_unityenvironment step tuple CONTINUOUS range DISCRETE list array range BehaviorMapping convert_to_barracuda convert convert_to_onnx _make_frozen_graph _enforce_onnx_conversion convert_frozen_to_onnx info model_path makedirs tf_optimize make_model _get_output_node_names _get_input_node_names info brain_name optimize_graph _get_frozen_graph_node_names add _get_frozen_graph_node_names name add node set brain_name info set_verbosity ConfigProto join isdir print replaceFilenameExtension add_argument exit verbose source_file ArgumentParser target_file sqrt topologicalSort list hasattr layers addEdge Graph print inputs set len list hasattr layers print filter match trim_model compile data layers print tensors float16 replace layers dumps data dtype layers isinstance print name tensors inputs outputs shape zip array_without_brackets to_json globals Build array_equal pool reduce Build tanh mad tanh mul Build concat add sigmoid sub mad _ tanh mul Build concat add sigmoid mad print sorted keys add_argument_group add_argument ArgumentParser resequence_and_append obs from_observations steps_from_proto vector_actions AgentBuffer append reset_agent vector_observations array visual_observations enumerate make_demo_buffer load_demonstration zip observation_shapes enumerate isdir isfile get_demo_files write SerializeToString _EncodeVarint len parse_args start_learning join save_state join join train_model seed API_VERSION load_model print debug run_training dumps randint set_log_level set_warnings_enabled warning add_timer_metadata as_dict __version__ DEBUG INFO get_version_string parse_command_line run_cli add_argument ArgumentParser from_dict experiment_config_path load_config fields_dict update items list check_and_structure structure register_structure_hook unstructure defaultdict dict_to_defaultdict register_structure_hook register_unstructure_hook structure RLock get_timer_root reset_timers put _send_response StepResponse env_factory list behavior_specs _generate_all_results set_log_level apply get_and_reset_stats set_actions StatsSideChannel action set_configuration EngineConfigurationChannel payload BEHAVIOR_SPECS STEP EnvironmentParametersChannel items EnvironmentResponse isinstance reset RESET step join SACTrainer GhostTrainer PPOTrainer get_minimum_reward_buffer_size trainer_type isdir get update list items copy MemorySettings structure to_settings list items isinstance pop items list print dict pop items list get print set add append keys range len get pop unstructure print convert_behaviors convert_samplers_and_curriculum convert_samplers output_config_path curriculum remove_nones print write_to_yaml_file convert sampler trainer_config_path parse_args get rcls list zeros_like size reversed range append discount_rewards arange ones BehaviorSpec append array int ones AgentExperience append zeros sum range len pop action_shape to_agentbuffer make_fake_trajectory is_action_discrete observation_shapes int BehaviorSpec zeros Mock Mock ActionInfo publish_trajectory_queue range create_mock_steps AgentProcessor empty create_mock_policy add_experiences Mock assert_has_calls ActionInfo publish_trajectory_queue range call create_mock_steps append AgentProcessor empty create_mock_policy add_experiences Mock assert_has_calls ActionInfo end_episode publish_trajectory_queue range call create_mock_steps append AgentProcessor empty create_mock_policy add_experiences AgentManager create_mock_policy Mock get_nowait AgentManagerQueue put Mock assert_any_call remove record_environment_stats AgentManager add_writer StatsReporter write_stats join remove _get_candidate_names convert _get_default_tempdir dirname abspath isfile next TrainerSettings create_policy_mock SerializationSettings model_path reset_default_graph checkpoint TrainerSettings TFPolicy initialize_or_load BehavioralCloningSettings create_bc_module create_mock_3dball_behavior_specs update items list create_mock_3dball_behavior_specs BehavioralCloningSettings create_bc_module update items list create_mock_3dball_behavior_specs BehavioralCloningSettings current_lr create_bc_module update items list create_mock_3dball_behavior_specs BehavioralCloningSettings create_bc_module update items list create_mock_banana_behavior_specs BehavioralCloningSettings create_bc_module update items list create_mock_banana_behavior_specs BehavioralCloningSettings create_bc_module flatten list range len append range AgentBuffer resequence_and_append get_batch construct_fake_buffer assert_array make_mini_batch AgentBuffer reset_agent array resequence_and_append sample_mini_batch construct_fake_buffer AgentBuffer resequence_and_append construct_fake_buffer AgentBuffer resequence_and_append list construct_fake_buffer AgentBuffer truncate values safe_load convert_behaviors safe_load convert enumerate remove_nones load_demonstration demo_to_buffer dirname abspath load_demonstration demo_to_buffer dirname abspath dirname abspath dirname abspath mock_open BytesIO DemonstrationMetaProto write_delimited from_dict safe_load curriculum from_dict safe_load curriculum from_dict safe_load curriculum from_dict safe_load EnvironmentParameterManager environment_parameters create_tf_graph setup_test_behavior_specs load_weights init_load_weights zip assert_array_equal get_weights PPOTrainer create_policy GhostController GhostTrainer PPOTrainer subscribe_trajectory_queue setup_test_behavior_specs put advance make_fake_trajectory from_name_behavior_id AgentManagerQueue add_policy brain_name create_policy GhostController GhostTrainer PPOTrainer simulate_rollout get_nowait setup_test_behavior_specs _swap_snapshots advance publish_policy_queue from_name_behavior_id AgentManagerQueue add_policy brain_name create_policy clear safe_load MagicMock parse_command_line clear parse_command_line parse_command_line DISCRETE int BehaviorSpec create_input_placeholders observation_shapes create_behavior_spec TFPolicy setup_test_behavior_specs TrainerSettings join _set_step initialize_or_load create_policy_mock SerializationSettings model_path _compare_two_policies checkpoint list evaluate agent_id create_steps_from_behavior_spec behavior_spec assert_array_equal TrainerSettings list evaluate agent_id create_steps_from_behavior_spec behavior_spec create_policy_mock reset_default_graph TrainerSettings TFPolicy update_normalization to_agentbuffer setup_test_behavior_specs make_fake_trajectory zeros range run evolve PPOOptimizer TFPolicy setup_test_behavior_specs update simulate_rollout behavior_spec _create_ppo_optimizer_ops_mock reset_default_graph update simulate_rollout behavior_spec _create_ppo_optimizer_ops_mock reset_default_graph update simulate_rollout behavior_spec _create_ppo_optimizer_ops_mock reset_default_graph items list get_trajectory_value_estimates to_agentbuffer make_fake_trajectory _create_ppo_optimizer_ops_mock next_obs reset_default_graph assert_array_almost_equal array discount_rewards Mock brain_name _increment_step from_name_behavior_id assert_called_with add_policy PPOTrainer _update_policy simulate_rollout setup_test_behavior_specs MemorySettings from_name_behavior_id add_policy PPOTrainer create_policy list values Mock brain_name from_name_behavior_id add_policy PPOTrainer PPOOptimizer TFPolicy setup_test_behavior_specs SACOptimizer simulate_rollout behavior_spec evaluate_batch simulate_rollout prepare_update _execute_model behavior_spec update_dict make_mini_batch policy BehavioralCloningSettings create_optimizer_mock reward_signal_eval reward_signal_update create_optimizer_mock reward_signal_eval reward_signal_update create_optimizer_mock reward_signal_eval reward_signal_update create_optimizer_mock reward_signal_eval reward_signal_update create_optimizer_mock reward_signal_eval reward_signal_update create_optimizer_mock reward_signal_eval reward_signal_update create_optimizer_mock reward_signal_eval reward_signal_update create_optimizer_mock reward_signal_eval reward_signal_update TrainerSettings FakeTrainer set_is_policy_updating end_episode list create_rl_trainer values items list construct_fake_buffer create_rl_trainer _clear_update_buffer Mock create_rl_trainer set_is_policy_updating subscribe_trajectory_queue advance put make_fake_trajectory publish_policy_queue AgentManagerQueue add_policy get_nowait range Mock list assert_has_calls create_rl_trainer subscribe_trajectory_queue summary_freq checkpoint_interval put make_fake_trajectory publish_policy_queue advance AgentManagerQueue add_policy get_nowait range TFPolicy setup_test_behavior_specs SACOptimizer update simulate_rollout create_sac_optimizer_mock behavior_spec reset_default_graph simulate_rollout create_sac_optimizer_mock behavior_spec update_reward_signals reset_default_graph SACTrainer save_model simulate_rollout num_experiences setup_test_behavior_specs behavior_spec from_name_behavior_id add_policy brain_name create_policy SACTrainer list SACTrainer values setup_test_behavior_specs from_name_behavior_id brain_name create_policy list items items list isinstance zip RunOptions check_if_different TrainerSettings RunOptions structure structure structure RunOptions from_dict check_dict_is_at_least safe_load as_dict EnvironmentSettings print EnvironmentParameterManager evolve SimpleEnvironment _check_environment_trains hyperparameters evolve SimpleEnvironment _check_environment_trains hyperparameters evolve SimpleEnvironment _check_environment_trains network_settings evolve SimpleEnvironment hyperparameters _check_environment_trains network_settings evolve MemoryEnvironment hyperparameters _check_environment_trains evolve SimpleEnvironment _check_environment_trains hyperparameters evolve SimpleEnvironment _check_environment_trains hyperparameters evolve SimpleEnvironment _check_environment_trains network_settings evolve SimpleEnvironment hyperparameters _check_environment_trains network_settings evolve MemoryEnvironment hyperparameters _check_environment_trains evolve SimpleEnvironment SelfPlaySettings _check_environment_trains evolve SimpleEnvironment SelfPlaySettings _check_environment_trains evolve SimpleEnvironment SelfPlaySettings _check_environment_trains evolve SimpleEnvironment SelfPlaySettings _check_environment_trains evolve SimpleEnvironment BehavioralCloningSettings _check_environment_trains simple_record evolve SimpleEnvironment BehavioralCloningSettings hyperparameters _check_environment_trains simple_record evolve SimpleEnvironment BehavioralCloningSettings hyperparameters _check_environment_trains simple_record clear assert_called_once_with Mock get_stats_summaries add_stat add_writer StatsReporter float range write_stats clear Mock add_property add_writer StatsReporter assert_called_once_with sleep TensorboardWriter StatsSummary write_stats close SubprocessEnvManager simple_env_factory _check_environment_trains default_config default_config close SubprocessEnvManager MagicMock TrainerSettings basic_mock_brain BehaviorSpec get_action empty FakePolicy TrainerSettings MagicMock basic_mock_brain DecisionSteps get_action array FakePolicy TrainerSettings MagicMock basic_mock_brain ActionInfo DecisionSteps get_action array FakePolicy _convert_version_string TrainerSettings sess MagicMock basic_mock_brain graph SerializationSettings assert_called_once_with brain_name checkpoint FakePolicy GhostController MagicMock GhostController TrainerController MagicMock assert_called_with MagicMock start_learning assert_called_once MagicMock assert_not_called start_learning assert_called_once MagicMock MagicMock assert_called_once MagicMock advance add assert_not_called behaviors behaviors TrainerFactory generate _load_config StringIO mkdir join handle_existing_directories join set_parameter_state LESSON_NUM load_state NOTAREALKEY get_parameter_state save_state join NNCheckpoint time add_checkpoint set_parameter_state CHECKPOINTS track_final_checkpoint append from_observations range ones items list to_agentbuffer add set make_fake_trajectory extract_stack filename get __old_np_array _check_no_float64 get _check_no_float64 __old_np_zeros get __old_np_ones _check_no_float64 endswith len print HasField hasattr get_attr isinstance get_attr tensor_shape ndarray isinstance shape int_val bool_val float_val ListFields name ndarray isinstance str tensor_content ndarray product isinstance get_tensor_dtype print get_tensor_dims unpack int_val bool_val array float_val enter append add set Build mul sub insert Build tolist append range len locate_actual_output_node name find_tensor_by_name split locate_actual_output_node name lstm find_tensor_by_name find_forget_bias split get_layer_shape id Struct tensor get_layer_rank layer_ranks hasattr name patch_data rank input_shapes out_shapes input get_attr append replace_strings_in_list tensors embody astype op inputs zip enumerate print float32 patch_data_fn model_tensors map_ignored_layer_to_its_input co_argcount len items list hasattr get_tensors name print process_layer eval slow_but_stable_topological_sort ModelBuilderContext sort assign_ids pop range insert len layers verbose Struct process_model open print_known_operations fuse compress node GraphDef Model dims_to_barracuda_shape insert get_tensor_dims inputs MessageToJson ParseFromString cleanup_layers read memories sort write trim summary print_supported_ops print join exit walk float check_coverage join remove mkdir rmdir exists documentElement getAttribute parse join clean_previous_results parse_results get_unity_executable_path exit returncode get_base_path copy2 init_venv add_argument ArgumentParser split strip run_standalone_build override_config_file run_inference get_base_path rename abspath checkout_csharp_version exists run dirname get_base_output_path init_venv override_legacy_config_file copy int time join print run_standalone_build makedirs find_executables join time print run python run_training csharp exists join move get_unity_executable_path print makedirs dirname get_base_output_path run join X_OK frozenset splitext append access walk check_call check_call check_call list _override_config_dict values items list isinstance update list values check_call str UnityToGymWrapper print step reset sample UnityEnvironment range reset UnityEnvironment close UnityToGymWrapper get_steps is_action_discrete format EngineConfigurationChannel randn set_configuration_parameters discrete_action_branches len action_size any set_actions is_action_continuous column_stack join basename replace glob debug getcwd normpath validate_environment_path debug add setLevel getLogger basicConfig setLevel tuple vector_action_size mean reshape array data compressed_data reshape process_pixels shape array mean isnan array _raise_on_nan_and_inf sum is_action_discrete _generate_split_indices ones discrete_action_branches len astype _raise_on_nan_and_inf any cast split append _process_vector_observation bool _process_visual_observation array observation_shapes enumerate range len get_ident TimerStack perf_counter push items list merge reset method_handlers_generic_handler add_generic_rpc_handlers download_and_extract_zip get_local_binary_path_if_exists debug range glob hexdigest join get_tmp_dir join chmod gettempdir makedirs uuid4 join int str remove get_tmp_dir exists chmod print glob rmtree urlopen print_progress hexdigest print int min max uuid4 join str get_tmp_dir load_local_manifest urlopen UnityEnvironment close MockCommunicator UnityEnvironment MockCommunicator _executable_args UnityEnvironment MockCommunicator index get_steps obs close reset MockCommunicator zip UnityEnvironment observation_shapes len get_steps obs zip ones step close MockCommunicator set_actions zeros UnityEnvironment observation_shapes len UnityEnvironment close MockCommunicator validate_environment_path validate_environment_path launch_executable PermissionError set_log_level rmtree get_tmp_dir RemoteRegistryEntry register UnityEnvRegistry create_registry make close reset step range delete_binaries close RpcCommunicator close RpcCommunicator close RpcCommunicator list extend ObservationProto AgentInfoProto append prod range len fromarray uint8 BytesIO astype save ObservationProto generate_compressed_data extend shape ObservationProto shape tolist extend obs concatenate action_mask agent_id ObservationProto AgentInfoProto append generate_uncompressed_proto_obs proto_from_steps generate_compressed_data process_pixels rand generate_compressed_data process_pixels rand _process_vector_observation generate_list_agent_proto enumerate generate_compressed_proto_obs rand extend AgentInfoProto _process_visual_observation generate_uncompressed_proto_obs generate_compressed_proto_obs rand AgentInfoProto extend list sort CONTINUOUS agent_id BehaviorSpec steps_from_proto generate_list_agent_proto range BehaviorSpec steps_from_proto DISCRETE generate_list_agent_proto action_mask BehaviorSpec steps_from_proto DISCRETE generate_list_agent_proto action_mask BehaviorSpec steps_from_proto DISCRETE generate_list_agent_proto action_mask CONTINUOUS BehaviorSpec steps_from_proto generate_list_agent_proto action_mask BrainParametersProto behavior_spec_from_proto extend CONTINUOUS generate_list_agent_proto BehaviorSpec CONTINUOUS generate_list_agent_proto BehaviorSpec generate_side_channel_messages process_side_channel_message send_int IntChannel FloatPropertiesChannel process_side_channel_message generate_side_channel_messages get_property set_property uuid4 process_side_channel_message generate_side_channel_messages RawBytesChannel send_raw_data get_and_clear_received_messages len buffer read_bool append write_bool IncomingMessage range OutgoingMessage buffer write_int32 read_int32 IncomingMessage OutgoingMessage IncomingMessage write_float32 buffer read_float32 OutgoingMessage read_string write_string buffer IncomingMessage OutgoingMessage IncomingMessage buffer OutgoingMessage read_float32_list write_float32_list set_configuration channel_id EngineConfigurationChannel generate_side_channel_messages process_side_channel_message set_configuration_parameters RawBytesChannel read_float32 read_int32 IncomingMessage get_and_clear_received_messages default_config channel_id generate_side_channel_messages process_side_channel_message read_string set_float_parameter RawBytesChannel read_float32 read_int32 IncomingMessage EnvironmentParametersChannel IncomingMessage write_float32 write_string buffer write_int32 get_and_reset_stats on_message_received StatsSideChannel OutgoingMessage DecisionSteps action_mask empty BehaviorSpec TerminalSteps empty BehaviorSpec BehaviorSpec create_random_action enumerate BehaviorSpec create_empty_action set_gauge TimerStack startswith print find_packages find validate_packages remove replace frozenset endswith set add walk print git_ls_files get_release_tag check_all_files compile join print extract_version_string set values join format set_academy_version_string print set_package_version set_extension_package_version enumerate split print | <img src="docs/images/image-banner.png" align="middle" width="3000"/> # Unity ML-Agents Toolkit [](https://github.com/Unity-Technologies/ml-agents/tree/release_4_docs/docs/) [](LICENSE) ([latest release](https://github.com/Unity-Technologies/ml-agents/releases/tag/latest_release)) ([all releases](https://github.com/Unity-Technologies/ml-agents/releases)) **The Unity Machine Learning Agents Toolkit** (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents. Agents can be trained using reinforcement learning, imitation learning, neuroevolution, or other machine learning methods through a | 3,322 |
porouspaper/svo-games | ['unity'] | ['Unity: A General Platform for Intelligent Agents'] | ml-agents-envs/mlagents_envs/communicator_objects/capabilities_pb2.py ml-agents/mlagents/trainers/components/reward_signals/curiosity/model.py ml-agents-envs/mlagents_envs/communicator_objects/command_pb2.py ml-agents/mlagents/trainers/cli_utils.py ml-agents/mlagents/trainers/run_experiment.py ml-agents-envs/mlagents_envs/mock_communicator.py ml-agents/mlagents/trainers/policy/__init__.py ml-agents-envs/mlagents_envs/communicator_objects/unity_to_external_pb2.py ml-agents-envs/mlagents_envs/communicator.py gym-unity/gym_unity/envs/__init__.py ml-agents-envs/mlagents_envs/communicator_objects/brain_parameters_pb2.py ml-agents/mlagents/trainers/learn.py ml-agents/mlagents/trainers/tests/test_sampler_class.py ml-agents/mlagents/trainers/meta_curriculum.py ml-agents/mlagents/trainers/tests/test_barracuda_converter.py ml-agents-envs/mlagents_envs/side_channel/raw_bytes_channel.py ml-agents/mlagents/trainers/trainer/trainer.py gym-unity/gym_unity/__init__.py ml-agents-envs/mlagents_envs/side_channel/__init__.py utils/validate_meta_files.py ml-agents/mlagents/trainers/trainer_controller.py ml-agents/mlagents/trainers/components/bc/model.py ml-agents/mlagents/trainers/tests/test_curriculum.py ml-agents/mlagents/trainers/action_info.py ml-agents/mlagents/trainers/tests/test_ppo.py ml-agents/mlagents/tf_utils/__init__.py ml-agents/mlagents/trainers/components/reward_signals/__init__.py ml-agents-envs/setup.py ml-agents-envs/mlagents_envs/side_channel/engine_configuration_channel.py ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_output_pb2.py ml-agents/mlagents/trainers/tests/mock_brain.py ml-agents/mlagents/trainers/tests/test_bcmodule.py ml-agents/mlagents/trainers/tests/test_trainer_controller.py ml-agents-envs/mlagents_envs/side_channel/incoming_message.py ml-agents/mlagents/trainers/components/reward_signals/reward_signal_factory.py ml-agents-envs/mlagents_envs/rpc_utils.py ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_initialization_output_pb2.py ml-agents/setup.py ml-agents/tests/yamato/setup_venv.py ml-agents/mlagents/trainers/barracuda.py ml-agents/mlagents/trainers/optimizer/tf_optimizer.py utils/run_markdown_link_check.py ml-agents/mlagents/trainers/env_manager.py ml-agents/mlagents/trainers/ppo/trainer.py ml-agents/mlagents/trainers/policy/policy.py ml-agents-envs/mlagents_envs/communicator_objects/agent_action_pb2.py ml-agents/mlagents/model_serialization.py ml-agents-envs/mlagents_envs/tests/test_rpc_communicator.py ml-agents-envs/mlagents_envs/tests/test_envs.py ml-agents/mlagents/trainers/brain.py utils/validate_inits.py ml-agents-envs/mlagents_envs/side_channel/float_properties_channel.py ml-agents/mlagents/trainers/tests/test_meta_curriculum.py ml-agents/mlagents/trainers/components/reward_signals/curiosity/signal.py ml-agents/mlagents/trainers/simple_env_manager.py ml-agents-envs/mlagents_envs/side_channel/outgoing_message.py ml-agents-envs/mlagents_envs/exception.py ml-agents/mlagents/trainers/curriculum.py ml-agents-envs/mlagents_envs/registry/remote_registry_entry.py ml-agents/mlagents/trainers/tests/test_policy.py ml-agents/mlagents/trainers/trainer/__init__.py ml-agents/mlagents/trainers/upgrade_config.py ml-agents-envs/mlagents_envs/communicator_objects/unity_message_pb2.py ml-agents/mlagents/trainers/tests/test_learn.py ml-agents/mlagents/trainers/policy/nn_policy.py ml-agents/tests/yamato/scripts/run_gym.py ml-agents-envs/mlagents_envs/communicator_objects/agent_info_pb2.py ml-agents/mlagents/trainers/tests/test_demo_loader.py ml-agents-envs/mlagents_envs/communicator_objects/observation_pb2.py utils/validate_versions.py ml-agents-envs/mlagents_envs/tests/test_rpc_utils.py ml-agents/mlagents/trainers/models.py ml-agents-envs/mlagents_envs/tests/test_timers.py ml-agents/mlagents/trainers/__init__.py ml-agents-envs/mlagents_envs/communicator_objects/custom_reset_parameters_pb2.py ml-agents-envs/mlagents_envs/tests/test_registry.py ml-agents-envs/mlagents_envs/communicator_objects/agent_info_action_pair_pb2.py Gardening Game/Library/PackageCache/[email protected]/Tools/tensorflow_to_barracuda.py ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_input_pb2.py ml-agents/mlagents/trainers/tests/test_nn_policy.py ml-agents-envs/mlagents_envs/timers.py ml-agents/tests/yamato/check_coverage_percent.py ml-agents/mlagents/trainers/tests/test_simple_rl.py ml-agents/mlagents/trainers/exception.py ml-agents/mlagents/trainers/tests/test_distributions.py Gardening Game/Library/PackageCache/[email protected]/Tools/barracuda.py gym-unity/gym_unity/tests/test_gym.py utils/make_readme_table.py ml-agents/mlagents/tf_utils/tf.py ml-agents/mlagents/trainers/tests/test_ghost.py ml-agents/mlagents/trainers/buffer.py ml-agents-envs/mlagents_envs/side_channel/side_channel.py ml-agents-envs/mlagents_envs/side_channel/environment_parameters_channel.py ml-agents/mlagents/trainers/tests/test_subprocess_env_manager.py ml-agents/mlagents/trainers/subprocess_env_manager.py ml-agents/mlagents/trainers/tensorflow_to_barracuda.py ml-agents/mlagents/trainers/agent_processor.py ml-agents-envs/mlagents_envs/communicator_objects/engine_configuration_pb2.py ml-agents-envs/mlagents_envs/tests/test_env_utils.py ml-agents/mlagents/trainers/tests/test_rl_trainer.py ml-agents-envs/mlagents_envs/rpc_communicator.py ml-agents/mlagents/trainers/training_status.py ml-agents-envs/mlagents_envs/communicator_objects/demonstration_meta_pb2.py ml-agents-envs/mlagents_envs/__init__.py gym-unity/setup.py ml-agents/mlagents/trainers/behavior_id_utils.py ml-agents/mlagents/trainers/tests/test_config_conversion.py ml-agents/mlagents/trainers/sac/network.py ml-agents/mlagents/trainers/distributions.py ml-agents/mlagents/trainers/policy/tf_policy.py ml-agents/mlagents/trainers/optimizer/__init__.py ml-agents-envs/mlagents_envs/registry/__init__.py ml-agents/mlagents/trainers/tests/simple_test_envs.py ml-agents/mlagents/trainers/tests/__init__.py ml-agents-envs/mlagents_envs/communicator_objects/unity_output_pb2.py ml-agents-envs/mlagents_envs/env_utils.py ml-agents-envs/mlagents_envs/communicator_objects/space_type_pb2.py ml-agents/mlagents/trainers/trainer_util.py ml-agents/mlagents/trainers/tests/test_trainer_util.py ml-agents-envs/mlagents_envs/logging_util.py ml-agents/mlagents/trainers/components/reward_signals/extrinsic/signal.py ml-agents/mlagents/trainers/sac/trainer.py ml-agents-envs/mlagents_envs/side_channel/side_channel_manager.py ml-agents/mlagents/trainers/sampler_class.py ml-agents/tests/yamato/training_int_tests.py ml-agents/mlagents/trainers/tests/test_sac.py ml-agents/mlagents/trainers/trajectory.py ml-agents/mlagents/trainers/settings.py ml-agents/mlagents/trainers/ppo/optimizer.py ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_initialization_input_pb2.py ml-agents-envs/mlagents_envs/base_env.py ml-agents-envs/mlagents_envs/communicator_objects/header_pb2.py ml-agents/mlagents/trainers/tests/test_stats.py ml-agents/mlagents/trainers/components/reward_signals/gail/model.py ml-agents/mlagents/trainers/tests/test_reward_signals.py ml-agents-envs/mlagents_envs/side_channel/stats_side_channel.py ml-agents/mlagents/trainers/components/reward_signals/gail/signal.py ml-agents-envs/mlagents_envs/tests/test_side_channel.py ml-agents-envs/mlagents_envs/registry/base_registry_entry.py ml-agents/mlagents/trainers/ghost/controller.py ml-agents/mlagents/trainers/sac/optimizer.py ml-agents/tests/yamato/standalone_build_tests.py ml-agents-envs/mlagents_envs/environment.py ml-agents/mlagents/trainers/tests/test_training_status.py ml-agents/mlagents/trainers/demo_loader.py ml-agents/mlagents/trainers/ghost/trainer.py ml-agents-envs/mlagents_envs/registry/binary_utils.py ml-agents/tests/yamato/editmode_tests.py ml-agents/mlagents/trainers/tests/test_settings.py ml-agents/mlagents/trainers/components/bc/module.py ml-agents-envs/mlagents_envs/communicator_objects/unity_input_pb2.py ml-agents-envs/mlagents_envs/tests/test_steps.py ml-agents/mlagents/trainers/tests/test_buffer.py ml-agents/mlagents/trainers/trainer/rl_trainer.py Gardening Game/Library/PackageCache/[email protected]/Tools/keras_to_barracuda.py ml-agents/mlagents/trainers/tests/test_agent_processor.py ml-agents-envs/mlagents_envs/communicator_objects/unity_to_external_pb2_grpc.py ml-agents/mlagents/trainers/brain_conversion_utils.py ml-agents/tests/yamato/yamato_utils.py ml-agents/tests/yamato/scripts/run_llapi.py ml-agents/mlagents/trainers/stats.py ml-agents-envs/mlagents_envs/registry/unity_env_registry.py ml-agents/mlagents/trainers/tests/test_trajectory.py ml-agents/mlagents/trainers/optimizer/optimizer.py Struct fuse print_known_operations compress lstm fuse_batchnorm_weights Model parse_args BarracudaWriter Build mean rnn simplify_names sort write trim summary to_json gru setup_constants get_epsilon replace_strings_in_list nested_model embody extract_strings process_model convert input_layer flatten ModelBuilderContext get_input_layer_shape get_layer_shape pool_to_HW flatten sqr_diff process_layer process_model get_layer_rank slow_but_stable_topological_sort get_attr basic_lstm ModelBuilderContext order_by get_epsilon get_tensor_dtype replace_strings_in_list debug embody by_op get_tensor_dims strided_slice remove_duplicates_from_list axis_to_barracuda by_name locate_actual_output_node convert strides_to_HW get_tensor_data very_slow_but_stable_topological_sort gru VerifyVersionCommand UnityGymException ActionFlattener UnityToGymWrapper create_mock_vector_steps test_gym_wrapper_multi_visual_and_vector test_gym_wrapper create_mock_group_spec test_branched_flatten setup_mock_unityenvironment test_gym_wrapper_visual test_gym_wrapper_single_visual_and_vector VerifyVersionCommand _get_frozen_graph_node_names export_policy_model _make_frozen_graph _get_output_node_names _get_input_node_names convert_frozen_to_onnx _enforce_onnx_conversion SerializationSettings _process_graph set_warnings_enabled generate_session_config MetaCurriculum ActionInfo AgentManager AgentProcessor AgentManagerQueue BarracudaWriter fuse print_known_operations compress Build sort lstm write fuse_batchnorm_weights trim mean gru Model summary Struct parse_args to_json rnn BehaviorIdentifiers create_name_behavior_id BrainParameters CameraResolution get_global_agent_id behavior_spec_to_brain_parameters BufferException AgentBuffer StoreConfigFile _load_config DetectDefaultStoreTrue DetectDefault load_config _create_parser Curriculum make_demo_buffer write_demo get_demo_files load_demonstration write_delimited demo_to_buffer OutputDistribution DiscreteOutputDistribution MultiCategoricalDistribution GaussianDistribution EnvManager EnvironmentStep SamplerException TrainerConfigError CurriculumError TrainerError MetaCurriculumError CurriculumLoadingError UnityTrainerException CurriculumConfigError write_timing_tree create_sampler_manager create_environment_factory write_run_options parse_command_line run_training write_training_status try_create_meta_curriculum main run_cli get_version_string EncoderType NormalizerTensors ScheduleType ModelUtils main parse_command_line MultiRangeUniformSampler UniformSampler SamplerFactory SamplerManager GaussianSampler Sampler TrainerSettings PPOSettings strict_to_cls RewardSignalSettings EnvironmentSettings check_and_structure RewardSignalType TrainerType HyperparamSettings NetworkSettings SACSettings SelfPlaySettings EngineSettings RunOptions GAILSettings CurriculumSettings CheckpointSettings BehavioralCloningSettings ExportableSettings defaultdict_to_dict CuriositySettings SimpleEnvManager StatsWriter StatsSummary ConsoleWriter StatsReporter GaugeWriter TensorboardWriter StatsPropertyType CSVWriter worker EnvironmentResponse EnvironmentRequest UnityEnvWorker StepResponse SubprocessEnvManager EnvironmentCommand get_layer_shape pool_to_HW flatten sqr_diff process_layer process_model get_layer_rank slow_but_stable_topological_sort get_attr basic_lstm ModelBuilderContext order_by get_epsilon get_tensor_dtype replace_strings_in_list debug embody by_op get_tensor_dims strided_slice remove_duplicates_from_list axis_to_barracuda by_name locate_actual_output_node convert strides_to_HW get_tensor_data very_slow_but_stable_topological_sort gru TrainerController TrainerFactory initialize_trainer handle_existing_directories StatusMetaData StatusType GlobalTrainingStatus AgentExperience Trajectory SplitObservations remove_nones write_to_yaml_file convert_behaviors main parse_args BCModel BCModule create_reward_signal RewardSignal CuriosityModel CuriosityRewardSignal ExtrinsicRewardSignal GAILModel GAILRewardSignal GhostController GhostTrainer Optimizer TFOptimizer NNPolicy Policy TFPolicy UnityPolicyException PPOOptimizer PPOTrainer get_gae discount_rewards SACPolicyNetwork SACTargetNetwork SACNetwork SACOptimizer SACTrainer create_mock_pushblock_brain create_steps_from_brainparams simulate_rollout make_brain_parameters setup_mock_brain make_fake_trajectory create_mock_banana_brain create_mock_steps create_mock_brainparams create_mock_3dball_brain RecordEnvironment clamp SimpleEnvironment MemoryEnvironment test_end_episode test_agent_deletion test_agent_manager_queue test_agentprocessor test_agent_manager test_agent_manager_stats create_mock_brain create_mock_policy test_barracuda_converter test_policy_conversion test_bcmodule_rnn_update test_bcmodule_update test_bcmodule_constant_lr_update test_bcmodule_dc_visual_update create_bc_module test_bcmodule_defaults test_bcmodule_rnn_dc_update test_buffer_sample construct_fake_buffer test_num_experiences assert_array fakerandint test_buffer test_buffer_truncate test_remove_nones test_convert_behaviors test_main default_reset_parameters test_load_bad_curriculum_file_raises_error test_get_parameters test_init_curriculum_happy_path test_increment_lesson test_unsupported_version_raises_error test_load_demo test_demo_mismatch test_edge_cases test_load_demo_dir test_multicategorical_distribution test_tanh_distribution test_gaussian_distribution test_load_and_set dummy_config test_publish_queue test_process_trajectory basic_options test_run_training test_yaml_args test_sampler_configs test_bad_env_path test_commandline_args test_env_args test_increment_lessons_with_reward_buff_sizes test_convert_from_dict test_increment_lessons measure_vals reward_buff_sizes test_get_config test_set_lesson_nums test_restore_curriculums test_simple_metacurriculum test_curriculum_config test_min_visual_size test_load_save create_policy_mock test_normalization ModelVersionTest test_policy_evaluate _compare_two_policies basic_mock_brain test_take_action_returns_action_info_when_available test_convert_version_string test_take_action_returns_nones_on_missing_values test_take_action_returns_empty_with_no_agents FakePolicy test_trainer_increment_step test_trainer_update_policy test_ppo_optimizer_update test_ppo_optimizer_update_curiosity test_process_trajectory test_rl_functions test_add_get_policy test_bad_config _create_fake_trajectory _create_ppo_optimizer_ops_mock dummy_config test_ppo_optimizer_update_gail test_ppo_get_value_estimates test_gail_dc_visual sac_dummy_config reward_signal_update reward_signal_eval test_extrinsic extrinsic_dummy_config test_gail_rnn test_curiosity_cc test_gail_cc ppo_dummy_config test_curiosity_dc curiosity_dummy_config test_curiosity_visual test_curiosity_rnn create_optimizer_mock gail_dummy_config FakeTrainer create_rl_trainer test_rl_trainer create_mock_brain test_summary_checkpoint test_advance test_clear_update_buffer test_sac_update_reward_signals test_add_get_policy create_sac_optimizer_mock test_sac_optimizer_update dummy_config test_advance test_sac_save_load_buffer test_empty_samplers sampler_config_1 check_value_in_intervals incorrect_uniform_sampler test_incorrect_sampler test_sampler_config_1 sampler_config_2 incorrect_sampler_config test_incorrect_uniform_sampler test_sampler_config_2 test_strict_to_cls check_if_different test_is_new_instance test_no_configuration test_trainersettings_structure test_reward_signal_structure test_simple_ghost_fails test_gail test_visual_advanced_sac _check_environment_trains test_visual_sac test_2d_ppo test_simple_sac test_simple_ghost default_reward_processor test_simple_asymm_ghost test_gail_visual_ppo test_simple_ppo test_gail_visual_sac test_recurrent_ppo DebugWriter test_recurrent_sac test_simple_asymm_ghost_fails test_visual_advanced_ppo test_visual_ppo test_2d_sac simple_record test_tensorboard_writer test_stat_reporter_add_summary_write test_tensorboard_writer_clear test_gauge_stat_writer_sanitize ConsoleWriterTest test_csv_writer test_stat_reporter_property MockEnvWorker mock_env_factory SubprocessEnvManagerTest test_subprocess_env_raises_errors create_worker_mock test_subprocess_env_endtoend test_initialization_seed test_start_learning_trains_until_max_steps_then_saves basic_trainer_controller trainer_controller_with_take_step_mocks test_advance_adds_experiences_to_trainer_and_trains trainer_controller_with_start_learning_mocks test_start_learning_trains_forever_if_no_train_model test_initialize_ppo_trainer test_load_config_invalid_yaml test_load_config_missing_file test_handles_no_config_provided dummy_config test_load_config_valid_yaml test_existing_directories test_globaltrainingstatus StatsMetaDataTest test_trajectory_to_agentbuffer test_split_obs np_zeros_no_float64 np_array_no_float64 _check_no_float64 np_ones_no_float64 RLTrainer Trainer main check_coverage main clean_previous_results TestResults parse_results main main main run_training override_config_file init_venv get_unity_executable_path override_legacy_config_file get_base_path run_standalone_build checkout_csharp_version _override_config_dict undo_git_checkout get_base_output_path test_closing test_run_environment test_closing test_run_environment VerifyVersionCommand ActionType BehaviorMapping TerminalStep DecisionSteps BehaviorSpec TerminalSteps BaseEnv DecisionStep Communicator UnityEnvironment validate_environment_path launch_executable get_platform UnityCommunicatorStoppedException UnityObservationException UnityWorkerInUseException UnityException UnityCommunicationException UnityTimeOutException UnitySideChannelException UnityEnvironmentException UnityActionException get_logger set_log_level MockCommunicator RpcCommunicator UnityToExternalServicerImplementation _generate_split_indices process_pixels behavior_spec_from_proto _raise_on_nan_and_inf observation_to_np_array steps_from_proto _process_vector_observation _process_visual_observation _get_thread_timer TimerNode merge_gauges hierarchical_timer add_metadata get_timer_tree get_timer_root reset_timers get_timer_stack_for_thread set_gauge timed GaugeNode TimerStack UnityToExternalProtoServicer add_UnityToExternalProtoServicer_to_server UnityToExternalProtoStub BaseRegistryEntry ZipFileWithProgress get_tmp_dir get_local_binary_path_if_exists get_local_binary_path load_local_manifest load_remote_manifest download_and_extract_zip print_progress RemoteRegistryEntry UnityEnvRegistry EngineConfigurationChannel EngineConfig EnvironmentParametersChannel FloatPropertiesChannel IncomingMessage OutgoingMessage RawBytesChannel SideChannel SideChannelManager StatsAggregationMethod StatsSideChannel test_initialization test_reset test_returncode_to_signal_name test_log_file_path_is_set test_close test_step test_port_defaults test_handles_bad_filename test_check_communication_compatibility test_set_logging_level test_validate_path mock_glob_method test_launch_executable test_validate_path_empty create_registry test_basic_in_registry delete_binaries test_rpc_communicator_checks_port_on_create test_rpc_communicator_create_multiple_workers test_rpc_communicator_close test_batched_step_result_from_proto_raises_on_nan test_process_pixels test_process_visual_observation_bad_shape test_agent_behavior_spec_from_proto proto_from_steps_and_action test_batched_step_result_from_proto test_action_masking_continuous test_action_masking_discrete_1 generate_list_agent_proto generate_uncompressed_proto_obs test_batched_step_result_from_proto_raises_on_infinite generate_compressed_proto_obs test_vector_observation proto_from_steps test_action_masking_discrete generate_compressed_data test_action_masking_discrete_2 test_process_pixels_gray test_process_visual_observation test_raw_bytes test_int_channel test_message_float_list IntChannel test_engine_configuration test_message_bool test_message_string test_float_properties test_environment_parameters test_message_int32 test_stats_channel test_message_float32 test_decision_steps test_specs test_terminal_steps test_empty_terminal_steps test_action_generator test_empty_decision_steps test_timers decorated_func table_line ReleaseInfo validate_packages main NonTrivialPEP420PackageFinder main set_academy_version_string _escape_non_none extract_version_string print_release_tag_commands check_versions set_package_version set_version join isdir print replaceFilenameExtension add_argument exit verbose source_file ArgumentParser target_file sqrt topologicalSort list hasattr layers addEdge Graph print inputs set len list hasattr layers print filter match trim_model compile Struct get_tensor_shape_lambda insert data layers print tensors float16 layers isinstance name tensors inputs strip_tensforlow_postfix replace layers dumps data dtype layers isinstance print name tensors inputs outputs shape zip array_without_brackets to_json globals Build array_equal pool reduce Build tanh mad tanh mul Build concat add sigmoid sub mad _ tanh mul Build concat add sigmoid mad print sorted keys get list replace_strings_in_list extract_strings flatten process_model get_input_layer_shape enter get id verbose Struct values list hasattr name patch_data shape out_shapes append defaults get replace_strings_in_list embody astype visititems enumerate isinstance print in_args float32 patch_data_fn co_argcount get_input_layer_shape decode print_known_operations layers compress print tensors File write trim pprint loads Model verbose summary Struct process_model print_supported_ops endswith len print HasField hasattr print get_attr get_attr isinstance get_attr tensor_shape ndarray isinstance shape int_val bool_val float_val ListFields name ndarray isinstance str tensor_content ndarray product isinstance get_tensor_dtype print get_tensor_dims unpack int_val bool_val array float_val append add set Build mul sub insert Build tolist append range len locate_actual_output_node name find_tensor_by_name split locate_actual_output_node name lstm group find_tensor_by_name find_forget_bias split get_layer_shape id Struct tensor get_layer_rank layer_ranks hasattr name patch_data rank input_shapes out_shapes input get_attr append replace_strings_in_list tensors embody astype op inputs zip enumerate print float32 patch_data_fn model_tensors map_ignored_layer_to_its_input co_argcount len items get_tensors process_layer eval slow_but_stable_topological_sort ModelBuilderContext sort assign_ids pop range insert len open fuse node GraphDef inputs MessageToJson ParseFromString cleanup_layers read memories sort setup_constants MagicMock create_mock_vector_steps UnityToGymWrapper sample create_mock_group_spec setup_mock_unityenvironment step MagicMock create_mock_vector_steps UnityToGymWrapper create_mock_group_spec setup_mock_unityenvironment MagicMock create_mock_vector_steps UnityToGymWrapper sample create_mock_group_spec setup_mock_unityenvironment step MagicMock create_mock_vector_steps UnityToGymWrapper sample reset create_mock_group_spec setup_mock_unityenvironment step MagicMock create_mock_vector_steps UnityToGymWrapper sample reset create_mock_group_spec setup_mock_unityenvironment step tuple CONTINUOUS range DISCRETE list array range BehaviorMapping convert_to_barracuda convert convert_to_onnx _make_frozen_graph _enforce_onnx_conversion convert_frozen_to_onnx info model_path tf_optimize make_model _get_output_node_names _get_input_node_names info brain_name optimize_graph _get_frozen_graph_node_names add _get_frozen_graph_node_names name add node set brain_name info set_verbosity ConfigProto is_action_discrete sum add_argument_group add_argument ArgumentParser resequence_and_append obs from_observations steps_from_proto vector_actions AgentBuffer append reset_agent vector_observations array visual_observations enumerate make_demo_buffer camera_resolutions load_demonstration behavior_spec_to_brain_parameters zip enumerate isdir isfile get_demo_files write SerializeToString _EncodeVarint len parse_args start_learning join save_state join join pop SamplerManager MetaCurriculum try_restore_all_curriculum train_model seed API_VERSION load_model print debug run_training dumps randint set_log_level set_warnings_enabled warning add_timer_metadata as_dict __version__ DEBUG INFO get_version_string parse_command_line run_cli add_argument ArgumentParser from_dict experiment_config_path load_config fields_dict update items list check_and_structure structure register_structure_hook defaultdict dict_to_defaultdict register_structure_hook register_unstructure_hook structure get_timer_root reset_timers put _send_response StepResponse env_factory list _generate_all_results set_log_level get_and_reset_stats set_actions StatsSideChannel action set_configuration EngineConfigurationChannel external_brains payload set_float_parameter STEP EnvironmentParametersChannel items EnvironmentResponse EXTERNAL_BRAINS reset RESET step dims_to_barracuda_shape insert get_tensor_dims min_lesson_length join SACTrainer GhostTrainer PPOTrainer warning trainer_type isdir get update list items copy MemorySettings structure to_settings list items isinstance unstructure curriculum output_config_path remove_nones print write_to_yaml_file sampler convert_behaviors trainer_config_path parse_args get rcls list zeros_like size reversed range append discount_rewards Mock CameraResolution arange ones BehaviorSpec append array range ones AgentExperience append zeros sum range len vector_action_space_size pop number_visual_observations to_agentbuffer make_fake_trajectory vector_observation_space_size create_mock_brainparams create_mock_brainparams create_mock_brainparams create_mock_brainparams create_mock_brainparams zeros Mock Mock ActionInfo publish_trajectory_queue range create_mock_steps AgentProcessor empty create_mock_policy add_experiences Mock assert_has_calls ActionInfo publish_trajectory_queue range call create_mock_steps append AgentProcessor empty create_mock_policy add_experiences Mock assert_has_calls ActionInfo end_episode publish_trajectory_queue range call create_mock_steps append AgentProcessor empty create_mock_policy add_experiences AgentManager create_mock_policy Mock get_nowait AgentManagerQueue put Mock assert_any_call remove record_environment_stats AgentManager add_writer StatsReporter write_stats join remove _get_candidate_names convert _get_default_tempdir dirname abspath isfile next TrainerSettings join export_policy_model sess save_model graph create_policy_mock SerializationSettings model_path reset_default_graph brain_name TrainerSettings initialize_or_load NNPolicy BehavioralCloningSettings create_bc_module create_mock_3dball_brain update items list BehavioralCloningSettings create_bc_module create_mock_3dball_brain update items list BehavioralCloningSettings current_lr create_bc_module create_mock_3dball_brain update items list BehavioralCloningSettings create_bc_module create_mock_3dball_brain update items list BehavioralCloningSettings create_mock_banana_brain create_bc_module update items list BehavioralCloningSettings create_mock_banana_brain create_bc_module flatten list range len append range AgentBuffer resequence_and_append get_batch construct_fake_buffer assert_array make_mini_batch AgentBuffer reset_agent array resequence_and_append sample_mini_batch construct_fake_buffer AgentBuffer resequence_and_append construct_fake_buffer AgentBuffer resequence_and_append list construct_fake_buffer AgentBuffer truncate values load convert_behaviors main Mock assert_called_with Namespace remove_nones Curriculum Curriculum Curriculum load_demonstration demo_to_buffer dirname abspath load_demonstration demo_to_buffer dirname abspath dirname abspath dirname abspath mock_open BytesIO DemonstrationMetaProto write_delimited create_tf_graph brain_name setup_mock_brain load_weights init_load_weights zip assert_array_equal get_weights PPOTrainer create_policy GhostController GhostTrainer PPOTrainer subscribe_trajectory_queue advance put make_fake_trajectory BrainParameters from_name_behavior_id AgentManagerQueue add_policy brain_name create_policy GhostController GhostTrainer PPOTrainer simulate_rollout get_nowait advance _swap_snapshots setup_mock_brain publish_policy_queue BrainParameters from_name_behavior_id AgentManagerQueue add_policy brain_name create_policy clear safe_load MagicMock parse_command_line clear parse_command_line parse_command_line parse_command_line safe_load CurriculumSettings MetaCurriculum increment_lessons Mock MetaCurriculum assert_called_with increment_lessons assert_not_called MetaCurriculum assert_called_with MetaCurriculum assert_has_calls try_restore_all_curriculum MetaCurriculum SimpleEnvironment MetaCurriculum _check_environment_trains setup_mock_brain NNPolicy TrainerSettings join _set_step save_model initialize_or_load create_policy_mock _compare_two_policies list create_steps_from_brainparams evaluate brain agent_id assert_array_equal TrainerSettings list create_steps_from_brainparams evaluate brain agent_id create_policy_mock reset_default_graph TrainerSettings NNPolicy update_normalization to_agentbuffer make_fake_trajectory BrainParameters zeros range run MagicMock TrainerSettings basic_mock_brain BehaviorSpec get_action empty FakePolicy TrainerSettings MagicMock basic_mock_brain DecisionSteps get_action array FakePolicy TrainerSettings MagicMock basic_mock_brain ActionInfo DecisionSteps get_action array FakePolicy _convert_version_string setup_mock_brain evolve PPOOptimizer NNPolicy make_fake_trajectory update brain simulate_rollout _create_ppo_optimizer_ops_mock reset_default_graph update brain simulate_rollout _create_ppo_optimizer_ops_mock reset_default_graph update brain simulate_rollout _create_ppo_optimizer_ops_mock reset_default_graph items list get_trajectory_value_estimates to_agentbuffer _create_fake_trajectory _create_ppo_optimizer_ops_mock next_obs reset_default_graph assert_array_almost_equal array discount_rewards Mock brain_name _increment_step BrainParameters assert_called_with add_policy PPOTrainer _update_policy simulate_rollout brain_name MemorySettings setup_mock_brain add_policy PPOTrainer create_policy list values Mock brain_name make_brain_parameters add_policy PPOTrainer make_brain_parameters setup_mock_brain SACOptimizer PPOOptimizer NNPolicy simulate_rollout evaluate_batch brain brain simulate_rollout prepare_update _execute_model update_dict make_mini_batch policy BehavioralCloningSettings create_optimizer_mock reward_signal_eval reward_signal_update create_optimizer_mock reward_signal_eval reward_signal_update create_optimizer_mock reward_signal_eval reward_signal_update create_optimizer_mock reward_signal_eval reward_signal_update create_optimizer_mock reward_signal_eval reward_signal_update create_optimizer_mock reward_signal_eval reward_signal_update create_optimizer_mock reward_signal_eval reward_signal_update create_optimizer_mock reward_signal_eval reward_signal_update TrainerSettings set_is_policy_updating FakeTrainer create_mock_brain end_episode list create_rl_trainer values items list construct_fake_buffer create_rl_trainer _clear_update_buffer create_rl_trainer set_is_policy_updating subscribe_trajectory_queue advance put make_fake_trajectory publish_policy_queue AgentManagerQueue get_nowait range assert_has_calls create_rl_trainer subscribe_trajectory_queue summary_freq checkpoint_interval put make_fake_trajectory publish_policy_queue advance AgentManagerQueue get_nowait range setup_mock_brain SACOptimizer NNPolicy update brain simulate_rollout create_sac_optimizer_mock reset_default_graph brain simulate_rollout create_sac_optimizer_mock update_reward_signals reset_default_graph SACTrainer save_model brain simulate_rollout num_experiences setup_mock_brain add_policy brain_name create_policy SACTrainer list Mock SACTrainer values make_brain_parameters add_policy brain_name create_policy SamplerManager sample_all sampler_config_1 sampler_config_2 SamplerManager SamplerManager sample_all incorrect_uniform_sampler incorrect_sampler_config list items RunOptions check_if_different TrainerSettings RunOptions structure structure print evolve SimpleEnvironment _check_environment_trains hyperparameters evolve SimpleEnvironment _check_environment_trains hyperparameters evolve SimpleEnvironment _check_environment_trains network_settings evolve SimpleEnvironment hyperparameters _check_environment_trains network_settings evolve MemoryEnvironment hyperparameters _check_environment_trains evolve SimpleEnvironment _check_environment_trains hyperparameters evolve SimpleEnvironment _check_environment_trains hyperparameters evolve SimpleEnvironment _check_environment_trains network_settings evolve SimpleEnvironment hyperparameters _check_environment_trains network_settings evolve MemoryEnvironment hyperparameters _check_environment_trains evolve SimpleEnvironment SelfPlaySettings _check_environment_trains evolve SimpleEnvironment SelfPlaySettings _check_environment_trains evolve SimpleEnvironment SelfPlaySettings _check_environment_trains evolve SimpleEnvironment SelfPlaySettings _check_environment_trains evolve SimpleEnvironment BehavioralCloningSettings _check_environment_trains simple_record evolve SimpleEnvironment BehavioralCloningSettings hyperparameters _check_environment_trains simple_record evolve SimpleEnvironment BehavioralCloningSettings hyperparameters _check_environment_trains simple_record clear assert_called_once_with Mock get_stats_summaries add_stat add_writer StatsReporter float range write_stats clear Mock add_property add_writer StatsReporter assert_called_once_with sleep TensorboardWriter StatsSummary write_stats close SubprocessEnvManager simple_env_factory _check_environment_trains default_config default_config close SubprocessEnvManager GhostController MagicMock GhostController TrainerController MagicMock assert_called_with MagicMock start_learning assert_called_once MagicMock assert_not_called start_learning assert_called_once MagicMock MagicMock assert_called_once MagicMock advance add assert_not_called behaviors BrainParametersMock behaviors BrainParameters generate TrainerFactory brain_name _load_config StringIO mkdir join handle_existing_directories join set_parameter_state LESSON_NUM load_state NOTAREALKEY get_parameter_state save_state append from_observations range ones items list to_agentbuffer add set make_fake_trajectory extract_stack filename get __old_np_array _check_no_float64 get _check_no_float64 __old_np_zeros get __old_np_ones _check_no_float64 join format print exit walk float check_coverage join remove mkdir rmdir exists documentElement getAttribute parse join clean_previous_results parse_results get_unity_executable_path exit returncode get_base_path copy2 init_venv add_argument ArgumentParser split strip run_standalone_build int time join init_venv override_config_file print exit override_legacy_config_file get_base_path rename run_standalone_build run checkout_csharp_version exists get_base_output_path python run_training csharp exists join move get_unity_executable_path print makedirs dirname get_base_output_path run check_call check_call check_call list _override_config_dict values items list isinstance update list values check_call str format UnityToGymWrapper print step reset sample UnityEnvironment range reset UnityEnvironment close UnityToGymWrapper get_steps is_action_discrete EngineConfigurationChannel randn set_configuration_parameters discrete_action_branches len action_size any set_actions is_action_continuous column_stack join format basename replace glob debug getcwd normpath validate_environment_path debug format add setLevel getLogger basicConfig setLevel tuple vector_action_size mean reshape array data compressed_data reshape process_pixels shape array mean isnan array _raise_on_nan_and_inf sum is_action_discrete _generate_split_indices ones discrete_action_branches len astype _raise_on_nan_and_inf any cast split append _process_vector_observation bool _process_visual_observation array observation_shapes enumerate range len get_ident TimerStack perf_counter push items list merge reset method_handlers_generic_handler add_generic_rpc_handlers download_and_extract_zip get_local_binary_path_if_exists debug range glob hexdigest join get_tmp_dir join chmod gettempdir makedirs uuid4 join int str remove get_tmp_dir exists chmod print glob rmtree urlopen print_progress hexdigest print int min max uuid4 join str get_tmp_dir load_local_manifest urlopen UnityEnvironment close MockCommunicator UnityEnvironment MockCommunicator _executable_args UnityEnvironment MockCommunicator index get_steps obs close reset MockCommunicator zip UnityEnvironment observation_shapes len get_steps obs zip ones step close MockCommunicator set_actions zeros UnityEnvironment observation_shapes len UnityEnvironment close MockCommunicator validate_environment_path validate_environment_path launch_executable PermissionError set_log_level rmtree get_tmp_dir RemoteRegistryEntry register UnityEnvRegistry create_registry make close reset step range delete_binaries close RpcCommunicator close RpcCommunicator close RpcCommunicator list extend ObservationProto AgentInfoProto append prod range len fromarray uint8 BytesIO astype save ObservationProto generate_compressed_data extend shape ObservationProto shape tolist extend obs concatenate action_mask agent_id ObservationProto AgentInfoProto append generate_uncompressed_proto_obs proto_from_steps generate_compressed_data process_pixels rand generate_compressed_data process_pixels rand _process_vector_observation generate_list_agent_proto enumerate generate_compressed_proto_obs rand extend AgentInfoProto _process_visual_observation generate_uncompressed_proto_obs generate_compressed_proto_obs rand AgentInfoProto extend list sort CONTINUOUS agent_id BehaviorSpec steps_from_proto generate_list_agent_proto range BehaviorSpec steps_from_proto DISCRETE generate_list_agent_proto action_mask BehaviorSpec steps_from_proto DISCRETE generate_list_agent_proto action_mask BehaviorSpec steps_from_proto DISCRETE generate_list_agent_proto action_mask CONTINUOUS BehaviorSpec steps_from_proto generate_list_agent_proto action_mask BrainParametersProto behavior_spec_from_proto extend CONTINUOUS generate_list_agent_proto BehaviorSpec CONTINUOUS generate_list_agent_proto BehaviorSpec generate_side_channel_messages process_side_channel_message send_int IntChannel FloatPropertiesChannel process_side_channel_message generate_side_channel_messages get_property set_property uuid4 process_side_channel_message generate_side_channel_messages RawBytesChannel encode send_raw_data get_and_clear_received_messages len buffer read_bool append write_bool IncomingMessage range OutgoingMessage buffer write_int32 read_int32 IncomingMessage OutgoingMessage IncomingMessage write_float32 buffer read_float32 OutgoingMessage read_string write_string buffer IncomingMessage OutgoingMessage IncomingMessage buffer OutgoingMessage read_float32_list write_float32_list set_configuration channel_id EngineConfigurationChannel generate_side_channel_messages process_side_channel_message set_configuration_parameters RawBytesChannel read_float32 read_int32 IncomingMessage get_and_clear_received_messages default_config channel_id generate_side_channel_messages process_side_channel_message read_string set_float_parameter RawBytesChannel read_float32 read_int32 IncomingMessage EnvironmentParametersChannel IncomingMessage write_float32 write_string buffer write_int32 get_and_reset_stats on_message_received StatsSideChannel OutgoingMessage DecisionSteps action_mask empty BehaviorSpec TerminalSteps empty BehaviorSpec BehaviorSpec create_random_action enumerate BehaviorSpec create_empty_action set_gauge TimerStack startswith print find_packages find validate_packages remove replace frozenset endswith set add walk join print extract_version_string set values join format set_academy_version_string print set_package_version enumerate split print | <img src="docs/images/image-banner.png" align="middle" width="3000"/> # Unity ML-Agents Toolkit [](https://github.com/Unity-Technologies/ml-agents/tree/release_2_docs/docs/) [](LICENSE) ([latest release](https://github.com/Unity-Technologies/ml-agents/releases/tag/latest_release)) ([all releases](https://github.com/Unity-Technologies/ml-agents/releases)) **The Unity Machine Learning Agents Toolkit** (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents. Agents can be trained using reinforcement learning, imitation learning, neuroevolution, or other machine learning methods through a | 3,323 |
pouyaAB/Pay-Attention | ['imitation learning'] | ['Pay Attention! - Robustifying a Deep Visuomotor Policy Through Task-Focused Visual Attention'] | autoencoders/tower.py test_lstm_on_robot.py autoencoders/vanilla.py gpu.py DatasetController_morph.py local_config.py model_e2e.py nf_train_mean_cost.py train_lstm_alone.py autoencoders/pyramid.py notused/Utilities.py nf_mdn_rnn.py image_transformer.py model.py latent_from_model.py create_dir DatasetController show_image GPU imageTransformer create_dir signal_handler EncodeDataset signal_handler ModelController signal_handler ModelController RobotController signal_handler signal_handler ModelTester signal_handler TrainLstm Encoder_text Generator_text Discriminator_texual Discriminator_texual Encoder_text_tower Generator_text Generator Encoder Discriminator Utils mkdir fromarray dtype uint8 show print transpose min astype shape max len exit | # Pay Attention! Robustifying a Deep Visuomotor Policy through Task-Focused Visual Attention ## Dataset Please download the dataset from this [link](https://drive.google.com/file/d/1zo0DtuIjLWhFkpZdk9o-26tJ54iXg1pV/view?usp=sharing). In the downloaded dataset, you can find two folders. Each contains demonstrations (images and commands) for one task. Each demonstration folder contains a demonstration performed by controlling the robot and another folder a human performed the same task by hand. Most of the demonstrations are recorded from 3 different angles using 3 cameras. Each demonstration folder is named randomly and there exists a corresponding text file. The text file contains rows of commands sent to the robot by the demonstrator each row has its timestamp. The same timestamps are also used to name the corresponding images in the robot folder. Besides the dataset containing the demonstrations, you also need the corresponding attention map for each image. The folder named `processed_inputs_attention_28_new_objects` contains the attention maps generated by the teacher network for all the demonstrations but only for one of the cameras since we didn't ready used all the camera angles in this work. This folder is included in the GitHub project. In the project, the class `DatasetController` is responsible for reading and managing the dataset. It can be used to return batches of images and their corresponding commands to be used by the architecture. After downloading the dataset you need to extract it somewhere and change the config (`local_config.py`) file accordingly. ``` - Dataset - 5001 (Picking up task) | 3,324 |
ppke-nlpg/whats-wrong-python | ['chunking'] | ["What's Wrong, Python? -- A Visual Differ and Graph Library for NLP in Python"] | libwwnlp/render/renderers/abstract_renderer.py Qt5GUI/GUI/ChooseFormat.py libwwnlp/render/layouts/span_layout.py libwwnlp/render/renderers/single_sentence_renderer.py ioformats/other_formats.py ioformats/tab_processor.py libwwnlp/model/token.py libwwnlp/render/layouts/abstract_layout.py libwwnlp/model/nlp_instance.py libwwnlp/render/renderers/alignment_renderer.py libwwnlp/render/backends/matplotlib_writer.py libwwnlp/nlp_canvas.py libwwnlp/render/backends/svg_writer.py libwwnlp/render/layouts/dependency_layout.py libwwnlp/corpus_navigator.py Qt5GUI/filter_panel.py Qt5GUI/gui_main.py libwwnlp/configurable.py ioformats/corpus_format.py Qt5GUI/qt5_nlp_canvas.py libwwnlp/render/layouts/alignment_layout.py libwwnlp/render/backends/bokeh_writer.py libwwnlp/model/edge.py Qt5GUI/GUI/GUI.py whatswrong.py libwwnlp/model/filter.py libwwnlp/render/layouts/token_layout.py test CorpusFormat Terminal GizaAlignmentFormat TheBeastFormat BioNLP2009SharedTaskFormat Tree LispSExprFormat check_eof GaleAlignmentFormat CoNLL2009 CCG CoNLL2000 CoNLL2005 TabFormat CoNLL2004 CoNLL2006 CoNLL2008 MaltTab CoNLL2002 CoNLL2003 params_at_path Configurable CorpusNavigator NLPCanvas Edge EdgeRenderType Filter NLPInstance RenderType nlp_diff Token BokehRenderer MPLRenderer SVGWriteRenderer AbstractLayout middle AlignmentLayout DependencyLayout SpanLayout TokenLayout AbstractRenderer AlignmentRenderer SingleSentenceRenderer FilterPanel main MyWindow MyForm Qt5NLPCanvas Ui_ChooseFormat Ui_MainWindow test_process isinstance get_edges list add_edge properties add_tokens set add split_point render_type NLPInstance values show exec_ exit raise_ MyForm QApplication | # _What's Wrong With My NLP?_ reimplemented in Python 3 (whats-wrong-python) _What's Wrong With My NLP?_: A visualizer for Natural Language Processing problems. Original project page and source: https://code.google.com/archive/p/whatswrong/ _What's Wrong With My NLP?_ is rewritten in Python 3 using SVG instead of JAVA canvas. # Features - The program can open and diff the following formats (and it is easy to implement others): - CCG - MaltTab (tested) - CoNLL 2000 - CoNLL 2002 | 3,325 |
ppuliu/GloRE | ['relation extraction'] | ['Global Relation Embedding for Relation Extraction'] | scripts/test_mlp.py scripts/interactive_rel2vec.py scripts/train_mlp.py src/rel2vec_utils.py src/mlp.py src/run_mlp.py src/seq2seq.py src/rel2vec_data_utils.py src/mlp_data_utils.py src/run_rel2vec.py scripts/train_rel2vec.py src/rel2vec_model.py scripts/test_rel2vec.py steps.py main main main main main mlp load_test_data get_batch load_train_data compute_target_matrix setup_logging compute_feature_matrix data_to_token_ids read_word2vec initialize_vocabulary prepare_data sentence_to_token_ids create_vocabulary create_init_embeddings Rel2VecModel print_variables calc_sample_scale test main train create_input_files read_data create_model gen_scores decode_interactive main train model_with_buckets attention_seq2seq sequence_loss_by_example _extract_argmax_and_embed sequence_loss attention_decoder rnn_decoder basic_rnn_seq2seq join list items print call load_config makedirs append range compute_target_matrix compute_feature_matrix compute_target_matrix compute_feature_matrix format print append array range reshape len append range choice join basicConfig dictConfig getenv dirname exists makedirs sorted getLogger endswith debug strip close len split info float open dict Exists float split str format_list initialize_vocabulary getLogger endswith debug write close sentence_to_token_ids info open data_to_token_ids join range create_vocabulary read_word2vec format initialize_vocabulary getLogger endswith reshape sqrt uniform info enumerate seed int join format get_batch run_summary_op getLogger print print_variables strftime shape save info append float range run int list scores format print sort len flatten zip sum range run trainable_variables format name eval info append float sum range len endswith ArgumentParser targets_file sorted exit map split input append parse_args create_input_files format moana_file unlink features_file eval emb_score_file their_pr_file listdir ConfigProto log_dir our_pr_file isdir add_argument rmtree isfile print format getLogger endswith debug len close split info append float enumerate open batch_size getLogger Rel2VecModel num_layers model_dir run restore encoder_size decoder_size initialize_all_variables max_gradient_norm SummaryWriter get_checkpoint_state size info decoder_vocab_size join learning_rate print graph model_checkpoint_path optimization_algorithm learning_rate_decay_factor encoder_vocab_size model_dir read_data data_dir exit input unlink ConfigProto listdir setup_logging fresh_start isdir prepare_data rmtree isfile makedirs join initialize_vocabulary getLogger data_dir len decoder_vocab_file ConfigProto model_dir encoder_vocab_file info _START_VOCAB range encoder_vocab_size decoder_vocab_size setup_logging join initialize_vocabulary print data_dir decoder_vocab_file encoder_size model_dir encoder_vocab_file ConfigProto encoder_vocab_size decoder_vocab_size len gen_scores train decode_interactive output_size | ## Global Relation Embedding for Relation Extraction (GloRE) GloRE is a relation embedding model that can be used to augment existing relation extraction models and improve their performance. Most remarkably, for the top 1,000 relational facts discovered by the best existing model (PCNN+ATT), the precision can be improved from 83.9% to 89.3%. ## Prerequisite * Python 2.7 * Tensorflow 0.11 ## Install Tensorflow 0.11 (GPU support) ``` export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.11.0-cp27-none-linux_x86_64.whl pip install --ignore-installed --upgrade $TF_BINARY_URL | 3,326 |
pquochuy/idsegan | ['speech enhancement'] | ['SEGAN: Speech Enhancement Generative Adversarial Network', 'Improving GANs for Speech Enhancement'] | isegan/generator.py isegan/data_loader.py dsegan/bnorm.py dsegan/data_loader.py dsegan/generator.py dsegan/main.py isegan/main.py dsegan/discriminator.py segan/model.py dsegan/ops.py isegan/discriminator.py isegan/ops.py segan/bnorm.py dsegan/model.py make_tfrecords.py segan/data_loader.py segan/generator.py segan/discriminator.py segan/main.py isegan/model.py isegan/bnorm.py segan/ops.py _int64_feature encoder_proc read_and_slice _bytes_feature slice_signal main VBN pre_emph de_emph read_and_decode discriminator AEGenerator pre_emph_test main Model SEGAN leakyrelu minmax_normalize minmax_denormalize tensor_summary prelu repeat_elements average_gradients batch_to_time atrous_conv1d nn_deconv conv1d conv2d gaussian_noise_layer highway time_to_batch deconv downconv histogram_summary sample_random_walk audio_summary residual_block variables_on_gpu0 scalar_summary VBN pre_emph de_emph read_and_decode discriminator AEGenerator pre_emph_test main Model SEGAN leakyrelu minmax_normalize minmax_denormalize tensor_summary prelu repeat_elements average_gradients batch_to_time atrous_conv1d nn_deconv conv1d conv2d gaussian_noise_layer highway time_to_batch deconv downconv histogram_summary sample_random_walk audio_summary residual_block variables_on_gpu0 scalar_summary VBN pre_emph de_emph read_and_decode discriminator AEGenerator Generator pre_emph_test main Model SEAE SEGAN leakyrelu minmax_normalize minmax_denormalize tensor_summary prelu repeat_elements average_gradients batch_to_time atrous_conv1d nn_deconv conv1d conv2d gaussian_noise_layer highway time_to_batch deconv downconv histogram_summary sample_random_walk audio_summary residual_block variables_on_gpu0 scalar_summary int list zip append range read slice_signal join write SerializeToString tostring Example read_and_slice zip split join format noisy_dir save_path print TFRecordWriter len default_timer encoder_proc close unlink out_file splitext wav_dir listdir enumerate flush makedirs reshape concat zeros range read TFRecordReader decode_raw float32 pre_emph set_shape int32 cast parse_single_example as_list int expand_dims pre_emph float32 placeholder seed name append synthesis_path ConfigProto random_normal zeros range reshape randn scalar histogram audio xavier_initializer expand_dims format _linear f sigmoid range as_list get_shape xavier_initializer as_list print as_list split conv1d repeat_elements xavier_initializer get_shape expand_dims get_variable concat reduce_mean zip append expand_dims | ## Improving GANs for Speech Enhancement ### Introduction This is the repository of the DSEGAN, ISEGAN, (and the baseline SEGAN) in our original paper: H. Phan, I. V. McLoughlin, L. Pham, O. Y. Chén, P. Koch, M. De Vos, and A. Mertins, "[_Improving GANs for Speech Enhancement_](https://arxiv.org/pdf/2001.05532.pdf)," IEEE Signal Processing Letters, 2020. <span style="color:red">*(accepted)*</span> ISEGAN (Iterated SEGAN) and DSEGAN (Deep SEGAN) were built upon the SEGAN proposed by [Pascual _et al._](https://arxiv.org/abs/1703.09452) and SEGAN repository from [santi-pdp](https://github.com/santi-pdp/segan). Different from SEGAN with a single generator, ISEGAN and DSEGAN have multiple generators which are chained to perform multi-stage enhancement mapping: [//]: # <img src="assets/idsegan.png" alt="idsegan.png" width="400"/> The enhacement result of one generator is supposed to be further enhanced/corrected by the next generator in the chain. DSEGAN's generators are independent while ISEGAN's generators share parameters. Similar to SEGAN, the generators are based on fully convolutional architecture and receive raw speech waveforms to accomplish speech enhancement: [//]: # <img src="assets/generator.png" alt="generator" width="300"/> | 3,327 |
pquochuy/sasegan | ['speech enhancement'] | ['SEGAN: Speech Enhancement Generative Adversarial Network', 'Self-Attention Generative Adversarial Network for Speech Enhancement'] | sasegan/data_loader.py sasegan/selfattention.py make_tfrecords.py sasegan/ops.py sasegan/main.py sasegan/discriminator.py sasegan/model.py sasegan/bnorm.py sasegan/generator.py _int64_feature encoder_proc read_and_slice _bytes_feature slice_signal main VBN pre_emph de_emph read_and_decode discriminator AEGenerator Generator pre_emph_test main Model SEGAN leakyrelu minmax_normalize minmax_denormalize prelu repeat_elements average_gradients batch_to_time atrous_conv1d nn_deconv conv1d conv2d gaussian_noise_layer highway time_to_batch deconv downconv sample_random_walk residual_block variables_on_gpu0 _l2normalize spectral_normed_weight sn_downconv conv1x1 sn_deconv snconv2d sn_non_local_block_sim sn_conv1x1 int list zip append range read slice_signal join write SerializeToString tostring Example read_and_slice zip split join format noisy_dir save_path print TFRecordWriter len default_timer encoder_proc close unlink out_file splitext wav_dir listdir enumerate flush makedirs reshape concat zeros range read TFRecordReader decode_raw float32 pre_emph set_shape int32 cast parse_single_example as_list int expand_dims pre_emph float32 placeholder seed name append synthesis_path ConfigProto random_normal zeros range reshape randn xavier_initializer expand_dims format _linear f sigmoid range as_list get_shape xavier_initializer as_list print as_list split conv1d repeat_elements xavier_initializer get_shape expand_dims get_variable concat reduce_mean zip append expand_dims as_list _l2normalize reshape squeeze matmul add_to_collection assign range get_variable xavier_initializer expand_dims xavier_initializer get_shape expand_dims | ## Self-Attention Generative Adversarial Network for Speech Enhancement ### Introduction This is the repository of the sel-attention GAN for speech enhancement (SASEGAN) in our original paper: H. Phan, H. L. Nguyen, O. Y. Chén, P. Koch, N. Q. K. Duong, I. McLoughlin, and A. Mertins, "[_Self-Attention Generative Adversarial Network for Speech Enhancement_](https://arxiv.org/pdf/2010.09132)," Proc. ICASSP, 2021. SASEGAN integrates non-local based self-attention to convolutional layers of SEGAN [Pascual _et al._](https://arxiv.org/abs/1703.09452) to improve sequential modelling. [//]: # <img src="assets/sasegan.png" alt="sasegan.png" width="800"/> **The project is developed with TensorFlow 1**. ([Go to Tensorflow 2 Version](https://github.com/usimarit/sasegan)) ### Dependencies * tensorflow_gpu 1.9 | 3,328 |
pradip026/MachineLearning_Pytorch | ['multiple object tracking'] | ['Simple Online and Realtime Tracking'] | utils/utils.py utils/datasets.py utils/parse_config.py models.py sort.py YOLOLayer create_modules Darknet EmptyLayer KalmanBoxTracker iou Sort convert_bbox_to_z associate_detections_to_trackers convert_x_to_bbox parse_args ImageFolder ListDataset parse_data_config parse_model_config compute_ap build_targets bbox_iou_numpy to_categorical weights_init_normal load_classes bbox_iou non_max_suppression pop int YOLOLayer Sequential ZeroPad2d MaxPool2d add_module Conv2d ModuleList EmptyLayer Upsample append BatchNorm2d LeakyReLU sum enumerate minimum maximum float sqrt linear_assignment iou concatenate reshape append zeros empty enumerate add_argument ArgumentParser rstrip strip open startswith append split dict strip split open data normal_ __name__ constant_ concatenate size maximum sum range clamp min max minimum eps expand_dims maximum data sort new squeeze size shape unsqueeze cuda unique bbox_iou append max is_cuda cat enumerate int fill_ FloatTensor ones concatenate size range unsqueeze bbox_iou zeros argmax log | # MachineLearning_Pytorch Object detection in images, and tracking across video frames Full story at: https://towardsdatascience.com/object-detection-and-tracking-in-pytorch-b3cf1a696a98 References: 1. YOLOv3: https://pjreddie.com/darknet/yolo/ 2. Erik Lindernoren's YOLO implementation: https://github.com/eriklindernoren/PyTorch-YOLOv3 3. YOLO paper: https://pjreddie.com/media/files/papers/YOLOv3.pdf 4. SORT paper: https://arxiv.org/pdf/1602.00763.pdf 5. Alex Bewley's SORT implementation: https://github.com/abewley/sort | 3,329 |
pralab/secml | ['adversarial defense', 'adversarial attack'] | ['Foolbox: A Python toolbox to benchmark the robustness of machine learning models', 'Technical Report on the CleverHans v2.1.0 Adversarial Examples Library'] | src/secml/optim/function/c_function_rosenbrock.py src/secml/ml/peval/metrics/c_metric_auc_wmw.py src/secml/array/tests/test_c_array_utils_dataanalysis.py src/secml/ml/classifiers/multiclass/c_classifier_multi_ova.py docs/source/pyplots/hist.py src/secml/explanation/__init__.py src/secml/ml/classifiers/multiclass/c_classifier_multi.py src/secml/ml/scalers/c_scaler_norm.py src/secml/optim/constraints/tests/test_c_constraint.py src/secml/testing/c_unittest.py src/secml/adv/attacks/evasion/foolbox/tests/test_c_attack_evasion_foolbox_ead.py src/secml/explanation/c_explainer_gradient_input.py src/secml/adv/attacks/c_attack_mixin.py src/secml/figure/_plots/c_plot_classifier.py src/secml/ml/features/normalization/c_normalizer_linear.py docs/source/pyplots/xlabel.py src/secml/ml/classifiers/c_classifier.py src/secml/adv/attacks/evasion/foolbox/tests/test_c_attack_evasion_foolbox_cw.py src/secml/ml/classifiers/pytorch/c_classifier_pytorch.py src/secml/data/tests/test_c_dataset_pytorch.py src/secml/settings.py src/secml/ml/classifiers/gradients/tests/mixin_classifier_gradient_testcases.py src/secml/ml/classifiers/gradients/tests/test_classes/c_classifier_gradient_test_logistic.py src/secml/ml/stats/tests/test_c_density_estimation.py src/secml/figure/tests/test_plot.py src/secml/ml/classifiers/gradients/tests/test_classes/c_classifier_gradient_test.py src/secml/adv/attacks/evasion/cleverhans/c_attack_evasion_cleverhans_losses.py src/secml/explanation/c_explainer_gradient.py src/secml/data/loader/c_dataloader_imgfolders.py src/secml/ml/classifiers/loss/tests/test_c_loss_cross_entropy.py src/secml/figure/_plots/c_plot_stats.py src/secml/ml/classifiers/reject/c_classifier_reject_threshold.py src/secml/ml/scalers/tests/test_c_scaler_minmax.py src/secml/utils/tests/test_c_log.py src/secml/ml/peval/metrics/c_confusion_matrix.py src/secml/explanation/tests/test_c_explainer_influence_functions.py src/secml/data/selection/c_ps_spanning.py src/secml/ml/kernels/c_kernel_histintersect.py src/secml/ml/kernels/tests/test_c_kernel_laplacian.py src/secml/data/loader/c_dataloader_imgclients.py src/secml/ml/features/normalization/tests/test_c_normalizer_minmax.py docs/source/pyplots/plot.py src/secml/optim/optimizers/line_search/tests/test_line_search_bisect.py src/secml/adv/attacks/evasion/tests/test_c_attack_evasion_pgd.py src/secml/ml/classifiers/loss/c_loss.py src/secml/data/loader/c_dataloader_mnist.py src/secml/adv/attacks/evasion/cleverhans/c_attack_evasion_cleverhans.py src/secml/ml/features/normalization/c_normalizer_tfidf.py src/secml/data/loader/c_dataloader_sklearn.py src/secml/ml/classifiers/loss/tests/test_c_loss_regression.py src/secml/data/loader/tests/test_dataloader.py src/secml/ml/kernels/c_kernel_euclidean.py src/secml/figure/_plots/c_plot_fun.py src/secml/ml/__init__.py docs/source/pyplots/tick_params.py src/secml/utils/dict_utils.py src/secml/ml/scalers/tests/test_c_scaler_std.py src/secml/ml/classifiers/tests/__init__.py src/secml/optim/function/c_function_beale.py src/secml/data/loader/tests/test_dataloader_imgclients.py src/secml/optim/__init__.py src/secml/core/decorators.py src/secml/data/__init__.py docs/source/pyplots/errorbar.py src/secml/array/tests/test_c_array_casting.py src/secml/data/selection/c_ps_kmedians.py docs/source/pyplots/plot_fun.py src/secml/array/tests/c_array_testcases.py src/secml/ml/kernels/tests/test_c_kernel_rbf.py src/secml/array/tests/test_c_ndarray.py src/secml/array/tests/test_c_array_properties.py src/secml/array/c_array.py src/secml/adv/attacks/evasion/foolbox/tests/test_c_attack_evasion_foolbox_ddn.py src/secml/explanation/c_explainer_influence_functions.py src/secml/ml/classifiers/secure/__init__.py src/secml/ml/stats/c_distribution_gaussian.py src/secml/optim/constraints/c_constraint.py src/secml/ml/features/normalization/c_normalizer_unitnorm.py src/secml/data/splitter/__init__.py src/secml/ml/classifiers/sklearn/tests/test_c_classifier_sgd.py docs/source/pyplots/plot_path.py src/secml/ml/stats/__init__.py src/secml/optim/optimizers/c_optimizer.py src/secml/core/tests/test_c_creator.py src/secml/ml/classifiers/gradients/tests/test_mixin_classifier_gradient_svm.py src/secml/optim/optimizers/c_optimizer_pgd_exp.py src/secml/optim/optimizers/line_search/c_line_search.py src/secml/ml/classifiers/sklearn/tests/test_c_classifier_sklearn.py src/secml/ml/classifiers/gradients/tests/test_mixin_classifier_gradient_ridge.py src/secml/ml/classifiers/loss/c_loss_hinge.py src/secml/ml/classifiers/pytorch/tests/test_c_classifier_pytorch_blobs.py src/secml/figure/__init__.py src/secml/figure/_plots/c_plot.py src/secml/ml/classifiers/sklearn/tests/test_c_classifier_svm.py src/secml/ml/features/normalization/tests/test_c_normalizer_dnn.py src/secml/ml/classifiers/reject/c_classifier_reject.py src/secml/optim/constraints/tests/__init__.py src/secml/ml/scalers/c_scaler_std.py src/secml/adv/attacks/poisoning/c_attack_poisoning.py src/secml/ml/tests/c_module_testcases.py docs/source/pyplots/xlim.py src/secml/figure/c_figure.py src/secml/optim/function/tests/test_function_quadratic.py src/secml/adv/attacks/evasion/foolbox/tests/c_attack_evasion_foolbox_testcases.py src/secml/data/loader/c_dataloader_lfw.py src/secml/ml/kernels/tests/test_c_kernel_chebyshev_distance.py src/secml/optim/optimizers/c_optimizer_pgd_ls.py src/secml/data/loader/loader_utils.py src/secml/ml/peval/c_perfevaluator.py docs/source/pyplots/xticks.py src/secml/ml/kernels/c_kernel_linear.py src/secml/figure/_plots/plot_utils.py src/secml/ml/classifiers/gradients/tests/test_mixin_classifier_gradient_logistic.py docs/source/pyplots/grid.py src/secml/adv/attacks/poisoning/__init__.py src/secml/data/c_dataset_pytorch.py src/secml/adv/attacks/evasion/c_attack_evasion_pgd_exp.py src/secml/figure/tests/test_plot_roc.py src/secml/ml/classifiers/sklearn/tests/test_c_classifier_logistic.py src/secml/ml/classifiers/sklearn/tests/test_c_classifier_knn.py src/secml/optim/function/c_function_linear.py src/secml/optim/function/__init__.py src/secml/ml/classifiers/pytorch/__init__.py src/secml/ml/scalers/c_scaler_minmax.py src/secml/explanation/c_explainer_integrated_gradients.py src/secml/ml/classifiers/sklearn/c_classifier_random_forest.py src/secml/ml/kernels/c_kernel_rbf.py src/secml/adv/seceval/c_sec_eval_data.py src/secml/data/splitter/c_datasplitter_labelkfold.py src/secml/ml/peval/metrics/c_metric_accuracy.py src/secml/utils/__init__.py src/secml/model_zoo/tests/test_model_zoo.py src/secml/array/tests/test_c_array_utils_search.py src/secml/data/loader/tests/test_dataloader_imgfolders.py docs/source/pyplots/scatter.py src/secml/ml/classifiers/loss/c_loss_logistic.py src/secml/ml/peval/c_perfevaluator_xval_multiclass.py src/secml/adv/attacks/evasion/cleverhans/tests/c_attack_evasion_cleverhans_testcases.py src/secml/array/tests/test_c_array_indexing.py src/secml/ml/peval/metrics/c_metric_precision.py src/secml/optim/constraints/__init__.py src/secml/array/tests/test_c_array_utils_shapealteration.py src/secml/optim/optimizers/line_search/c_line_search_bisect_proj.py src/secml/figure/tests/test_plot_classifier.py src/secml/optim/constraints/tests/test_c_constraint_box.py src/secml/adv/attacks/evasion/foolbox/fb_attacks/fb_basic_iterative_attack.py src/secml/optim/constraints/c_constraint_l1.py src/secml/optim/optimizers/__init__.py src/secml/core/exceptions.py src/secml/ml/features/normalization/c_normalizer_mean_std.py src/secml/optim/optimizers/tests/test_c_optimizer_pgd_exp.py src/secml/ml/classifiers/multiclass/tests/test_c_classifier_multi_ova.py src/secml/ml/peval/metrics/c_metric_test_error.py src/secml/adv/attacks/poisoning/c_attack_poisoning_logistic_regression.py src/secml/adv/attacks/poisoning/tests/test_c_attack_poisoning_svm.py src/secml/ml/kernels/tests/test_c_kernel_histintersect.py src/secml/adv/attacks/evasion/foolbox/fb_attacks/fb_pgd_attack.py src/secml/figure/_plots/c_plot_ds.py src/secml/ml/classifiers/clf_utils.py src/secml/adv/seceval/__init__.py src/secml/data/selection/c_ps_center.py src/secml/ml/classifiers/tests/c_classifier_testcases.py src/secml/optim/constraints/tests/test_c_constraint_l1.py src/secml/ml/classifiers/loss/c_loss_cross_entropy.py src/secml/ml/scalers/c_scaler_sklearn.py src/secml/ml/classifiers/loss/tests/test_c_softmax.py src/secml/adv/attacks/poisoning/c_attack_poisoning_ridge.py src/secml/utils/mixed_utils.py src/secml/optim/constraints/c_constraint_l2.py src/secml/adv/seceval/c_sec_eval.py src/secml/adv/__init__.py src/secml/data/selection/tests/test_prototypes_selection.py src/secml/core/type_utils.py src/secml/ml/classifiers/regularizer/c_regularizer_l1.py src/secml/ml/classifiers/sklearn/c_classifier_ridge.py src/secml/ml/scalers/tests/test_c_scaler_norm.py src/secml/data/loader/c_dataloader_icubworld.py src/secml/ml/classifiers/sklearn/c_classifier_svm.py src/secml/data/splitter/tests/test_train_test_split.py src/secml/ml/classifiers/secure/c_classifier_sec_svm.py src/secml/ml/features/normalization/tests/__init__.py docs/source/pyplots/contour.py src/secml/optim/function/tests/test_function_beale.py src/secml/adv/attacks/evasion/tests/test_c_attack_evasion_pgd_ls_multiclass.py src/secml/ml/features/reduction/c_reducer_lda.py src/secml/adv/attacks/evasion/tests/c_attack_evasion_testcases.py src/secml/ml/classifiers/regularizer/c_regularizer_l2.py src/secml/ml/classifiers/gradients/tests/test_classes/c_classifier_gradient_test_ridge.py src/secml/ml/classifiers/__init__.py src/secml/adv/attacks/evasion/tests/test_c_attack_evasion_pgd_ls.py src/secml/ml/classifiers/sklearn/tests/test_c_classifier_random_forest.py src/secml/ml/tests/__init__.py src/secml/ml/c_module.py src/secml/ml/scalers/tests/c_scaler_testcases.py src/secml/optim/optimizers/tests/test_c_optimizer_pgd.py src/secml/ml/features/reduction/c_reducer_pca.py src/secml/optim/function/tests/test_function_3hcamel.py src/secml/ml/peval/metrics/tests/test_roc.py src/secml/ml/kernels/tests/__init__.py src/secml/adv/attacks/evasion/foolbox/fb_attacks/fb_deepfool_attack.py src/secml/adv/attacks/evasion/tests/test_c_attack_evasion_pgd_exp.py src/secml/optim/optimizers/tests/test_c_optimizer_scipy.py docs/source/pyplots/loglog.py src/secml/ml/peval/metrics/c_metric_mse.py src/secml/array/tests/test_c_array_classmethods.py src/secml/optim/optimizers/c_optimizer_pgd.py src/secml/adv/attacks/evasion/foolbox/losses/ead_loss.py src/secml/data/splitter/c_datasplitter_stratkfold.py src/secml/adv/attacks/evasion/foolbox/c_attack_evasion_foolbox.py src/secml/data/selection/tests/plot_ps.py src/secml/ml/classifiers/gradients/tests/test_mixin_classifier_gradient_sgd.py src/secml/ml/features/normalization/c_normalizer_dnn.py src/secml/data/tests/test_cdataset.py src/secml/adv/attacks/evasion/foolbox/tests/test_c_attack_evasion_foolbox_pgd.py src/secml/ml/kernels/c_kernel.py src/secml/data/loader/c_dataloader_cifar.py src/secml/ml/classifiers/gradients/tests/test_classes/c_classifier_gradient_test_linear.py src/secml/ml/features/normalization/c_normalizer_minmax.py src/secml/core/c_creator.py src/secml/data/splitter/tests/test_chronological_splitter.py src/secml/core/attr_utils.py src/secml/adv/attacks/evasion/c_attack_evasion.py src/secml/ml/kernels/c_kernel_poly.py src/secml/ml/features/normalization/c_normalizer.py src/secml/ml/classifiers/sklearn/tests/test_c_classifier_decision_tree.py src/secml/ml/classifiers/sklearn/c_classifier_logistic.py src/secml/adv/attacks/evasion/foolbox/tests/test_secml_autograd.py src/secml/__init__.py src/secml/ml/features/reduction/tests/test_c_reducer_lda.py src/secml/ml/peval/metrics/c_metric_fnr_at_fpr.py src/secml/ml/classifiers/multiclass/tests/test_c_classifier_multi_ovo.py src/secml/adv/seceval/tests/test_c_sec_eval_evasion.py docs/source/pyplots/bar.py src/secml/data/loader/tests/test_dataloader_pytorch.py src/secml/ml/features/normalization/tests/test_c_normalizer_unitnorm.py src/secml/optim/optimizers/line_search/c_line_search_bisect.py src/secml/figure/_plots/c_plot_metric.py src/secml/ml/features/tests/__init__.py src/secml/ml/kernels/c_kernel_laplacian.py src/secml/ml/classifiers/gradients/mixin_classifier_gradient.py src/secml/data/splitter/c_datasplitter_openworld.py src/secml/ml/classifiers/reject/__init__.py src/secml/ml/kernels/tests/test_c_kernel_linear.py src/secml/ml/classifiers/reject/tests/__init__.py docs/source/pyplots/contourf.py src/secml/optim/function/c_function_quadratic.py src/secml/optim/optimizers/tests/c_optimizer_testcases.py src/secml/parallel/__init__.py src/secml/ml/classifiers/loss/__init__.py setup.py src/secml/data/splitter/c_datasplitter.py src/secml/ml/classifiers/pytorch/tests/test_c_classifier_pytorch_conv.py src/secml/optim/optimizers/c_optimizer_scipy.py src/secml/ml/classifiers/reject/c_classifier_dnr.py src/secml/ml/scalers/__init__.py src/secml/_globals.py src/secml/adv/attacks/c_attack.py src/secml/array/tests/test_c_array_utils_comparison.py src/secml/ml/classifiers/regularizer/c_regularizer.py src/secml/optim/function/c_function_3hcamel.py src/secml/array/tests/test_c_array_sysoverloads.py src/secml/ml/classifiers/sklearn/c_classifier_sgd.py src/secml/ml/features/c_preprocess.py src/secml/data/selection/c_ps_random.py src/secml/optim/function/tests/test_function_mccormick.py src/secml/adv/attacks/poisoning/tests/__init__.py src/secml/test_simple.py src/secml/data/selection/c_ps_border.py src/secml/figure/tests/test_plot_metric.py src/secml/utils/tests/test_download_utils.py src/secml/ml/peval/metrics/c_metric_fnr_at_th.py src/secml/ml/classifiers/gradients/mixin_classifier_gradient_ridge.py src/secml/ml/classifiers/multiclass/c_classifier_multi_ovo.py src/secml/data/c_dataset_header.py src/secml/adv/attacks/evasion/foolbox/tests/test_c_attack_evasion_foolbox_deepfool.py src/secml/array/array_utils.py src/secml/ml/classifiers/c_classifier_dnn.py src/secml/adv/attacks/poisoning/tests/test_c_attack_poisoning_ridge.py src/secml/ml/classifiers/gradients/mixin_classifier_gradient_linear.py src/secml/ml/features/normalization/__init__.py src/secml/parallel/parfor.py src/secml/explanation/tests/test_c_explainer_gradient_input.py src/secml/optim/optimizers/tests/test_c_optimizer_pgd_ls_discrete.py src/secml/core/tests/test_attr_utils.py src/secml/ml/peval/metrics/c_metric.py src/secml/array/tests/test_c_array_utils_appendmerge.py src/secml/optim/optimizers/line_search/__init__.py docs/source/pyplots/subplot.py src/secml/data/c_dataset.py src/secml/array/tests/test_c_array_saveload.py src/secml/ml/features/normalization/tests/c_normalizer_testcases.py src/secml/utils/pickle_utils.py src/secml/ml/classifiers/sklearn/tests/test_c_classifier_ridge.py src/secml/adv/attacks/evasion/foolbox/fb_attacks/fb_cw_attack.py src/secml/ml/classifiers/c_classifier_linear.py src/secml/figure/tests/test_plot_constraint.py src/secml/ml/classifiers/sklearn/c_classifier_knn.py src/secml/adv/attacks/evasion/cleverhans/tests/test_c_attack_evasion_cleverhans.py src/secml/ml/classifiers/sklearn/__init__.py src/secml/testing/__init__.py src/secml/adv/attacks/evasion/c_attack_evasion_pgd.py src/secml/explanation/c_explainer.py src/secml/adv/attacks/evasion/tests/test_c_attack_evasion_pgd_ls_mnist.py src/secml/utils/c_file_manager.py src/secml/adv/attacks/poisoning/c_attack_poisoning_svm.py src/secml/optim/function/c_function.py src/secml/optim/function/tests/__init__.py src/secml/adv/attacks/evasion/cleverhans/tests/test_c_attack_evasion_cleverhans_mnist.py src/secml/adv/attacks/evasion/c_attack_evasion_pgd_ls.py src/secml/adv/attacks/evasion/tests/__init__.py src/secml/data/loader/c_dataloader_pytorch.py src/secml/ml/classifiers/gradients/tests/test_classes/__init__.py src/secml/adv/attacks/evasion/foolbox/fb_attacks/fb_fgm_attack.py src/secml/array/tests/test_csr_sparse.py src/secml/adv/attacks/evasion/foolbox/losses/deepfool_loss.py src/secml/adv/attacks/evasion/__init__.py src/secml/ml/peval/metrics/c_metric_f1.py src/secml/data/loader/tests/test_dataloader_svmlight.py src/secml/ml/classifiers/sklearn/c_classifier_decision_tree.py src/secml/optim/function/tests/test_function.py docs/source/pyplots/xticklabels.py src/secml/ml/classifiers/regularizer/__init__.py src/secml/ml/kernels/tests/test_c_kernel_poly.py src/secml/data/splitter/c_datasplitter_kfold.py src/secml/ml/classifiers/gradients/mixin_classifier_gradient_logistic.py src/secml/ml/features/__init__.py src/secml/adv/attacks/__init__.py src/secml/ml/classifiers/reject/tests/test_c_classifier_reject_threshold.py src/secml/core/constants.py src/secml/ml/classifiers/pytorch/tests/test_c_classifier_pytorch_dnn.py docs/source/pyplots/semilogy.py src/secml/adv/attacks/poisoning/tests/test_c_attack_poisoning_logistic_regression.py src/secml/data/loader/c_dataloader_svmlight.py src/secml/figure/_plots/__init__.py src/secml/adv/attacks/evasion/foolbox/tests/test_c_attack_evasion_foolbox_fgm.py src/secml/figure/tests/test_cfigure.py src/secml/ml/classifiers/loss/c_loss_squared.py src/secml/array/c_array_interface.py src/secml/ml/features/tests/c_preprocess_testcases.py src/secml/ml/classifiers/pytorch/tests/__init__.py src/secml/utils/list_utils.py src/secml/ml/peval/metrics/__init__.py src/secml/array/tests/test_c_array_utils_mathelementwise.py src/secml/ml/peval/metrics/c_metric_recall.py src/secml/explanation/tests/test_c_explainer_integrated_gradients.py src/secml/model_zoo/load_model.py src/secml/ml/classifiers/gradients/tests/test_classes/c_classifier_gradient_test_svm.py src/secml/optim/optimizers/tests/__init__.py src/secml/ml/features/normalization/tests/test_c_normalizer_mean_std.py src/secml/ml/classifiers/loss/tests/test_c_loss_classification.py src/secml/data/data_utils.py src/secml/ml/features/normalization/tests/test_c_normalizer_tfidf.py src/secml/ml/classifiers/sklearn/tests/test_c_classifier_nearest_centroid.py src/secml/explanation/tests/test_c_explainer_gradient.py src/secml/adv/attacks/evasion/foolbox/losses/ce_loss.py src/secml/adv/attacks/poisoning/tests/c_attack_poisoning_testcases.py src/secml/ml/peval/metrics/c_metric_tpr_at_fpr.py src/secml/array/c_dense.py src/secml/ml/classifiers/reject/tests/test_c_classifier_reject.py src/secml/ml/peval/metrics/c_metric_tpr_at_th.py src/secml/ml/peval/metrics/c_metric_th_at_fpr.py src/secml/optim/function/c_function_mccormick.py src/secml/ml/peval/metrics/c_metric_mae.py src/secml/array/tests/__init__.py src/secml/data/loader/__init__.py src/secml/array/tests/test_c_array_utils_dataalteration.py src/secml/ml/classifiers/multiclass/__init__.py src/secml/ml/classifiers/reject/tests/test_c_classifier_dnr.py src/secml/figure/_plots/c_plot_constraint.py src/secml/ml/features/reduction/c_reducer.py src/secml/data/tests/test_cdataset_header.py docs/source/conf.py src/secml/figure/_plots/c_plot_sec_eval.py docs/source/pyplots/legend.py src/secml/ml/classifiers/sklearn/c_classifier_nearest_centroid.py src/secml/optim/constraints/tests/test_c_constraint_l2.py src/secml/ml/classifiers/pytorch/tests/c_classifier_pytorch_testcases.py src/secml/ml/classifiers/sklearn/c_classifier_sklearn.py src/secml/ml/peval/metrics/c_metric_pauc.py src/secml/ml/peval/tests/test_perf_evaluator_multiclass.py src/secml/data/loader/tests/test_dataloader_mnist.py src/secml/ml/classifiers/gradients/__init__.py docs/source/pyplots/semilogx.py src/secml/ml/scalers/tests/__init__.py src/secml/adv/attacks/evasion/foolbox/losses/cw_loss.py src/secml/ml/classifiers/secure/tests/test_c_classifier_sec_svm.py src/secml/ml/features/reduction/__init__.py src/secml/core/__init__.py src/secml/adv/attacks/evasion/foolbox/fb_attacks/fb_ddn_attack.py src/secml/ml/peval/metrics/c_roc.py src/secml/ml/classifiers/loss/c_loss_epsilon_insensitive.py src/secml/array/tests/test_c_array_copy.py src/secml/figure/tests/test_plot_function.py src/secml/adv/attacks/evasion/cleverhans/tests/__init__.py src/secml/adv/attacks/evasion/foolbox/tests/test_c_attack_evasion_foolbox_basic_iterative.py docs/source/pyplots/subplots_adjust.py src/secml/ml/peval/tests/test_perf_evaluator.py docs/source/pyplots/clabel.py src/secml/ml/classifiers/loss/c_softmax.py src/secml/optim/function/tests/test_function_rosenbrock.py src/secml/ml/classifiers/regularizer/c_regularizer_elastic_net.py src/secml/ml/classifiers/gradients/mixin_classifier_gradient_sgd.py src/secml/ml/kernels/c_kernel_chebyshev_distance.py src/secml/data/selection/__init__.py src/secml/utils/c_log.py docs/source/pyplots/colorbar.py src/secml/model_zoo/tests/_test_model_clf.py src/secml/ml/peval/__init__.py src/secml/utils/tests/test_pickle_utils.py src/secml/adv/attacks/evasion/foolbox/secml_autograd.py src/secml/array/tests/test_c_array_utils_mixed.py src/secml/ml/features/reduction/tests/test_c_reducer_pca.py src/secml/optim/function/tests/c_function_testcases.py src/secml/optim/optimizers/tests/test_c_optimizer_pgd_ls.py src/secml/ml/kernels/tests/test_c_kernel_euclidean.py src/secml/data/splitter/c_chronological_splitter.py src/secml/optim/constraints/c_constraint_box.py src/secml/ml/stats/c_density_estimation.py src/secml/array/tests/test_c_array_init.py src/secml/data/splitter/tests/test_data_splitter.py src/secml/ml/peval/metrics/tests/test_metrics.py src/secml/data/splitter/c_datasplitter_shuffle.py src/secml/adv/attacks/evasion/foolbox/fb_attacks/fb_ead_attack.py src/secml/array/__init__.py src/secml/model_zoo/__init__.py src/secml/data/splitter/c_train_test_split.py src/secml/utils/download_utils.py src/secml/ml/kernels/__init__.py src/secml/ml/peval/c_perfevaluator_xval.py src/secml/ml/kernels/tests/c_kernel_testcases.py src/secml/data/loader/c_dataloader.py src/secml/ml/peval/metrics/c_metric_auc.py src/secml/adv/attacks/evasion/tests/test_c_attack_evasion_pgd_ls_reject_threshold.py src/secml/array/c_sparse.py src/secml/data/selection/c_prototypes_selector.py src/secml/ml/classifiers/gradients/tests/__init__.py src/secml/adv/attacks/evasion/foolbox/losses/logits_loss.py parse_readme read git_version find_version write_rev install_deps f f f f f _config_fpath parse_config _parse_env_config _parse_env test_simple _NoValueType git_version _write_rev global_filterwarnings _read CAttack CAttackMixin CAttackEvasion CAttackEvasionPGD CAttackEvasionPGDExp CAttackEvasionPGDLS _CModelCleverhans CAttackEvasionCleverhans _CClvrh_params _py_func_with_gradient _CClassifierToTF CAttackEvasionCleverhansLossesMixin CAttackEvasionCleverhansTestCases TestCAttackEvasionCleverhans TestCAttackEvasionCleverhansMNIST CAttackEvasionFoolbox _FoolboxModel as_carray SecmlAutogradFunction SecmlLayer as_tensor CFoolboxBasicIterativeL1 CFoolboxBasicIterative CFoolboxBasicIterativeLinf CFoolboxBasicIterativeL2 CFoolboxL2CarliniWagner _L2CarliniWagnerAttack CFoolboxL2DDN CFoolboxDeepfoolLinf CFoolboxDeepfool CFoolboxDeepfoolL2 _EADAttack CFoolboxEAD CFoolboxFGML1 CFoolboxFGM CFoolboxFGMLinf CFoolboxFGML2 CFoolboxPGD CFoolboxPGDL2 CFoolboxPGDL1 CFoolboxPGDLinf CELoss CWLoss DeepfoolLoss EADLoss LogitsLoss CAttackEvasionFoolboxTestCases TestCAttackEvasionFoolboxBasicIterativeL2 TestCAttackEvasionFoolboxBasicIterativeL1 TestCAttackEvasionFoolboxBasicIterativeLinf TestCAttackEvasionFoolboxCW TestCAttackEvasionFoolboxDDN TestCAttackEvasionFoolboxDeepfoolL2CELoss TestCAttackEvasionFoolboxDeepfoolL2Logits TestCAttackEvasionFoolboxDeepfoolLInfCELoss TestCAttackEvasionFoolboxDeepfoolLInfLogits TestCAttackEvasionFoolboxEAD TestCAttackEvasionFoolboxFGML2 TestCAttackEvasionFoolboxFGMLinf TestCAttackEvasionFoolboxFGML1 TestCAttackEvasionFoolboxPGDL2 TestCAttackEvasionFoolboxPGDL1 TestCAttackEvasionFoolboxPGDLinf TestSecmlAutograd CAttackEvasionTestCases TestCAttackEvasionPGD TestCAttackEvasionPGDExp TestCAttackEvasionPGDLS TestCAttackEvasionPGDLSMNIST TestCAttackEvasionPGDLSMNIST TestCAttackEvasionPGDLSRejectThreshold CAttackPoisoning CAttackPoisoningLogisticRegression CAttackPoisoningRidge CAttackPoisoningSVM _CAttackPoisoningLinTest CAttackPoisoningTestCases TestCAttackPoisoningLogisticRegression TestCAttackPoisoningRidge TestCAttackPoisoningSVMLinear TestCAttackPoisoningSVMRBF CSecEval CSecEvalData TestCSecEval tuple_sequence_tondarray is_vector_index tuple_atomic_tolist _instance_data CArray _CArrayInterface CDense _shape_atleast_2d CSparse _expand_nnz_bool CArrayTestCases TestCSparse TestCArrayCasting TestCArrayClassMethods TestCArrayCopy TestCArrayIndexing TestCArrayInit TestCArrayProperties TestCArraySaveLoad TestCArraySystemOverloads TestCArrayUtilsAppendMerge TestCArrayUtilsComparison TestCArrayUtilsDataAlteration TestCArrayUtilsDataAnalysis TestCArrayUtilsMathElementWise TestCArrayUtilsMixed TestCArrayUtilsSearch TestCArrayUtilsShapeAlteration TestCDense _check_is_attr_name is_readwrite extract_attr add_readonly has_getter as_protected has_protected is_protected as_public has_private is_readonly is_public get_property is_readable get_private add_readwrite has_property has_setter is_writable get_protected as_private has_super import_package_classes CCreator _check_class_types_duplicates import_class_types deprecated NotFittedError is_list is_tuple is_intlike is_str is_posinf is_dict is_set is_inf to_builtin is_bool is_bytes is_list_of_lists is_float is_neginf is_scalarlike is_floatlike is_slice is_int is_nan is_ndarray is_scalar is_scsarray TestAttributeUtilities Foo Doo Coo TestCCreator Foo CDataset CDatasetHeader CDatasetPyTorch label_binarize_onehot CDataLoader CDataLoaderCIFAR100 CDataLoaderCIFAR10 CDataLoaderCIFAR CDataLoaderICubWorld28 CDataLoaderICubWorld CDataLoaderImgClients CDataLoaderImgFolders CDataLoaderLFW CDataLoaderMNIST CDataLoaderPyTorch CDLRandomCircles CDLBoston CDLRandomBinary CDLDiabetes CDLRandomRegression CDLRandomMoons CDLRandomToy CDLRandomBlobs CDLRandomCircleRegression CDLDigits CDLRandomBlobsRegression CDLRandom CDLIris CDataLoaderSvmLight resize_img crop_img TestCDataLoader TestCDataLoaderImgClients TestCDataLoaderImgFolders TestCDataLoaderMNIST TestCDataLoaderPytorch TestCDataLoaderSvmLight CPrototypesSelector CPSBorder CPSCenter CPSKMedians CPSRandom CPSSpanning TestPS CChronologicalSplitter CDataSplitter CDataSplitterKFold CDataSplitterLabelKFold CDataSplitterOpenWorldKFold CDataSplitterShuffle CDataSplitterStratifiedKFold CTrainTestSplit TestCChronologicalSplitter TestCDataSplitter TestCTrainTestSplit TestDataset TestCDatasetHeader TestCDatasetPyTorch CExplainer CExplainerGradient CExplainerGradientInput CExplainerInfluenceFunctions CExplainerIntegratedGradients TestCExplainerGradient TestCExplainerGradientInput TestCExplainerInfluenceFunctions TestCExplainerIntegratedGradients CFigure TestCFigure TestCPlot TestCPlotClassifier TestCPlotConstraint TestCPlot TestCPlotClassifier TestCRoc CPlot CPlotClassifier CPlotConstraint CPlotDataset CPlotFunction CPlotMetric CPlotSecEval _cmpt_sec_eval_curve CPlotStats create_points_grid CModule convert_binary_labels check_binary_labels CClassifier CClassifierDNN CClassifierLinearMixin CClassifierGradientMixin CClassifierGradientLinearMixin CClassifierGradientLogisticMixin CClassifierGradientRidgeMixin CClassifierGradientSGDMixin CClassifierGradientMixinTestCases TestCClassifierGradientLogisticMixin TestCClassifierGradientRidgeMixin TestCClassifierGradientSGDMixin TestCClassifierGradientSVMMixin CClassifierGradientTest CClassifierGradientTestLinear CClassifierGradientTestLogisticRegression CClassifierGradientTestRidge CClassifierGradientTestSVM CLossRegression CLoss CLossClassification _check_binary_score CLossCrossEntropy CLossEpsilonInsensitive CLossEpsilonInsensitiveSquared CLossHingeSquared CLossHinge CLossLogistic CLossSquare CLossQuadratic CSoftmax TestCLossClassification TestCLossCrossEntropy TestCLossRegression TestCSoftmax CClassifierMulticlass CClassifierMulticlassOVA _fit_one_ova _forward_one_ova _fit_one_ovo CClassifierMulticlassOVO _forward_one_ovo TestCClassifierMultiOVA TestCClassifierMultiOVO get_layers CClassifierPyTorch CClassifierPyTorchTestCases Net TestCClassifierPyTorchBlobs TestCClassifierPyTorchMNIST TestCClassifierPyTorchDNN CRegularizer CRegularizerElasticNet CRegularizerL1 CRegularizerL2 CClassifierDNR CClassifierReject CClassifierRejectThreshold TestCClassifierDNR CClassifierRejectTestCases TestCClassifierRejectThreshold CClassifierSecSVM TestCClassifierSecSVM CClassifierDecisionTree CClassifierKNN CClassifierLogistic CClassifierNearestCentroid CClassifierRandomForest CClassifierRidge CClassifierSGD CWrapperSkLearnMixin CClassifierSkLearn _fit_one_ova CClassifierSVM TestCClassifierDecisionTree TestCClassifierKNN TestCClassifierLogistic TestCClassifierNearestCentroid TestCClassifierRandomForest TestCClassifierRidge TestCClassifierSGD TestCClassifierSkLearn TestCClassifierSVM CClassifierTestCases CPreProcess CNormalizer CNormalizerDNN CNormalizerLinear CNormalizerMeanStd CNormalizerMinMax CNormalizerTFIDF CNormalizerUnitNorm CNormalizerTestCases mlp TestCNormalizerPyTorch TestCNormalizerMeanStd TestCNormalizerMinMax TestCNormalizerTFIDF TestCNormalizerUnitNorm CReducer CLDA CPCA TestCLda TestCPca CPreProcessTestCases CKernel CKernelChebyshevDistance CKernelEuclidean CKernelHistIntersect CKernelLaplacian CKernelLinear CKernelPoly CKernelRBF CCKernelTestCases TestCKernelChebyshevDistance TestCKernelEuclidean TestCKernelHistIntersect TestCKernelLaplacian TestCKernelLinear TestCKernelPoly TestCKernelRBF _evaluate_one CPerfEvaluator CPerfEvaluatorXVal CPerfEvaluatorXValMulticlass CMetricConfusionMatrix CMetric CMetricAccuracy CMetricAUC CMetricAUCWMW CMetricF1 CMetricFNRatFPR CMetricFNRatTH CMetricMAE CMetricMSE CMetricPartialAUC CMetricPrecision CMetricRecall CMetricTestError CMetricTHatFPR CMetricTPRatFPR CMetricTPRatTH average CRoc refine_roc CBaseRoc TestCMetrics TestCRoc CMetricAllNan TestCPerfEvaluator CMetricFirstNan TestCPerfEvaluatorMulticlass CScalerMinMax CScalerNorm CScalerSkLearn CScalerStd CScalerTestCases TestCScalerMinMax TestCScalerNorm TestCScalerStd CDensityEstimation CDistributionGaussian TestCClass CModuleTestCases TestCModule _get_models_dict _dl_data_versioned load_model TestModelZoo _test_model_clf CConstraint CConstraintBox CConstraintL1 CConstraintL2 CConstraintTestCases TestConstraintBox TestCConstraintL1 TestCConstraintL2 CFunction CFunctionThreeHumpCamel CFunctionBeale CFunctionLinear CFunctionMcCormick CFunctionQuadratic CFunctionRosenbrock CFunctionTestCases TestCFunction TestCFunctionThreeHumpCamel TestCFunctionBeale TestCFunctionMcCormick TestCFunctionCircle TestCFunctionRosenbrock COptimizer COptimizerPGD COptimizerPGDExp COptimizerPGDLS COptimizerScipy CLineSearch CLineSearchBisect CLineSearchBisectProj TestLineSearch COptimizerTestCases TestCOptimizerPGD TestCOptimizerPGDExp TestCOptimizerPGDLS TestCOptimizerPGDLSDiscrete TestCOptimizerScipy element_wise_power parfor2 parfor CUnitTest ignore_function abspath file_exist make_folder make_folder_incwd dirsep folder_exist copy_folder normpath expanduser get_tempfile splitext copy_file listdir join remove_folder remove_file make_rand_folder split CTimer CLog merge_dicts load_dict LastInDict invert_dict SubLevelsDict md5 dl_file dl_file_gitlab find_duplicates check_is_fitted AverageMeter OrderedFlexibleClass load save TestCLog TestDownloadUtils TestPickleUtils decode _minimal_ext_cmd git_version read write_rev parse_version join write open append strip rstrip readlines zeros range get read ConfigParser getboolean reversed getint getfloat append gen_candidates isfile show CFigure test_dot plot join write open ERROR filterwarnings set_verbosity get_default_graph getrandbits type input_shape view getenv main tuple CArray isinstance empty is_int _check_is_attr_name _check_is_attr_name startswith _check_is_attr_name _check_is_attr_name _check_is_attr_name _check_is_attr_name _check_is_attr_name setattr as_protected __class__ property setattr as_protected __class__ property _check_is_attr_name _check_is_attr_name _check_is_attr_name _check_is_attr_name _check_is_attr_name _check_is_attr_name parse_modes any __dict__ CLog import_module __module__ find_duplicates integer isinstance is_int is_float any isinstance isinstance is_int is_bytes is_float is_str is_bool max arange Lock __doc__ Lock Lock Lock Lock LINEAR size LANCZOS resize int size round size range zeros ravel performance_score meshgrid reshape linspace concatenate __doc__ check_binary_labels CClassifierGradientTestLogisticRegression CClassifierGradientTestRidge CClassifierGradientTestSVM ravel format binarize_dataset verbose Y info X fit format info format binarize_subset verbose Y info X fit format info items list CRegularizerL2 CLossLogistic CRegularizerL2 CLossSquare SVC CArray get_data CLossHinge __doc__ __doc__ str any enumerate compute_performance set_params format item info enumerate append zip len linspace interp zeros std enumerate group dl_file_gitlab join utcnow _dl_data_versioned file_exist join import_module abspath load_state _dl_data_versioned getenv Pool min cpu_count min cpu_count print format append enumerate skipif skip importorskip staticmethod __doc__ main abspath makedirs rmtree rmdir abspath remove abspath copytree copy randint update items list tolist get int join format strip write remove_file flush make_folder rstrip format quote lstrip startswith urlparse add seen_add seen2times_add set condition is_str | # SecML: Secure and Explainable Machine Learning in Python [](.) [](.) [](.) [](https://www.apache.org/licenses/LICENSE-2.0) SecML is an open-source Python library for the **security evaluation** of Machine Learning algorithms. It is equipped with **evasion** and **poisoning** adversarial machine learning attacks, and it can **wrap models and attacks** from other different frameworks. ## Table of Contents | 3,330 |
pranoy-panda/ICAPR2017_Dehazing | ['image dehazing'] | ['Image Dehazing via Joint Estimation of Transmittance Map and Environmental Illumination'] | src/data_generation/helper_functions.py src/final_assembly/Final_code.py src/data_generation/preprocess.py src/cnn_network/network.py src/final_assembly/init.py src/data_generation/init.py add_haze patch_generate return_A exp ones copy flatten shape append median array ones shape astype uniform array | # Image Dehazing via Joint Estimation of Transmittance Map and Environmental Illumination | Input | Transmittance Map | Dehazed Image | | ------------- | ------------- | ------------- | |  |  |  Haze limits the visibility of outdoor images, due to the existence of fog, smoke and dust in the atmosphere. In this work, we present an end to end system, which takes a hazy image as its input and returns a dehazed image. The proposed method learns the mapping between a hazy image and its corresponding transmittance map and the environmental illumination, by using a multi-scale Convolutional Neural Network. This repository contains a python implementation of the same. - Authors: [Sanchayan Santra](http://san-santra.github.io/), [Ranjan Mondal](https://www.isical.ac.in/~ranjan15_r/), [Pranoy Panda](http://pranoy-panda.github.io/), [Nishant Mohanty](https://www.linkedin.com/in/nishantmohanty/), [Shubham Bhuyan](https://www.linkedin.com/in/shubham-bhuyan-326947137/) - Paper : [https://arxiv.org/abs/1812.01273](https://arxiv.org/pdf/1812.01273.pdf) - Conference: 9th International Conference on Advances in Pattern Recognition (ICAPR), 2017 ## Requirements: 1. Python 2.7+ or 3.5+. | 3,331 |
prasanna4567/COVID-19_MLDM | ['malware classification'] | ['A New Burrows Wheeler Transform Markov Distance'] | lib/plot_text.py lib/call_backs.py input_callback selected_code CustomJS | # COVID-19 Literature Clustering  # Goal Given the large number of literature and the rapid spread of COVID-19, it is difficult for health professionals to keep up with new information on the virus. Can clustering similar research articles together simplify the search for related publications? How can the content of the clusters be qualified? By using clustering for labelling in combination with dimensionality reduction for visualization, the collection of literature can be represented by a scatter plot. On this plot, publications of highly similar topic will share a label and will be plotted near each other. In order, to find meaning in the clusters, topic modelling will be performed to find the keywords of each cluster. By using Bokeh, the plot will be interactive. User’s will have the option of seeing the plot as a whole or filtering the data by cluster. If a narrower scope is required, the plot will also have a search function which will limit the output to only papers containing the search term. Hovering over points on the plot will give basic information like title, author, journal, and abstract. Clicking on a point will bring up a menu with a URL that can be used to access the full publication. This is a difficult time in which health care workers, sanitation staff, and many other essential personnel are out there keeping the world afloat. While adhering to quarantine protocol, the Kaggle CORD-19 competition has given us an opportunity to help in the best way we can as computer science students. It should be noted, however, that we are not epidemiologists, and it is not our place to gauge the importance of these papers. This tool was created to help make it easier for trained professionals to sift through many, many publications related to the virus, and find their own determinations. - ### [View the Interactive COVID-19 Literature Clustering Plot Here](https://maksimekin.github.io/COVID19-Literature-Clustering/plots/t-sne_covid-19_interactive.html) - ### [View the CORD-19 Dataset Analysis Notebook Here](https://maksimekin.github.io/COVID19-Literature-Clustering/COVID19_literature_clustering.html) ##### Chase Pipkin from Freethink put together this great video featuring our work on COVID-19 Literature Clustering | 3,332 |
pratikpv/predicting_bitcoin_market | ['sentiment analysis'] | ['Predictive analysis of Bitcoin price considering social sentiments'] | merge_data_files.py merge_crypto_gnews_reddit_sentiment merge_crypto_gnews_sentiment list_diff append list columns to_datetime strptime concat to_csv index strftime range timedelta DataFrame read_csv enumerate to_csv concat read_csv | # Predictive analysis of Bitcoin price considering social sentiments. # ABSTRACT We report on the use of sentiment analysis on news and social media to analyze and predict the price of Bitcoin. Bitcoin is the leading cryptocurrency and has the highest market capitalization among digital currencies. Predicting Bitcoin values may help understand and predict potential market movement and future growth of the technology. Unlike (mostly) repeating phenomena like weather, cryptocurrency values do not follow a repeating pattern and mere past value of Bitcoin does not reveal any secret of future Bitcoin value. Humans follow general sentiments and technical analysis to invest in the market. Hence considering people’s sentiment can give a good degree of prediction. We focus on using social sentiment as a feature to predict future Bitcoin value, and in particular, consider Google News and | 3,333 |
pravitc/Neural-style-transfer-using-Pytorch | ['style transfer'] | ['A Neural Algorithm of Artistic Style'] | style_transfer.py image_convert load_image get_features gram_mat size Compose convert unsqueeze max squeeze transpose array clip detach items list layer t size mm view | # Neural-style-transfer-using-Pytorch Neural style transfer is an optimization technique used to take three images, a content image, a style reference image (such as an artwork by a famous painter), and the input image you want to style — and blend them together such that the input image is transformed to look like the content image, but “painted” in the style of the style image. # Requirements 1.Convolutional Neural Netwroks 2. Pytorch framework. The test will run for 2000 steps which will take approximately 20-30min in GPU or Colab. # Reference 1. https://arxiv.org/abs/1508.06576 A Neural Algorithm of Artistic Style | 3,334 |
previtus/fake_news_generation_mark_I | ['misinformation', 'text generation'] | ['The Myths of Our Time: Fake News'] | 2 load articles, filter into txt files/datasets.py 2 load articles, filter into txt files/datasets_byUrlNames.py 4 select only innovative sentences via the levenstein/analysis_in_one_file.py 2 load articles, filter into txt files/load_functions.py 2 load articles, filter into txt files/keywords.py load join_into_file load_from_urls all_keywords get_urls save_to_txt_file ls string_to_words string_to_sentences cd load items sorted list print len shuffle tqdm filter listdir range open sorted list print len shuffle tqdm filter append listdir range open load sorted list print len shuffle tqdm filter append listdir range open load sorted list print len shuffle tqdm filter append listdir range open print join save_to_txt_file decode print chdir getcwd print | # The Myths of Our Time: Fake News Artwork submitted: [[NeurIPS Workshop]](http://www.aiartonline.com/community/vit-ruzicka-eunsu-kang-david-gordon-ankita-patel-jacqui-fashimpaur-manzil-zaheer/) Short paper submitted: [[ISEA'19]](http://isea2019.isea-international.org/daily26.asp) Pipeline for fake news generation. This process uses several other github repos, here we have the "how to's" text files.  | 3,335 |
primle/LSMDC-Context | ['video captioning'] | ['Enriching Video Captions With Contextual Text'] | download_moviescripts.py | # LSMDC-Context Instructions and code to generate the Large Scale Movie Description Challenge (LSMDC) - Context dataset used in the paper [Enriching Video Captions With Contextual Text](https://arxiv.org/abs/2007.14682). This is an augmented version of the original dataset with movie scripts as contextual text. The source code of the model described in the paper can be found in the [S2VT-Pointer](https://github.com/primle/S2VT-Pointer) repository. ## Disclaimer The source code was written for my master thesis with limited time, without the intention to publish it. Because of legal reasons, the dataset used in the publication cannot be shared. This repository contains the steps to create the dataset and store it in a tokenized format used in [S2VT-Pointer](https://github.com/primle/S2VT-Pointer). ## Usage | 3,336 |
princeton-nlp/LM-BFF | ['few shot learning'] | ['Making Pre-trained Language Models Better Few-shot Learners'] | tools/generate_k_shot_data.py tools/generate_labels.py tools/gather_result.py src/dataset.py run.py tools/get_sbert_embedding.py tools/ensemble.py tools/generate_template.py src/processors.py tools/sort_template.py tools/sort_mapping.py src/models.py src/trainer.py src/label_search.py tools/sort_prompt.py main DynamicTrainingArguments DynamicDataTrainingArguments ModelArguments input_example_to_tuple tokenize_multipart_input FewShotDataset input_example_to_string OurInputFeatures select_neighbors eval_pairing_acc select_likely_words find_labels init eval_pairing_corr BertForPromptFinetuning RobertaForPromptFinetuning resize_token_type_embeddings SnliProcessor text_classification_metrics MrpcProcessor ColaProcessor MnliMismatchedProcessor QqpProcessor MnliProcessor StsbProcessor QnliProcessor RteProcessor TextClassificationProcessor WnliProcessor Sst2Processor default_dev_objective Trainer get_glue_label main get_labels main main get_label load_datasets split_header main DynamicDataTrainingArguments ModelArguments generate search_template get_text load_dataset main main get_sentence load_datasets split_header main main main from_pretrained do_eval save_model resize_token_embeddings save_logit prompt model_id Trainer no_train warning do_train device output_dir save build_compute_metrics_fn do_predict cuda predictions seed no_predict basicConfig set_seed save_at_last gpt3_in_context_tail template resize_token_type_embeddings append save_logit_dir parse_json_file to range is_world_master update format FewShotDataset replace mean template_list gpt3_in_context_num save_pretrained array_id info fp16 parse_args_into_dataclasses train task_name join n_gpu metrics evaluate model_name_or_path bool HfArgumentParser local_rank len warn int decode format _convert_token_to_id replace pad_token_id warn upper lower enc append enumerate split int astype mean argsort append median max range argsort append argmax sum take take select_neighbors join list product cdist select_likely_words take info append numpy enumerate data hasattr Embedding token_type_embeddings size split join format strip len tolist append zeros enumerate open ArgumentParser n_models argmax data_dir get_labels k parse_args glue_compute_metrics eval enumerate load int print add_argument condition zeros str isinstance split join read_csv DataFrame list tolist get_label split_header shuffle startswith task items load_datasets to_csv mode makedirs append_output_file prediction_loop get_eval_dataloader use_seed_labels dirname output_file word_mapping get_vocab label_ids use_space_word find_labels int _convert_token_to_id replace upper lower append range split decode get_text vocab_size cuda decoder_start_token_id max list append range cat _convert_token_to_id size new_zeros mean item long print sort min tqdm len append readlines tolist split join format replace print generate write load_dataset open makedirs t5_model search_template split append tolist SentenceTransformer encode stack tqdm sbert_model get_sentence sort write mapping_dir open prompt_dir template_dir | # LM-BFF (**B**etter **F**ew-shot **F**ine-tuning of **L**anguage **M**odels) This is the implementation of the paper [Making Pre-trained Language Models Better Few-shot Learners](https://arxiv.org/pdf/2012.15723.pdf). LM-BFF is short for **b**etter **f**ew-shot **f**ine-tuning of **l**anguage **m**odels. ## Quick links * [Overview](#overview) * [Requirements](#requirements) * [Prepare the data](#prepare-the-data) * [Run the model](#run-lm-bff) * [Quick start](#quick-start) * [Experiments with multiple runs](#experiments-with-multiple-runs) * [Using demonstrations with filtering](#using-demonstrations-with-filtering) | 3,337 |
princewang1994/TextSnake.pytorch | ['scene text detection'] | ['TextSnake: A Flexible Representation for Detecting Text of Arbitrary Shapes'] | util/detection.py util/visualize.py train_textsnake.py dataset/total_text/Evaluation_Protocol/Python_scripts/Pascal_VOC.py util/augmentation.py dataset/synth-text/make_list.py util/shedule.py dataset/synth_text.py dataset/dataload.py eval_textsnake.py util/summary.py util/misc.py util/config.py network/resnet.py network/loss.py dataset/total_text.py demo.py dataset/deploy.py dataset/data_util.py dataset/total_text/Evaluation_Protocol/Python_scripts/polygon_wrapper.py util/option.py network/vgg.py network/textnet.py dataset/total_text/Evaluation_Protocol/Python_scripts/Deteval.py main write_to_file inference main write_to_file inference validation save_model load_model main train TextDataset pil_load_img TextInstance pil_load_img DeployDataset SynthText TotalText gt_reading_mod many_to_many input_reading_mod detection_filtering sigma_calculation tau_calculation one_to_one one_to_many input_reading_mod detection_filtering gt_reading_mod approx_area_of_intersection iou shapely_area area_of_intersection area shapely_area_of_intersection iod TextLoss ResNet50 TextNet Upsample make_layers VGG16 VGG Rotate AugmentColor SquarePadding Compose RandomMirror RandomResizedLimitCrop RandomContrast Augmentation RandomResizedCrop Resize BaseTransform Normalize RandomBrightness Padding print_config update_config TextDetector norm2 merge_polygons disjoint_find split_edge_seqence AverageMeter cos split_long_edges fill_hole rescale_result mkdirs regularize_sin_cos vector_cos find_bottom to_device vector_sin find_long_edges disjoint_merge BaseOptions str2bool arg2str FixLR LogSummary visualize_network_output visualize_detection imwrite rescale_result to_device write_to_file exp_name vis_dir mkdirs format replace synchronize astype detect enumerate join time uint8 print numpy visualize_detection len join format load_model to TextNet print device DataLoader backbone_name checkepoch TextDetector save_dir output_dir inference DeployDataset cuda exp_name append concatenate zip TotalText call join format print mkdirs backbone_name save save_dir exp_name print format load load_state_dict save_model model zero_grad to_device write_scalars get_lr update format visualize_network_output avg item enumerate time criterion backward print AverageMeter step len FixLR DataParallel StepLR mgpu max_epoch Adam strftime range LogSummary start_epoch TextLoss resume lr SynthText validation log_dir parameters train array open loadmat list squeeze map iod enumerate split range where range where range where polygon zeros sum max minimum min max maximum buffer stack Polygon zeros_like maximum where polygon zeros sum max zeros_like maximum where polygon zeros sum max sum zeros_like maximum where polygon zeros round max Conv2d items list print items list format makedirs astype resize uint8 astype copy floodFill shape zeros bool sqrt sqrt sqrt norm2 concatenate append range len append len append len cumsum sum range append disjoint_find Polygon merge_two_polygon astype xy unique append array range len vars sorted items strftime join uint8 format imwrite concatenate astype vis_dir mkdir resize numpy max range exp_name len uint8 concatenate polylines COLOR_GRAY2BGR astype ascontiguousarray copy cvtColor | # TextSnake: A Flexible Representation for Detecting Text of Arbitrary Shapes A PyTorch implement of **TextSnake: A Flexible Representation for Detecting Text of Arbitrary Shapes** (ECCV 2018) by `Megvii` - Paper link: [arXiv:1807.01544](https://arxiv.org/abs/1807.01544) - Github: [princewang1994/TextSnake.pytorch](https://github.com/princewang1994/TextSnake.pytorch) - Blog: [TextSnake: A Flexible Representation for Detecting Text of Arbitrary Shapes](http://blog.prince2015.club/2019/01/06/TextSnake/) <div style="color:#0000FF" align="center"> <img src="http://princepicbed.oss-cn-beijing.aliyuncs.com/blog_20190120144708.png" width="630"/> </div> ## Paper  | 3,338 |
prismformore/expAT | ['person re identification'] | ['Bi-directional Exponential Angular Triplet Loss for RGB-Infrared Person Re-Identification'] | rgbir_exp/codes/datasets.py rgb_exp/codes/utils/re_ranking.py rgb_exp/codes/modeling/backbones/__init__.py rgb_exp/codes/modeling/baseline.py rgb_exp/codes/layers/__init__.py rgb_exp/codes/data/samplers/triplet_sampler.py rgb_exp/codes/data/build.py rgb_exp/codes/data/datasets/dukemtmcreid.py rgb_exp/codes/layers/AT_loss.py rgbir_exp/codes/solver.py rgb_exp/codes/data/datasets/__init__.py rgb_exp/codes/data/datasets/cuhk03.py rgb_exp/codes/data/datasets/eval_reid.py rgb_exp/codes/data/transforms/build.py rgbir_exp/codes/backbone.py rgb_exp/codes/data/transforms/__init__.py rgbir_exp/codes/criterions.py rgb_exp/codes/solver/build.py rgb_exp/codes/utils/reid_metric.py rgb_exp/codes/engine/trainer.py rgb_exp/codes/config/defaults.py rgb_exp/codes/layers/cluster_loss.py rgb_exp/codes/data/__init__.py rgb_exp/codes/utils/__init__.py rgb_exp/codes/data/datasets/market1501.py rgb_exp/codes/layers/center_loss.py rgb_exp/codes/data/datasets/bases.py rgb_exp/codes/layers/triplet_loss.py rgb_exp/codes/layers/range_loss.py rgbir_exp/codes/models.py rgbir_exp/codes/transforms.py rgb_exp/codes/modeling/__init__.py rgb_exp/codes/tools/train.py rgb_exp/codes/config/__init__.py rgbir_exp/codes/main.py rgb_exp/codes/data/transforms/transforms.py rgb_exp/codes/utils/logger.py rgb_exp/codes/tools/test.py rgb_exp/codes/modeling/backbones/resnet.py rgb_exp/codes/solver/__init__.py rgb_exp/codes/data/datasets/dataset_loader.py rgb_exp/codes/utils/iotools.py rgb_exp/codes/data/datasets/msmt17.py rgb_exp/codes/modeling/backbones/senet.py rgb_exp/codes/tools/__init__.py rgb_exp/codes/data/samplers/__init__.py rgb_exp/codes/engine/inference.py rgbir_exp/codes/settings.py rgb_exp/codes/solver/lr_scheduler.py rgb_exp/codes/data/collate_batch.py rgbir_exp/codes/eval.py ResNet Bottleneck CrossEntropyLabelSmoothLoss expATLoss RegDB_triplet_dataset Image_dataset SYSU_triplet_dataset RegDB_eval_datasets RegDB_wrapper SYSU_eval_datasets evaluate test run_train_val test_ckp ensure_dir Session run_test Baseline FeatureEmbedder IdClassifier weights_init_classifier weights_init_kaiming WarmupMultiStepLR RandomErasing RectScale RandomSizedRectCrop make_data_loader val_collate_fn train_collate_fn BaseDataset BaseImageDataset BaseVideoDataset CUHK03 ImageDataset read_image DukeMTMCreID eval_func Market1501 MSMT17 get_names init_dataset RandomIdentitySampler RandomIdentitySampler_alignedreid build_transforms RandomErasing inference create_supervised_evaluator create_supervised_trainer_with_center create_supervised_trainer do_train create_supervised_evaluator do_train_with_center normalize square_euclidean_dist expATLoss hard_example_mining_at CenterLoss ClusterLoss_local ClusterLoss RangeLoss hard_example_mining euclidean_dist CrossEntropyLabelSmooth TripletLoss normalize make_loss_with_center make_loss weights_init_classifier weights_init_kaiming Baseline build_model ResNet conv3x3 BasicBlock Bottleneck SENet SEResNetBottleneck SEBottleneck SEResNeXtBottleneck Bottleneck SEModule make_optimizer make_optimizer_with_center WarmupMultiStepLR main main train init_seeds check_isfile read_json write_json mkdir_if_missing setup_logger R1_mAP R1_mAP_reranking re_ranking norm format view evaluate print size expand t eval numpy addmm_ invert format asarray print cumsum astype float32 argsort shape mean int32 append sum range makedirs inf_batch get_train_dataloader query DataLoader load_checkpoints Session tensorboard SYSU_triplet_dataset save_checkpoints next SYSU_eval_datasets test eval info test_transforms_list gallery write Image_dataset train step writer sorted writerow close test_ckp listdir open test_transforms_list gallery format test_times test query Image_dataset DataLoader load_checkpoints info zeros range Session SYSU_eval_datasets affine bias kaiming_normal_ weight __name__ constant_ bias normal_ weight __name__ constant_ gallery NAMES init_dataset NUM_WORKERS query ImageDataset DataLoader num_train_pids build_transforms train tensor list zip list zip convert invert format asarray print cumsum astype float32 argsort shape mean int32 append sum range Compose Normalize items list Engine DataParallel to attach DEVICE format getLogger print RE_RANKING info create_supervised_evaluator run to DataParallel to DataParallel CHECKPOINT_PERIOD DEVICE Timer getLogger add_event_handler MAX_EPOCHS EVAL_PERIOD NAME create_supervised_trainer attach info LOG_PERIOD ModelCheckpoint create_supervised_evaluator OUTPUT_DIR EPOCH_COMPLETED run CHECKPOINT_PERIOD DEVICE Timer create_supervised_trainer_with_center CENTER_LOSS_WEIGHT getLogger add_event_handler MAX_EPOCHS EVAL_PERIOD NAME attach info LOG_PERIOD ModelCheckpoint create_supervised_evaluator OUTPUT_DIR EPOCH_COMPLETED run clamp t clamp addmm_ expand ne view size min squeeze t eq float max expand_as t sqrt addmm_ expand data ne view size min squeeze expand t eq gather max NUM_INSTANCE METRIC_LOSS_TYPE format SAMPLER MARGIN IMS_PER_BATCH print CLUSTER_MARGIN CrossEntropyLabelSmooth expATLoss TripletLoss ClusterLoss METRIC_LOSS_TYPE format MARGIN print CrossEntropyLabelSmooth expATLoss TripletLoss CenterLoss RangeLoss NECK_FEAT LAST_STRIDE NECK Baseline NAME PRETRAIN_CHOICE PRETRAIN_PATH WEIGHT_DECAY_BIAS named_parameters BASE_LR BIAS_LR_FACTOR WEIGHT_DECAY WEIGHT_DECAY_BIAS SGD named_parameters parameters BASE_LR BIAS_LR_FACTOR WEIGHT_DECAY ArgumentParser make_data_loader opts load_param OUTPUT_DIR DEVICE_ID freeze parse_args inference merge_from_file format build_model config_file setup_logger WEIGHT merge_from_list mkdir info add_argument manual_seed_all manual_seed STEPS WARMUP_METHOD GAMMA make_loss do_train make_data_loader PRETRAIN_PATH make_optimizer load_state_dict PRETRAIN_CHOICE format make_loss_with_center replace build_model IF_WITH_CENTER eval do_train_with_center WARMUP_FACTOR WARMUP_ITERS load print make_optimizer_with_center WarmupMultiStepLR init_seeds train makedirs makedirs print format isfile dirname mkdir_if_missing setFormatter join getLogger addHandler StreamHandler Formatter DEBUG setLevel FileHandler zeros_like float16 max exp transpose expand append sum range cat size astype mean unique addmm_ minimum print t int32 zeros numpy len | # expAT: Bi-directional Exponential Angular Triplet Loss for RGB-Infrared Person Re-Identification <img src="./triplet_issue.png" width = "600" alt="expAT" align=center /> Paper accepted by the **IEEE Transactions on Image Processing**: [arXiv](https://arxiv.org/abs/2006.00878), [IEEE Xplore](https://ieeexplore.ieee.org/document/9303428) Most existing works use Euclidean metric based constraints to resolve the discrepancy between features of different modalities. However, these methods are incapable of learning angularly discriminative feature embedding because Euclidean distance cannot measure the included angle between embedding vectors effectively. As an angularly discriminative feature space is important for a stable feature space, and also important for the classification branch in training as pointed out in the paper, we **abandon the Euclidean metric based loss function and propose a novel ranking loss function, named Bi-directional Exponential Angular Triplet Loss, to help learn an angularly separable common feature space by explicitly constraining the included angles between embedding vectors.** The proposed Exponential Angular Triplet (expAT) Loss is formulated as: <img src="./expAT_formu.png" width = "600" alt="expAT" align=center /> Moreover, to help stabilize and learn the magnitudes of embedding vectors, we adopt a common space batch normalization layer, which is a variant of batch normalization, to recalibrate feature generated by the backbone model. Quantitative experiments on the SYSU-MM01 and RegDB dataset support our analysis. On SYSU-MM01 dataset, the performance is improved from 7.40% / 11.46% to 38.57% / 38.61% for rank-1 accuracy / mAP compared with the baseline. The proposed method can be generalized to the task of single-modality Re-ID and improves the rank-1 accuracy / mAP from 92.0% / 81.7% to 94.7% / 86.6% on the Market-1501 dataset, from 82.6% / 70.6% to 87.6% / 77.1% on the DukeMTMC-reID dataset. ## Prerequisite - Python>=3.6 | 3,339 |
prithv1/DMG | ['domain generalization'] | ['Learning to Balance Specificity and Invariance for In and Out of Domain Generalization'] | models/subnetwork_supermask_model.py trainers/multihead_trainer.py dataloaders/__init__.py train_model.py data/DomainNet/create_hdf5.py trainers/subnetwork_supermask_trainer.py models/__init__.py trainers/__init__.py utils/misc.py config.py models/supermasks.py dataloaders/domain_datasets.py models/multihead_model.py models/basic_model.py trainers/aggregate_trainer.py utils/inverse_lr_scheduler.py Config process_txt create_dataset DomainDataset Aggregate_DomainDataset Basic_Model MultiHead_Model Identity SubNetwork_SuperMask_Model SuperMask Aggregate_Trainer MultiHead_Trainer SubNetwork_SuperMask_Trainer InvLR weights_init list COLOR_BGR2RGB print resize File close tqdm process_txt imread array range cvtColor len normal_ size __name__ fill_ | # Domain-Specific-Masks-for-Generalization Pytorch implementation of the paper: **Learning to Balance Specificity and Invariance for In and Out of Domain Generalization** Prithvijit Chattopadhyay, Yogesh Balaji, Judy Hoffman ECCV 2020 *We introduce Domain-specific Masks for Generalization, a model for improving both in-domain and out-of-domain generalization performance. For domain generalization, the goal is to learn from a set of source domains to produce a single model that will best generalize to an unseen target domain. As such, many prior approaches focus on learning representations which persist across all source domains with the assumption that these domain agnostic representations will generalize well. However, often individual domains contain characteristics which are unique and when leveraged can significantly aid in-domain recognition performance. To produce a model which best generalizes to both seen and unseen domains, we propose learning domain specific masks. The masks are encouraged to learn a balance of domain-invariant and domain-specific features, thus enabling a model which can benefit from the predictive power of specialized features while retaining the universal applicability of domain-invariant features. We demonstrate competitive performance compared to naive baselines and state-of-the-art methods on both PACS and DomainNet.*  Table of Contents ================= * [Setup and Dependencies](#setup-and-dependencies) | 3,340 |
prunednnsurprisinglymodular-neurips20/nn_modularity | ['graph clustering'] | ['Pruned Neural Networks are Surprisingly Modular'] | src/experiment_tagging.py src/cnn/__init__.py src/lesion/experimentation.py src/tests/test_lesion.py src/generate_datasets.py src/lesion/__init__.py src/tests/test_utils.py src/train_nn.py src/mix_datasets.py src/lesion/output.py src/meta.py src/pointers.py devops/patches/scipy/sparse/linalg/eigen/lobpcg/lobpcg.py src/spectral_cluster_model.py src/utils.py devops/patches/sklearn/manifold/spectral_embedding_.py src/cnn/extractor.py src/tests/test_spectral_clustering.py src/cnn/convertor.py src/random_init.py src/visualization.py src/tests/test_cnn.py _report_nonhermitian _b_orthonormalize lobpcg _makeOperator _applyConstraints _get_indx _save _as2d _graph_is_connected spectral_embedding _set_diag _graph_connected_component SpectralEmbedding get_model_path circle_counting_data_gen line_counting_data_gen preprocess_batch_cifar10 main generate_random_datast set_n_cpus main compute_ncut_random_init_mlp run tester_cnn_tensors_to_flat_weights_and_graph layer_info_to_layer_shapes conv_layer_to_weight_mats shuffle_weights_nonzero my_config mlp_int_to_tup weights_array_to_cluster_quality run_clustering cnn_layers_to_weights_array shuffle_weights_nonzero_distribution cut_vol_between_layers delete_isolated_ccs_refactored shuffle_and_cluster cnn_tensors_to_flat_weights_and_graph cnn_tup_to_int cut_vol cnn_layer_tup_to_int cluster_proportions_per_layer cnn_int_to_tup shuffle_weights weights_to_layer_widths compute_ncut connected_comp_analysis weights_to_graph cluster_net mlp_tup_to_int shuffle_weights_layer_all_distribution mlp_config cnn_config ncut delete_isolated_ccs train_model generate_training_tag create_mlp_layers create_model pruning_config general_config save_weights get_pruning_params load_data create_cnn_layers mlp_config get_two_model_paths cnn_config run get_sparsity picklify enumerate2 all_logging_disabled multi_combinations_with_replacement load_model2 build_clustering_results cohen_d_stats splitter get_weights_paths compute_pvalue NumpyEncoder extract_weights suppress unpicklify load_weights cohen_d extract_classification_metrics preprocess_dataset load_weights_from_checkpoint heatmap_fixed draw_ow_weight_dependency_graph set_square_nodes_positions run_double_spectral_cluster set_nodes_positions draw_mlp_clustering_report plot_eigenvalue_report _compute_weighted_dist draw_clustered_mlp draw_metrics run_spectral_cluster plot_weighted_dist_mat plot_learning_curve nodify get_color_mapper extact_layer_widths build_weighted_dist_mat draw_cluster_by_layer plot_eigenvalues plot_eigenvalues_old build_cluster_graph cnn2mlp SimpleMLP sparsify extract_cnn_weights expand_bias_conv_layer expand_pool_layer build_bias_pool_layer expand_conv_layer _flatten_single_damage _evaluate _apply_lesion_trial _damaged_neurons_gen perform_lesion_experiment _perform_lesion_sub_experiment _single_damaged_neurons_gen _extract_layer_label_metadata _damage_neurons _layers_labels_gen _double_conditional_damaged_neurons_gen _classification_metrics plot_all_damaged_clusters draw_tw_cond_dependency_graph plot_double_pvalue_mat plot_damaged_cluster build_double_mat build_double_joint_interaction_mat report_lesion_test layer_cluster_taxonomify plot_accuracy_profile plot_cluster_scatter enrich_score_double_conditional_df build_double_joint_imp_grouped_df build_tw_cond_imp_merged_df compute_damaged_cluster_stats _build_taxonomy_translator plot_overall_damaged_clusters plot_double_heatmap build_conditional_double_df build_double_pvalue_mat test_expand_conv_layer test_expand_pool_layer test_damaged_neurons_gen test_cnn2mlp test_compute_ncut test_shuffle_methods test_two_methods_cnn_clustering_pvalue test_compute_pvalue test_choen_d savetxt norm spacing print max conj array aslinearoperator dot cho_solve conj B inv dot cholesky conj argsort _b_orthonormalize _report_nonhermitian where eigh _applyConstraints conjugate _save A ones shape _get_indx append sum _as2d M asarray bmat sqrt B _makeOperator print min dot eye cho_factor conj issparse tocsr ravel logical_or fill zeros sum range connected_components isspmatrix todia size tocsr tocoo _set_diag check_array rand warn eigh aspreconditioner smoothed_aggregation_solver isspmatrix uniform lobpcg check_symmetric csgraph_laplacian T check_random_state toarray _deterministic_vector_sign_flip eye ravel eigsh list sorted glob Path max zeros rgb2gray enumerate resize line randint add set append zeros range randint add set append zeros circle_perimeter range randint seed next load_data preprocess_batch_cifar10 gen generate_random_datast str permutation picklify print len unpicklify enumerate Sequential create_mlp_layers compile enumerate enumerate int enumerate append ceil append popleft len deque range append enumerate int product shape ceil zeros range cnn_layer_tup_to_int append flatten shape permutation permutation zeros_like flatten shape len flatten shape zeros_like fit bmat len transpose coo_matrix append abs enumerate time layer_info_to_layer_shapes print weights_to_graph cnn_layers_to_weights_array cnn_tensors_to_flat_weights_and_graph zip weights_to_graph extract_cnn_weights fit SpectralClustering append zeros weights_to_layer_widths range print cut_vol cut_vol_between_layers zeros weights_to_layer_widths enumerate sum mlp_tup_to_int copy Counter argsort append zeros abs range print sum unique compute_ncut print cluster_net ncut connected_components weights_to_layer_widths Counter zeros range len splitter any zip_longest next tee connected_components weights_to_layer_widths weights_to_graph mlp_tup_to_int delete add set shape append range enumerate len list delete_isolated_ccs_refactored weights_array_to_cluster_quality weights_to_graph map load_weights cnn_tensors_to_flat_weights_and_graph append range update tester_cnn_tensors_to_flat_weights_and_graph delete_isolated_ccs_refactored std weights_array_to_cluster_quality concatenate print weights_to_graph shuffle_and_cluster len compute_pvalue mean load_weights cnn_tensors_to_flat_weights_and_graph full delete_isolated_ccs generate_training_tag strftime Path format astype int32 add_artifact str extract_cnn_weights picklify info extract_weights reshape to_categorical append Dense extend Dropout Conv2D extend Dense MaxPooling2D append Dropout create_mlp_layers create_cnn_layers add_artifact str format evaluate glob TensorBoard extend summary save info ModelCheckpoint compile fit train_model format create_model get_sparsity add_source_file prune_low_magnitude rmtree save_weights get_pruning_params mkdir load_data info get_two_model_paths exists disable PruneLowMagnitude load_model2 list zip extract_weights iter Path reshape update Series append sum len loads Path read_text list range product len set_xticklabels set_yticklabels get_yticklabels set_xlim get_xticklabels heatmap set_ylim len sqrt sqrt pop extract_classification_metrics update parent result full len get_weights_paths next extend rainbow dict linspace iter enumerate int arange reshape flatten sqrt linspace update list splitter arange set_square_nodes_positions astype zip full enumerate Series table subplots weights_to_graph from_scipy_sparse_matrix nodes load_weights set_nodes_positions draw_metrics extact_layer_widths get_color_mapper add_edge splitter sorted list product items DiGraph islice shape load_weights nodify extact_layer_widths zip sum enumerate add_node tee splitter sorted subplots graphviz_layout islice pprint load_weights nodify extact_layer_widths get_color_mapper sum enumerate build_cluster_graph tee set_major_locator connected_components A subplots isinstance MaxNLocator subgraph sort weights_to_graph from_scipy_sparse_matrix warn load_weights eigvals max normalized_laplacian_matrix set_major_locator connected_components subplots extract_cnn_weights isinstance MaxNLocator print sort weights_to_graph load_weights laplacian eye most_common LinearOperator eigsh subplots get_weights_paths set_title plot_eigenvalues draw_cluster_by_layer subplots get_weights_paths set_title suptitle draw_clustered_mlp list columns subplots set_index plot concat islice axvline extend enumerate2 read_text loads Path zip DataFrame int str split apply transform dropna DataFrame build_cluster_graph pivot xticks heatmap_fixed subplots list subplots graphviz_layout DiGraph draw unstack values extract_weights load_model2 extract_cnn_weights list sparsify product print reshape shape zeros range enumerate list sparsify product zeros_like print reshape zeros range sparsify tile zeros sparsify ones_like sparsify print expand_bias_conv_layer expand_pool_layer iter append build_bias_pool_layer next expand_conv_layer update confusion_matrix deepcopy list len zip set_weights deepcopy list splitter permutation print zip next array enumerate print sum _single_damaged_neurons_gen sum _layers_labels_gen _single_damaged_neurons_gen _layers_labels_gen _evaluate _damaged_neurons_gen tuple _damage_neurons append append _damaged_neurons_gen _flatten_single_damage _evaluate Path str list _apply_lesion_trial get_ignore_layers run_spectral_cluster extract_weights append next range glob get_weights_and_biases extact_layer_widths print preprocess_dataset _extract_layer_label_metadata progress_iter print sum groupby list set_levels set_index enrich_score_double_conditional_df sort_index concat extend warn apply droplevel unstack zip append DataFrame xs len deepcopy list format subplots plot set_xticklabels set_text set_xticks range set_ylim int list subplots suptitle axis zip ceil chain range plot_damaged_cluster len list subplots set_title plot xlabel AutoMinorLocator grid ylabel swarmplot axhline set_minor_locator legend zip xticks DataFrame set_ylim get_position T list subplots set_title plot set_position len _build_taxonomy_translator index apply legend xticks DataFrame range drop plot_all_damaged_clusters display perform_lesion_experiment print compute_damaged_cluster_stats plot_overall_damaged_clusters plot_accuracy_profile pivot reset_index _build_taxonomy_translator apply fill_diagonal diag values T fill_diagonal copy diag values texts iterrows subplots arange set_text copy set_size heatmap_fixed take get_text zip zeros set_weight len build_double_mat astype fill_diagonal values set_ticklabels list vmin subplots replace zip yticks vmax colorbar set_ticks keys heatmap_fixed color_palette xkcd_palette len legendHandles subplots reset_index text set_xlabel apply scatterplot set_ylabel color_palette range len sort_values reset_index replace apply rename reset_index merge apply index reset_index values apply add_edges_from subplots graphviz_layout DiGraph draw apply add_nodes_from values ones reshape tester eye array ones array tester _damaged_neurons_gen cumsum concatenate pair_damage_tester single_damage_tester tee adj_matrix fast_gnp_random_graph toarray run evaluate preprocess_dataset predict_classes cnn2mlp reshape to_categorical print upper mean lower load_model2 get_model_path shuffle_weights reshape shuffle_weights_layer_all_distribution shuffle_weights_nonzero_distribution shuffle_weights_nonzero normal | prunednnsurprisinglymodular-neurips20/nn_modularity | 3,341 |
ptakopysk/crosssynt | ['machine translation'] | ['Error Analysis of Cross-lingual Tagging and Parsing'] | tools/err_distro_evaluator.py tools/monotranslate_tb_src2tgt.py tools/translate_tokens.py tools/monotr_lm.py tools/treecomb_2.py tools/evaluator.py tools/kl.py tools/readablealign2simplealign.py tools/iso2wals.py tools/monotranslate_tb.py tools/translate_conll_src2tgt_feats.py tools/treecomb.py tools/trtable_src2tgt_feats.py tools/project_parse_1.py tools/simplify_deprel.py tools/sentences2conllu.py tools/translate_tb_monoalign.py tools/treecomb_1_weighted.py tools/labelcomb_weighted.py tools/monotranslate_text_src2tgt.py tools/words2freqlist_simple.py tools/hun_merge_partialAlign.py tools/chrF.py tools/iso2iso.py tools/pad_empty_sents.py tools/freqlistPrint.py tools/monotranslate_tb_src2tgt_oov.py tools/wals_find_similar.py tools/words2freqlist.py tools/reordering_paste.py tools/translate_word.py tools/score_word.py tools/matchingwords_tb_src2tgt.py tools/monotranslate.py tools/labelcomb.py tools/treecomb_1.py tools/klcpos3.py tools/lang_sim_wals_tgt_src.py tools/project_tags_bible_weighted.py tools/project_parse_1_weighted.py tools/text2bigrams.py tools/s_sal_2_s_en.py tools/eval_lang_sim.py tools/translate_conll_src2tgt.py tools/feats2FEAT.py tools/project_tags_bible.py tools/s_s_sal_2_als.py tools/charskl_tb_src2tgt.py tools/eval_srcsel.py tools/kl2agickl.py tools/trtable_src2tgt.py tools/monoalign.py tools/translate_tokens_monoalign.py tools/jw.py tools/monotranslate_tb_text_src2tgt.py tb2freq create_parser get_correct extract_ngrams f1 main next_token next_token Evaluation evaluate f l readfile kl2agickl kl2invkl4 readfile new_ngram_deque similarity simscore align relposition diagsim dicesim lensim print_alignment save_trtable deacc_dewov init jw_safe align_files isvow simscore translatecased sortedtgtdict wordcount translateline translate lensim processtbline translatetbline deacc_dewov init translate_internal srcwordfreq tgtwordfreq isvow translate_try jw_safe freqsim LM align2dict align2dict shift_i2o get_lines Bigrams translate translate translate translate translate get_sentence mst _getCycle _reverse _mergeCycles mst2dict filter_entry filter_entry similarity devow Freqlist line2key Freqlist Counter add_argument ArgumentParser join defaultdict strip len range split range ngram readline format ref get_correct print extract_ngrams beta f1 readline deprel split dict int reader open defaultdict endswith popleft strip close N range append new_ngram_deque zip unidecode sub get_jaro_distance str print diagsim dicesim lensim deacc_dewov jw_safe len simscore sorted dict range len print join len str load deacc_dewov simscore str print generate deacc_dewov translate_internal translate_try str print sortedtgtdict wordcount translate_try simscore str print str print wordcount srcwordfreq tgtwordfreq abs log score freqsim translate upper title lower istitle isupper append lower prevdeque split rstrip split append int defaultdict split int list readline split append len get lower join list strip startswith append split items list add set append popitem maxsize clear _getCycle set _reverse append maxsize _mergeCycles dict split append sort get_jaro_distance devow unidecode | ptakopysk/crosssynt | 3,342 |
pte1236/Gen-CUDE | ['denoising'] | ['Unsupervised Neural Universal Denoiser for Finite-Input General-Output Noisy Channel'] | synthetic/pytorch/AISTAT_4ary_Gen-CUDE-pytorch-nonsquare.py synthetic/keras/AISTAT_binary_Gen-CUDE.py synthetic/pytorch/AISTAT_4ary_Gen-CUDE-pytorch.py synthetic/pytorch/AISTAT_binary_Gen-CUDE-pytorch.py synthetic/pytorch/utils.py synthetic/keras/AISTAT_10ary_Gen-CUDE.py synthetic/pytorch/AISTAT_10ary_Gen-CUDE-pytorch.py synthetic/pytorch/MLP_based_models.py synthetic/keras/AISTAT_4ary_Gen-CUDE-nonsquare.py synthetic/keras/utils.py synthetic/keras/AISTAT_4ary_Gen-CUDE.py find_nearest_integer base_symbol set_seed transform_to_wide input_context_without_middle_symbol Quantizer_4ary con_noisy_awgn error_rate p_vector_from_wide_pdf_table middle_y decision_boundary net_output PRINT transform_to_narrow Quantizer_v1 init_params sym_mat source_generator_v2 MLP decision_boundary net_output PRINT find_nearest_integer set_seed input_context_without_middle_symbol con_noisy_awgn error_rate p_vector_from_wide_pdf_table Quantizer_v1 init_params base_symbol softmax sym_mat transform_to_wide Quantizer_4ary middle_y transform_to_narrow source_generator_v2 seed manual_seed print str write now arange ones range int random copy zeros float argmax range randn zeros range len round int_ zeros range int_ len zeros round range len dtype astype dtype astype zeros hstack range len zeros range len uniform_ parameters kaiming_normal_ to numpy arange base_symbol deepcopy arange int_ print range len base_symbol deepcopy int_ print range uniform kaiming_uniform_ reshape exp | # Gen-CUDE * Gen-CUDE is an unsupervised neural network-based universal denoiser for the finite-input, general-output channel. * Code accompanying the paper "Unsupervised Neural Universal Denoiser for Finite-Input General-Output Noisy Channel" (https://arxiv.org/abs/2003.02623). * Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS) 2020, Palermo, Italy. PMLR: Volume 108. Copyright 2020 by the author(s). # Requirements * Python 3.6.6 * CUDA v9.2 * Tensorflow v1.15.0 * Keras v2.2.4 # Results | 3,343 |
pth1993/vnSRL | ['semantic parsing'] | ['Vietnamese Semantic Role Labelling'] | vnSRL.py lib.py getVoice getWord getFunctionType getListChunkVer classificationSVMTest convertData phraseType convertToDataFrame getHeadWord ilpSolving readingParameterFromFile isSType dataToTree getPath process output2File reformTag1 getHeadWordType getSubCategorization getHalfPath createWordEmbeddingPredicateTest removeSenNoPredicate getPhraseType createWordEmbeddingHeadwordTest isPhraseType getFeatureTest getTagFunction collect readTestData labelEncoderData semanticRoleClassifier chunkingTest createTestData getPredicate importWordEmbedding getPosition pop append join add_features Tree append range len rstrip name add_features get_leaves get_children detach get_children collect join digits replace split digits replace split transform transpose range len DataFrame join list len readlines open range append split search_nodes append add_features up get_sisters copy append process range len reformTag1 name up get_common_ancestor extend append get_leaves search_nodes get_sisters reformTag1 name up copy traverse getVoice list getSubCategorization word len getFunctionType getHalfPath lower classes_ getPhraseType append getPath sum range getPosition asarray replace len append range split asarray replace len append range split convertToDataFrame asarray toarray concatenate astype labelEncoderData decision_function predict int list varValue sorted asarray insert reshape tolist solve LpProblem dict shape dicts zip append variables range len append ilpSolving classificationSVMTest asarray replace get_leaves append range len append len range len join word len write inverse_transform range open | # Vietnamese Semantic Role Labelling (vnSRL) v1.0.0 - 2016-02-20 ----------------------------------------------------------------- Code by **Thai-Hoang Pham**, **Xuan-Khoai Pham** ## 1. Introduction The **vnSRL** system is used to labelling semantic roles of arguments for each predicate in a Vietnamese sentence. This software is written by Python 2.x. ## 2. Installation This software depends on NumPy, SciPy, Scikit-learn, Pandas, Pulp, ETE2, six Python packages for scientific computing. You must have them installed prior to using vnSRL. The simple way to install them is using pip: ```sh # pip install -U numpy scipy scikit-learn pandas pulp ete2 | 3,344 |
ptran1203/photorealistic_style_transfer | ['style transfer'] | ['Photorealistic Style Transfer via Wavelet Transforms'] | data_processing.py train.py scripts/create_tfrec.py inference.py utils.py ops.py model.py preprocess_input preprocess_image build_input_pipe decode_sample main parse_args check_path WCT2 WaveLetUnPooling WaveLetPooling _conv2d get_predict_function _get_output gram_matrix WhiteningAndColoring _conv2d_transpose _copy_input main parse_args http_get_img get_local_img read_img image_resize download_weight display_outputs DownloadProgressBar create_df write_tfrecords bytes_feature main parse_args image_example preprocess_input parse_single_example decode_png resize TFRecordDataset map apply repeat ignore_errors prefetch batch add_argument ArgumentParser output makedirs load_weight imwrite isdir glob style print read_img transfer check_path alpha WCT2 content image_size conv2d_transpose conv2d layer hasattr input _get_output get_layer _copy_input shape cast float32 einsum train_tfrec join checkpoint_path val_tfrec resume isfile train makedirs read asarray bytearray COLOR_RGB2BGR imdecode urlopen image_resize cvtColor COLOR_RGB2BGR imread image_resize cvtColor expand_dims http_get_img any get_local_img float resize show add_subplot axis imshow figure isfile makedirs constant type numpy isinstance join print append listdir len output_dir | # photorealistic_style_transfer <a href="https://colab.research.google.com/github/ptran1203/photorealistic_style_transfer/blob/master/WCT2.ipynb" target="_parent"><img src="https://camo.githubusercontent.com/52feade06f2fecbf006889a904d221e6a730c194/68747470733a2f2f636f6c61622e72657365617263682e676f6f676c652e636f6d2f6173736574732f636f6c61622d62616467652e737667" alt="Open In Colab" data-canonical-src="https://colab.research.google.com/assets/colab-badge.svg"></a> Photorealistic Style Transfer via Wavelet Transforms - https://arxiv.org/abs/1903.09760 Keras + tensorflow implementation of WCT2. Original implementation in [PyTorch](https://github.com/clovaai/WCT2) by [Jaejun-yoo](https://github.com/jaejun-yoo) ## 1. Usage ### 1.1 Download dataset ``` wget -O https://github.com/ptran1203/photorealistic_style_transfer/releases/download/v1.0/tfrecords.zip unzip tfrecords.zip ``` | 3,345 |
ptran1203/style_transfer | ['style transfer'] | ['Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization'] | utils.py dataloader.py model.py DataGenerator Reduction AdaptiveInstanceNorm StyleTransferModel pickle_load norm de_norm show_images http_get_img pickle_save preprocess image_resize deprocess de_norm cv2_imshow reshape shape deprocess full range read asarray norm bytearray COLOR_BGR2GRAY imdecode urlopen image_resize preprocess expand_dims cvtColor float resize | ### keras implemetation of [Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization](https://arxiv.org/pdf/1703.06868.pdf)  The model architecture proposed by Huang et al., a fixed VGG19 is used to encode both content and style image. The outputs are passed through the adaptive instance normalization (AdaIN) which normalizes the content feature then scale and shift by mean and variance calculated from style feature to have similar global context with the style image. Then, a decoder is used to generate new image from the normalized feature. ------ #### :art: Stylizing result | |  |  |  | |--|--|--|--| |||  |  | |||  |  | |||  |  | | 3,346 |
ptraverse/MC-GAN3 | ['style transfer'] | ['Multi-Content GAN for Few-Shot Font Style Transfer'] | options/train_options.py data/image_folder.py train_Stack.py data/data_loader.py train.py util/kernel_size.py util/image_pool.py util/png.py test_Stack.py models/base_model.py models/models.py models/StackGAN_model.py util/html.py data/base_data_loader.py options/base_options.py test.py util/util.py util/plot_loss.py test_video.py models/networks.py options/test_options.py util/visualizer.py models/cGAN_model.py BaseDataLoader Data normalize_stack PartialData CreateDataLoader FlatData StackDataLoader DataLoader PartialDataLoader is_image_file make_dataset ImageFolder default_loader font_transform BaseModel cGANModel create_model InputTransformation define_G_3d get_norm_layer GANLoss ResnetGenerator ResnetDecoder ResnetBlock define_D weights_init conv_norm_relu_module ResnetEncoder define_Dec define_G ResnetGenerator_3d_conv convTranspose_norm_relu_module define_Enc NLayerDiscriminator define_preNet print_network BaseOptions TestOptions TrainOptions HTML ImagePool encode print_numpy varname diagnose_network VerticalFlip mkdirs HorizontalFlip mkdir info save_image tensor2im Visualizer size Compose initialize partial StackDataLoader stack DataLoader PartialDataLoader is_image_file join sorted append walk int arange view mean permute range initialize model print cGANModel name StackGANModel str hasattr fill_ print bias normal_ __name__ print BatchNorm2d partial InstanceNorm2d apply cuda ResnetGenerator_3d_conv get_norm_layer print ResnetGenerator UnetGenerator apply cuda get_norm_layer print UnetEncoder apply ResnetEncoder cuda get_norm_layer print ResnetDecoder apply UnetDecoder cuda get_norm_layer print apply NLayerDiscriminator cuda get_norm_layer InputTransformation print apply cuda print parameters transpose numpy print parameters fromarray reshape squeeze astype save zeros range print join search print float64 astype flatten shape mkdir makedirs | Unsuccessful implementation (so far) of paper below + upgrade to python3 + training for free in google colab in 2020: ---- # MC-GAN in PyTorch <img src="https://people.eecs.berkeley.edu/~sazadi/MCGAN/datasets/ft51_1_fake_B.gif" width="90%"/> This is a python3 update of the implementation of the [Multi-Content GAN for Few-Shot Font Style Transfer](https://arxiv.org/abs/1712.00516). The code was written by [Samaneh Azadi](https://github.com/azadis). If you use this code or our [collected font dataset](https://github.com/azadis/AdobeFontDropper#mc-gan-traintest) for your research, please cite: Multi-Content GAN for Few-Shot Font Style Transfer; [Samaneh Azadi](https://people.eecs.berkeley.edu/~sazadi/), [Matthew Fisher](https://research.adobe.com/person/matt-fisher/), [Vladimir Kim](http://vovakim.com/), [Zhaowen Wang](https://research.adobe.com/person/zhaowen-wang/), [Eli Shechtman](https://research.adobe.com/person/eli-shechtman/), [Trevor Darrell](https://people.eecs.berkeley.edu/~trevor/), in arXiv, 2017. ## Prerequisites: - Linux or macOS - ~~Python 2.7~~ *Python3* | 3,347 |
pui-nantheera/DepthEstimation | ['depth estimation'] | ['Fast Depth Estimation for View Synthesis'] | predicting.py data_reader.py depthmapnet.py utils.py data_reader_predict.py training.py Reader Reader DenseMapNet Predictor Predictor Settings ElapsedTimer | Project page: https://pui-nantheera.github.io/Palantir_depth_estimation/ Reference: Fast Depth Estimation for View Synthesis, accepted to present at EUSIPCO2020. https://arxiv.org/pdf/2003.06637.pdf Note that this code has been adapted from <a href="https://github.com/roatienza/densemapnet">DenseMapNet</a>. | 3,348 |
pumpkinman008/StoryGeneration | ['story generation'] | ['Hierarchical Neural Story Generation'] | storygeneration/beam.py storygeneration/tests/test_example.py storygeneration/model.py storygeneration/multipara.py storygeneration/utils.py storygeneration/sample.py storygeneration/tests/test_beam.py storygeneration/sentiment.py flask_storygeneration.py storygeneration/train.py storygeneration/tests/test_train.py storygeneration/tests/test_utils.py forms.py storygeneration/combined.py results theme ThemeForm BeamSearch get_tweets_for_model checkSent remove_noise generateStory storyGen get_all_words Model sample main remove_noise get_all_words get_tweets_for_model TextLoader TestBeamMethods naive_predict TestStringMethods TestUtilsMethods TestUtilsMethods generateStory data validate_on_submit ThemeForm TextAreaField SelectField lemmatize WordNetLemmatizer pos_tag lower sub startswith append remove_noise classify word_tokenize dict sample strip checkSent split storyGen sample parse_args add_argument ArgumentParser parse_args Model add_argument ArgumentParser | # Hierarchical Story Generation ## Abstract <p>Story generation involves developing a system that can write stories in a manner such that the similarity between the story written by the system is close to stories written by a human. The story generation system that we are working on generates a well-structured, coherent, and semantically correct short story. Our system sees to it that coherency is maintained between sentences as well as paragraphs alike and the plot as well as thematic ideas are carried along throughout the story. Certain characters as well as subplots are introduced as the story progresses. The generated story relies heavily on the input sentences as given by the user. The user gives a few introductory lines to the story as an input, based on which a coherent story is churned out. Keywords from the user input such as the characters and settings are extracted by the system and fed into the sequence-to-sequence model which generates the story. The user can also select a certain theme to be maintained throughout the story. The theme could be anything, for example comedy, based on which the entire mood of the story gets decided and likewise, sentences are generated to evoke a sense of light heartedness or comedy. Thus our system relies on the input provided by the user as well as the theme selected by them as a starting point to be taken into consideration while generating the story. It must be kept in mind that stories must stick to their narrative and not deviate from its intended idea. A basic text generation system might part ways with the main idea of a bunch of texts and deviate off topic altogether by shifting its focus on some unimportant pieces of text. Our system on the other hand does not deviate from the main idea of the story. We achieve this by training our system in a hierarchical fashion. Our system first generates prompts from the user input. A prompt is a short sentence or sentences which conveys the idea of input text. Our system sticks to this prompt while generating the output text. Hence, by making use of a hierarchical fashion to | 3,349 |
pupil-labs/pupil | ['gaze estimation'] | ['Pupil: An Open Source Platform for Pervasive Eye Tracking and Mobile Gaze-based Interaction'] | pupil_src/shared_modules/gaze_mapping/gazer_3d/gazer_headset.py update_license_header.py pupil_src/shared_modules/version_utils.py pupil_src/shared_modules/gaze_mapping/__init__.py pupil_src/shared_modules/file_methods.py pupil_src/shared_modules/head_pose_tracker/base_head_pose_tracker.py pupil_src/launchables/__init__.py pupil_src/shared_modules/head_pose_tracker/controller/offline_localization_controller.py pupil_src/shared_modules/os_utils.py pupil_src/shared_modules/gaze_producer/ui/offline_calibration_timeline.py pupil_src/tests/video_capture/file_backend/__init__.py pupil_src/tests/surface_tracker/fixtures/__init__.py pupil_src/shared_modules/network_api/controller/frame_publisher_controller.py pupil_src/shared_modules/gaze_mapping/gazer_3d/gazer_hmd.py pupil_src/shared_modules/pupil_recording/update/update_utils.py pupil_src/shared_modules/background_helper.py pupil_src/shared_modules/scan_path/storage.py pupil_src/shared_modules/pupil_detector_plugins/visualizer_pye3d/eye.py pupil_src/shared_modules/plugin_manager.py pupil_src/shared_modules/pupil_detector_plugins/detector_2d_plugin.py pupil_src/shared_modules/surface_tracker/surface_marker_aggregate.py pupil_src/tests/test_stdlib_utils.py pupil_src/shared_modules/head_pose_tracker/ui/offline_localizaion_menu.py pupil_src/shared_modules/surface_tracker/surface_tracker_offline.py pupil_src/shared_modules/scan_path/tasks/preprocessing.py pupil_src/shared_modules/tasklib/manager.py pupil_src/shared_modules/calibration_choreography/natural_feature_plugin.py pupil_src/shared_modules/network_api/ui/__init__.py pupil_src/shared_modules/tasklib/background/create.py pupil_src/tests/surface_tracker/test_surface_file_store.py pupil_src/shared_modules/system_timelines.py pupil_src/shared_modules/roi.py pupil_src/shared_modules/head_pose_tracker/ui/offline_optimization_menu.py deployment/deploy_service/finalize_bundle.py pupil_src/shared_modules/system_graphs.py pupil_src/shared_modules/network_api/controller/pupil_remote_controller.py pupil_src/shared_modules/scan_path/algorithm.py pupil_src/shared_modules/surface_tracker/surface_marker_detector.py pupil_src/shared_modules/head_pose_tracker/function/utils.py pupil_src/shared_modules/surface_tracker/surface_tracker_online.py pupil_src/shared_modules/video_overlay/workers/overlay_renderer.py pupil_src/main.py deployment/deploy_service/version.py pupil_src/shared_modules/fixation_detector.py pupil_src/launchables/eye.py pupil_src/shared_modules/av_writer.py pupil_src/shared_modules/pupil_data_relay.py pupil_src/shared_modules/head_pose_tracker/__init__.py pupil_src/shared_modules/head_pose_tracker/function/pick_key_markers.py pupil_src/shared_modules/video_overlay/plugins/generic_overlay.py pupil_src/shared_modules/vis_circle.py pupil_src/shared_modules/surface_tracker/cache.py pupil_src/shared_modules/stdlib_utils.py pupil_src/shared_modules/head_pose_tracker/controller/offline_detection_controller.py pupil_src/shared_modules/head_pose_tracker/controller/online_controller.py pupil_src/shared_modules/surface_tracker/surface_tracker.py pupil_src/shared_modules/surface_tracker/surface.py pupil_src/shared_modules/gaze_producer/controller/reference_location_controllers.py pupil_src/shared_modules/time_sync.py pupil_src/shared_modules/task_manager.py pupil_src/shared_modules/vis_fixation.py pupil_src/shared_modules/gaze_producer/gaze_from_offline_calibration.py pupil_src/shared_modules/head_pose_tracker/worker/__init__.py deployment/deploy_capture/version.py pupil_src/shared_modules/pupil_recording/update/mobile.py pupil_src/shared_modules/hololens_relay.py pupil_src/shared_modules/surface_tracker/surface_offline.py pupil_src/shared_modules/tasklib/background/patches.py pupil_src/shared_modules/video_overlay/models/config.py pupil_src/shared_modules/zmq_tools.py pupil_src/shared_modules/launchable_args.py pupil_src/shared_modules/gaze_producer/controller/calculate_all_controller.py pupil_src/shared_modules/gaze_producer/model/gaze_mapper_storage.py pupil_src/shared_modules/gaze_producer/ui/on_top_menu.py pupil_src/shared_modules/gprof2dot.py pupil_src/shared_modules/gaze_producer/worker/validate_gaze.py pupil_src/shared_modules/csv_utils.py pupil_src/shared_modules/head_pose_tracker/controller/export_controller.py pupil_src/shared_modules/network_api/ui/frame_publisher_menu.py pupil_src/shared_modules/video_capture/hmd_streaming.py pupil_src/shared_modules/calibration_choreography/controller/gui_monitor.py pupil_src/shared_modules/network_time_sync.py pupil_src/shared_modules/gl_utils/draw.py pupil_src/shared_modules/video_capture/uvc_backend.py pupil_src/shared_modules/head_pose_tracker/ui/gl_renderer_utils.py pupil_src/shared_modules/circle_detector.py pupil_src/shared_modules/pupil_recording/info/recording_info_utils.py pupil_src/shared_modules/pupil_recording/info/__init__.py pupil_src/shared_modules/gaze_producer/ui/gaze_mapper_timeline.py pupil_src/shared_modules/pupil_detector_plugins/__init__.py pupil_src/launchables/player.py pupil_src/shared_modules/head_pose_tracker/ui/gl_window.py deployment/generate_msi_installer.py pupil_src/shared_modules/gaze_producer/model/reference_location.py pupil_src/shared_modules/tasklib/__init__.py pupil_src/shared_modules/log_display.py pupil_src/shared_modules/calibration_choreography/mixin/monitor_selection_mixin.py pupil_src/tests/test_csv_utils.py pupil_src/launchables/service.py pupil_src/shared_modules/gaze_producer/ui/reference_location_timeline.py pupil_src/shared_modules/plugin.py pupil_src/shared_modules/gaze_mapping/notifications.py pupil_src/shared_modules/gaze_producer/worker/fake_gpool.py pupil_src/shared_modules/surface_tracker/background_tasks.py pupil_src/tests/test_raw_data_exporter.py pupil_src/tests/surface_tracker/fixtures/fixtures_surface_v01_apriltag.py pupil_src/shared_modules/plugin_timeline.py pupil_src/shared_modules/pupil_recording/recording_utils.py pupil_src/shared_modules/pupil_recording/update/new_style.py pupil_src/shared_modules/surface_tracker/surface_online.py pupil_src/shared_modules/calibration_choreography/mixin/__init__.py pupil_src/shared_modules/annotations.py pupil_src/shared_modules/head_pose_tracker/storage/localization_storage.py pupil_src/shared_modules/scan_path/__init__.py pupil_src/shared_modules/player_methods.py pupil_src/shared_modules/head_pose_tracker/function/solvepnp.py pupil_src/tests/__init__.py pupil_src/shared_modules/head_pose_tracker/worker/detection_worker.py pupil_src/shared_modules/pupil_detector_plugins/color_scheme.py pupil_src/shared_modules/methods.py pupil_src/shared_modules/gaze_producer/gaze_producer_base.py pupil_src/shared_modules/pupil_recording/info/recording_info_2_1.py deployment/find_opengl_bigsur.py pupil_src/shared_modules/vis_watermark.py pupil_src/shared_modules/pupil_recording/__init__.py pupil_src/shared_modules/accuracy_visualizer.py pupil_src/shared_modules/vis_polyline.py pupil_src/tests/surface_tracker/fixtures/fixtures_surface_definition_files.py pupil_src/shared_modules/calibration_choreography/controller/marker_window_controller.py pupil_src/shared_modules/video_overlay/ui/management.py pupil_src/shared_modules/pupil_recording/info/recording_info_2_2.py pupil_src/tests/gaze_mapping/test_notifications.py pupil_src/launchables/marker_detectors.py pupil_src/tests/video_capture/common.py pupil_src/shared_modules/remote_recorder.py pupil_src/shared_modules/calibration_choreography/single_marker_plugin.py pupil_src/shared_modules/seek_control.py pupil_src/shared_modules/imu_timeline.py pupil_src/shared_modules/head_pose_tracker/worker/optimization_worker.py pupil_src/shared_modules/gaze_producer/worker/map_gaze.py pupil_src/shared_modules/gaze_producer/ui/gaze_mapper_menu.py pupil_src/shared_modules/head_pose_tracker/offline_head_pose_tracker.py pupil_src/shared_modules/audio_utils.py pupil_src/shared_modules/hotkey.py pupil_src/shared_modules/pupil_producers.py pupil_src/shared_modules/head_pose_tracker/function/triangulate_marker.py pupil_src/shared_modules/video_export/plugins/imotions_exporter.py pupil_src/shared_modules/video_export/plugin_base/isolated_frame_exporter.py pupil_src/tests/surface_tracker/test_surface_marker.py pupil_src/shared_modules/head_pose_tracker/worker/export_worker.py pupil_src/shared_modules/gl_utils/utils.py pupil_src/shared_modules/gl_utils/window_position_manager.py pupil_src/shared_modules/network_api/model/frame_format.py pupil_src/tests/test_observable.py pupil_src/shared_modules/gaze_producer/ui/reference_location_menu.py pupil_src/tests/annotations/test_annotation_deserialization.py pupil_src/shared_modules/storage.py pupil_src/shared_modules/scan_path/tasks/__init__.py pupil_src/shared_modules/surface_tracker/gui.py pupil_src/shared_modules/scan_path/utils.py pupil_src/shared_modules/video_overlay/utils/constraints.py pupil_src/shared_modules/pupil_groups.py pupil_src/shared_modules/video_capture/ndsi_backend.py pupil_src/tests/surface_tracker/test_surface_serializer.py pupil_src/shared_modules/calibration_choreography/hmd_plugin.py pupil_src/shared_modules/head_pose_tracker/function/__init__.py pupil_src/shared_modules/scan_path/tasks/base.py pupil_src/shared_modules/head_pose_tracker/ui/detection_renderer.py pupil_src/shared_modules/head_pose_tracker/ui/visualization_menu.py pupil_src/shared_modules/math_helper/intersections.py pupil_src/shared_modules/math_helper/__init__.py pupil_src/shared_modules/video_export/plugin_base/video_exporter.py pupil_src/shared_modules/blink_detection.py pupil_src/shared_modules/gaze_producer/ui/__init__.py pupil_src/shared_modules/gaze_producer/__init__.py pupil_src/shared_modules/video_capture/__init__.py pupil_src/shared_modules/gaze_producer/ui/storage_edit_menu.py pupil_src/shared_modules/recorder.py pupil_src/shared_modules/video_capture/base_backend.py pupil_src/shared_modules/pupil_detector_plugins/visualizer_pye3d/utilities.py pupil_src/tests/surface_tracker/__init__.py pupil_src/shared_modules/video_capture/utils.py pupil_src/shared_modules/data_changed.py pupil_src/shared_modules/head_pose_tracker/ui/offline_head_pose_tracker_timeline.py pupil_src/shared_modules/math_helper/transformations.py pupil_src/shared_modules/head_pose_tracker/ui/__init__.py pupil_src/shared_modules/network_api/model/__init__.py pupil_src/shared_modules/tasklib/interface.py pupil_src/shared_modules/video_capture/file_backend.py pupil_src/shared_modules/raw_data_exporter.py pupil_src/shared_modules/pupil_recording/update/__init__.py pupil_src/shared_modules/gaze_producer/controller/gaze_mapper_controller.py pupil_src/shared_modules/surface_tracker/surface_marker.py pupil_src/shared_modules/video_overlay/utils/image_manipulation.py pupil_src/shared_modules/camera_intrinsics_estimation.py pupil_src/shared_modules/marker_auto_trim_marks.py pupil_src/shared_modules/head_pose_tracker/online_head_pose_tracker.py pupil_src/shared_modules/surface_tracker/__init__.py pupil_src/shared_modules/gaze_producer/model/__init__.py pupil_src/shared_modules/gaze_mapping/utils.py pupil_src/shared_modules/display_recent_gaze.py pupil_src/shared_modules/observable.py pupil_src/shared_modules/head_pose_tracker/storage/__init__.py pupil_src/shared_modules/network_api/controller/__init__.py pupil_src/shared_modules/pupil_recording/info/recording_info_2_3.py pupil_src/shared_modules/camera_models.py pupil_src/shared_modules/gaze_producer/worker/__init__.py pupil_src/shared_modules/pupil_detector_plugins/detector_base_plugin.py pupil_src/shared_modules/pupil_recording/recording.py deployment/deploy_player/finalize_bundle.py pupil_src/shared_modules/visualizer.py pupil_src/shared_modules/gaze_producer/model/legacy/__init__.py pupil_src/shared_modules/gaze_producer/worker/create_calibration.py pupil_src/shared_modules/tasklib/background/__init__.py pupil_src/shared_modules/gl_utils/__init__.py pupil_src/shared_modules/gaze_producer/model/reference_location_storage.py pupil_src/shared_modules/tasklib/background/task.py pupil_src/shared_modules/pupil_recording/info/recording_info.py pupil_src/shared_modules/gl_utils/trackball.py pupil_src/shared_modules/surface_tracker/surface_file_store.py pupil_src/shared_modules/pupil_detector_plugins/pye3d_plugin.py pupil_src/shared_modules/calibration_choreography/controller/__init__.py pupil_src/shared_modules/gaze_mapping/gazer_base.py pupil_src/shared_modules/gaze_producer/ui/calibration_menu.py pupil_src/shared_modules/video_export/plugins/eye_video_exporter.py pupil_src/shared_modules/gaze_producer/worker/detect_circle_markers.py pupil_src/shared_modules/gaze_producer/controller/calibration_controller.py pupil_src/shared_modules/head_pose_tracker/ui/online_head_pose_tracker_menu.py pupil_src/shared_modules/head_pose_tracker/controller/__init__.py pupil_src/shared_modules/video_overlay/ui/menu.py pupil_src/shared_modules/head_pose_tracker/storage/general_settings.py pupil_src/shared_modules/gaze_producer/ui/select_and_refresh_menu.py pupil_src/shared_modules/calibration_choreography/__init__.py pupil_src/shared_modules/audio_playback.py pupil_src/shared_modules/service_ui.py pupil_src/shared_modules/pupil_recording/update/invisible.py pupil_src/shared_modules/head_pose_tracker/controller/offline_optimization_controller.py pupil_src/shared_modules/head_pose_tracker/ui/offline_head_pose_tracker_menu.py pupil_src/tests/video_capture/file_backend/test_file_backend.py pupil_src/shared_modules/head_pose_tracker/storage/detection_storage.py pupil_src/tests/surface_tracker/fixtures/fixtures_surface_v01_square.py pupil_src/shared_modules/gaze_mapping/gazer_3d/bundle_adjustment.py pupil_src/shared_modules/calibration_choreography/controller/gui_window.py pupil_src/shared_modules/tasklib/observers.py pupil_src/shared_modules/gaze_producer/model/legacy/calibration_v1.py pupil_src/shared_modules/pupil_detector_plugins/visualizer_2d.py pupil_src/shared_modules/gaze_producer/model/calibration_storage.py pupil_src/shared_modules/gaze_mapping/matching.py pupil_src/shared_modules/head_pose_tracker/ui/offline_detection_menu.py pupil_src/shared_modules/network_api/network_api_plugin.py pupil_src/shared_modules/video_overlay/workers/frame_fetcher.py pupil_src/shared_modules/gaze_mapping/gazer_3d/__init__.py pupil_src/shared_modules/head_pose_tracker/ui/head_pose_tracker_3d_renderer.py pupil_src/shared_modules/gaze_mapping/gazer_3d/calibrate_3d.py pupil_src/shared_modules/cv2_writer.py pupil_src/shared_modules/square_marker_detect.py deployment/deploy_capture/finalize_bundle.py pupil_src/shared_modules/log_history.py pupil_src/shared_modules/gaze_mapping/gazer_2d.py pupil_src/shared_modules/gaze_producer/model/legacy/calibration_storage_updater.py pupil_src/shared_modules/video_overlay/__init__.py pupil_src/shared_modules/audio/__init__.py pupil_src/shared_modules/calibration_choreography/base_plugin.py pupil_src/shared_modules/gaze_producer/gaze_from_recording.py pupil_src/shared_modules/pupil_detector_plugins/visualizer_pye3d/__init__.py pupil_src/shared_modules/video_overlay/ui/interactions.py pupil_src/shared_modules/surface_tracker/surface_serializer.py pupil_src/shared_modules/gaze_producer/ui/reference_location_renderer.py pupil_src/shared_modules/scan_path/tasks/background.py pupil_src/shared_modules/video_export/plugins/world_video_exporter.py pupil_src/shared_modules/network_api/__init__.py pupil_src/shared_modules/pupil_detector_plugins/visualizer_pye3d/pose.py pupil_src/shared_modules/scan_path/controller.py pupil_src/shared_modules/gaze_producer/model/gaze_mapper.py pupil_src/shared_modules/vis_light_points.py pupil_src/shared_modules/head_pose_tracker/function/get_initial_guess.py pupil_src/tests/test_roi.py pupil_src/launchables/world.py pupil_src/tests/video_capture/__init__.py pupil_src/shared_modules/vis_cross.py deployment/deploy_player/version.py pupil_src/shared_modules/head_pose_tracker/worker/localization_worker.py pupil_src/shared_modules/gaze_producer/model/calibration.py pupil_src/shared_modules/gaze_mapping/gazer_3d/utils.py pupil_src/shared_modules/head_pose_tracker/function/bundle_adjustment.py pupil_src/shared_modules/video_overlay/controllers/overlay_manager.py pupil_src/shared_modules/calibration_choreography/screen_marker_plugin.py pupil_src/shared_modules/pupil_recording/info/recording_info_2_0.py pupil_src/shared_modules/batch_exporter.py pupil_src/shared_modules/video_overlay/plugins/eye_overlay.py pupil_src/shared_modules/gaze_producer/controller/__init__.py pupil_src/shared_modules/make_unique.py pupil_src/shared_modules/pupil_recording/update/old_style.py pupil_src/shared_modules/head_pose_tracker/storage/optimization_storage.py pupil_src/shared_modules/network_api/ui/pupil_remote_menu.py pupil_src/shared_modules/surface_tracker/offline_utils.py pupil_src/tests/surface_tracker/fixtures/fixtures_surface_v00_square.py pupil_src/shared_modules/tasklib/background/shared_memory.py pupil_src/shared_modules/video_overlay/plugins/__init__.py get_files write_header _find_library_patched SoftwareComponent set_bundled_glfw_environ_var clear_settings launcher eye_profiled eye Is_Alive_Manager circle_detector player_drop player player_profiled service service_profiled world world_profiled CorrelatedAndCoordinateTransformedResult ValidationInput CalculationResult Accuracy_Visualizer CorrelationError AccuracyPrecisionResult create_annotation Annotation_Capture AnnotationPlugin AnnotationDefinition Annotation_Player Audio_Playback FileSeekError _load_audio_from_world_video_files LoadedAudio Audio_Viz_Transform _load_audio_from_audio_files NoAudioLoadedError _load_audio_single load_audio JPEG_Writer MPEG_Writer NonMonotonicTimestampError write_timestamps MPEG_Audio_Writer AV_Writer _AudioPacketIterator IPC_Logging_Task_Proxy Task_Proxy example_generator EarlyCancellationError main get_recording_dirs Batch_Exporter Batch_Export Blink_Detection Offline_Blink_Detection on_resize _gen_pattern_grid _make_grid Camera_Intrinsics_Estimation Fisheye_Dist_Camera Radial_Dist_Camera Dummy_Camera Camera_Model find_pupil_circle_marker get_nested_clusters CircleTracker getEllipsePts add_parents marker_3d_pose find_concentric_circles bench write_key_value_file CSV_Exporter read_key_value_file CV_Writer Listener Announcer _create_new_token _read_token_from_file _write_token_to_file _get_token_file_path _normalize_token Display_Recent_Gaze save_object bench_save next_export_sub_dir Serialized_Dict bench_load Persistent_Dict PLData_Writer _load_object_legacy Incremental_Legacy_Pupil_Data_Loader _Empty load_pldata_file _recursive_deep_copy load_object compat_iteritems SysprofParser PerfParser compat_keys LineParser sorted_iteritems XmlParser GprofParser Parser Struct DotWriter HProfParser add JsonParser Event compat_itervalues percentage Function Object UndefinedEvent AXEParser Call times XPerfParser ratio SleepyParser main Profile naturalJoin XmlTokenizer OprofileParser PstatsParser Theme Cycle XmlToken ParseError XmlTokenMismatch CallgrindParser fail Hololens_Relay generate_markdown_hotkey_docs Hotkey glfont_generator IMURecording get_limits merge_arrays Imu_Exporter Imu_Bisector IMUTimeline Fusion fuser PupilArgParser HelpfulArgumentParser Log_Display duration_from_level color_from_level Log_History Log_to_Callback by_number_at_end Marker_Auto_Trim_Marks filter_subsets get_system_info make_eye_kernel size_deviation denormalize gen_pattern_grid timer find_hough_circles convexity_defect make_change_loglevel_fn pruning_quick_combine dist_pts_ellipse chessboard equalize find_kink erase_specular curvature metric is_round trace split_at_angle calibrate_camera normalize cart_to_spherical timeit dif_gaus split_at_corner_index find_slope_disc find_slope_disc_test find_change_in_general_direction GetAnglesPolyline container_decode iter_catch project_distort_pts points_at_corner_index circle_grid find_kink_and_dir_change spherical_to_cart delta_t bin_thresholding jump_time slew_time_dummy Clock_Sync_Follower Time_Echo_Server Clock_Sync_Master slew_time get_time jump_time_dummy Time_Echo patch_pyre_zhelper_cdll Prevent_Idle_Sleep enclosing_window transparent_circle correlate_data find_closest PupilDataBisector transparent_image_overlay Bisector Affiliator Mutable_Bisector PupilDataCollector exact_window PupilTopic Plugin System_Plugin_Base Plugin_List import_runtime_plugins Plugin_Manager PluginTimeline Pupil_Data_Relay Pupil_Groups Pupil_From_Recording Pupil_Producer_Base Offline_Pupil_Detection DisabledPupilProducer Gaze_Positions_Exporter Pupil_Positions_Exporter _Base_Positions_Exporter Raw_Data_Exporter Recorder available_gb get_auto_name writable_dir Remote_Recording_State Remote_Recorder_Core Remote_Recorder Handle RoiModel Roi Seek_Control Service_UI sliceable_deque unique SingleFileStorage Storage StorageItem System_Graphs System_Timelines TaskManager TaskUI ManagedTask Clock_Service Time_Sync pupil_version_string get_version get_tag_commit write_version_file parse_version pupil_version Visualizer Vis_Circle Vis_Cross Vis_Fixation Vis_Light_Points PolylineStyleController Vis_Polyline Vis_Watermark Msg_Dispatcher Msg_Pair_Server Msg_Receiver ZMQ_handler Msg_Pair_Client Msg_Pair_Base Msg_Streamer ZMQ_Socket FixationDetectionMethod detect_fixations can_use_3d_gaze_mapping Offline_Fixation_Detector Fixation_Detector Fixation_Result_Factory gaze_dispersion vector_dispersion fixation_from_data Fixation_Detector_Base remove_all_observers _WeakReferenceToMethodByName _install_protection_descriptor_if_not_exists _get_wrapper_or_raise_if_not_exists _StrongReferenceToCallable _is_classmethod ReplaceWrapperError add_observer remove_observer _WrapperProtectionDescriptor _ObservableMethodWrapper ObserverError _get_wrapper_and_create_if_not_exists _ReferenceNoLongerValidError Observable decode detect_markers_robust get_close_markers m_marker_to_screen detect_markers m_screen_to_marker correct_gradient reversedEnumerate draw_markers bench get_default_audio_mode beep _windows_beep _linux_tink is_sound_enabled set_audio_mode _linux_beep _darwin_tink _windows_tink _platform_specific_switch is_voice_enabled _unknown_tink tink _darwin_beep _unknown_beep get_audio_mode get_audio_mode_list ChoreographyMode ChoreographyAction UnsupportedChoreographyModeError ChoreographyNotification CalibrationChoreographyPlugin _BaseHMDChoreographyPlugin HMD3DChoreographyPlugin NaturalFeatureChoreographyPlugin NaturalFeatureTracker ScreenMarkerChoreographyPlugin AutoStopTracker SingleMarkerChoreographyPlugin SingleMarkerMode available_calibration_choreography_plugins patch_loaded_plugins_with_choreography_plugin default_calibration_choreography_plugin GUIMonitor GUIWindow MarkerWindowStateAnimatingMarker MarkerWindowStateOpened _MarkerWindowState MarkerWindowController MarkerWindowStateAnimatingInMarker _easeInOutQuad MarkerWindowStateAnimatingOutMarker MarkerWindowStateShowingMarker MarkerWindowStateClosed UnhandledMarkerWindowStateError MarkerWindowStateIdle _interp_fn _map_value MonitorSelectionMixin Model2D Model2D_Monocular Model2D_Binocular Gazer2D NotEnoughReferenceDataError NotEnoughPupilDataError Matches CalibrationError FitDidNotConvergeError NotEnoughDataError Model GazerBase RealtimeMatcher _CalibrationResultFields _CalibrationSuccessFields _SerializedNamedTupleMixin _VersionedNotificationMixin _CalibrationSetupFields CalibrationFailureNotification CalibrationResultNotification CalibrationSuccessNotification CalibrationSetupNotification _CalibrationFailureFields _NotificationMixin closest_matches_monocular _find_nearest_idx closest_matches_binocular_batch _filter_pupil_list_by_confidence closest_matches_binocular closest_matches_monocular_batch _match_data_batch user_selectable_gazer_classes gazer_labels_by_class_names registered_gazer_classes gazer_classes_by_class_name BundleAdjustment SphericalCamera calibrate_binocular calibrate_monocular calibrate_hmd Gazer3D Model3D_Binocular Model3D_Monocular Model3D GazerHMD3D MissingEyeTranslationsError ModelHMD3D_Monocular ModelHMD3D_Binocular transform_points_by_extrinsic find_rigid_transform calculate_nearest_points_to_targets get_initial_eye_camera_rotation calculate_nearest_linepoints_to_points _clamp_norm_point inverse_extrinsic split_extrinsic get_eye_cam_pose_in_world transform_points_by_pose merge_extrinsic GazeFromOfflineCalibration GazeFromRecording GazeProducerBase CalculateAllController CalibrationController GazeMapperController ReferenceDetectionController ReferenceEditController Calibration CalibrationStorage GazeMapper GazeMapperStorage ReferenceLocation ReferenceLocationStorage CalibrationStorageUpdater CalibrationV1 _gazer_class_and_params_from_gaze_mapper_result update_offline_calibrations_to_latest_version CalibrationMenu GazeMapperMenu GazeMapperTimeline OfflineCalibrationTimeline OnTopMenu ReferenceLocationMenu ReferenceLocationRenderer ReferenceLocationTimeline SelectAndRefreshMenu StorageEditMenu _create_calibration create_task _create_ref_dict CircleMarkerDetectionTask FakeIPC FakeGPool _map_gaze _apply_manual_correction create_task NotEnoughPupilData validate _create_ref_dict create_bg_task _circle_points_offset _draw_circle_filled _circle_points_around_zero draw_circle_filled_func_builder Trackball make_coord_system_eye_camera_based basic_gl_setup adjust_gl_view get_window_frame_rect _Margins custom_gl_error_handling get_monitor_workarea_rect make_coord_system_norm_based is_window_visible get_framebuffer_scale _Rectangle get_window_content_rect make_coord_system_pixel_based GLFWErrorReporting get_content_scale get_window_frame_size_margins clear_gl_screen get_window_title_bar_rect window_coordinate_to_framebuffer_coordinate cvmat_to_glmat Coord_System current_context _will_window_be_visible_in_monitor WindowPositionManager Head_Pose_Tracker_Base Offline_Head_Pose_Tracker Online_Head_Pose_Tracker ExportController OfflineDetectionController OfflineLocalizationController OfflineOptimizationController OnlineController BundleAdjustment _get_frame_id_to_extrinsics_init calculate _get_marker_id_to_extrinsics_init _get_bin _check_bins_availability _decide_key_markers _get_key_markers run _calculate _run_solvepnp calculate _check_result_reasonable _prepare_data_for_solvepnp _calculate calculate _prepare_data_for_triangulation _check_result_reasonable _run_triangulation get_marker_extrinsics_origin merge_extrinsics get_marker_points_4d_origin get_camera_pose rod_to_euler split_extrinsics find_origin_marker_id timer get_marker_points_3d_origin svdt convert_matrix_to_extrinsic convert_marker_extrinsics_to_points_3d convert_extrinsic_to_matrix get_none_camera_extrinsics to_camera_coordinate OfflineMarkerLocation OfflineDetectionStorage OnlineDetectionStorage OnlineSettings SettingsStorage OfflineSettingsStorage OfflineCameraLocalization OnlineLocalizationStorage Localization OfflineLocalizationStorage OptimizationStorage Markers3DModel DetectionRenderer set_rotate_center render_camera_trace _render_frustum render_camera_frustum shift_render_center render_strip_in_3d_window render_coordinate render_centroid render_polygon_in_3d_window GLWindow HeadPoseTracker3DRenderer OfflineDetectionMenu OfflineHeadPoseTrackerMenu OfflineHeadPoseTrackerTimeline LocalizationTimeline DetectionTimeline OfflineLocalizationMenu OfflineOptimizationMenu OnlineHeadPoseTrackerMenu OnlineOptimizationMenu VisualizationMenu _detect online_detection get_markers_data dedupliciate_markers calc_perimeter offline_detection _export_model export_routine _write_csv _export_poses online_localization get_pose_data offline_localization offline_optimization optimization_routine online_optimization nearest_intersection nearest_linepoint_to_point nearest_intersection_points orthogonalization_matrix vector_product inverse_matrix euler_matrix translation_matrix shear_matrix vector_norm quaternion_from_matrix quaternion_inverse Arcball projection_matrix unit_vector rotation_from_matrix random_rotation_matrix quaternion_from_euler affine_matrix_from_points decompose_matrix clip_matrix quaternion_conjugate quaternion_rotation_matrix quaternion_slerp quaternion_about_axis arcball_map_to_sphere scale_from_matrix euler_from_quaternion angle_between_vectors scale_matrix quaternion_from_rotation_matrix random_quaternion quaternion_matrix quaternion_imag superimposition_matrix arcball_nearest_axis projection_from_matrix translation_from_matrix shear_from_matrix euler_from_matrix rotation_matrix random_vector compose_matrix identity_matrix reflection_matrix concatenate_matrices is_same_transform arcball_constrain_to_axis about_axis_from_quaternion reflection_from_matrix quaternion_multiply quaternion_real _import_module NetworkApiPlugin FramePublisherController PupilRemoteController FrameFormat FramePublisherMenu PupilRemoteMenu Color Detector2DPlugin PupilDetectorPlugin DetectorPropertyProxy Pye3DPlugin draw_eyeball_outline draw_pupil_outline draw_ellipse available_detector_plugins LeGrandEye BasicEye PosedObject rotate_v1_on_v2 transform_as_homogeneous_vector cart2sph make_homogeneous_vector enclosed_angle normalize transform_as_homogeneous_point make_homogeneous_point sph2cart Eye_Visualizer PupilRecording _is_pupil_mobile_recording _is_old_style_player_recording get_recording_type _attempt_changing_file_owners_on_macOS RecordingType InvalidRecordingException assert_valid_rec_dir _is_pupil_invisible_recording assert_valid_recording_type RecordingInfo RecordingInfoInvalidError RecordingInfoFile _RecordingInfoFile_2_0 _RecordingInfoFile_2_1 _RecordingInfoFile_2_2 _RecordingInfoFile_2_3 string_from_recording_version validator_version_string string_from_uuid seconds_from_nanoseconds nanoseconds_from_seconds validator_optional_type read_info_invisible_json_file read_pupil_invisible_info_file parse_duration_string read_info_csv_file default_system_info validator_type default_recording_name uuid_from_string validator_uuid_string read_info_json_file _validated_conf_data _find_and_load_densified_worn_data _convert_gaze pi_gaze_items _find_raw_path _find_worn_path _generate_pprf_2_1_info_file transform_invisible_to_corresponding_new_style _rename_pi_files _pi_realtime_recorded_gaze_items _transform_invisible_v1_0_to_pprf_2_1 android_system_info _load_timestamps_data _pi_path_core_path_pairs _find_timestamps_200hz_path _rewrite_timestamps _load_raw_data _pi_posthoc_200hz_gaze_items _find_worn_200hz_path _load_worn_data _equalize_length_if_necessary BrokenFirstFrameRecordingIssue _find_raw_200hz_path _find_and_load_realtime_recorded_worn_data matched_files_by_name_pattern transform_mobile_to_corresponding_new_style _generate_pprf_2_0_info_file _transform_mobile_v1_2_to_pprf_2_0 _rename_mobile_files _rewrite_timestamps update_newstyle_20_21 check_min_player_version update_newstyle_22_23 recording_update_to_latest_new_style update_newstyle_21_22 check_for_worldless_recording_new_style update_recording_v04_to_v074 _generate_pprf_2_0_info_file update_recording_v082_to_v083 _read_rec_version_legacy update_recording_v073_to_v074 _infer_start_time_system_from_legacy update_recording_v083_to_v086 update_recording_v05_to_v074 update_recording_v0913_to_v13 update_recording_v113_v114 update_recording_v18_v19 update_recording_v03_to_v074 update_recording_v111_v113 update_recording_v091_to_v093 update_recording_v114_v116 update_recording_v086_to_v087 update_recording_v14_v18 update_recording_v074_to_v082 update_recording_v19_v111 _infer_start_time_synced_from_legacy update_meta_info _update_recording_to_old_style_v1_16 update_recording_v087_to_v091 _delete_all_lookup_files update_recording_bytes_to_unicode _warn_imprecise_value_inference _update_info_version_to update_recording_v094_to_v0913 update_recording_v13_v14 update_recording_v093_to_v094 transform_old_style_to_pprf_2_0 _try_patch_world_instrinsics_file _rewrite_times update_recording _generate_all_lookup_tables _assert_compatible_meta_version np_sort_by_named_columns ScanPathAlgorithm ScanPathController ScanPathParams ScanPathStorage np_normalize sec_to_ns ns_to_sec timestamp_ns generate_frames_with_gaze generate_frame_indices_with_deserialized_gaze scan_path_numpy_array_from generate_frames FakeGPool np_denormalize scan_path_zeros_numpy_array ScanPathBackgroundTask generate_frames_with_corrected_gaze _BaseTask ScanPathPreprocessingTask CanceledState UninitializedState CompletedState StartedState ActiveState _BaseState Exporter data_processing_generator gaze_on_surface_generator background_video_processor get_export_proxy video_processing_generator background_data_processor background_gaze_on_surface Cache rgb_to_rgba GUI Surface_Window _get_norm_to_points_trans _get_points_to_norm_trans Heatmap_Mode surface_locater_callable marker_detection_callable Surface_Location Surface _Surface_File_Store_V00 Surface_File_Store _Surface_File_Store_V01 _Surface_File_Store_Base _parse_surface_marker_uid_components _Apriltag_V3_Marker_Detection create_surface_marker_uid _Square_Marker_Detection Surface_Marker parse_surface_marker_type Surface_Marker_Type parse_surface_marker_tag_family parse_surface_marker_tag_id Surface_Base_Marker Surface_Marker_Aggregate MarkerDetectorController Surface_Base_Marker_Detector Surface_Square_Marker_Detector ApriltagFamily MarkerType Surface_Apriltag_V3_Marker_Detector Surface_Apriltag_V3_Marker_Detector_Params MarkerDetectorMode Surface_Offline Surface_Online InvalidSurfaceDefinition _Surface_Serializer_V01 _Surface_Serializer_Base _Surface_Serializer_V00 Surface_Tracker Surface_Tracker_Offline _CacheRelevantDetectorParams Surface_Tracker_Online TaskInterface UniqueTaskManager PluginTaskManager raise_exception create Patch KeyboardInterruptHandlerPatch IPCLoggingPatch SharedMemory BackgroundTask BackgroundGeneratorFunction TypedBackgroundGeneratorFunction _routine_wrapper BackgroundRoutine _generator_wrapper EndofVideoError SourceMode Base_Source SourceInfo StreamError Base_Manager NoMoreVideoError InitialisationError Playback_Source File_Manager OnDemandDecoder File_Source BrokenStream Decoder FakeFrame Frame FileSeekError BufferedDecoder RGBFrame Uint8BufferFrame HMD_Streaming_Source BGRFrame GrayFrame NDSI_Manager NDSI_Source Check_Frame_Stripes Video VideoSet Exposure_Time LookupTableNotInitializedError InvalidContainerError TJSAMP UVC_Source UVC_Manager Eye_Video_Exporter _add_pupil_ellipse _no_change _process_frame _iMotionsExporterNo3DGazeDataError _get_recording_start_date _copy_info_csv iMotions_Exporter _csv_exported_gaze_data World_Video_Exporter _export_world_video GlobalContainer _find_video_file IsolatedFrameExporter _convert_video_file VideoExporter OverlayManager Configuration Eye_Overlay Video_Overlay current_mouse_pos Draggable UIManagement UIManagementEyes UIManagementGeneric OverlayMenuRenderer make_alpha_slider EyesOverlayMenuRenderer make_hflip_switch make_vflip_switch GenericOverlayMenuRenderer make_scale_slider BooleanConstraint NoConstraint ConstraintedPosition ConstraintedValue BaseConstraint InclusiveConstraint ScaleTransform float_to_int VerticalFlip PupilRenderer HorizontalFlip ImageManipulator FrameFetcher OverlayRenderer EyeOverlayRenderer testfile test_read_write_key_value_file TestExceptionThrowingMethods FakeObservable TestDifferentKindsOfObservers TestWrapperProtectionDescriptor TestRemovingObservers test_observers_can_be_observed TestWrappedMethodCalls TestDeletingObserverObjects TestExceptionThrowingObservers TestObserverCalls observable TestDeletingObservableObjects TestObservabilityOfMethods test_pupil_positions_exporter_capture _test_exporter test_pupil_positions_exporter_pi test_gaze_positions_exporter_pi test_gaze_positions_exporter_capture invalid_model test_fixture_invalid_model test_model_revalidation test_model_init_validity test_fixture_valid_model valid_model test_model_init_bounds test_model_invalidation_by_set test_frame_size_bounds_scaling test_model_invalidation_by_frame_size test_bounds_cutoff test_model_revalidation_bounds test_unique test_operators test_deserialize_definitions_from_file_missing_version expected_definitions_json_object expected_definitions test_deserialize_definitions_from_file_invalid_json test_deserialize_definitions_from_file_definitions_not_a_map test_expected_version test_deserialize_definitions_from_file test_deserialize_definitions_from_file_missing_definitions test_setup_notification_serialization _dict_subset _test_notification_serialization test_result_notification_serialization test_failure_notification_serialization test_success_notification_serialization test_file_store_v01_after_update _test_file_store_read_write test_file_store_v00 test_file_store_v01_before_update test_surface_marker_deserialize test_surface_marker_uid_helpers test_surface_marker_from_raw_detection test_surface_serializer_V01_square _test_surface_serializer_with_surfaces test_surface_serializer_V00 test_surface_serializer_V01_apriltag _test_surface_serializer_with_surface_marker_aggregates surface_definition_v01_after_update_dir surface_definition_v00_dir surface_definition_v01_before_update_dir _create_dir_with_surface_definition_file surface_marker_aggregates_deserialized surface_marker_aggregates_serialized surface_pairs surface_marker_aggregate_pairs surfaces_deserialized surfaces_serialized surface_marker_aggregates_deserialized surface_marker_aggregates_serialized surface_pairs surface_marker_aggregate_pairs surfaces_deserialized surfaces_serialized surface_marker_aggregates_deserialized surface_marker_aggregates_serialized surface_pairs surface_marker_aggregate_pairs surfaces_deserialized surfaces_serialized surface_marker_aggregate_pairs_v01_mixed surfaces_serialized_v01_mixed surfaces_deserialized_v01_mixed surface_pairs_v01_mixed surface_marker_aggregates_serialized_v01_mixed surface_marker_aggregates_deserialized_v01_mixed test_file_source_init test_file_source_recent_events test_get_rec_set_name single_fill_gaps broken_fill_gaps multiple_fill_gaps print walk str _MEIPASS glob Path next join remove format print glob sleep recording warning XSUB PULL socket expanduser Context Thread Msg_Dispatcher replace bind Value setDaemon start Msg_Receiver poll recv XPUB notify NOTSET value Msg_Dispatcher getLogger addHandler debug ERROR Msg_Receiver terminate warning ZMQ_handler destroy_window Msg_Streamer setLevel Context rsplit runctx format locals join print call getLogger ZMQ_handler Msg_Pair_Client send get_frame_count setLevel addHandler sleep append Context CircleTracker debug ERROR info get_frame INFO recv File_Source new_data index SimpleNamespace len recent_events decode set_framebuffer_size_callback Timeline_Menu UI setLevel str addHandler Scrolling_Menu init_ui get set_scroll_callback iconbar Bisector on_char get_dt info resolve clipboard version keys make_context_current SIGINT join recv toggle_general_settings chars timestamp Button SimpleNamespace clean update_clipboard getLogger poll_events window_hint RGBA list min_data_confidence Stretching_Menu destroy_window append normalize Named_Texture camera_render_size Msg_Dispatcher set_drop_callback TRUE insert Thumb Container new_window_position init clear set_cursor_pos_callback set_clipboard_string get_window_size SCALE_TO_MONITOR frame_size get_window_pos basic_gl_setup denormalize buttons Slider ZMQ_handler on_click all on_key timestamps handle_notifications is_window_visible update create_window WindowPositionManager configuration ERROR Persistent_Dict Growing_Menu Info_Text Msg_Receiver signal min_calibration_confidence Icon on_notify window_coordinate_to_framebuffer_coordinate extend user_timelines swap_buffers NOTSET get_system_info Plugin_List meta_info timelines wait set_key_callback gl_display menubar set_default set_mouse_button_callback set_char_callback Separator PupilDataBisector terminate Affiliator on_resize Text_Input Context capture format debug close reversed get_cursor_pos plugins PupilRecording get_initializers File_Source import_runtime_plugins sort glViewport new_data set_window_pos quickbar delta_t swap_buffers get_roboto_font_path glClearColor getLogger basic_gl_setup adjust_gl_view poll_events window_hint ZMQ_handler add_font set_color_float setLevel set_default RESIZABLE get_framebuffer_size addHandler destroy_window Context get format Msg_Dispatcher set_drop_callback TRUE create_window WindowPositionManager ERROR Persistent_Dict close get_content_scale display_multiline_string signal init info new_window_position make_context_current INFO clear_gl_screen SIGINT join clear set_align_string notify SCALE_TO_MONITOR get_window_pos set_window_pos update_recording assert_valid_recording_type rsplit runctx locals join print call recent_events get_system_info Plugin_List getLogger warning ZMQ_handler map_pupil_to_gaze send setLevel register get_audio_mode str socket user_dir addHandler set_audio_mode clean handle_notifications append Msg_Streamer Context get get_default_audio_mode patch_loaded_plugins_with_choreography_plugin format Msg_Dispatcher value debug ERROR available_calibration_choreography_plugins Persistent_Dict close Msg_Receiver registered_gazer_classes signal plugins info zip version min_calibration_confidence on_notify poll SIGINT join clear recv active_gaze_mapping_plugin service_should_run import_runtime_plugins get_initializers notify launch_eye_process dict SimpleNamespace Poller delta_t rsplit runctx locals join print call recent_events decode set_framebuffer_size_callback send UI setLevel values str addHandler Scrolling_Menu get patch_loaded_plugins_with_choreography_plugin set_scroll_callback iconbar version get_dt on_char clipboard keys make_context_current SIGINT join recv notify toggle_general_settings launch_eye_process chars Button SimpleNamespace clean update_clipboard getLogger poll_events window_hint add Stretching_Menu destroy_window append normalize Named_Texture get_default_audio_mode Msg_Dispatcher set_drop_callback TRUE available_calibration_choreography_plugins registered_gazer_classes new_window_position init clear set_cursor_pos_callback set_clipboard_string get_window_size SCALE_TO_MONITOR frame_size get_window_pos bool basic_gl_setup denormalize buttons ZMQ_handler on_click all VISIBLE set_audio_mode on_key handle_notifications update create_window WindowPositionManager configuration pupil_detection_enabled ERROR Persistent_Dict Growing_Menu Info_Text Msg_Receiver signal min_calibration_confidence Icon on_notify pop window_coordinate_to_framebuffer_coordinate trigger_main_window_redraw swap_buffers NOTSET get_system_info Plugin_List restore_window Switch set_key_callback timer gl_display swap_interval Selector get_audio_mode menubar set_default set_mouse_button_callback set_char_callback user_dir Separator terminate Context format value debug close get_cursor_pos plugins get_initializers import_runtime_plugins glViewport new_data set_window_pos quickbar delta_t rsplit runctx locals join print call chr chr namedtuple chr _load_audio_from_world_video_files _load_audio_from_audio_files PupilRecording sorted mp4 sorted videos load str seek debug stem time_base audio tolist iter with_name next array open join T format Video savetxt load_pts splitext save load_container array split rand range sleep join is_pupil_rec_dir walk chr chr cpu_count preview ArgumentParser description show_progess export_to_dir add Export_Process sleep append get_recording_dirs parse_args expanduser range get format Value Persistent_Dict close set start info is_alive Temp rec_dir join out_file_path isdir print error add_argument len chr get_current_context adjust_gl_view make_context_current chr append range reshape array amax amin dict zeros_like resize max adaptiveThreshold array append sum ADAPTIVE_THRESH_GAUSSIAN_C range THRESH_BINARY_INV ones_like find_concentric_circles mean GaussianBlur int ellipse min median std len get_nested_clusters findContours fitEllipse array append max append add_parents T cos pi matmul getRotationMatrix2D linspace sin column_stack zeros solvePnP astype getEllipsePts VideoCapture read COLOR_BGR2GRAY print find_concentric_circles waitKey set imshow range cvtColor len sniff readline seek reader writer writerow items isinstance makedirs dirname _get_token_file_path _get_token_file_path join format expanduser expanduser expanduser deque join load join sorted format int iglob Mapping isinstance MappingProxyType print time print load_pupil_data_file time keys float write compile compile compile compile set compile compile compile sort compat_keys stdin multipleInput Format strip edge_thres prune_root DotWriter getFunctionId open list add_option prune prune_leaf exit stdinInput totalMethod parse OptionParser node_thres leaf root keys stdout show_samples graph sort theme_skew write output wrap colour_nodes_by_selftime fileno chr sort_values DataFrame set_index to_markdown set_align_string set_color_float add_font get_opensans_font_path Context update Fusion enumerate names view recarray dtype dtype chr chr format sub chr time time projectPoints sqrt arccos arctan2 cos sin asarray inRange ones float32 asarray getStructuringElement MORPH_ELLIPSE erode dilate GaussianBlur inRange int medianBlur max inpaint asarray getStructuringElement MORPH_ELLIPSE dilate float inRange uint16 HoughCircles around circle HOUGH_GRADIENT findChessboardCorners sum Vector angle append range len cross arctan2 sum roll append zip append range zip append range zip append abs zip list sort add set zip abs append zip mean append findCirclesGridDefault zeros calibrateCamera append range float64 evaluate pi pop extend set fn append range len getuser uname __doc__ __name__ iter demux int getattr min len type len asarray clip searchsorted append sort list int addWeighted tuple map copy clip circle addWeighted join rsplit format isdir insert debug dir import_module getattr isfile append listdir chr chr chr chr free chr join open chr cygl_rgba chr chr check_output replace decode join base_version replace get_tag_commit is_prerelease Version split join _MEIPASS pupil_version_string debug getattr print join pupil_version_string chr chr chr chr chr chr chr int min tolist rad2deg searchsorted len max pdist arccos frame_size array unprojectPoints vector_dispersion clear list extendleft popleft from_data Fixation_Result_Factory timestamps reversed warning gaze_dispersion info deque append len _get_wrapper_and_create_if_not_exists _install_protection_descriptor_if_not_exists getattr isinstance _is_classmethod setattr __self__ hasattr get_wrapped_bound_method isinstance getattr _WrapperProtectionDescriptor type __name__ _get_wrapper_or_raise_if_not_exists _get_wrapper_or_raise_if_not_exists getattr triu_indices pdist array where pop tuple transpose tolist resize sqrt tolist int decode threshold roll getPerspectiveTransform resize correct_gradient abs transpose THRESH_OTSU adaptiveThreshold append sum findContours ADAPTIVE_THRESH_MEAN_C warpPerspective cornerSubPix drawContours getStructuringElement reshape MORPH_CROSS min float32 THRESH_BINARY erode array format polylines putText m_marker_to_screen tuple int0 perspectiveTransform copy array array array where detect_markers vstack list tolist add sum range get_close_markers slice calcOpticalFlowPyrLK copy set mean norm T sort min array join detect_markers_robust draw_markers img File_Capture get_frame warning _platform_specific_switch is_sound_enabled _platform_specific_switch is_sound_enabled unknown_fn system linux_fn darwin_fn windows_fn Popen Popen Popen Popen print print print print chr get list default_calibration_choreography_plugin available_calibration_choreography_plugins append __name__ enumerate NamedTuple OrderedDict debug warning len debug closest_matches_monocular_batch closest_matches_binocular_batch len debug _find_nearest_idx min array append max debug _find_nearest_idx min array append max _find_nearest_idx min array append max _find_nearest_idx min array append max searchsorted registered_gazer_classes filter get_initial_eye_camera_rotation SphericalCamera BundleAdjustment calculate calculate find_rigid_transform SphericalCamera inverse_extrinsic transform_points_by_pose BundleAdjustment ravel list asarray calculate SphericalCamera linspace get_initial_eye_camera_rotation BundleAdjustment split_extrinsic T asarray split_extrinsic T asarray dot split_extrinsic dot asarray concatenate svd T mean dot diag ravel find_rigid_transform split_extrinsic transform_points_by_extrinsic eye dot norm T diag transform_points_by_extrinsic calculate_nearest_linepoints_to_points zip append zeros chr chr namedtuple debug mapper_args mapping_plugin_name from_g_pool by_ts_window timestamps exact_window frame_index_range minimum_confidence gazer_classes_by_class_name gazer_class import_runtime_plugins registered_gazer_classes CalibrationResult get_params mapping_index_range params gazer_classes_by_class_name max import_runtime_plugins registered_gazer_classes map_pupil_to_gaze gazer_cls _apply_manual_correction list get_in_range validation_index_range from_g_pool by_ts_window timestamps params exact_window gazer_classes_by_class_name calc_acc_prec_errlines registered_gazer_classes import_runtime_plugins glVertexPointer g GL_DOUBLE r glEnableClientState GL_VERTEX_ARRAY glColor4f glDrawArrays _circle_points_offset_f b GL_POLYGON a copy hstack linspace pi VISIBLE get_window_attrib ICONIFIED flatten eye glClearColor glBlendFunc glEnable glClear glMatrixMode glViewport glLoadIdentity glOrtho max glLoadIdentity glOrtho glMatrixMode glMatrixMode glLoadIdentity degrees gluPerspective float atan glLoadIdentity glOrtho glMatrixMode get_monitor_workarea get_window_pos get_window_size get_window_frame_size get_window_content_rect get_window_frame_size_margins get_window_frame_rect get_window_frame_size_margins get_current_context make_context_current get_monitor_workarea_rect get_window_size intersection _Rectangle get_window_frame_size_margins chr list _get_marker_id_to_extrinsics_init set _get_frame_id_to_extrinsics_init InitialGuess range calculate keys set calculate keys set _decide_key_markers _check_bins_availability len int digitize _calculate _prepare_data_for_solvepnp reshape _run_solvepnp merge_extrinsics _check_result_reasonable solvePnP split_extrinsics any to_camera_coordinate combinations _prepare_data_for_triangulation keys reshape undistort_points_to_ideal_point_coordinates svdt _run_triangulation convertPointsFromHomogeneous T triangulatePoints array concatenate array split_extrinsics eye sqrt array matmul arctan2 merge_extrinsics rod_to_euler split_extrinsics matmul convertPointsFromHomogeneous T matmul convert_extrinsic_to_matrix get_marker_extrinsics_origin items allclose svd T size mean dot sqrt range diag len glLoadTransposeMatrixf glMultTransposeMatrixf GL_LINE GL_FILL glBegin glEnd GL_POLYGON glColor4f glPolygonMode glVertex3f GL_FRONT_AND_BACK glBegin glEnd glColor4f GL_LINE_STRIP glVertex3f glPointSize glBegin glEnd GL_POINTS glLoadIdentity glColor4f glVertex3f render_strip_in_3d_window eye zip _render_frustum resolution K shift_render_center render_coordinate render_polygon_in_3d_window render_strip_in_3d_window asarray corners calc_perimeter gray detect unique sorted _detect File_Source zip seek_to_frame set timestamps searchsorted get_frame append SimpleNamespace range _export_model _export_poses join format _write_csv info join format info _write_csv len convert_extrinsic_to_matrix get_camera_pose sorted calculate Serialized_Dict set get_pose_data find_markers_in_frame append keys range calculate current_markers marker_id_to_extrinsics calculate frame_id_to_extrinsics all_key_markers IntrinsicsTuple D K marker_id_to_extrinsics list sorted optimization_routine len shuffle Markers3DModel set find_markers_in_frame BundleAdjustment range enumerate BundleAdjustment Markers3DModel dot mag normalise nearest_intersection_points dot sqrt norm identity dot unit_vector identity squeeze eig array cos identity dot sin unit_vector array diag T squeeze eig atan2 trace array dot unit_vector identity diag squeeze eig array trace dot unit_vector array identity T squeeze eig dot array len dot unit_vector tan identity T vector_norm squeeze eig identity cross dot atan array T vector_norm asin inv cos copy atan2 dot any negative zeros array dot euler_matrix identity radians cos sin svd T concatenate inv identity quaternion_matrix roll dot eigh pinv vstack sum array identity sqrt atan2 empty cos sin array cos vector_norm unit_vector eps asarray sqrt dot array outer eigh trace negative empty array identity negative array negative array pi dot sin negative unit_vector acos sqrt rand pi sqrt negative array vector_norm dot arcball_constrain_to_axis array atleast_1d sqrt sum array atleast_1d sqrt expand_dims sum array sum array dot identity array import_module chr chr chr _draw_circle_filled draw_polyline tuple RGBA ellipse2Poly as_float draw_ellipse draw_ellipse norm arccos arctan2 empty cos sin T arccos dot normalize clip make_homogeneous_point make_homogeneous_vector norm asarray dot cross eye allclose normalize auto does_recording_contain_info_file _is_pupil_mobile_recording _is_old_style_player_recording assert_valid_rec_dir _is_pupil_invisible_recording resolve _attempt_changing_file_owners_on_macOS is_video_file read_info_json_file read_info_csv_file read_info_csv_file getLogger debug getuser dedent run str isinstance rec_dir parse_version uuid_from_string join join join read_info_json_file _transform_invisible_v1_0_to_pprf_2_1 parse_version info _rename_pi_files replace videos _rewrite_timestamps Path patch_recording_if_affected PupilRecording _convert_gaze with_name _generate_pprf_2_1_info_file _try_patch_world_instrinsics_file int validate RECORDING_SOFTWARE_NAME_PUPIL_INVISIBLE android_system_info save_file parse_version default_recording_name create_empty_file read_info_json_file replace _pi_path_core_path_pairs int replace name group files match with_name int rec_dir _rewrite_times read_pupil_invisible_info_file info get _find_timestamps_200hz_path Path _find_raw_200hz_path _find_worn_200hz_path matched_files_by_name_pattern _equalize_length_if_necessary _validated_conf_data _load_raw_data _load_timestamps_data _find_and_load_densified_worn_data _load_worn_data _equalize_length_if_necessary _validated_conf_data _load_raw_data _load_timestamps_data _find_raw_path _load_worn_data _find_worn_path is_file is_file is_file replace with_suffix name is_file replace with_suffix load str fromfile str dtype fromfile str _find_and_load_realtime_recorded_worn_data find_closest _validated_conf_data concatenate _load_timestamps_data append _load_worn_data _find_worn_path min warning len ones warning len filter iterdir is_file _transform_mobile_v1_2_to_pprf_2_0 read_info_csv_file parse_version info _generate_pprf_2_0_info_file replace videos _rewrite_timestamps _rename_mobile_files Path PupilRecording with_name _try_patch_world_instrinsics_file get uuid4 validate parse_duration_string read_info_csv_file save_file default_system_info default_recording_name float create_empty_file replace name group files match with_name update_newstyle_20_21 update_newstyle_22_23 check_min_player_version read_file_from_recording update_newstyle_21_22 save_object videos info Path PupilRecording update_writeable_properties_from debug read_file_from_recording unlink save_file _convert_gaze PupilRecording iterdir create_empty_file update_writeable_properties_from read_file_from_recording create_empty_file save_file items update_writeable_properties_from info error group read_file_from_recording match any save_file save from_default keys create_empty_file _generate_pprf_2_0_info_file replace debug Path info _update_recording_to_old_style_v1_16 with_name _infer_start_time_system_from_legacy debug _infer_start_time_synced_from_legacy RECORDING_SOFTWARE_NAME_PUPIL_CAPTURE _read_rec_version_legacy update_recording_v04_to_v074 update_recording_v082_to_v083 update_recording_v073_to_v074 update_recording_v083_to_v086 update_recording_v05_to_v074 read_info_csv_file update_recording_v0913_to_v13 update_recording_v113_v114 update_recording_v18_v19 update_recording_v03_to_v074 update_recording_v111_v113 update_recording_v091_to_v093 update_recording_v114_v116 update_recording_v086_to_v087 debug update_recording_v14_v18 update_recording_v074_to_v082 update_recording_v19_v111 update_meta_info update_recording_v087_to_v091 update_recording_bytes_to_unicode error update_recording_v094_to_v0913 update_recording_v13_v14 update_recording_v093_to_v094 join info update_meta_info read_info_csv_file _update_info_version_to pop join save_object _update_info_version_to info load_object join save_object _update_info_version_to info load_object keys get join save_object _clamp_norm_point _update_info_version_to info load_object _update_info_version_to info get join save_object _update_info_version_to info load_object join save_object _update_info_version_to info load_object listdir decode arange rate interp1d frames demux interpolate save open mux samples encode debug close info load join _update_info_version_to frame_size add_stream len join save_object tuple _update_info_version_to rename info load_object _update_info_version_to info _update_info_version_to info copy_recorded_annotations _update_info_version_to copy_cached_annotations info get uuid4 read_info_csv_file info update_meta_info make_update _update_info_version_to _delete_all_lookup_files _update_info_version_to _delete_all_lookup_files _update_info_version_to unlink Path join save_object format convert info load_object listdir pop join save_object info load_object load_object join save_object info load join save_object dict info append load join save_object rename info append get join debug _warn_imprecise_value_inference strptime timestamp warning info load str _warn_imprecise_value_inference min timestamps warning info append FileFilter warning str from_file default_intrinsics save open str parent conversion save info fromfile raw_time join filter_patterns error recording_update_to_latest_new_style _generate_all_lookup_tables update_offline_calibrations_to_latest_version get_recording_type check_for_worldless_recording_new_style _assert_compatible_meta_version PupilRecording resolve SimpleNamespace File_Source PupilRecording dict reversed zeros view recarray asarray scan_path_zeros_numpy_array enclosing_window VideoSet stem len by_ts_window timestamps scan_path_numpy_array_from PupilRecording load_or_build_lookup flatnonzero rec_dir enclosing_window by_ts_window index timestamps generate_frames File_Source get_frame index PupilRecording get_frame_count rec_dir generate_frames update_from_frame ScanPathAlgorithm handle_frame str value format File_Source getLogger debug getpid get_frame_count SimpleNamespace next_unvisited_idx get_frame_index value handle_sample next_unvisited_idx map_section Exporter IPC_Logging_Task_Proxy save_surface_statisics_to_file array array array _parse_surface_marker_uid_components _parse_surface_marker_uid_components _parse_surface_marker_uid_components value split SQUARE APRILTAG_V3 chr error join format_stack isgeneratorfunction isroutine apply should_terminate_flag generator_function send _TaskYieldSignal _TaskCanceledSignal _TaskCompletedSignal routine send apply auto chr meta_info duration_s start_time_synced_s get_frame_count round str recording_uuid strftime recording_name fromtimestamp system_info PupilRecording int join File_Source recording_software_version start_time_system_s min_player_version SimpleNamespace start_time_system_s fromtimestamp meta_info PupilRecording projectPoints find_closest denormalize frame_size unprojectPoints zip append exact_window init_dict_for_window chr recent_events Plugin_List meta_info videos getLogger GlobalContainer by_ts_window warning notifications from_init_dict write_video_frame values str sorted basename list timestamps getpid dirname Affiliator append expanduser enclosing_window format debug seek_to_frame close Bisector plugins zip PupilRecording info resolve MPEG_Audio_Writer get_frame on_notify float pop join remove time File_Source import_runtime_plugins index dict isfile len int exact_window File_Source cleanup find_closest frame_rate seek_to_frame close timestamps MPEG_Writer get_frame SimpleNamespace write_video_frame process_frame get_frame_index chr denormalize get_cursor_pos get_content_scale get_current_context normalize update copy Mock assert_has_calls FakeController bound_method add_observer on_bound_method dict_export tuple csv_export_labels _test_exporter _test_exporter _test_exporter RoiModel set_invalid RoiModel bounds RoiModel RoiModel dump _deserialize_definitions_from_file seek StringIO dump seek StringIO dump seek StringIO dump seek StringIO dump seek StringIO from_dict _test_notification_serialization append from_dict as_dict zip _test_file_store_read_write _test_file_store_read_write _test_file_store_read_write list write_surfaces_to_file Surface_File_Store read_surfaces_from_file deserialize create_surface_marker_uid product set dict_from_surface surface_from_dict dict_from_surface_marker_aggregate surface_marker_aggregate_from_dict _test_surface_serializer_with_surface_marker_aggregates _test_surface_serializer_with_surfaces _test_surface_serializer_with_surface_marker_aggregates _test_surface_serializer_with_surfaces _test_surface_serializer_with_surface_marker_aggregates _test_surface_serializer_with_surfaces uuid4 join str Persistent_Dict gettempdir save makedirs SimpleNamespace File_Source | # Pupil <a href="https://pupil-labs.com" rel="noopener" target="_blank"> <p align="center"> <img src="https://raw.githubusercontent.com/wiki/pupil-labs/pupil/media/images/pupil_labs_pupil_core_repo_banner.jpg" alt="Pupil Labs - Pupil Core software: open source eye tracking platform."/> </p> | 3,350 |
pursuer0123/T-GCN | ['traffic prediction'] | ['T-GCN: A Temporal Graph ConvolutionalNetwork for Traffic Prediction'] | visualization.py gru.py tgcn.py input_data.py utils.py main.py baselines.py gcn.py preprocess_data evaluation GCN GRUCell preprocess_data load_los_data load_sz_data TGCN evaluation tgcnCell calculate_laplacian sparse_to_tuple weight_variable_glorot normalized_adj plot_result plot_error int mat append range len var norm mean_absolute_error sqrt mean_squared_error sum mat read_csv mat read_csv array MultiRNNCell static_rnn reshape transpose tgcnCell matmul unstack append diags tocoo astype float32 flatten coo_matrix sum array data tocoo transpose shape SparseTensor normalized_adj csr_matrix astype float32 eye sqrt random_uniform show plot savefig figure legend show plot savefig figure legend | This is a TensorFlow implementation of T-GCN: A Temporal Graph Convolutional Network for Traffic Prediction. # The manuscript ## T-GCN: A Temporal Graph Convolutional Network for Traffic Prediction Accurate and real-time traffic forecasting plays an important role in the Intelligent Traffic System and is of great significance for urban traffic planning, traffic management, and traffic control. However, traffic forecasting has always been considered an open scientific issue, owing to the constraints of urban road network topological structure and the law of dynamic change with time, namely, spatial dependence and temporal dependence. To capture the spatial and temporal dependence simultaneously, we propose a novel neural network-based traffic forecasting method, the temporal graph convolutional network (T-GCN) model, which is in combination with the graph convolutional network (GCN) and gated recurrent unit (GRU). Specifically, the GCN is used to learn complex topological structures to capture spatial dependence and the gated recurrent unit is used to learn dynamic changes of traffic data to capture temporal dependence. Then, the T-GCN model is employed to traffic forecasting based on the urban road network. Experiments demonstrate that our T-GCN model can obtain the spatio-temporal correlation from traffic data and the predictions outperform state-of-art baselines on real-world traffic datasets. The manuscript can be visited at https://ieeexplore.ieee.org/document/8809901 or https://arxiv.org/abs/1811.05320 If this repo is useful in your research, please kindly consider citing our paper as follow. ``` Bibtex @article{zhao2019tgcn, title={T-GCN: A Temporal Graph Convolutional Network for Traffic Prediction}, | 3,351 |
purushothamgowthu/deep-photo-styletransfer | ['style transfer', 'semantic segmentation'] | ['DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs', 'Deep Photo Style Transfer'] | gen_all.py | # deep-photo-styletransfer Code and data for paper "[Deep Photo Style Transfer](https://arxiv.org/abs/1703.07511)" ## Disclaimer **This software is published for academic and non-commercial use only.** ## Setup This code is based on torch. It has been tested on Ubuntu 14.04 LTS. Dependencies: * [Torch](https://github.com/torch/torch7) (with [matio-ffi](https://github.com/soumith/matio-ffi.torch) and [loadcaffe](https://github.com/szagoruyko/loadcaffe)) * [Matlab](https://www.mathworks.com/) or [Octave](https://www.gnu.org/software/octave/) CUDA backend: | 3,352 |
pvougiou/Aligning-Reddit-and-Wikipedia | ['response generation'] | ['A Neural Network Approach for Knowledge-Driven Response Generation'] | Python/Alignment.py | # Aligning Reddit and Wikipedia A dataset that aligns knowledge from Wikipedia in the form of sentences with sequences of Reddit utterances. The dataset consists of sequences of comments and a number of Wikipedia sentences that were allocated randomly from the Wikipedia pages to which each sequence is aligned. The resultant dataset consists of 15k sequences of comments that are aligned with 75k Wikipedia sentences. For a detailed description of this dataset please refer to original paper: https://aclweb.org/anthology/C/C16/C16-1318.pdf. ## Contents * The HDF5 files (i) `Aligned-Dataset/reddit.h5` and (ii) `Aligned-Dataset/wikipedia.h5` are built in such a way that each sequence of comments on Reddit is aligned with 20 Wikipedia sentences. * `Inspect-Dataset.ipynb` is a Python script on iPython Notebook that allows easier inspection of the above aligned dataset. * The folders `Data/Reddit` and `Data/Wikipedia` contain the respective Reddit sequences of comments and Wikipedia sentences as these have been initially extracted by utilising the search feature of both their APIs (i.e. https://www.reddit.com/dev/api/ and https://www.mediawiki.org/wiki/API:Main_page). ## BibTeX Please cite the following paper should you use this dataset in your work. ``` | 3,353 |
pwang724/neural-style-transfer | ['style transfer'] | ['A Neural Algorithm of Artistic Style'] | scripts/loss.py scripts/model.py scripts/utils.py scripts/stylize.py losses build_part_vgg19 arg_parser gram_matrix down_sample make_output_folder constant unstack reduce_sum pool concat conv item split add_argument ArgumentParser isinstance reshape transpose shape Tensor int size resize max open join basename splitext makedirs | # Neural Style Transfer Simple tensorflow implementation of NST by [Gatys and Bethge](https://arxiv.org/abs/1508.06576). Synthesizes a composite image with content specified by one image and style specified by another. #### Details Implementation of the original algorithm uses a pre-trained [VGG19 network](https://github.com/machrisaa/tensorflow-vgg)\. Loosely inspired by [this](https://pytorch.org/tutorials/advanced/neural_style_tutorial.html) and [this](https://github.com/VainF/Neural-Style-Transfer-Gatys). Content layer = **[conv4_2]**\ Style layer = **[conv1_1, conv2_1, conv3_1, conv4_1, and conv5_1]**\ Style weight = **[.2, .2, .2, .2, .2]** "Style" is defined as a correlation matrix, where the **_ij_**th value of the matrix is dot product between the filtered images at depth **i** and depth **j** at a particular layer. Style loss is defined as the MSE between the correlation matrices of the input and style image at a particular layer. "Content" is defined as the activations of a particular layer. Content loss is defined as the MSE between the activations of the input and content image for a particular layer. Total loss is defined as the weighted sum of style loss and content loss. | 3,354 |
pykao/ISLES2017-mRS-prediction | ['lesion segmentation'] | ['Predicting Clinical Outcome of Stroke Patients with Tractographic Feature'] | utils_40.py heatmap.py fiber_tracking_HCP1021.py predict_40.py registerBrain.py analysis.py extract_oskar_features.py paths.py predict_wo_rfecv.py predict.py fiber_tracking.py utils.py extract_oskar_features_40.py plot_confusion_matrix image_features get_train_dataset find_3d_surface find_3d_roundness statistics_of_features twenty_two_statistics_of_feature statistics_of_a_feature image_features get_train_dataset find_3d_surface find_3d_roundness statistics_of_features twenty_two_statistics_of_feature statistics_of_a_feature MoveLesionsMNIMask Lesions2MNI152_star ISLES2017TrainingGTPaths RegisterBrain ISLES2017TrainingInVol2RefVolPaths ISLES2017TrainingADCPaths Lesions2MNI152 extract_modified_volumetric_spatial_features extract_morphological_features divide_hcp extract_volumetric_features extract_tract_features weight_conversion get_train_dataset extract_spatial_features threshold_connectivity_matrix reshape_by_padding_upper_coords extract_volumetric_spatial_features extract_new_tractographic_features find_list find_3d_surface extract_gt_mRS get_lesion_weights ReadImage get_modified_lesion_weights get_hcp_connectivity_matrice find_3d_roundness extract_tractographic_features extract_modified_volumetric_spatial_features extract_morphological_features divide_hcp extract_volumetric_features extract_tract_features weight_conversion get_train_dataset extract_spatial_features threshold_connectivity_matrix reshape_by_padding_upper_coords extract_volumetric_spatial_features extract_new_tractographic_features find_list find_3d_surface extract_gt_mRS get_lesion_weights ReadImage get_modified_lesion_weights get_hcp_connectivity_matrice find_3d_roundness extract_tractographic_features arange set_yticklabels xticks max yticks show list ylabel colorbar imshow title range format product astype tight_layout get_yticklabels print text xlabel len sort join percentile var linspace zeros std hstack twenty_two_statistics_of_feature range hstack statistics_of_a_feature reshape vstack marching_cubes_classic major_axis_length area astype pi regionprops print join copy join print call split makedirs call zeros range shape join loadmat list ones tuple reshape shape max copy absolute amax copy count_nonzero join int dtype multiply shape ReadImage reshape_by_padding_upper_coords zeros float dsi_studio_path range amax count_nonzero join int dtype multiply shape ReadImage reshape_by_padding_upper_coords zeros float dsi_studio_path range amax isles2017_dir zeros get_train_dataset keys enumerate zeros get_train_dataset keys enumerate count_nonzero join get_train_dataset find_list sort keys ReadImage zeros dsi_studio_path enumerate join get_train_dataset find_list sort astype centroid keys ReadImage zeros dsi_studio_path regionprops enumerate join get_train_dataset find_list major_axis_length find_3d_surface find_3d_roundness sort astype keys ReadImage zeros minor_axis_length dsi_studio_path regionprops enumerate join get_train_dataset find_list weight_conversion sum ones sort multiply threshold_connectivity_matrix keys get_lesion_weights get_modified_lesion_weights zeros loadmat dsi_studio_path enumerate count_nonzero dtype get_train_dataset multiply shape reshape_by_padding_upper_coords sum dsi_studio_path range find_list ReadImage float keys enumerate join int sort zeros amax count_nonzero join get_train_dataset find_list dtype int sort multiply keys shape ReadImage reshape_by_padding_upper_coords zeros float dsi_studio_path range amax enumerate join get_train_dataset find_list sum get_hcp_connectivity_matrice ones sort multiply divide keys get_lesion_weights get_modified_lesion_weights zeros loadmat dsi_studio_path enumerate | # Prediction of Modified Rankin Scale (mRS) in Stroke Patients with Tractographic Features This repository extracts the tractograpic feature, other first-order features and the state-of-the-art feature from the stroke lesion. A random forest regressor is used with one type of feature to predict the modified Rankin Scale of stroke patients. ## Citations [Predicting the overall survival of brain tumor patients using tractographic feature](https://link.springer.com/chapter/10.1007/978-3-030-11726-9_12) `Kao, Po-Yu, et al. "Brain tumor segmentation and tractographic feature extraction from structural mr images for overall survival prediction." International MICCAI Brainlesion Workshop. Springer, Cham, 2018.` [Predicting the clinical outcome of stroke patients using tractographic feature](https://arxiv.org/abs/1907.10419) `Kao, Po-Yu, et al. "Predicting Clinical Outcome of Stroke Patients with Tractographic Feature." International MICCAI Brainlesion Workshop. Springer, Cham, 2019.` ## Dataset [Ischemic Stroke Lesion Segmentation (ISLES) 2017](http://www.isles-challenge.org/ISLES2017/) ## Dependencies | 3,355 |
pythonpanda2/active-learning-md | ['active learning'] | ['Machine Learning Inter-Atomic Potentials Generation Driven by Active Learning: A Case Study for Amorphous and Liquid Hafnium dioxide'] | workflow/BayesOpt_SOAP.py workflow/activesample.py activesample activesample | ## Active learning workflow for Gaussian Approximation Potential (GAP) Documentation for the active learning workflow developed as a part of the article "Machine Learning Inter-Atomic Potentials Generation Driven by Active Learning: A Case Study for Amorphous and Liquid Hafnium dioxide". __For more details, please refer to the [paper](https://www.nature.com/articles/s41524-020-00367-7).__ If you are using this active learning workflow in your research paper, please cite us as ``` @article{sivaraman2020machine, title={Machine-learned interatomic potentials by active learning: amorphous and liquid hafnium dioxide}, author={Sivaraman, Ganesh and Krishnamoorthy, Anand Narayanan and Baur, Matthias and Holm, Christian and Stan, Marius and Cs{\'a}nyi, G{\'a}bor and Benmore, Chris and V{\'a}zquez-Mayagoitia, {\'A}lvaro}, journal={npj Computational Materials}, | 3,356 |
pytorchbearer/torchbearer | ['data visualization'] | ['Torchbearer: A Model Fitting Library for PyTorch'] | tests/callbacks/test_cutout.py torchbearer/callbacks/mixup.py torchbearer/callbacks/weight_decay.py tests/metrics/test_roc_auc_score.py tests/test_cv_utils.py torchbearer/metrics/timer.py tests/callbacks/test_terminate_on_nan.py torchbearer/callbacks/unpack_state.py tests/callbacks/test_callbacks.py torchbearer/bases.py torchbearer/callbacks/imaging/imaging.py torchbearer/metrics/default.py tests/callbacks/test_init.py torchbearer/callbacks/aggregate_predictions.py torchbearer/metrics/wrappers.py torchbearer/callbacks/imaging/inside_cnns.py tests/callbacks/test_csv_logger.py torchbearer/metrics/__init__.py tests/callbacks/test_unpack_state.py tests/metrics/test_primitives.py torchbearer/trial.py torchbearer/callbacks/tensor_board.py tests/callbacks/test_live_loss_plot.py torchbearer/callbacks/pycm.py setup.py torchbearer/metrics/metrics.py tests/callbacks/test_printer.py torchbearer/callbacks/manifold_mixup.py tests/callbacks/test_weight_decay.py torchbearer/callbacks/early_stopping.py docs/conf.py torchbearer/state.py tests/callbacks/test_aggregate_predictions.py tests/test_end_to_end.py docs/_static/examples/tensorboard.py tests/callbacks/test_mixup.py tests/metrics/test_timer.py torchbearer/callbacks/torch_scheduler.py torchbearer/callbacks/csv_logger.py torchbearer/callbacks/printer.py tests/callbacks/test_pycm.py torchbearer/callbacks/between_class.py torchbearer/metrics/decorators.py tests/callbacks/imaging/test_inside_cnns.py torchbearer/callbacks/gradient_clipping.py tests/metrics/test_wrappers.py torchbearer/callbacks/lsuv.py tests/callbacks/test_torch_scheduler.py torchbearer/callbacks/decorators.py docs/_static/examples/visdom_note.py torchbearer/__init__.py torchbearer/callbacks/callbacks.py tests/test_magics.py torchbearer/cv_utils.py tests/callbacks/test_checkpointers.py tests/test_state.py torchbearer/callbacks/init.py torchbearer/callbacks/label_smoothing.py torchbearer/callbacks/__init__.py torchbearer/callbacks/cutout.py torchbearer/metrics/aggregators.py tests/callbacks/test_manifold_mixup.py torchbearer/metrics/roc_auc_score.py tests/metrics/test_lr.py torchbearer/version.py tests/metrics/test_aggregators.py tests/callbacks/test_tensor_board.py tests/callbacks/test_label_smoothing.py torchbearer/callbacks/terminate_on_nan.py tests/callbacks/test_gradient_clipping.py tests/test_bases.py tests/callbacks/test_sample_pairing.py torchbearer/callbacks/live_loss_plot.py tests/metrics/test_decorators.py torchbearer/metrics/primitives.py torchbearer/magics.py tests/callbacks/test_early_stopping.py tests/metrics/test_metrics.py torchbearer/callbacks/checkpointers.py tests/callbacks/imaging/test_imaging.py torchbearer/callbacks/imaging/__init__.py tests/callbacks/test_decorators.py docs/_static/examples/distributed_data_parallel.py torchbearer/metrics/lr.py torchbearer/callbacks/sample_pairing.py tests/callbacks/test_between_class.py tests/test_trial.py tests/metrics/test_default.py sync ToyModel worker setup cleanup average_gradients sync_model grad flatten SimpleModel SimpleModel TestCallback TestApexCrit TestBaseCrit TestMetric TestCVUtils TestEndToEnd Net loss NetWithState TestMagics TestStateKey TestState TestTrialValEvalPred TestWithClosureAndLoader TestMockOptimizer TestWithGenerators _StateMaker TestTrialFunctions TestWithData TestRun TestCallbackListInjection TestTestPass TestFitPass TestTrialMembers TestReplay TestAggregatePredictions TestBCPlus TestCallbackList TestModelCheckpoint TestMostRecent TestCheckpointer TestInterval TestBest TestCSVLogger TestCutOut TestDecorators TestEarlyStopping TestGradientClipping TestGradientNormClipping TestSimpleInits TestWeightInit TestLsuv TestLabelSmoothingRegularisation TestLiveLossPlot TestModule TestManifoldMixup TestModule2 TestModel TestMixupAcc TestMixupInputs TestFormatMetrics TestConsolePrinter TestTqdm TestPyCM TestHandlers TestSamplePairing TestTensorbardText TestTensorBoardImages TestTensorBoardProjector TestTensorBoard TestTerminateOnNaN TestReduceLROnPlateau TestCosineAnnealingLR TestMultiStepLR TestExponentialLR TestCyclicLR TestTorchScheduler TestStepLR TestLambdaLR TestUnpackState TestWeightDecay TestFromState TestHandlers TestImagingCallback TestCachingImagingCallback TestMakeGrid TestClassAppearanceModel TestRunningMetric TestStd TestRunningMean TestVar TestMean TestDecorators TestDefaultAccuracy TestLR TestAdvancedMetric TestMetricList TestMetricTree TestMeanSquaredError TestCategoricalAccuracy TestBinaryAccuracy TestLoss TestEpoch TestTopKCategoricalAccuracy TestRocAucScore TestTimer TestTimerMetric TestBatchLambda TestEpochLambda TestToDict cite apex_closure no_grad _forward_with_exceptions _get_param_list set_doc _patch_call Metric base_closure enable_grad get_metric Callback train_valid_splitter DatasetValidationSplitter SubsetDataset get_train_valid_sets is_notebook torchbearer set_notebook State state_key StateKey get_printer load_batch_predict update_device_and_dtype deep_to load_batch_infinite load_batch_none inject_callback Trial inject_sampler load_batch_standard inject_printer MockModel get_default MockOptimizer CallbackListInjection AggregatePredictions BCPlus CallbackList ModelCheckpoint Interval Best MostRecent _Checkpointer CSVLogger RandomErase Cutout BatchCutout CutMix on_criterion on_step_validation LambdaCallback on_start_epoch count_args on_sample bind_to only_if on_init on_step_training on_checkpoint once on_forward_validation on_end once_per_epoch on_criterion_validation on_sample_validation on_start_validation on_start on_end_validation on_start_training add_to_loss on_backward on_end_training on_forward on_end_epoch EarlyStopping GradientNormClipping GradientClipping ZeroBias LsuvInit WeightInit KaimingNormal XavierNormal KaimingUniform XavierUniform LabelSmoothingRegularisation LiveLossPlot no_print LSUV _mixup ManifoldMixup _mixup_inputs MixupAcc Mixup ConsolePrinter Tqdm _format_metrics _to_pyplot PyCM SamplePairing VisdomParams get_writer TensorBoard AbstractTensorBoard TensorBoardText TensorBoardImages TensorBoardProjector close_writer TerminateOnNaN ExponentialLR StepLR TorchScheduler LambdaLR MultiStepLR ReduceLROnPlateau CosineAnnealingLR CyclicLR UnpackState WeightDecay L1WeightDecay L2WeightDecay _to_pyplot FromState ImagingCallback _cache_images _to_file _to_tensorboard _to_visdom MakeGrid CachingImagingCallback _CAMWrapper ClassAppearanceModel _cam_loss RunningMean RunningMetric Std Var Mean var default_for_key std _wrap_and_add_to_tree lambda_metric running_mean mean to_dict DefaultAccuracy _get_lr LR super AdvancedMetric MetricList add_default get_default MetricTree super TopKCategoricalAccuracy MeanSquaredError BinaryAccuracy CategoricalAccuracy Loss Epoch RocAucScore super TimerMetric _TimerMetric super BatchLambda ToDict EpochLambda master init_process_group destroy_process_group data get_world_size all_reduce parameters float data get_world_size all_reduce parameters float sync_model average_gradients view SGD DataLoader run setup with_train_generator cleanup DDP Trial node DistributedSampler rank hash to next CrossEntropyLoss format MNIST print parameters isinstance exc_info format warn int randperm floor train_valid_splitter TensorDataset isinstance set_notebook getargspec Tqdm Callback list isinstance range to is_tensor is_floating_point len next deep_to next deep_to items list dtype isinstance Interval Best str sorted list join OrderedDict rounder keys Blues VisdomParams join SummaryWriter Visdom add VisdomWriter makedirs discard close join join isclass __name__ add_child isclass child_func MetricTree __name__ append param_groups isclass metric | **Note:** We're moving to PyTorch Lightning! Read about the move [here](https://medium.com/pytorch/pytorch-frameworks-unite-torchbearer-joins-pytorch-lightning-c588e1e68c98). From the end of February, torchbearer will no longer be actively maintained. We'll continue to fix bugs when they are found and ensure that torchbearer runs on new versions of pytorch. However, we won't plan or implement any new functionality (if there's something you'd like to see in a training library, consider creating an issue on [PyTorch Lightning](https://github.com/PyTorchLightning/pytorch-lightning)). <img alt="logo" src="https://raw.githubusercontent.com/pytorchbearer/torchbearer/master/docs/_static/img/logo_dark_text.svg?sanitize=true" width="100%"/> [](https://badge.fury.io/py/torchbearer) [](https://www.python.org/) [](https://pytorch.org/) [](https://travis-ci.com/pytorchbearer/torchbearer) [](https://codecov.io/gh/pytorchbearer/torchbearer) [](https://torchbearer.readthedocs.io/en/latest/?badge=latest) [](https://pepy.tech/project/torchbearer) <p align="center"> <a href="http://pytorchbearer.org">Website</a> • <a href="https://torchbearer.readthedocs.io/en/latest/">Docs</a> • <a href="#examples">Examples</a> • <a href="#install">Install</a> • <a href="#citing">Citing</a> • | 3,357 |
q1park/spacetime | ['causal inference'] | ['Moment-Matching Graph-Networks for Causal Inference'] | spacetime/simulate.py spacetime/sampler.py spacetime/models.py spacetime/losses.py spacetime/__init__.py spacetime/trainers.py spacetime/constraint.py spacetime/utils.py spacetime/metrics.py spacetime/optimizers.py spacetime/spacetime.py InductiveCausation MutualInformationTest RobustRegressionTest _listprod _cond_diag ELBOLoss InteractionLoss LagrangianLoss InfoLoss _kernel Losses _cond_cross count_accuracy compute_BiCScore binary_accuracy compute_local_BiCScore adjacency_error GraphVector clones LayerNorm SublayerConnection SEMCAE GraphMatrix EmbedBlock AttentionBlock DAGGAE DAGGNN LinearBlock PositionalEncoding Coefficients OptimModule Control OptimGen OptimGraph KDE PDFVisualizer Histogram SCalculator Simulator SpaceTime NodeData Validator DAGTrainer SEMTrainer check_nan print_format Parameters ortho_norm plot_graphs ModelStore torch_pad row_norm logger_stats plot_conditionals plot_trials Logger plot_marginals plot_joints rand_norm mean float expand reversed matmul enumerate inverse _kernel inverse _kernel T setdiff1d concatenate tril intersect1d float max flatnonzero len sum eq append range compute_local_BiCScore where values tuple log dict sum prod range amax items list sum rand_norm show subplots zip plot_loggers len show models subplots plot_temp zip len items list subplots set_title len contour enumerate items list subplots set_title len contour enumerate subplots set_title plot nodes legend zip enumerate len items list str map log10 dict recall keys list | ## Conditional Moment-Matching Graph-Neural-Networks (CMM-GNN) #### Reference: https://arxiv.org/abs/2007.10507 #### Enables: ###### State of the art Directed Acyclic Graph (DAG) structure learning ###### Accurate interventional sampling of non-linear structural equation models (SEM's) #### Includes PyTorch implementations of: ###### DAG-NOTEARS: https://arxiv.org/abs/1803.01422 ###### DAG-GNN: https://arxiv.org/abs/1904.10098 ###### GAE: https://arxiv.org/abs/1911.07420 ###### CMM Loss Function: https://arxiv.org/abs/1606.04218 | 3,358 |
qGentry/MetaBiLSTM | ['word embeddings', 'part of speech tagging', 'morphological tagging'] | ['Morphosyntactic Tagging with a Meta-BiLSTM Model over Context Sensitive Token Encodings'] | src/meta_bilstm/train_utils/trainer.py src/meta_bilstm/models/char_model.py src/meta_bilstm/nn_utils/losses.py src/meta_bilstm/utils/preprocessing.py src/meta_bilstm/utils/dataset.py setup.py src/meta_bilstm/models/word_model.py src/meta_bilstm/meta_wrapper.py src/meta_bilstm/bin/train_model.py src/meta_bilstm/models/meta_model.py main ModelWrapper main CharBiLSTM CharEmbeddings MetaBiLSTM WordPretrainedEmbbedings WordEmbeddingLayer WordBiLSTM WordTrainableEmbeddings seq_loss calc_accuracy Trainer PosTagDataset _collate_fn create_dataloader Preprocessor setup train_model add_argument Trainer ArgumentParser device parse_args train_data range len sum append len DataLoader | # MetaBiLSTM Pure pytorch implementation of Meta BiLSTM sequence tagger from this paper https://arxiv.org/pdf/1805.08237v1.pdf | 3,359 |
qarchli/pytorch-gan-for-outlier-detection | ['outlier detection', 'active learning'] | ['Generative Adversarial Active Learning for Unsupervised Outlier Detection'] | utils.py train.py main.py model.py Generator Discriminator parse_args load_data plot RunBuilder add_argument ArgumentParser pop format reset_index read_table astype int32 values show str savefig linspace legend len | # pytorch-gan-for-outlier-detection ## Overview This is the PyTorch Implementation of this paper: [Generative Adversarial Active Learning for Unsupervised Outlier Detection](https://arxiv.org/abs/1809.10816) by Yezheng Liu, Zhe Li, Chong Zhou, Yuanchun Jiang, Jianshan Sun, Meng Wang and Xiangnan He. This repository also corresponds to the code for the post I have written on [Generative Adversarial Networks for Unsupervised Outlier Detection](https://qarchli.github.io/2020-04-12-gans-for-outlier-detection/). ## Dependencies Install the requirements using this command: ```bash sudo pip install -r requirements.txt ``` | 3,360 |
qcappart/ROD_oracle | ['combinatorial optimization'] | ['How to Evaluate Machine Learning Approaches for Combinatorial Optimization: Application to the Travelling Salesman Problem'] | oracle.py concorde_translater.py dataset.py retrieve_concorde_output call_concorde_solver create_concorde_input DataReader compute_tour_nodes display_current_situation compute_tour_length astype call devnull open array shape range str plot pause title clf append range len max list cost_multiplier display display_current_situation len create_concorde_input delete choice dict call_concorde_solver retrieve_concorde_output append zeros sum array range temp_file_path | # ROD_oracle Parametrized oracle for computing the ROD (ratio of optimal decisions). Implementation related to "How to Evaluate Machine Learning Approaches for Combinatorial Optimization: Application to the Travelling Salesman Problem"  ## Requirements Python 3.5+ Numpy 1.15 Scipy 1.1 Matplotlib 3.0 Tqdm You will also need to install [Concorde](http://www.math.uwaterloo.ca/tsp/concorde.html) to use the oracle. To work with the code, the solver code must be downloaded and placed at the project root. After compiling it, the executable for the TSP concorde solver should be found at `./concorde/TSP/concorde` if you are located at the project root. | 3,361 |
qianguih/RSNet | ['semantic segmentation'] | ['Recurrent Slice Networks for 3D Segmentation of Point Clouds'] | train.py data/utils/data_prep_util.py data/utils/eulerangles.py data/utils/indoor3d_util.py data/utils/plyfile.py layers/slice_pool_layer/slice_pool_layer.py layers/slice_pool_layer/build.py layers/slice_unpool_layer/slice_unpool_layer.py data/utils/tf_util.py eval_iou_accuracy.py net.py data/utils/pc_util.py data/gen_indoor3d_h5.py data/collect_indoor3d_data.py load_data.py utils.py layers/slice_unpool_layer/build.py load_obj gen_slice_idx gen_slice_idx_routine loadDataFile load_h5 iterate_data RSNet repackage_hidden AverageMeter accuracy avg_class_acc save_checkpoint adjust_learning_rate insert_batch load_ply_normal pad_arr_rows batch_mkdir save_h5_data_label_normal load_h5_data_label_normal load_h5_data_label_seg get_sampling_command load_h5 get_category_names save_h5 load_ply_data get_obj_filenames export_ply quat2euler euler2quat mat2euler angle_axis2euler euler2angle_axis euler2mat collect_point_label point_label_to_obj room2blocks_plus_normalized room2samples_wrapper_normalized sample_data room2samples_plus_normalized room2blocks_wrapper room2blocks room2blocks_wrapper_normalized room2samples room2blocks_plus sample_data_label write_ply pyplot_draw_point_cloud draw_point_cloud read_ply point_cloud_three_views_demo point_cloud_to_volume pyplot_draw_volume point_cloud_to_volume_batch point_cloud_three_views volume_to_point_cloud _open_stream _lookup_type PlyData _split_line PlyProperty PlyParseError make2d PlyListProperty PlyElement batch_norm_template batch_norm_for_conv1d conv2d_transpose dropout fully_connected conv3d batch_norm_for_conv2d batch_norm_for_fc avg_pool2d conv2d conv1d avg_pool3d max_pool3d max_pool2d _variable_with_weight_decay batch_norm_for_conv3d _variable_on_cpu SP Slice_Pool Slice_Unpool SU readlines close len zeros range open zeros range gen_slice_idx_routine ones int float range File int list transpose min astype shuffle copy floor float range copyfile save param_groups max topk size t eq mul_ expand_as append sum max range str format print save_h5 zeros PlyData write range join print join len join mkdir File close create_dataset File close create_dataset File File read array read array append array cos sin eps asarray atan2 sqrt flat cos sin angle_axis2mat join concatenate ones loadtxt glob print exit write close save append range open loadtxt write astype close range open choice sample_data int uniform ceil expand_dims sample_data_label range append len uint8 astype print load exit loadtxt uint8 astype room2blocks zeros max range print load exit loadtxt int arange min shuffle choice ceil zeros float range uint8 astype room2samples zeros max range print load exit loadtxt squeeze point_cloud_to_volume flatten append expand_dims range zeros float astype append vstack array range data read array write array describe int exp abs transpose min mean sqrt argsort round argwhere zeros sum max range euler2mat concatenate draw_point_cloud fromarray uint8 read_ply save point_cloud_three_views set_xlabel add_subplot scatter set_ylabel figure set_zlabel pyplot_draw_point_cloud volume_to_point_cloud append split dtype len property hasattr property property property multiply add_to_collection xavier_initializer _variable_on_cpu l2_loss truncated_normal_initializer | # Introduction This is the official inplementation of [Recurrent Slice Networks for 3D Segmentation on Point Clouds](https://arxiv.org/abs/1802.04402) (RSNet), which is going to appear in CVPR 2018. RSNet is a powerful and conceptually simple network for 3D point cloud segmentation tasks. It is fast and memory-efficient. In this repository, we release codes for training a RSNet on the S3DIS segmentation dataset. Training on other datasets can be easily achieved by following the same process. # Citation If you find our work useful in your research, please consider citing: @article{huang2018recurrent, title={Recurrent Slice Networks for 3D Segmentation on Point Clouds}, author={Huang, Qiangui and Wang, Weiyue and Neumann, Ulrich}, journal={arXiv preprint arXiv:1802.04402}, year={2018} | 3,362 |
qianlinjun/delf-pytorch | ['image retrieval'] | ['Large-Scale Image Retrieval with Attentive Deep Local Features'] | utils/__init__.py utils/logger.py helper/feeder.py extract/folder.py train/config.py helper/matcher.py helper/__init__.py train/delf.py train/solver.py train/dataloader.py helper/delf_helper.py train/layers.py utils/misc.py extract/extractor.py train/main.py extract/pca.py __to_tensor__ __is_cuda__ FeatureExtractor __build_delf_config__ __cuda__ __to_var__ DatasetFolder find_classes make_dataset ImageFolder accimage_loader default_loader has_file_allowed_extension pil_loader DelfPCA nms CalculateKeypointCenters GetDelfFeatureFromSingleScale GetDelfFeatureFromMultiScale GenerateCoordinates PrintResult DelfFeaturePostProcessing CalculateReceptiveBoxes ApplyPcaAndWhitening PrintGpuMemoryStats Feeder __build_delf_config__ __cuda__ get_ransac_image_byte read_image get_inliers load_image_into_numpy_array get_attention_image_byte str2bool get_loader __freeze_weights__ __load_weights_from__ __print_freeze_status__ __cuda__ __deep_copy_module__ __unfreeze_weights__ Delf_V1 WeightedSum2d Reshape SpatialAttention2d ConcatTable CMul Identity Flatten main __to_tensor__ __is_cuda__ __cuda__ __to_var__ Solver plot_overlap savefig Logger LoggerMonitor AverageMeter mkdir_p compute_precision_top_k is_available parse_known_args add_argument print ArgumentParser lower sort join sorted has_file_allowed_extension append expanduser listdir walk stack repeat floor arange GenerateCoordinates cat FloatTensor index_select transpose matmul div float narrow nms CalculateKeypointCenters PrintResult index_select uniform __concat_tensors_in_list__ print format max_memory_cached max_memory_allocated print int ones_like view upsample size clamp squeeze t DelfFeaturePostProcessing index_select CalculateReceptiveBoxes round forward_for_serving norm CalculateKeypointCenters squeeze div ApplyPcaAndWhitening expand_as mul sort new clamp index_select resize_as_ long size convert astype uint8 cKDTree query array ransac fromarray uint8 format BytesIO print astype dstack shape save BytesIO plot_matches COLOR_BGR2RGB inverted axis close transformed getvalue DMatch KeyPoint drawMatches savefig tostring get_inliers append sum cvtColor column_stack CenterCrop ToTensor Compose Resize RandomCrop ImageFolder DataLoader RandomHorizontalFlip append parameters enumerate parameters enumerate str requires_grad format named_children print parameters enumerate print format load_state_dict print deepcopy format named_children cuda gpu_id seed finetune_epoch range manual_seed_all train_path_for_pretraining format keypoint_sample_size finetune_sample_size finetune_crop_size manual_seed is_available float train_path_for_finetuning keypoint_epoch keypoint_crop_size print manualSeed get_loader randint train Solver Delf_V1 asarray arange plot numbers enumerate len topk size t eq mul_ expand_as append sum max makedirs | <<<<<<< HEAD # Pytorch Implementation of Deep Local Feature (DeLF) PyTorch Implementation of "Large-Scale Image Retrieval with Attentive Deep Local Features" reference: https://arxiv.org/pdf/1612.06321.pdf ## Prerequisites + PyTorch + python3 + CUDA ## Training DeLF There are 2 steps for DeLF training: (1) finetune stage, and (2) keypoint stage. | 3,363 |
qiaott/AncientPainitng2NaturalImage | ['style transfer'] | ['Ancient Painting to Natural Image: A New Solution for Painting Processing'] | options/train_options.py data/image_folder.py data/aligned_dataset.py image-preprocessing/main.py data/custom_dataset_data_loader.py models/cycle.py data/data_loader.py train.py models/networks_/resnet.py util/image_pool.py util/png.py util/get_data.py models/base_model.py models/net.py models/models.py models/lr_scheduler.py util/html.py data/base_data_loader.py models/DSTN.py options/base_options.py test.py data/base_dataset.py image-preprocessing/config.py image-preprocessing/file_function.py image-preprocessing/augmentation.py models/networks_/__init__.py util/util.py models/cyclegan.py models/networks.py models/test_model.py data/unaligned_dataset.py data/single_dataset.py options/test_options.py util/visualizer.py AlignedDataset BaseDataset get_transform __scale_width BaseDataLoader CustomDatasetDataLoader CreateDataset CreateDataLoader is_image_file ImageFolder default_loader make_dataset SingleDataset UnalignedDataset random_brightness random_crop random_contrast random_rotation resize_images count_each_class create_train_val_split aug_train is_image get_split_info class_info print_all_imgs read_all_imgs train_mean train_std check_and_mkdir return_phase BaseModel CycleGANModel CycleGANModel DSTN create_model var UpsampleConvLayer Vgg16 subtract_imagenet_mean_batch init_vgg16 MultConst UpBasicblock preprocess_batch Bottleneck image_content_pre ConvLayer Net gram_matrix softmax Basicblock UpBottleneck GramMatrix Inspiration get_norm_layer GANLoss ResnetGenerator weights_init_orthogonal ResnetBlock weights_init_normal weights_init_xavier define_D UnetGenerator define_G init_weights UnetSkipConnectionBlock get_scheduler print_network NLayerDiscriminator weights_init_kaiming TestModel ResNet Bottleneck cfg conv3x3 resnet BasicBlock BaseOptions TestOptions TrainOptions GetData HTML ImagePool encode tensor2im_ print_numpy varname diagnose_network mkdirs mkdir info save_image tensor2im Visualizer fineSize print Lambda Scale RandomCrop BICUBIC RandomHorizontalFlip append phase int size initialize name UnalignedDataset print AlignedDataset SingleDataset CustomDatasetDataLoader name print initialize is_image_file join sorted append walk uniform randint shape len warpAffine flatten mean getRotationMatrix2D randrange append range print sep walk is_image print makedirs str format is_image print shape sep imread walk imwrite is_image print resize sep check_and_mkdir imread walk walk format is_image print append sep walk imwrite is_image print val_num walk class_info sep check_and_mkdir imread return_phase print count_each_class sep str imwrite is_image print random_rotation splitext sep walk imread range list is_image map sep walk imread range list is_image map sqrt sep walk imread range initialize CycleGANModel model print name TestModel DSTN transpose chunk cat Variable size FloatTensor join Vgg16 print load_lua system parameters save zip state_dict expand_as preprocess_batch subtract_imagenet_mean_batch bmm size transpose view data uniform constant __name__ data constant xavier_normal uniform __name__ data constant uniform __name__ kaiming_normal data constant print orthogonal uniform __name__ print apply BatchNorm2d partial InstanceNorm2d LambdaLR ReduceLROnPlateau StepLR get_norm_layer ResnetGenerator UnetGenerator init_weights cuda init_weights NLayerDiscriminator cuda get_norm_layer print parameters print ResNet cfg load_url load_state_dict transpose numpy tile numpy tile print parameters fromarray save print join search print float64 flatten astype mkdir makedirs | # AncientPainitng2NaturalImage Pytorch implementation for the paper [[Ancient Painting to Natural Image: A New Solution for Painting Processing]](https://arxiv.org/pdf/1901.00224.pdf) .  ## Getting Started ### Installation - Install PyTorch and dependencies from http://pytorch.org - Install Torch vision from the source. ```bash git clone https://github.com/pytorch/vision cd vision | 3,364 |
qidiso/mobilefacenet-V2 | ['face verification'] | ['MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices'] | symbol_utils.py fmobilefacenet.py get_symbol DResidual Residual ConvOnly Act Conv Linear get_fc1 get_head Act Conv residual_unit_v3 LeakyReLU Convolution Act BatchNorm Convolution BatchNorm Convolution Conv Linear DResidual range get DResidual Residual FullyConnected Variable Conv BatchNorm Linear Pooling FullyConnected print Act BatchNorm Flatten Dropout get _set_attr Act Conv BatchNorm Pooling Act min Conv BatchNorm residual_unit_v3 | # mobilefacenet-V2 now we get more higher accuray: [lfw][12000]Accuracy-Flip: 0.99667+-0.00358 [agedb_30][12000]Accuracy-Flip: 0.96667+-0.00167 use my modified mobilenet network. lr-batch-epoch: 0.01 11738 1 testing verification.. (12000, 512) infer time 39.129495 [lfw][36000]XNorm: 22.729305 [lfw][36000]Accuracy-Flip: 0.99667+-0.00358 | 3,365 |
qijiezhao/pseudo-3d-pytorch | ['action recognition', 'video classification'] | ['Learning Spatio-Temporal Representation with Pseudo-3D Residual Networks'] | p3d_model.py downsample_basic_block conv_T get_optim_policies Bottleneck P3D131 conv_S P3D63 P3D199 P3D data isinstance FloatTensor Variable zero_ avg_pool3d cuda cat P3D P3D load_state_dict P3D int list isinstance BatchNorm3d len exit extend parameters modules info append BatchNorm2d Linear | # Pseudo-3D Residual Networks This repo implements the network structure of P3D[1] with PyTorch, pre-trained model weights are converted from caffemodel, which is supported from the [author's repo](https://github.com/ZhaofanQiu/pseudo-3d-residual-networks) ### Requirements: - pytorch - numpy ### Structure details In the author's official repo, only P3D-199 is released. Besides this deepest P3D-199, I also implement P3D-63 and P3D-131, which are respectively modified from ResNet50-3D and ResNet101-3D, the two nets may bring more convenience to users who have only memory-limited GPUs. ### Pretrained weights (Pretrained weights of P3D63 and P3D131 are not yet supported) (tips: I feel sorry to canceal the download urls of pretrained weights because of some private reasons. For more information you could send emails to me.) | 3,366 |
qingyu95/ICDAR2017-DATASET | ['optical character recognition'] | ['PP-OCR: A Practical Ultra Lightweight OCR System'] | ppocr/modeling/backbones/rec_mobilenet_v3.py tools/infer/predict_system.py ppocr/utils/save_load.py ppocr/modeling/heads/rec_srn_all_head.py deploy/pdserving/ocr_local_server.py ppocr/data/det/sast_process.py ppocr/data/det/db_process.py ppocr/data/rec/text_image_aug/augment.py ppocr/data/cls/__init__.py ppocr/modeling/heads/rec_attention_head.py deploy/pdserving/rec_web_client.py deploy/pdserving/clas_rpc_server.py ppocr/modeling/losses/det_db_loss.py ppocr/modeling/heads/cls_head.py tools/export_model.py deploy/pdserving/rec_rpc_server.py tools/eval.py tools/infer/predict_det.py ppocr/utils/__init__.py deploy/pdserving/clas_web_client.py deploy/hubserving/ocr_system/module.py tools/eval_utils/eval_det_utils.py ppocr/data/det/dataset_traversal.py deploy/hubserving/ocr_det/params.py ppocr/modeling/__init__.py deploy/slim/prune/export_prune_model.py ppocr/data/det/make_shrink_map.py deploy/hubserving/ocr_det/module.py ppocr/modeling/heads/rec_ctc_head.py ppocr/utils/character.py tools/infer_det.py ppocr/postprocess/east_postprocess.py setup.py tools/infer/predict_cls.py ppocr/modeling/losses/rec_srn_loss.py ppocr/modeling/heads/__init__.py ppocr/data/det/east_process.py ppocr/modeling/backbones/det_mobilenet_v3.py ppocr/postprocess/lanms/__main__.py deploy/pdserving/params.py ppocr/modeling/common_functions.py ppocr/optimizer.py tools/test_hubserving.py ppocr/utils/check.py deploy/slim/quantization/export_model.py ppocr/data/rec/dataset_traversal.py ppocr/postprocess/locality_aware_nms.py tools/infer/predict_rec.py deploy/hubserving/ocr_system/params.py ppocr/postprocess/lanms/__init__.py ppocr/postprocess/db_postprocess.py deploy/pdserving/det_web_client.py ppocr/__init__.py ppocr/modeling/backbones/det_resnet_vd_sast.py ppocr/data/cls/dataset_traversal.py deploy/pdserving/rec_local_server.py deploy/slim/quantization/quant.py ppocr/data/det/make_border_map.py ppocr/data/cls/randaugment.py deploy/pdserving/det_rpc_server.py ppocr/modeling/backbones/__init__.py tools/eval_utils/eval_cls_utils.py deploy/hubserving/ocr_rec/module.py ppocr/data/__init__.py ppocr/modeling/losses/__init__.py ppocr/modeling/heads/self_attention/model.py ppocr/modeling/losses/det_east_loss.py ppocr/modeling/backbones/rec_resnet_fpn.py ppocr/modeling/backbones/rec_resnet_vd.py tools/train.py ppocr/modeling/losses/rec_ctc_loss.py ppocr/data/reader_main.py deploy/pdserving/clas_local_server.py ppocr/modeling/heads/rec_seq_encoder.py ppocr/modeling/architectures/det_model.py ppocr/data/det/random_crop_data.py tools/eval_utils/eval_rec_utils.py ppocr/data/det/data_augment.py ppocr/modeling/heads/det_sast_head.py ppocr/modeling/heads/det_east_head.py __init__.py tools/infer_rec.py tools/inference_to_serving.py ppocr/utils/utility.py ppocr/modeling/stns/__init__.py ppocr/modeling/backbones/det_resnet_vd.py ppocr/modeling/losses/det_basic_loss.py deploy/pdserving/ocr_web_client.py ppocr/postprocess/sast_postprocess.py paddleocr.py ppocr/modeling/losses/cls_loss.py ppocr/modeling/losses/rec_attention_loss.py train_data/my_gen.py ppocr/modeling/architectures/cls_model.py ppocr/data/rec/text_image_aug/warp_mls.py tools/infer/utility.py ppocr/modeling/architectures/__init__.py ppocr/modeling/losses/det_sast_loss.py ppocr/modeling/stns/tps.py tools/eval_utils/eval_det_iou.py deploy/pdserving/ocr_rpc_server.py ppocr/postprocess/lanms/.ycm_extra_conf.py tools/program.py train_data/gen_label.py ppocr/modeling/heads/det_db_head.py tools/eval_utils/__init__.py deploy/slim/prune/sensitivity_anal.py tools/infer_cls.py ppocr/data/rec/__init__.py ppocr/modeling/architectures/rec_model.py deploy/hubserving/ocr_rec/params.py ppocr/utils/stats.py deploy/pdserving/det_local_server.py ppocr/data/rec/img_tools.py deploy/slim/prune/pruning_and_finetune.py main PaddleOCR download_with_progressbar parse_args maybe_download readme OCRDet Config read_params OCRRec Config read_params OCRSystem Config read_params TextClassifierHelper OCRService TextClassifierHelper OCRService cv2_to_base64 DetService TextDetectorHelper DetService TextDetectorHelper cv2_to_base64 TextSystemHelper OCRService TextSystemHelper OCRService cv2_to_base64 Config read_params TextRecognizerHelper OCRService TextRecognizerHelper OCRService cv2_to_base64 main main eval_function main get_pruned_params main set_paddle_flags main set_paddle_flags get_optimizer pact cosine_decay_with_warmup RMSProp AdamDecay _reader_quit reader_main _term_group random_crop SimpleReader RandAugment RawRandAugment TrainReader EvalTestReader AugmentData DBProcessTrain DBProcessTest EASTProcessTrain EASTProcessTest MakeBorderMap extend_line draw_border_map _distance validate_polygons polygon_area MakeShrinkMap crop_area random_select is_poly_outside_rect is_poly_in_rect RandomCropData split_regions region_wise_random_select SASTProcessTrain SASTProcessTest SimpleReader LMDBReader Config blur process_image get_warpR srn_other_inputs flag rad get_warpAffine process_image_srn add_gasuss_noise get_img_data jitter resize_norm_img get_bounding_box_rect get_crop warp resize_norm_img_chinese resize_norm_img_srn cvtColor tia_perspective tia_distort tia_stretch WarpMLS deconv_bn_layer conv_bn_layer create_tmp_var get_para_bias_attr ClsModel DetModel RecModel MobileNetV3 ResNet ResNet MobileNetV3 ResNet ResNet ClsHead DBHead EASTHead SASTHead AttentionPredict CTCPredict EncoderWithReshape SequenceEncoder EncoderWithRNN SRNPredict pre_post_process_layer prepare_encoder wrap_encoder wrap_encoder_forFeature multi_head_attention wrap_layer_with_block positionwise_feed_forward encoder encoder_layer prepare_decoder ClsLoss MaskL1Loss DiceLoss BalanceLoss DBLoss EASTLoss SASTLoss AttentionLoss CTCLoss SRNLoss GridGenerator TPS LocalizationNetwork DBPostProcess EASTPostPocess intersection_iog standard_nms nms standard_nms_inds nms_locality intersection soft_nms weighted_merge SASTPostProcess GetCompilationInfoForFile IsHeaderFile MakeRelativePathsInFlagsAbsolute FlagsForFile DirectoryOfThisScript merge_quadrangle_n9 convert_rec_attention_infer_res cal_predicts_accuracy_srn convert_rec_label_to_lod CharacterOps cal_predicts_accuracy check_config_params save_model init_model _mkdir_if_not_exist load_params _load_state Time SmoothedValue TrainingStats check_and_read_gif get_check_reader_params initial_logger get_image_file_list get_check_global_params create_module main set_paddle_flags main set_paddle_flags parse_args main set_paddle_flags draw_det_res main set_paddle_flags main set_paddle_flags build_export train_eval_det_run merge_config build create_multi_devices_program preprocess ArgsParser check_gpu train_eval_rec_run AttrDict load_config train_eval_cls_run cv2_to_base64 main draw_server_result main set_paddle_flags test_reader cal_cls_acc eval_cls_run DetectionIoUEvaluator load_label_infor eval_det_run cal_det_metrics cal_det_res eval_rec_run test_rec_benchmark main TextClassifier TextDetector main TextRecognizer main sorted_boxes TextSystem resize_img str_count draw_text_det_res draw_boxes draw_ocr create_predictor base64_to_cv2 parse_args draw_ocr_box_txt text_visual gen_det_label gen_rec_label get int error close exit tqdm join remove format print download_with_progressbar makedirs add_argument ArgumentParser format print error image_dir ocr PaddleOCR get_image_file_list parse_args Config Executor build_export load_model save_inference_model makedirs clone preprocess run config init_model get_ratios_by_loss Pruner CharacterOps set_sample_list_generator train_eval_rec_run opt load_config list prune train_eval_det_run build merge_config reader_main create_multi_devices_program info keys pop flops Program check_gpu global_scope load_sensitivities append name all_parameters eval_det_run sensitivity eval_function get_pruned_params dict str list items eval_rec_run eval_det_run convert quant_aware LayerHelper ParamAttr elementwise_sub relu elementwise_add create_parameter fill_constant create_global_var _decay_step_counter get cosine_decay_with_warmup Adam cosine_decay piecewise_decay get piecewise_decay cosine_decay print exit format getpgid print getpgrp killpg SIGKILL getpid update deepcopy function append range randint shape may_augment_annotation augment_image to_deterministic fillPoly _distance area broadcast_to fmax AddPath max clip length JT_ROUND range ET_CLOSEDPOLYGON power PyclipperOffset Polygon reshape min zeros array nan_to_num sqrt square tuple line zeros draw_border_map range len range clip polygon_area len range PyclipperOffset Polygon ones length fillPoly min area power JT_ROUND reshape len validate_polygons zeros AddPath max range ET_CLOSEDPOLYGON Execute array array append range min max clip choice int list min choice append max len random_select min astype shape int32 split_regions zeros max range region_wise_random_select int dtype crop_area zip min tolist resize append zeros array min max int transpose astype resize ceil zeros float int transpose astype resize ceil zeros max frombuffer imdecode COLOR_HSV2BGR random COLOR_BGR2HSV flag shape int min random copy shape range normal uint8 clip shape int min copy shape randint int max tan rad min float32 dot sqrt getPerspectiveTransform zeros array array float32 anglez Config blur tia_distort color shape reverse add_gasuss_noise jitter stretch get_crop crop perspective make distort tia_stretch noise randint tia_perspective cvtColor format append resize_norm_img resize_norm_img_chinese reshape info encode warp get_beg_end_flag_idx len asarray COLOR_BGR2GRAY shape resize zeros cvtColor int ones reshape astype tile reshape resize_norm_img_srn srn_other_inputs array encode get_char_num range len list WarpMLS arange generate append list WarpMLS arange generate append randint append list WarpMLS generate sqrt ParamAttr L2Decay Uniform conv2d conv2d_transpose scaled_dot_product_attention fc __combine_heads __split_heads_qkv __compute_qkv fc dropout layer_norm dropout embedding cast scale embedding scale post_process_layer positionwise_feed_forward multi_head_attention pre_process_layer encoder_layer range pre_process_layer prepare_encoder shape encoder encoder prepare_decoder topk sigmoid_cross_entropy_with_logits reshape min square reduce_sum reduce_mean cast DiceLoss MaskL1Loss cross_entropy reduce_sum reduce_mean abs reduce_sum reshape area buffer Polygon print reshape area Polygon append array append array append array exp arange copy intersection range append weighted_merge append join startswith IsHeaderFile compiler_flags_ exists compiler_flags_ GetCompilationInfoForFile compiler_working_dir_ MakeRelativePathsInFlagsAbsolute DirectoryOfThisScript nms_impl array copy reshape range decode len append int get_char_num range list reshape append array range len list reshape append array range len makedirs join basename load_program_state mkdtemp copy rmtree normpath exists update list format blocks set set_program_state shape warning info _load_state all_parameters get load format info load_params exists format save info basicConfig getLogger import_module getattr split append join listdir isdir COLOR_GRAY2RGB VideoCapture read info cvtColor test_rec_benchmark eval_cls_run append next range items array len join basename imwrite format polylines reshape dirname info makedirs get load dirname decode argmax get_char_num int64 astype mean reshape float32 load merge_config splitext open update items list split enumerate error exit sorted BuildStrategy with_data_parallel CompiledProgram ExecutionStrategy update time format eval_det_run save_model TrainingStats len log mean start info run array range makedirs save_model log cal_predicts_accuracy run eval_rec_run list cal_predicts_accuracy_srn apply range update format mean start zip info time TrainingStats makedirs dict array len save_model log run list apply range update format mean start zip eval_cls_run info time TrainingStats makedirs dict array len config merge_config check_gpu CharacterOps Program info parse_args opt load_config fromarray list COLOR_BGR2RGB draw_boxes draw_ocr array info append imread keys range cvtColor len join read time imwrite basename post float draw_server_result warning summary train_eval_cls_run time format reader_main info train_reader len concatenate cal_cls_acc len append array range run zip update deepcopy dirname makedirs load_label_infor combine_results evaluate_image append DetectionIoUEvaluator cal_det_metrics cal_det_res concatenate convert_rec_attention_infer_res astype float32 cal_predicts_accuracy_srn convert_rec_label_to_lod int64 run append array range cal_predicts_accuracy len eval_rec_run reader_main info check_and_read_gif TextClassifier text_classifier imread TextRecognizer text_recognizer list sorted range draw_ocr_box_txt fromarray text_sys COLOR_BGR2RGB vis_font_path TextSystem cvtColor get_input_names cls_model_dir AnalysisConfig enable_use_gpu gpu_mem disable_gpu disable_glog_info exit get_output_names append enable_mkldnn use_zero_copy_run get_output_tensor use_gpu format det_model_dir switch_use_feed_fetch_ops delete_pass info rec_model_dir set_cpu_math_library_num_threads create_paddle_predictor get_input_tensor set_mkldnn_cache_capacity polylines reshape imread max shape resize float array resize_img concatenate polylines astype int64 array range text_visual len seed int truetype Draw text new copy blend sqrt paste zip polygon getsize max enumerate isalpha len str truetype concatenate text create_blank_img append array enumerate uint8 b64decode fromstring IMREAD_COLOR imdecode encode polylines astype int64 zip array len | English | [简体中文](README_ch.md) ## Introduction PaddleOCR aims to create rich, leading, and practical OCR tools that help users train better models and apply them into practice. **Recent updates** - 2020.9.22 Update the PP-OCR technical article, https://arxiv.org/abs/2009.09941 - 2020.9.19 Update the ultra lightweight compressed ppocr_mobile_slim series models, the overall model size is 3.5M (see [PP-OCR Pipline](#PP-OCR-Pipline)), suitable for mobile deployment. [Model Downloads](#Supported-Chinese-model-list) - 2020.9.17 Update the ultra lightweight ppocr_mobile series and general ppocr_server series Chinese and English ocr models, which are comparable to commercial effects. [Model Downloads](#Supported-Chinese-model-list) - 2020.9.17 update [English recognition model](./doc/doc_en/models_list_en.md#english-recognition-model) and [Multilingual recognition model](doc/doc_en/models_list_en.md#english-recognition-model), `German`, `French`, `Japanese` and `Korean` have been supported. Models for more languages will continue to be updated. - 2020.8.24 Support the use of PaddleOCR through whl package installation，pelease refer [PaddleOCR Package](./doc/doc_en/whl_en.md) - 2020.8.21 Update the replay and PPT of the live lesson at Bilibili on August 18, lesson 2, easy to learn and use OCR tool spree. [Get Address](https://aistudio.baidu.com/aistudio/education/group/info/1519) | 3,367 |
qinjr/UBR4CTR | ['click through rate prediction'] | ['User Behavior Retrieval for Click-Through Rate Prediction'] | code/baselines.py code/utils.py code/rnn.py code/dataloader.py code/train_baselines.py code/ubr.py code/preprocess_taobao.py code/preprocess_tmall.py code/preprocess_alipay.py code/train.py code/elastic_client.py code/rec.py Taker DataLoader DataLoader_Multi DataLoader_Target ESReader ESWriter random_sample feateng get_ud remap_log_file neg_sample get_season insert_elastic gen_target_seq sort_raw_log feateng remap_log_file neg_sample isweekday insert_elastic gen_target_seq random_sample feateng gen_target_seq get_ud neg_sample remap get_season insert_elastic sort_log join_user_profile RecSum RecAtt RecBase dynamic_rnn _dynamic_rnn_loop _best_effort_input_batch_size raw_rnn static_rnn _infer_state_dtype static_bidirectional_rnn bidirectional_dynamic_rnn static_state_saving_rnn _rnn_step _transpose_batch_time _reverse_seq restore train_rec_model eval train train_ubr_model eval restore train UBRBase UBR_SA learned_init create_linear_initializer VecAttGRUCell MIMNCell expand str list format print set len list print sort append keys len randint write ESWriter append list keys print sort append get_shape concatenate transpose concat rank set_shape shape value all is_sequence get_shape _copy_some_through call_cell assert_same_structure flatten set_shape zip pack_sequence_as cond get_shape tuple merge_with unknown_shape stack set_shape reverse_sequence unstack zip append _reverse flatten tuple identity to_int32 value constant output_size _best_effort_input_batch_size tuple while_loop reduce_max _concat flatten shape set_shape zip pack_sequence_as reduce_min state_size is_sequence static_rnn state flatten pack_sequence_as state_size flatten tuple pack_sequence_as _reverse_seq format print exit RecAtt UBR_SA RecSum reset_default_graph GPUOptions log_loss DataLoader_Target time print take_behave append get_index sum roc_auc_score len log_loss DataLoader_Target time format print makedirs eval save take_behave append get_index train sum range roc_auc_score len DataLoader_Target time format print makedirs get_reward add_summary save take_behave append get_index train sum range len print exit RecAtt UBR_SA RecSum reset_default_graph GPUOptions DIEN MIMN DIN Caser HPMN GRU4Rec SASRec DataLoader DIEN MIMN DIN Caser HPMN GRU4Rec SASRec sqrt | # User Behavior Retrieval for CTR Prediction (UBR4CTR) A `tensorflow` implementation of all the compared models for our SIGIR 2020 paper: [User Behavior Retrieval for Click-Through Rate Prediction](https://arxiv.org/pdf/2005.14171.pdf) If you have any questions, please contact the author: [Jiarui Qin](http://jiaruiqin.me). ## Abstract > Click-through rate (CTR) prediction plays a key role in modern online personalization services. In practice, it is necessary to capture user's drifting interests by modeling sequential user behaviors to build an accurate CTR prediction model. However, as the users accumulate more and more behavioral data on the platform, it becomes non-trivial for the sequential models to make use of the whole behavior history of each user. First, directly feeding the long behavior sequence will make online inference time and system load infeasible. Second, there is much noise in such long histories to fail the sequential model learning. The current industrial solutions mainly truncate the sequences and just feed recent behaviors to the prediction model, which leads to a problem that sequential patterns such as periodicity or long-term dependency are not embedded in the recent several behaviors but in far back history. To tackle these issues, in this paper we consider it from the data perspective instead of just designing more sophisticated yet complicated models and propose User Behavior Retrieval for CTR prediction (UBR4CTR) framework. In UBR4CTR, the most relevant and appropriate user behaviors will be firstly retrieved from the entire user history sequence using a learnable search method. These retrieved behaviors are then fed into a deep model to make the final prediction instead of simply using the most recent ones. It is highly feasible to deploy UBR4CTR into industrial model pipeline with low cost. Experiments on three real-world large-scale datasets demonstrate the superiority and efficacy of our proposed framework and models. | 3,368 |
qinnzou/Gait-Recognition-Using-Smartphones | ['person identification', 'gait recognition'] | ['Deep Learning-Based Gait Recognition Using Smartphones in the Wild'] | code/identification/LSTMs/bidiLSTMAcc3.py code/identification/LSTMs/bidiLSTM6.py code/authentication/CNN-identification.py code/identification/CNN/CNN.py code/identification/LSTMs/singleLSTMGyr3.py code/identification/LSTMs/singleLSTMAcc3.py code/identification/CNN+LSTM/CNN-LSTM.py code/authentication/read-CNNckpt.py code/identification/LSTMs/doubleLSTMAcc3.py code/identification/LSTMs/singleLSTM6.py code/identification/LSTMs/bidiLSTMGyr3.py code/identification/LSTMs/doubleLSTMSqrt.py code/identification/LSTMs/doubleLSTMGyr3.py code/authentication/CNN+LSTM.py code/identification/LSTMs/bidiLSTMSqrt.py code/identification/LSTMs/doubleLSTMFix6.py code/authentication/unfix-cnn-lstm(ver).py code/identification/CNN+LSTM/lstm_fix.py code/identification/CNN+LSTM/cnn_fix.py code/authentication/unfix-cnn-lstm(hor).py code/identification/LSTMs/singleLSTMSqrt.py load_y bias_variable load_X weight_variable load_y load_X changex bias_variable weight_variable load_y bias_variable load_X weight_variable Config load_y last_full_connection_layer LSTM_Network load_X CNN_NetWork bias_variable weight_variable load_y last_full_connection_layer LSTM_Network load_X bias_variable weight_variable load_y model last_full_connection_layer load_X CNN_NetWork bias_variable weight_variable join sort transpose close append listdir array open int max reshape close open array len truncated_normal constant flatten append MultiRNNCell n_layers relu reshape transpose BasicLSTMCell static_rnn matmul n_steps n_hidden split reshape matmul max_pool conv2d elu bias_variable weight_variable concat bias_variable weight_variable Variable random_normal flatten relu transpose flatten | # Deep Learning-Based Gait Recognition Using Smartphones in the Wild This is the source code of Deep learning-based gait recogntion using smartphones in the wild. We provide the dataset and the pretrained model. Zou Q, Wang Y, Zhao Y, Wang Q and Li Q, Deep learning-based gait recogntion using smartphones in the wild, IEEE Transactions on Information Forensics and Security, vol. 15, no. 1, pp. 3197-3212, 2020. Comparing with other biometrics, gait has advantages of being unobtrusive and difficult to conceal. Inertial sensors such as accelerometer and gyroscope are often used to capture gait dynamics. Nowadays, these inertial sensors have commonly been integrated in smartphones and widely used by average person, which makes it very convenient and inexpensive to collect gait data. In this paper, we study gait recognition using smartphones in the wild. Unlike traditional methods that often require the person to walk along a specified road and/or at a normal walking speed, the proposed method collects inertial gait data under a condition of unconstraint without knowing when, where, and how the user walks. To obtain a high performance of person identification and authentication, deep-learning techniques are presented to learn and model the gait biometrics from the walking data. Specifically, a hybrid deep neural network is proposed for robust gait feature representation, where features in the space domain and in the time domain are successively abstracted by a convolutional neural network and a recurrent neural network. In the experiments, two datasets collected by smartphones on a total of 118 subjects are used for evaluations. Experiments show that the proposed method achieves over 93.5% and 93.7% accuracy in person identification and authentication, respectively. # Networks ## Network Architecture for Gait-extraction  ### Network Architecture Details for Gait-extraction  | 3,369 |
qipeng/gcn-over-pruned-trees | ['relation extraction'] | ['Graph Convolution over Pruned Dependency Trees Improves Relation Extraction'] | train.py utils/helper.py utils/vocab.py data/loader.py eval.py model/tree.py utils/constant.py prepare_vocab.py model/gcn.py utils/torch_utils.py model/trainer.py utils/scorer.py entity_masks count_oov load_tokens main build_vocab parse_args get_positions get_long_tensor DataLoader map_to_ids sort_all word_dropout GCNClassifier pool GCNRelationModel rnn_zero_state GCN unpack_batch GCNTrainer Trainer tree_to_adj head_to_tree tree_to_dist Tree FileLogger save_config print_config check_files ensure_dir check_dir load_config score parse_arguments load MyAdagrad change_lr load_config keep_partial_grad set_cuda flatten_indices save get_optimizer build_embedding Vocab load_glove_vocab add_argument ArgumentParser vocab_dir save list data_dir glove_dir count_oov load_tokens parse_args build_vocab build_embedding format wv_dim wv_file lower ensure_dir items print min_freq load_glove_vocab len print format len sorted format print len Counter VOCAB_PREFIX entity_masks sum Counter values LongTensor fill_ max PAD_ID enumerate list masked_fill Variable zeros Variable squeeze cuda int intersection_update add_child tolist len reversed add difference set append range enumerate zeros T children ones dist print format exit print format exit print format makedirs print format print format print items parse_args add_argument ArgumentParser max list sorted format print write Counter float sum keys range values len param_groups append range enumerate zero_ load_state_dict load uniform len set | Graph Convolution over Pruned Dependency Trees for Relation Extraction ========== This repo contains the *PyTorch* code for the paper [Graph Convolution over Pruned Dependency Trees Improves Relation Extraction](https://nlp.stanford.edu/pubs/zhang2018graph.pdf). This paper/code introduces a graph convolutional neural network (GCN) over pruned dependency trees for the task of relation extraction. A special tree pruning technique called the Path-centric Pruning is also introduced to eliminate irrelevant information from the trees while maximally maintaining relevant information. Compared to sequence models such as various LSTM-based models, this GCN model makes use of dependency structures to bridge remote words, therefore improves performance for long-range relations. Compared to previous recursive models such as the TreeLSTM, this GCN model achieves better performance while being much eariser to parallelize and therefore much more efficient. See below for an overview of the model architecture:  ## Requirements - Python 3 (tested on 3.6.5) - PyTorch (tested on 0.4.0) - tqdm | 3,370 |
qjadud1994/CRNN-Keras | ['optical character recognition', 'scene text recognition'] | ['An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition'] | Model.py Image_Generator.py Prediction.py parameter.py training.py Model_GRU.py text_to_labels labels_to_text TextImageGenerator get_Model ctc_lambda_func get_Model ctc_lambda_func label_to_hangul decode_label concatenate Input add list argmax | # CRNN (CNN+RNN) OCR(Optical Character Recognition) consists of text localization + text recognition. (text localization finds where the characters are, and text recognition reads the letters.) You can use this [text localizaion model](https://github.com/qjadud1994/OCR_Detector) I have studied. After performing localization, each text area is cropped and used as input for text recognition. An example of text recognition is typically the CRNN Combining the [text detector](https://github.com/qjadud1994/OCR_Detector) with a [CRNN](https://github.com/qjadud1994/CRNN-Keras) makes it possible to create an OCR engine that operates end-to-end. ## CRNN **[CRNN](https://arxiv.org/pdf/1507.05717.pdf)** is a network that combines CNN and RNN to process images containing sequence information such as letters. It is mainly used for OCR technology and has the following advantages. | 3,371 |
qphong/bes-mp | ['active learning'] | ['An Information-Theoretic Framework for Unifying Active Learning Problems'] | criteria/mes_criteria/evaluate_straddle.py optfunc.py levelsetestimation.py functions.py criteria/mes_criteria/evaluate_mnes2.py implicitlse.py criteria/mes_criteria/evaluate_dare.py criteria/evaluate_mes.py utils_for_continuous.py criteria/evaluate_pes.py criteria/evaluate_ei.py criteria/mes_criteria/evaluate_mnes3.py criteria/evaluate_ucb.py criteria/mes_criteria/evaluate_interval_rmes.py utils.py bayesianoptimization.py bbarn/process_bbarn.py get_required_placeholders get_intermediate_tensors get_placeholder_values evaluate_criterion get_initializers get_info func_2d_smallls func_1d_4modes log10P func_gp_prior negative_Branin negative_Goldstein negative_michaelwicz get_meshgrid get_gphyp_gpy call_func func_2d_largels maximize_func negative_hartmann3d get_required_placeholders get_intermediate_tensors get_placeholder_values evaluate_criterion get_required_placeholders get_intermediate_tensors get_placeholder_values evaluate_criterion draw_random_init_weights_features_np make_function_sample_np draw_random_init_weights_features duplicate_function_with_multiple_inputs make_function_sample find_maximum_with_multiple_init_tensor gen_fval_xs find_maximum_list_of_funcs perturb chol2inv sqrtm compute_mean_var_f get_duplicate_mask_np compute_mean_var_f_multiple_data evaluate_norm_entropy find_top_ks computeKnm merge_2dicts computeKmm_np get_uniform_random_vect computeKmm multichol2inv computeNKmm_multiple_data get_initializers find_top_k remove_duplicates_np compute_mean_f precomputeInvKs computeNKmm eval_invKmaxsams computeKnm_np compute_mean_f_np get_function_samples func_with_2d_input optimize_continuous_function sample_xmaxs_fmaxs sample_function get_gphyp ei mes imposeC2 imposeC3 pes ucb dare interval_rmes mnes mnes straddle ei pes print ucb mes interval_rmes placeholder eval_invKmaxsams reduce_max optimize_continuous_function precomputeInvKs sample_xmaxs_fmaxs sample_function get_initializers draw_random_init_weights_features_np concatenate print remove_duplicates_np zeros range run format minimize print reshape squeeze fun RBF optimize fix Constant GPRegression values meshgrid linspace concatenate seed rvs format print rand get_meshgrid zeros range reshape seed randn ones rand pi sqrt tile func_gp_prior reshape func_gp_prior get_meshgrid func_gp_prior get_meshgrid loadtxt get_meshgrid array get_meshgrid get_meshgrid get_meshgrid array get_meshgrid expand_dims mnes concat reshape sqrt compute_mean_var_f reshape abs constant ones dare straddle cos pi matmul sqrt cast eye tile expand_dims cond get_variable sqrt squeeze cos matmul squeeze f stack range get_variable argmax range minimize reshape extend find_maximum_with_multiple_init_tensor stack append range isinstance print reshape concat squeeze stack append range len randn reshape transpose rand cos inv pi matmul eig sqrt tile cholesky T squeeze cos matmul sqrt sqrt sum rand range svd rand matrix_solve while_loop transpose eye cholesky matrix_solve matmul tile eye cholesky expand_dims exp transpose square reduce_sum sqrt tile list exp reshape transpose square reduce_sum sqrt array range print set_diag squeeze computeKnm transpose reduce_sum chol2inv diag_part computeKmm computeNKmm clip_by_value T exp reshape dot sqrt tile sum T exp reshape dot sqrt tile sum reshape inv dot computeKnm_np eye computeKmm_np concat chol2inv pad computeKmm eye append range format set_diag print computeKnm concat transpose squeeze reduce_sum diag_part stack computeKmm clip_by_value append range computeNKmm_multiple_data constant reshape computeKnm squeeze range reshape squeeze top_k append find_top_k update copy concatenate reshape squeeze func tile append range enumerate zeros sum sqrt range get_duplicate_mask_np delete reshape chol2inv stack computeNKmm append range reshape concat chol2inv stack computeNKmm append range reshape minimize while_loop reshape squeeze concat multiple_func TensorArray uniform stack top_k assign func gather argmax get_variable draw_random_init_weights_features reshape stack append range format minimize while_loop reshape reduce_max cos TensorArray matmul reduce_sum sqrt stack assign append gather argmax range get_variable reshape cos matmul sqrt tile append expand_dims range value format minimize print compile compute_log_likelihood GPR ScipyOptimizer constant prob reshape squeeze sqrt Normal compute_mean_var_f clip_by_value cdf abs range evaluate_norm_entropy constant exp prob reshape squeeze log_cdf pi sqrt Normal reduce_mean compute_mean_var_f cast range log evaluate_norm_entropy constant reshape imposeC2 squeeze sqrt Normal compute_mean_var_f imposeC3 range constant exp squeeze log_cdf sqrt Normal compute_mean_var_f clip_by_value log_prob constant exp reshape computeKnm concat squeeze log_cdf matmul sqrt computeKmm log_prob constant reshape squeeze square pi sqrt cast compute_mean_var_f range log constant reshape squeeze sqrt compute_mean_var_f abs range constant exp reshape transpose squeeze log_cdf reduce_sum sqrt Normal stack compute_mean_var_f cast reduce_mean sample expand_dims range constant exp reshape transpose concat squeeze reduce_sum range sqrt Normal reduce_mean compute_mean_var_f clip_by_value sample expand_dims cdf log constant reshape squeeze reduce_mean compute_mean_var_f abs range | # An Information-Theoretic Framework for Unifying Active Learning Problems This is the source code for the paper: An Information-Theoretic Framework for Unifying Active Learning Problems, published at AAAI 2021. We address 3 problems: * Level Set Estimation  * Bayesian Optimization  * Implicit Level Set Estimation  ## Prerequisites The dependencies include: | 3,372 |
qq456cvb/PRIN | ['data augmentation'] | ['PRIN/SPRIN: On Extracting Point-wise Rotation Invariant Features', 'Pointwise Rotation-Invariant Network with Adaptive Sampling and 3D Spherical Voxel Convolution'] | train.py test.py dataset.py hyper.py model.py rnd_rot MyDataset rotmat Model load_test_set main BalancedSampler load_train_set dot z rotmat rand arccos pi join asarray print MyDataset File close append range join concatenate print File close range BalancedSampler getLogger batch_size load_test_set DataLoader BatchSampler save DEBUG copy2 setLevel cuda argmax seed locals list train_step view addHandler SourceFileLoader name repr Adam Model load_state_dict append sum range load_train_set state_dict format LongTensor param_groups ModuleType size astype perf_counter StreamHandler mean eval mkdir info float keys FileHandler load join deepcopy exec_module get_learning_rate enumerate print N_PARTS float32 parameters N_PTCLOUD len | # PRIN
## Pointwise Rotation-Invariant Network in PyTorch
# News
An improved version of PRIN (SPRIN) is released [here](https://github.com/qq456cvb/SPRIN) and described in [PRIN/SPRIN: On Extracting Point-wise Rotation Invariant Features](https://arxiv.org/abs/2102.12093), which achieves much better results.
## Overview
This repository is the Pytorch implementation of [PRIN (Pointwise Rotation-Invariant Network)](https://arxiv.org/pdf/1811.09361.pdf).
## Dependencies
* Install s2cnn (https://github.com/jonas-koehler/s2cnn) and its dependencies (pytorch, cupy, lie_learn, pynvrtc).
| 3,373 |
qq456cvb/SemanticTransfer | ['semantic correspondence'] | ['Semantic Correspondence via 2D-3D-2D Cycle'] | util/util_print.py loggers.py models/marrnet2.py networks/uresnet.py models/shapehd.py options/options_train.py datasets/shapenet.py models/__init__.py models/vpnet.py util/util_loadlib.py models/dense_embedding.py train_vp.py utils.py models/marrnetbase.py util/util_img.py models/marrnet1.py preprocess.py models/pointnet.py datasets/__init__.py models/viewpoint.py models/netinterface.py demo.py train_emb.py datasets/kpnet.py datasets.py networks/networks.py networks/revresnet.py models/wgangp.py imread_wrapper Dataset prob2real real2prob softmax project main vol2obj _LogCumulator CsvLogger ProgbarLogger BaseLogger TerminateOnNaN BatchCsvLogger ComposeLogger Progbar TensorBoardLogger ModelSaveLogger clear prob2real gen_transform_matrix bytes2np find_env_maps real2prob readexr gen_azimuth_elevation HardNegativePairSelector AverageMeter OnlineContrastiveLoss pdist main PairSelector adjust_image_attribute get_bbox denormalize_colors binarize rgb2gray jitter_colors add_lighting_noise bcolors resize alpha_blend imwrite_wrapper normalize_colors crop sample_vertex_from_mesh add_noise normalize_pc naive_read_pcd KeypointDataset DatasetKp prob2real real2prob DatasetDemo Dataset get_dataset STN3d Model PointNetDenseCls STNkd PointNetfeat Net Model Net Model MarrnetBaseModel top_n_err _get_num_samples print_grad_stats optimizer_load_state_dict data_parallel_decorator NetInterface parse_optimizer_specific_params STN3d feature_transform_reguliarzer PointNetDenseCls PointNetCls PointNetfeat STNkd Model_test Net Model Model_shapenet Net Model Net Model D Model G get_model batchnorm3d deconv3d_add3 fc VoxelDiscriminator conv3d_minus3 conv3d_half relu_leaky Conv3d_block Deconv3d_skip batchnorm ViewAsLinear VoxelGenerator batchnorm1d dropout relu ImageEncoder AziElePredictor Unet_3D VoxelDecoder deconv3d_2x maxpool RevBottleneck RevResNet _num_parameters revuresnet18 main revresnet18 deconv3x3 RevBasicBlock Net Net_inpaint add_general_arguments overwrite parse adjust_image_attribute get_bbox denormalize_colors binarize depth_to_mesh_df rgb2gray jitter_colors add_lighting_noise imread_wrapper resize alpha_blend imwrite_wrapper normalize_colors crop set_manual_seed set_gpu _check_gpu_setting_in_use _check_gpu bcolors lower imread zeros floor expand_dims stack sum arctan2 marching_cubes_lewiner append array dot resize prob2real scale_25d tuple cos zero_grad pi renderer DataLoader post_opt resize Model_test tensor ComposeLogger cuda open list transpose step waitKey Adam get_original_cwd imshow Model pred_silhou_thres getattr load_state_dict array sin append_data sample_vertex_from_mesh predict range postprocess init_dist concatenate get_writer Renderer astype close mean eval softmax item float flip net vol2obj enumerate load join uint8 norm T backward print reshape clamp float32 tqdm cross color_palette zeros to_obj_str numpy Dataset circle str list parse glob sort set add getroot find str join parse arccos replace arctan2 glob tqdm getroot save find remove glob print tqdm exists load_mesh max format replace glob inv copy tqdm vertices save array InputFile t mm view getLogger model batch_size KeypointDataset save HardNegativePairSelector max_epoch set_postfix append state_dict update stack info criterion OnlineContrastiveLoss AverageMeter parameters reset train len list tuple lower imwrite INTER_CUBIC dstack mean alpha_blend rgb2gray uniform deepcopy list shuffle adjust_image_attribute array range len normal deepcopy multiply tile sum array range deepcopy range range deepcopy logical_not min max where int pad round max norm arange rand choice cross take sum asarray readlines stack startswith array enumerate clip randn stack join split lower import_module drop_last batch_sampler items list load_state_dict zip state_dict list reshape argsort mean append numpy dict sgd_momentum sgd_dampening sgd_wdecay forward print detach bmm norm transpose mean cuda is_cuda import_module RevResNet RevResNet revnet named_children AvgPool2d register_forward_hook RevResNet _num_parameters resnet18 revresnet18 add_argument load items list Namespace print vars add_additional_arguments add_general_arguments parse_known_args add_arguments ArgumentParser append parse_args union tsdf_renderer back_project_ptcloud ones rand min astype where ptcld any array zeros max print _check_gpu check_output strip int decode print check_output split seed manual_seed_all manual_seed | # SemanticTransfer Code repo for the paper [Semantic Correspondence via 2D-3D-2D Cycle](https://arxiv.org/abs/2004.09061). # Demo Please run `demo.py`. # Pretrained Weights You can download them from [Google Drive](https://drive.google.com/drive/folders/1VN4dIrMqtIxb0CJleOx7aco21BUSL9qp?usp=sharing). # Training Training the full pipeline is somewhat involved and complicated, and our code is heavily based on [ShapeHD](https://github.com/xiumingzhang/GenRe-ShapeHD). In general, there are four steps: - Train ShapeHD model as outlined [here](https://github.com/xiumingzhang/GenRe-ShapeHD#shapehd-1). - Prepare synthetic ShapeNet model renderings by ``mitsuba`` and generate their corresponding viewpoints through ``preprocess.py``. | 3,374 |
qqlu/Amodal-Instance-Segmentation-through-KINS-Dataset | ['instance segmentation', 'semantic segmentation'] | ['Amodal Instance Segmentation With KINS Dataset'] | Reference Code/lib/utils/io.py Reference Code/lib/roi_data/keypoint_rcnn.py Reference Code/lib/nn/modules/normalization.py Reference Code/lib/utils/misc.py kitti_vis_without_cocoapi.py Reference Code/lib/modeling/MobileNetV2.py Reference Code/lib/datasets/json_dataset_amodal.py Reference Code/lib/modeling/fast_rcnn_heads_panet2_v1.py Reference Code/lib/utils/mobile_weights_helper.py Reference Code/lib/nn/parallel/parallel_apply.py Reference Code/lib/utils/boxes.py Reference Code/lib/model/roi_crop/functions/crop_resize.py Reference Code/lib/modeling/fast_rcnn_heads_split_amodal_class.py Reference Code/lib/model/roi_align/_ext/roi_align/__init__.py Reference Code/lib/roi_data/fast_rcnn_amodal.py Reference Code/lib/datasets/cityscapes/tools/convert_cityscapes_to_coco.py Reference Code/lib/model/roi_pooling/modules/roi_pool.py Reference Code/lib/modeling/FPN_mobile.py Reference Code/lib/modeling/collect_and_distribute_fpn_rpn_proposals_panet.py Reference Code/lib/utils/env.py Reference Code/lib/nn/parallel/replicate.py Reference Code/lib/modeling/MobileNetV2_imitateRes.py kitti_vis_with_cocoapi.py Reference Code/lib/utils/image.py Reference Code/tools/train_net_step_amodalinmodalseg.py Reference Code/lib/model/roi_crop/functions/roi_crop.py Reference Code/lib/utils/collections.py Reference Code/lib/roi_data/mask_rcnn_amodalinmodalseg.py Reference Code/lib/modeling/roi_xfrom/roi_align/build.py Reference Code/lib/utils/detectron_weight_helper.py Reference Code/lib/nn/parallel/scatter_gather.py Reference Code/lib/datasets/cityscapes_json_dataset_evaluator.py Reference Code/lib/model/utils/net_utils.py Reference Code/lib/model/roi_pooling/functions/roi_pool.py Reference Code/lib/model/nms/build.py Reference Code/lib/datasets/cityscapes/tools/convert_coco_model_to_cityscapes.py Reference Code/lib/nn/parallel/data_parallel.py Reference Code/lib/modeling/fast_rcnn_heads.py Reference Code/lib/modeling/rpn_heads_panet.py Reference Code/lib/nn/functional.py Reference Code/lib/core/test_engine.py Reference Code/lib/modeling/model_builder_amodal.py Reference Code/lib/modeling/model_builder_amodalinmodalseg_concat.py Reference Code/lib/model/roi_crop/modules/roi_crop.py Reference Code/tools/train_net_step_amodalinmodalseg_split_amodal_class_feature_fusion.py Reference Code/lib/modeling/rpn_heads.py Reference Code/lib/roi_data/mask_rcnn_amodal.py Reference Code/lib/nn/__init__.py Reference Code/lib/model/roi_crop/build.py Reference Code/lib/modeling/keypoint_rcnn_heads.py Reference Code/lib/nn/parallel/__init__.py Reference Code/lib/model/roi_crop/_ext/roi_crop/__init__.py Reference Code/lib/model/nms/nms_wrapper.py Reference Code/lib/roi_data/minibatch.py Reference Code/lib/roi_data/mask_rcnn.py Reference Code/tools/train_net_step_amodalinmodalseg_concat.py Reference Code/lib/roi_data/fast_rcnn_amodalinmodalseg.py Reference Code/lib/datasets/json_dataset_amodalinmodalseg.py Reference Code/lib/model/roi_align/modules/roi_align.py Reference Code/lib/modeling/model_builder_amodalinmodalseg_split_amodal_class_feature_fusion.py Reference Code/lib/modeling/mask_rcnn_heads.py Reference Code/lib/model/roi_align/build.py Reference Code/lib/model/nms/_ext/nms/__init__.py Reference Code/tools/train_net_step_panet123_v1.py Reference Code/lib/roi_data/loader.py Reference Code/lib/utils/fpn.py Reference Code/lib/modeling/model_builder_amodalinmodalseg_split_amodal_class.py Reference Code/lib/modeling/FPN_PANET1_v2_2_v1.py Reference Code/lib/utils/logging.py Reference Code/lib/roi_data/data_utils.py Reference Code/lib/datasets/roidb.py Reference Code/lib/model/nms/nms_gpu.py Reference Code/lib/modeling/fast_rcnn_heads_return_feature.py Reference Code/lib/nn/parallel/_functions.py Reference Code/lib/nn/modules/__init__.py Reference Code/lib/model/roi_pooling/build.py Reference Code/lib/modeling/generate_proposals.py Reference Code/lib/modeling/model_builder.py Reference Code/lib/datasets/voc_dataset_evaluator.py Reference Code/lib/roi_data/rpn.py Reference Code/lib/utils/blob.py Reference Code/lib/utils/training_stats.py Reference Code/lib/utils/subprocess.py Reference Code/tools/train_net_step_amodalinmodalseg_split_amodal_class.py Reference Code/lib/utils/segms.py Reference Code/tools/train_net_step_amodal.py Reference Code/lib/roi_data/loader_amodal.py Reference Code/lib/core/test_ori.py Reference Code/lib/core/test_debug.py Reference Code/lib/core/test.py Reference Code/lib/modeling/FPN.py Reference Code/lib/utils/keypoints.py Reference Code/lib/utils/net.py Reference Code/lib/modeling/collect_and_distribute_fpn_rpn_proposals.py Reference Code/lib/modeling/roi_xfrom/roi_align/modules/roi_align.py Reference Code/lib/model/roi_align/functions/roi_align.py Reference Code/lib/utils/resnet_weights_helper.py Reference Code/lib/model/roi_crop/functions/gridgen.py Reference Code/lib/datasets/json_dataset.py Reference Code/lib/utils/timer.py Reference Code/lib/datasets/voc_eval.py Reference Code/lib/modeling/ResNet.py Reference Code/lib/setup.py Reference Code/lib/roi_data/loader_amodalinmodalseg.py Reference Code/lib/modeling/generate_proposal_labels.py Reference Code/lib/modeling/model_builder_amodalinmodalseg.py Reference Code/lib/utils/vis.py Reference Code/lib/datasets/json_dataset_evaluator.py Reference Code/lib/datasets/task_evaluation.py Reference Code/lib/core/config.py Reference Code/lib/nn/init.py Reference Code/lib/utils/colormap.py Reference Code/lib/datasets/dataset_catalog.py Reference Code/tools/train_net.py Reference Code/lib/modeling/mask_rcnn_heads_panet23_v1.py Reference Code/lib/datasets/cityscapes/coco_to_cityscapes_id.py Reference Code/lib/model/roi_crop/modules/gridgen.py Reference Code/lib/model/roi_crop/_ext/crop_resize/__init__.py Reference Code/lib/model/roi_pooling/_ext/roi_pooling/__init__.py Reference Code/lib/core/test_v1.py Reference Code/lib/nn/modules/upsample.py Reference Code/lib/modeling/roi_xfrom/roi_align/_ext/roi_align/__init__.py Reference Code/lib/modeling/generate_anchors.py Reference Code/lib/roi_data/fast_rcnn.py Reference Code/tools/train_net_step.py Reference Code/lib/modeling/model_builder_panet123_v1.py Reference Code/lib/datasets/dummy_datasets.py Reference Code/lib/nn/modules/affine.py Reference Code/lib/modeling/roi_xfrom/roi_align/functions/roi_align.py Reference Code/tools/test_net.py make_json_dict merge_cfg_from_list merge_cfg_from_file _merge_a_into_b assert_and_infer_cfg merge_cfg_from_cfg _decode_cfg_value _check_and_coerce_cfg_value_type im_detect_all im_detect_mask_aug box_results_with_nms_and_limit _project_im_rois im_conv_body_and_branch_feature im_detect_mask_hflip segm_results_inmodal im_detect_bbox_re im_detect_bbox_scale im_detect_bbox_aspect_ratio box_results_with_nms_and_limit_return_keep im_detect_mask_scale im_conv_body_and_branch_feature_again segm_results_ensemble im_detect_ensemble im_detect_bbox_hflip _get_rois_blob im_detect_bbox segm_results im_conv_body_only keypoint_results im_detect_mask_and_branch_feature im_detect_keypoints im_detect_mask_aspect_ratio _get_blobs im_detect_bbox_aug im_detect_mask _add_multilevel_rois_for_test im_detect_all im_detect_mask_aug box_results_with_nms_and_limit _project_im_rois im_conv_body_and_branch_feature im_detect_mask_hflip segm_results_inmodal im_detect_bbox_re im_detect_bbox_scale im_detect_bbox_aspect_ratio box_results_with_nms_and_limit_return_keep im_detect_mask_scale segm_results_ensemble im_detect_ensemble im_detect_bbox_hflip _get_rois_blob im_detect_bbox segm_results im_conv_body_only keypoint_results im_detect_mask_and_branch_feature im_detect_keypoints im_detect_mask_aspect_ratio _get_blobs im_detect_bbox_aug im_detect_mask _add_multilevel_rois_for_test get_inference_dataset get_roidb_and_dataset get_eval_functions run_inference empty_results multi_gpu_test_net_on_dataset initialize_model_from_cfg test_net_on_dataset test_net extend_results segm_results keypoint_results _project_im_rois im_detect_all im_detect_keypoints im_detect_mask _get_blobs box_results_with_nms_and_limit _get_rois_blob im_detect_bbox _add_multilevel_rois_for_test im_detect_all im_detect_mask_aug box_results_with_nms_and_limit _project_im_rois im_detect_mask_hflip im_detect_bbox_scale im_detect_bbox_aspect_ratio im_detect_mask_scale im_detect_bbox_hflip _get_rois_blob im_detect_bbox segm_results im_conv_body_only keypoint_results im_detect_keypoints im_detect_mask_aspect_ratio _get_blobs im_detect_bbox_aug im_detect_mask _add_multilevel_rois_for_test evaluate_masks get_coco_dataset get_kitti_dataset get_common_dataset _merge_proposal_boxes_into_roidb _add_class_assignments _sort_proposals _filter_crowd_proposals JsonDataset add_proposals _merge_proposal_boxes_into_roidb _add_class_assignments _sort_proposals _filter_crowd_proposals JsonDatasetAmodal add_proposals JsonDatasetAmodalInmodalSeg _merge_proposal_boxes_into_roidb _add_class_assignments _sort_proposals _filter_crowd_proposals add_proposals _coco_bbox_results_one_category _do_keypoint_eval _write_coco_segms_results_file_ctype _coco_segms_results_one_category_ctype _do_segmentation_eval evaluate_boxes _do_detection_eval _write_coco_keypoint_results_file _log_detection_eval_metrics evaluate_keypoints _coco_kp_results_one_category _write_coco_bbox_results_file _write_coco_segms_results_file evaluate_masks _coco_segms_results_one_category evaluate_box_proposals add_bbox_regression_targets extend_with_flipped_entries combined_roidb_for_training rank_for_training _compute_targets filter_for_training _compute_and_log_stats evaluate_all _coco_eval_to_mask_results check_expected_results log_box_proposal_results _empty_keypoint_results _coco_eval_to_keypoint_results evaluate_boxes evaluate_keypoints _use_json_dataset_evaluator evaluate_masks_inmodal _voc_eval_to_box_results _empty_box_results _coco_eval_to_box_results _cs_eval_to_mask_results evaluate_masks_amodal _use_cityscapes_evaluator _empty_box_proposal_results log_copy_paste_friendly_results evaluate_box_proposals _empty_mask_results evaluate_masks _use_voc_evaluator voc_info _get_voc_results_file_template _do_matlab_eval evaluate_boxes _write_voc_results_files _do_python_eval parse_rec voc_eval voc_ap cityscapes_to_coco_without_person_rider cityscapes_to_coco cityscapes_to_coco_with_rider cityscapes_to_coco_all_random parse_args convert_coco_stuff_mat convert_cityscapes_instance_only getLabelID remove_momentum load_and_convert_coco_model parse_args convert_coco_blob_to_cityscapes_blob convert_coco_blobs_to_cityscape_blobs nms_gpu nms _import_symbols RoIAlignFunction RoIAlign RoIAlignAvg RoIAlignMax _import_symbols RoICropFunction AffineGridGenFunction RoICropFunction DenseAffine3DGridGen_rotate CylinderGridGenV2 DenseAffine3DGridGen Depth3DGridGen_with_mask DenseAffineGridGen AffineGridGenV2 _AffineGridGen Depth3DGridGen _RoICrop _import_symbols _import_symbols RoIPoolFunction _RoIPooling _import_symbols load_net _affine_theta compare_grid_sample _affine_grid_gen _crop_pool_layer save_net weights_normal_init mask_rcnn_fcn_head_v1upXconvs_ff mask_rcnn_fcn_head_v1upXconvs mask_rcnn_fcn_head_v1up4convs mask_rcnn_fcn_head_v0upshare mask_rcnn_fcn_head_v1up4convs_ff mask_rcnn_fcn_head_v1up4convs_gn mask_rcnn_losses mask_rcnn_fcn_head_v1up mask_rcnn_fcn_head_v1upXconvs_add mask_rcnn_fcn_head_v1upXconvs_gn mask_rcnn_fcn_head_v0up mask_rcnn_outputs ResNet_roi_conv5_head_for_masks CollectAndDistributeFpnRpnProposalsOp collect distribute CollectAndDistributeFpnRpnProposalsOp collect distribute fast_rcnn_losses roi_Xconv1fc_head fast_rcnn_outputs fast_rcnn_amodal_losses roi_2mlp_head roi_Xconv1fc_gn_head fast_rcnn_losses roi_Xconv1fc_head fast_rcnn_outputs roi_2mlp_head roi_Xconv1fc_gn_head fast_rcnn_losses roi_Xconv1fc_head fast_rcnn_outputs fast_rcnn_amodal_losses roi_2mlp_head roi_Xconv1fc_gn_head fast_rcnn_losses roi_Xconv1fc_head fast_rcnn_amodal_losses fast_rcnn_amodal_outputs fast_rcnn_class_outputs roi_2mlp_head roi_Xconv1fc_head_return_feature fpn_ResNet101_conv5_body fpn_ResNet152_conv5_body fpn_ResNet50_conv5_P2only_body fpn_ResNet50_conv5_body fpn fpn_ResNet101_conv5_P2only_body fpn_ResNet152_conv5_P2only_body topdown_lateral_module get_min_max_levels fpn_level_info_ResNet152_conv5 fpn_rpn_losses fpn_level_info_ResNet101_conv5 fpn_level_info_ResNet50_conv5 fpn_rpn_outputs fpn fpn_MobileNetV2_p2only_body topdown_lateral_module get_min_max_levels fpn_rpn_losses fpn_level_info_MobileNetV2_conv5 fpn_MobileNetV2_body fpn_rpn_outputs panet_downtop_lateral_module fpn_ResNet101_conv5_body fpn_ResNet152_conv5_body fpn_ResNet50_conv5_P2only_body fpn_ResNet50_conv5_body fpn fpn_ResNet101_conv5_P2only_body fpn_ResNet152_conv5_P2only_body topdown_lateral_module get_min_max_levels fpn_level_info_ResNet152_conv5 fpn_rpn_losses fpn_level_info_ResNet101_conv5 fpn_level_info_ResNet50_conv5 fpn_rpn_outputs generate_anchors _scale_enum _whctrs _ratio_enum _generate_anchors _mkanchors _filter_boxes GenerateProposalsOp GenerateProposalLabelsOp keypoint_outputs roi_pose_head_v1convX keypoint_losses mask_rcnn_fcn_head_v1upXconvs mask_rcnn_fcn_head_v1up4convs mask_rcnn_fcn_head_v0upshare mask_rcnn_fcn_head_v1up4convs_gn mask_rcnn_losses mask_rcnn_fcn_head_v1up mask_rcnn_fcn_head_v1upXconvs_gn mask_rcnn_fcn_head_v0up mask_rcnn_outputs ResNet_roi_conv5_head_for_masks conv_1x1_bn InvertedResidual conv_bn MobileNetV2 conv_1x1_bn residual_stage_detectron_mapping InvertedResidual conv_bn freeze_params MobileNetV2_body get_func Generalized_RCNN get_func Generalized_RCNN get_func Generalized_RCNN get_func Generalized_RCNN get_func Generalized_RCNN get_func Generalized_RCNN get_func Generalized_RCNN ResNet_roi_conv5_head basic_bn_stem basic_gn_stem bottleneck_transformation residual_stage_detectron_mapping ResNet50_conv4_body ResNet152_conv5_body ResNet_convX_body freeze_params ResNet101_conv5_body ResNet50_conv5_body add_stage basic_bn_shortcut ResNet101_conv4_body add_residual_block bottleneck_gn_transformation basic_gn_shortcut generic_rpn_outputs single_scale_rpn_losses generic_rpn_outputs_panet single_scale_rpn_outputs generic_rpn_losses generic_rpn_outputs single_scale_rpn_losses generic_rpn_losses single_scale_rpn_outputs RoIAlignFunction RoIAlign RoIAlignAvg RoIAlignMax _import_symbols group_norm XavierFill MSRAFill AffineChannel2d GroupNorm BilinearInterpolation2d DataParallel data_parallel get_a_var parallel_apply replicate scatter_kwargs gather scatter Broadcast Gather ReduceAddCoalesced _get_stream Scatter unmap compute_targets get_field_of_anchors get_fast_rcnn_blob_names _sample_rois_balance_sample _sample_rois _compute_targets add_fast_rcnn_blobs _add_multilevel_rois_panet _add_multilevel_rois add_fast_rcnn_blobs_panet _expand_bbox_targets get_fast_rcnn_blob_names _sample_rois_balance_sample _sample_rois _compute_targets add_fast_rcnn_blobs _add_multilevel_rois_panet _add_multilevel_rois add_fast_rcnn_blobs_panet _expand_bbox_targets get_fast_rcnn_blob_names _sample_rois _compute_targets add_fast_rcnn_blobs _add_multilevel_rois_panet _add_multilevel_rois add_fast_rcnn_blobs_panet _expand_bbox_targets finalize_keypoint_minibatch _within_box add_keypoint_rcnn_blobs collate_minibatch MinibatchSampler BatchSampler cal_minibatch_ratio pad_image_data RoiDataLoader collate_minibatch MinibatchSampler BatchSampler cal_minibatch_ratio pad_image_data RoiDataLoader collate_minibatch MinibatchSampler BatchSampler cal_minibatch_ratio pad_image_data RoiDataLoader add_mask_rcnn_blobs _expand_to_class_specific_mask_targets add_mask_rcnn_blobs _expand_to_class_specific_mask_targets add_mask_rcnn_blobs _expand_to_class_specific_mask_targets get_minibatch _get_image_blob get_minibatch_blob_names get_rpn_blob_names add_rpn_blobs _get_rpn_blobs serialize get_target_scale get_image_blob ones get_im_blob_sizes prep_im_for_blob get_max_shape im_list_to_blob deserialize zeros expand_boxes nms clip_xyxy_to_image bbox_transform unique_boxes clip_tiled_boxes aspect_ratio bbox_transform_inv boxes_area xywh_to_xyxy clip_boxes_to_image xyxy_to_xywh filter_small_boxes flip_boxes box_voting soft_nms AttrDict colormap load_detectron_weight mobile_weights_name_pattern resnet_weights_name_pattern exit_on_error set_up_matplotlib get_runtime_dir get_py_bin_ext remove_negative_area_roi_blobs add_multilevel_roi_blobs add_multilevel_roi_blobs_panet map_rois_to_fpn_levels aspect_ratio_rel aspect_ratio_abs save_object cache_url _get_reference_md5sum _get_file_md5sum assert_cache_file_is_ok download_url _progress_bar get_keypoints nms_oks flip_keypoints keypoints_to_heatmap_labels scores_to_probs flip_heatmaps get_person_class_index heatmaps_to_keypoints compute_oks log_stats SmoothedValue setup_logging_to_file send_email log_json_stats setup_logging is_image_file get_run_name ensure_optimizer_ckpt_params_order load_optimizer_state_dict get_imagelist_from_dir get_output_dir load_pretrained_imagenet_weights convert_state_dict _get_lr_change_ratio load_ckpt clip_gradient smooth_l1_loss affine_grid_gen get_group_gn _CorrectMomentum update_learning_rate decay_learning_rate save_ckpt load_pretrained_imagenet_weights convert_state_dict intersect_mask rle_mask_to_mask_wrt_box mask_to_bbox rle_mask_voting polys_to_mask flip_segms rle_mask_nms rle_mask_to_mask_wrt_box_2 polys_to_boxes rle_masks_to_boxes polys_to_mask_wrt_box process_in_parallel log_subprocess_output Timer TrainingStats vis_bbox_opencv convert_from_cls_format vis_one_image get_class_string kp_connections parse_args main parse_args log_training_stats main parse_args save_ckpt main parse_args save_ckpt main parse_args save_ckpt main parse_args save_ckpt main parse_args save_ckpt main parse_args save_ckpt main parse_args save_ckpt append normal constant LOAD_IMAGENET_PRETRAINED_WEIGHTS immutable set uniform GroupNorm _merge_a_into_b _merge_a_into_b _decode_cfg_value _check_and_coerce_cfg_value_type zip split deepcopy list items isinstance _decode_cfg_value _check_and_coerce_cfg_value_type literal_eval isinstance string_types str list ndarray isinstance tuple type array toc defaultdict im_conv_body_and_branch_feature im_detect_mask_and_branch_feature MAX_SIZE segm_results_inmodal im_detect_mask im_detect_mask_aug ENABLED im_detect_bbox_aug tic box_results_with_nms_and_limit_return_keep SCALE im_detect_bbox im_conv_body_and_branch_feature_again INMODAL_ON im_conv_body_only toc defaultdict segm_results_ensemble MAX_SIZE im_detect_mask_aug ENABLED tic vstack SCALE im_detect_mask len CLS_AGNOSTIC_BBOX_REG model BBOX_NORMALIZE_STDS BBOX_NORMALIZE_MEANS BBOX_NORMALIZE_TARGETS_PRECOMPUTED view squeeze shape BBOX_REG_WEIGHTS bbox_transform clip_tiled_boxes unique tile PYTORCH_VERSION_LESS_THAN_040 FASTER_RCNN reshape _get_blobs dot _add_multilevel_rois_for_test numpy array BBOX_REG CLS_AGNOSTIC_BBOX_REG model BBOX_NORMALIZE_STDS BBOX_NORMALIZE_MEANS BBOX_NORMALIZE_TARGETS_PRECOMPUTED view squeeze shape BBOX_REG_WEIGHTS bbox_transform clip_tiled_boxes unique tile PYTORCH_VERSION_LESS_THAN_040 FASTER_RCNN reshape _get_blobs dot _add_multilevel_rois_for_test numpy array BBOX_REG H_FLIP add_preds_t MAX_SIZE SCALE_H_FLIP mean im_detect_bbox_scale im_detect_bbox_aspect_ratio im_detect_bbox_hflip vstack SCALE im_detect_bbox SCALES ASPECT_RATIOS flip_boxes im_detect_bbox im_detect_bbox im_detect_bbox_hflip aspect_ratio_rel aspect_ratio MAX_SIZE im_detect_bbox_hflip SCALE im_detect_bbox reshape _add_multilevel_rois_for_test squeeze mask_net float32 CLS_SPECIFIC_MASK MULTILEVEL_ROIS zeros RESOLUTION reshape _add_multilevel_rois_for_test squeeze mask_net float32 CLS_SPECIFIC_MASK MULTILEVEL_ROIS zeros RESOLUTION im_conv_body_only H_FLIP exp amax MAX_SIZE im_detect_mask_hflip SCALE_H_FLIP mean SCALE im_detect_mask im_detect_mask_scale SCALES append im_conv_body_only MAX_SIZE im_detect_mask SCALE flip_boxes im_conv_body_only im_detect_mask_hflip im_detect_mask im_conv_body_only aspect_ratio_rel aspect_ratio im_detect_mask_hflip MAX_SIZE SCALE im_detect_mask squeeze float32 expand_dims MULTILEVEL_ROIS zeros _add_multilevel_rois_for_test keypoint_net HEATMAP_SIZE nms NUM_CLASSES hstack astype float32 ENABLED vstack NMS VOTE_TH box_voting soft_nms range nms list NUM_CLASSES astype float32 extend vstack NMS array range expand_boxes max decode NUM_CLASSES min astype maximum CLS_SPECIFIC_MASK int32 resize append zeros RESOLUTION array range expand_boxes max decode NUM_CLASSES min astype maximum CLS_SPECIFIC_MASK int32 resize append zeros RESOLUTION array range expand_boxes NUM_CLASSES astype maximum CLS_SPECIFIC_MASK int32 resize append zeros RESOLUTION range nms_oks NMS_OKS NUM_CLASSES get_person_class_index heatmaps_to_keypoints _project_im_rois hstack zeros float astype ROI_MAX_LEVEL map_rois_to_fpn_levels add_multilevel_roi_blobs add_multilevel_roi_blobs_panet ROI_MIN_LEVEL _get_rois_blob get_image_blob ones PYTORCH_VERSION_LESS_THAN_040 _get_blobs model ones PYTORCH_VERSION_LESS_THAN_040 _get_blobs model ones _get_blobs det_net MULTILEVEL_ROIS _add_multilevel_rois_for_test PYTORCH_VERSION_LESS_THAN_040 RPN_ONLY PRECOMPUTED_PROPOSALS log_copy_paste_friendly_results result_getter get_eval_functions check_expected_results JsonDataset toc format evaluate_all info average_time tic get_roidb Timer multi_gpu_test_net_on_dataset test_net len join list dump save_object load_ckpt format print NUM_CLASSES process_in_parallel get_runtime_dir get_py_bin_ext dict load_detectron abspath info range keys test_net_file get_roidb_and_dataset im_detect_all tuple empty_results abspath str save_object defaultdict imread sum extend_results dump format average_time vis_one_image timedelta PRECOMPUTED_PROPOSALS info VIS initialize_model_from_cfg enumerate join NUM_CLASSES dict len load load_detectron_weight load_ckpt Generalized_RCNN load_detectron eval DataParallel info cuda len PRECOMPUTED_PROPOSALS get_roidb JsonDataset range len segm_results keypoint_results im_detect_keypoints box_results_with_nms_and_limit im_conv_body_only get_image_blob get_image_blob get_image_blob get_image_blob join name ON_CLUSTER mkdir get_roidb info main enumerate AttrDict AttrDict AttrDict _merge_proposal_boxes_into_roidb _add_class_assignments _filter_crowd_proposals append range len dtype toarray csr_matrix astype bbox_overlaps zeros argmax max append enumerate iou toarray csr_matrix xyxy_to_xywh len max argmax toarray argsort decode array unique range remove _do_segmentation_eval _write_coco_segms_results_file format extend classes info abspath _coco_segms_results_one_category enumerate format _coco_segms_results_one_category_ctype extend classes info abspath enumerate sort astype extend getImgIds float enumerate sort astype extend getImgIds float enumerate str join save_object format evaluate COCOeval _log_detection_eval_metrics COCO accumulate loadRes info join remove name _do_detection_eval _write_coco_bbox_results_file _coco_bbox_results_one_category format extend classes info abspath enumerate sort astype extend getImgIds xyxy_to_xywh float enumerate str join save_object format evaluate COCOeval _log_detection_eval_metrics COCO accumulate loadRes info _get_thr_ind format summarize mean classes info enumerate sum arange zeros_like sort min astype hstack mean bbox_overlaps zeros float argmax max range enumerate join remove _do_keypoint_eval name _write_coco_keypoint_results_file format extend _coco_kp_results_one_category classes info abspath enumerate len sort astype extend getImgIds append float range enumerate len join save_object format evaluate COCOeval summarize sort COCO accumulate getImgIds loadRes info string_types add_bbox_regression_targets isinstance rank_for_training extend filter_for_training info _compute_and_log_stats len items list flip_keypoints flip_segms keypoint_flip_map copy extend append keypoints format info len ASPECT_LO argsort ASPECT_HI info append ASPECT_CROPPING float array _compute_targets astype bbox_transform_inv BBOX_REG_WEIGHTS zeros argmax bbox_overlaps format arange debug classes rjust zeros sum max enumerate len update evaluate_masks_inmodal evaluate_boxes MASK_ON evaluate_masks_amodal info INMODAL_ON _voc_eval_to_box_results _coco_eval_to_box_results _use_cityscapes_evaluator warn info _use_json_dataset_evaluator _use_voc_evaluator _coco_eval_to_mask_results _cs_eval_to_mask_results _use_cityscapes_evaluator _use_json_dataset_evaluator _use_json_dataset_evaluator evaluate_masks _coco_eval_to_mask_results info _use_json_dataset_evaluator evaluate_masks _coco_eval_to_mask_results info _coco_eval_to_keypoint_results info items list format _empty_box_proposal_results items list format keys ljust info max join list format items info keys join format error EXPECTED_RESULTS send_email EXPECTED_RESULTS_EMAIL info abs stats _empty_box_results stats _empty_mask_results _empty_keypoint_results stats _write_voc_results_files _do_matlab_eval copy _do_python_eval format get_roidb info append classes enumerate voc_info join save_object format voc_info mean mkdir classes info voc_eval enumerate join format voc_info info call ROOT_DIR join int parse findall text append find arange concatenate size maximum sum max range parse_rec cumsum argmax max sum range eps format astype mkdir info float enumerate minimum join maximum voc_ap argsort zeros bool array len add_argument exit ArgumentParser print_help print join len load join print endswith len zip append walk open items list format print shape convert_func convert_coco_blob_to_cityscapes_blob int list reshape astype float32 mean shape std range endswith list keys remove_momentum convert_coco_blobs_to_cityscape_blobs int nms_cuda dir _wrap_function getattr append callable items list File create_dataset items list asarray File from_numpy copy_ isinstance Conv2d normal_ modules Linear view grid_sample Variable Size size affine_grid zero_ max_pool2d POOLING_SIZE detach view Variable Size affine_grid zero_ detach Variable view zero_ detach data sum grid_sample backward Variable contiguous grad set_trace RoICropFunction randint forward cuda view size get_device binary_cross_entropy_with_logits float cuda add_stage ROI_XFORM_RESOLUTION DILATION int RPN_POST_NMS_TOP_N concatenate squeeze RPN_MAX_LEVEL RPN_COLLECT_SCALE RPN_MIN_LEVEL get_fast_rcnn_blob_names ROI_MAX_LEVEL map_rois_to_fpn_levels concatenate astype argsort int32 ROI_MIN_LEVEL empty range enumerate len arange smooth_l1_loss type_as mean get_device cuda cross_entropy smooth_l1_loss type_as mean get_device cuda cross_entropy ROI_MAX_LEVEL min RPN_MIN_LEVEL RPN_MAX_LEVEL ROI_MIN_LEVEL max str view smooth_l1_loss RPN_MIN_LEVEL shape RPN_MAX_LEVEL binary_cross_entropy_with_logits append float long range cross_entropy vstack _ratio_enum array hstack sqrt _whctrs round _mkanchors _whctrs _mkanchors view get_device sum cuda cross_entropy HEATMAP_SIZE join range parameters join import_module split append range add_residual_block trans_func shortcut_func USE_GN getattr zip append FPN_ON FPN_ON FPN_ON view smooth_l1_loss size binary_cross_entropy_with_logits float long cross_entropy var view mean shape sqrt len shape mul reduce sqrt shape mul reduce sqrt list scatter_kwargs device_count replicate parallel_apply range items list map isinstance join isinstance _worker len start append range Lock items list broadcast_coalesced tuple _all_buffers copy apply parameters type modules append __new__ range enumerate len tuple extend device_count Stream str generate_anchors int arange COARSEST_STRIDE meshgrid reshape MAX_SIZE transpose FieldOfAnchors ceil float ravel fill empty ROI_MAX_LEVEL KEYPOINTS_ON MASK_ON ROI_MIN_LEVEL range items list concatenate _sample_rois KEYPOINTS_ON _add_multilevel_rois append finalize_keypoint_minibatch enumerate items list concatenate _sample_rois KEYPOINTS_ON _add_multilevel_rois_panet append finalize_keypoint_minibatch enumerate minimum int FG_FRACTION add_mask_rcnn_blobs BATCH_SIZE_PER_IM KEYPOINTS_ON ones size _compute_targets hstack MASK_ON choice dict add_keypoint_rcnn_blobs _expand_bbox_targets append round array round KEYPOINTS_ON ones MASK_ON add_keypoint_rcnn_blobs append ceil range FG_FRACTION add_mask_rcnn_blobs BATCH_SIZE_PER_IM size hstack shuffle choice unique _expand_bbox_targets float enumerate minimum int _compute_targets argsort dict zeros array len CLS_AGNOSTIC_BBOX_REG clip int CLS_AGNOSTIC_BBOX_REG NUM_CLASSES shape zeros ROI_MAX_LEVEL KEYPOINTS_ON MASK_ON ROI_MIN_LEVEL _distribute_rois_over_fpn_levels ROI_MAX_LEVEL KEYPOINTS_ON MASK_ON ROI_MIN_LEVEL _distribute_rois_over_fpn_levels AMODAL_ON minimum ones keypoints_to_heatmap_labels size reshape hstack astype choice _within_box int32 range len FG_FRACTION BATCH_SIZE_PER_IM IMS_PER_BATCH NUM_KEYPOINTS MIN_KEYPOINT_COUNT_FOR_VALID_MINIBATCH sum array logical_and int IMS_PER_BATCH min ceil empty range len IMS_PER_BATCH default_collate append pad_image_data range len get_max_shape zeros append shape _expand_to_class_specific_mask_targets ones reshape hstack astype float32 copy rle_mask_to_mask_wrt_box_2 CLS_SPECIFIC_MASK polys_to_boxes array rle_masks_to_boxes zeros RESOLUTION argmax bbox_overlaps range polys_to_mask_wrt_box int RESOLUTION range RETINANET_ON RPN_ON RPN_ON add_fast_rcnn_blobs _get_image_blob RETINANET_ON add_rpn_blobs im_list_to_blob prep_im_for_blob MAX_SIZE PIXEL_MEANS append randint imread range len RPN_MAX_LEVEL RPN_MIN_LEVEL range items RPN_ASPECT_RATIOS list get_field_of_anchors concatenate SIZES _get_rpn_blobs STRIDE RPN_MAX_LEVEL round array field_of_anchors zeros ASPECT_RATIOS RPN_MIN_LEVEL range append enumerate num_cell_anchors arange argmax RPN_FG_FRACTION str transpose shape append sum debug unmap choice RPN_STRADDLE_THRESH fill empty int compute_targets dict RPN_BATCH_SIZE_PER_IM zeros bbox_overlaps field_size len im_list_to_blob prep_im_for_blob PIXEL_MEANS transpose get_max_shape zeros range len int COARSEST_STRIDE FPN_ON ceil float max get_target_scale min astype float32 shape resize append max get_target_scale min append round max float size warn dot array unique ndarray maximum isinstance ndarray isinstance minimum maximum minimum maximum minimum maximum minimum dtype exp BBOX_XFORM_CLIP astype shape zeros transpose log zeros shape copy copy max exp copy range average mean vstack float sum bbox_overlaps log len float32 uint8 ascontiguousarray reshape astype float32 items list isinstance detectron_weight_mapping copy_ Tensor state_dict compile compile use exit boxes_area sqrt log2 ROI_CANONICAL_LEVEL ROI_CANONICAL_SCALE floor clip concatenate astype vstack int32 zeros empty range arange concatenate astype vstack int32 zeros empty range delete int round resize sqrt resize abspath format replace assert_cache_file_is_ok download_url dirname info exists makedirs _get_reference_md5sum _get_file_md5sum int format write float round flush int urlopen strip md5 strip items list index copy where get_keypoints list items index copy int NUM_KEYPOINTS transpose scores_to_probs len maximum copy resize ceil zeros argmax range INFERENCE_MIN_SIZE astype float32 logical_and floor int32 zeros range HEATMAP_SIZE sum exp max range mean compute_oks append exp spacing sum array print format dumps RPN_ON hasattr print FPN_ON info sendmail SMTP MIMEText as_string basicConfig getLogger stdout setFormatter getLogger addHandler StreamHandler Formatter setLevel INFO FileHandler splitext lower is_image_file join listdir append get any append enumerate len deepcopy list defaultdict items __setstate__ param_groups any cast convert_state_dict named_modules mobile_weights_name_pattern copy_ ROOT_DIR list FPN_ON state_dict detectron_weight_mapping AffineChannel2d sqrt splitext IMAGENET_PRETRAINED_WEIGHTS load join items isinstance match Tensor join list int items startswith split sum size pow float abs requires_grad norm parameters sqrt mul_ max param_groups _CorrectMomentum info _get_lr_change_ratio info param_groups _CorrectMomentum enumerate info max view Variable Size affine_grid zero_ detach join epoch format isinstance no_save DataParallel save info step module makedirs detectron_weight_mapping load_state_dict DIM_PER_GP NUM_GROUPS resnet_weights_name_pattern append _flip_rle frPyObjects sum array decode decode maximum append frPyObjects sum array int intersect_mask min where max warpAffine max array min astype float32 resize zeros max min zeros max range len iou min astype maximum average shape array int32 append zeros sum max range len iou transpose maximum argsort append len len get_bounds zeros sum enumerate log_subprocess_output Popen open str list map device_count append range get format array_split NUM_GPUS close copy info enumerate load join isinstance PIPE split join wait close info len range concatenate rectangle decode axis get_class_string CHAIN_APPROX_NONE colormap basename ones len imshow shape savefig setp Axes range get_keypoints format plot findContours convert_from_cls_format close kp_connections copy add_axes autoscale get_cmap RETR_CCOMP minimum join set_size_inches isinstance Polygon print text reshape add_patch argsort figure Rectangle makedirs NUM_THREADS SGD assert_and_infer_cfg load_detectron use_tfboard basename Adam map device_count tic parse_args set_cfgs save_ckpt DATASETS average_time NUM_GPUS start_epoch info zip start_iter IterTic toc load_detectron_weight requires_grad combined_roidb_for_training NUM_CLASSES load_optimizer_state_dict empty_cache step GAMMA zero_grad DataLoader DataParallel ckpt_num_per_epoch list log_training_stats append PROPOSAL_FILES get_run_name IMS_PER_BATCH maskRCNN resume optimizer RoiDataLoader load_ckpt BASE_LR train IterToc cuda defaultdict cfg_from_file UpdateIterStats exit len run_name range cfg_from_list MinibatchSampler num_epochs pop load Generalized_RCNN print num_workers decay_learning_rate batch_size CUDA disp_interval SummaryWriter cfg_file format epoch lr items int backward TrainingStats lr_decay_gamma get_output_dir makedirs misc_args log_stats GetStats tblogger tb_log_stats state_dict setup_logging_to_file iter WARM_UP_ITERS join STEPS LogIterStats WARM_UP_FACTOR update_learning_rate next iter_size MAX_ITER start_step BatchSampler RPN_COLLECT_SCALE SNAPSHOT_ITERS WARM_UP_METHOD | # [Amodal Instance Segmentation through KINS Dataset](http://jiaya.me/papers/amodel_cvpr19.pdf) by [Lu Qi](http://www.luqi.info), Li Jiang, [Shu Liu](http://www.shuliu.me), [Xiaoyong Shen](http://xiaoyongshen.me/), [Jiaya Jia](http://www.cse.cuhk.edu.hk/leojia/). # Update! (16.02.2020) - **We update the new annotation with occlusion order in update_train_2020.json and update_test_2020.json. The visualization code is in vis_json_2020.py. Please download in here(https://drive.google.com/drive/folders/1FuXz1Rrv5rrGG4n7KcQHVWKvSyr3Tkyo?usp=sharing).** - "a_\*" and "i_\*" represent the amodal and inmodal annotation. - **The "oco_id" and "ico_id" represent the cluster id and the relative occlusion id in this cluster for instances.** As paper said, instances in an image are first partitioned into several disconnected clusters, each with a few connected instances for easy occlusion detection. Relative occlusion order is based on the distance of each instance to the camera. The non-overlapping instances are labeled as 0. As for the occluded instances in a cluster, order starts from 1 and increases by 1 when occluded once. ## Introduction This repository has released the training and test set of KINS. The annotation format follows COCO style. The mask can be decoded by COCOAPI. And the reference code of the method in CVPR 2019 paper '[Amodal Instance Segmentation through KINS Dataset](http://jiaya.me/papers/amodel_cvpr19.pdf)' has been released. The codebase is based on [pytorch-detectron](https://github.com/roytseng-tw/Detectron.pytorch). You can see some details from our released code. I am sorry that I can not transform it into the maskrcnn-benchmark with clear version. | 3,375 |
qslim/epcb-gnns | ['graph property prediction'] | ['Breaking the Expressive Bottlenecks of Graph Neural Networks'] | tu/main.py ogbg/ppa/main.py qm9/conv.py ogbg/code/conv.py qm9/model.py utils/config.py ogbg/ppa/model.py utils/qm9.py ogbg/ppa/conv.py ogbg/code/model.py tu/conv.py tu/model.py utils/jumping_knowledge.py ogbg/mol/conv.py qm9/main.py ogbg/code/main.py ogbg/mol/model.py ogbg/mol/main.py ogbg/code/proc.py ExpC_star GinConv CombC_star CombC ExpC main eval train In Net encode_y_to_arr test encode_seq_to_arr ASTNodeEncoder decode_arr_to_seq augment_edge get_vocab_mapping ExpC_star GinConv CombC_star CombC ExpC main eval train In Net ExpC_star GinConv CombC_star CombC ExpC add_zeros eval main train In Net ExpC_star GinConv CombC_star CombC ExpC train MyTransform test Net ExpC_star CombC_star CombC ExpC NormalizedDegree run_given_fold test get_dataset run_model main train k_fold Net process_config get_args get_config_from_json JumpingKnowledge QM9 format model backward print zero_grad to step range enumerate len view extend enumerate append to range cat len PygGraphPropPredDataset layers batch_size DataLoader device argmax In max decay_rate seed str dataset_name step_size StepLR hidden time_stamp Adam epochs append to sum process_config CrossEntropyLoss range manual_seed_all SummaryWriter format get_args dropout directory Compose Evaluator JK close num_vocab eval get_vocab_mapping manual_seed is_available root pooling add_scalars join learning_rate methods BN print max_seq_len min get_idx_split parameters ASTNodeEncoder train step array read_csv len format print append float sum array enumerate ones edge_index stack zeros cat y encode_seq_to_arr max len nonzero items list print decode_arr_to_seq get_vocab_mapping reg_criterion cls_criterion cpu numpy argmin task_type view float32 multicls_criterion zeros num_nodes y mse_loss to eval join NormalizedDegree float realpath TUDataset OneHotDegree dirname item to max nll_loss add_scalars format StepLR dataset_name print train Adam test range epochs parameters append to step net y view ones StratifiedKFold len from_numpy append zeros range split layers batch_size DataLoader argmax max decay_rate str dataset_name step_size hidden time_stamp append range get SummaryWriter dropout directory run_given_fold close JK k_folds_average zip pooling add_scalars enumerate learning_rate methods BN print min commit_id epochs array shuffle run_model parse_args add_argument ArgumentParser EasyDict config ts dir get_config_from_json id | # Breaking the Expression Bottleneck of Graph Neural Networks [](LICENSE) This is the code of the paper *Breaking the Expression Bottleneck of Graph Neural Networks*. ## Table of Contents <!-- omit in toc --> - [Requirements](#requirements) - [Run Experiments](#run-experiments) - [ogbg-ppa](#ogbg-ppa) - [ogbg-code](#ogbg-code) - [ogbg-molhiv & ogbg-molpcba](#ogbg-molhiv--ogbg-molpcba) | 3,376 |
qsyao/attack_landmark_detection | ['adversarial attack'] | ['Miss the Point: Targeted Adversarial Attack on Multiple Landmark Detection'] | train.py container.py network.py eval.py test.py plot.py attack.py utils.py data_loader.py mylogger.py ParameterDict Sequential Container ModuleList ModuleDict ParameterList Evaluater set_logger_dir _get_time_str _MyFormatter get_mylogger mkdir_p _set_file Up DoubleConv OutConv_Sigmoid Down UNet OutConv UNet_Pretrained calculate calculate_epsilon visualize voting make_dir pred2gt distance to_Image voting_channel set_logger_dir setFormatter getLogger addHandler _MyFormatter StreamHandler setLevel setFormatter join format isfile _get_time_str argv move addHandler _MyFormatter info FileHandler join format _get_time_str move rmtree dir_nonempty mkdir_p info _set_file makedirs list format print mean append median sum len list mean append sum len append list range zeros abs sqrt power min to_PIL save cpu max int reshape put shape zeros range get int topk list Process join shape start Queue cpu zeros range append int truetype str Draw text min polygon pred2gt rectangle unsqueeze to_PIL cpu max enumerate len mkdir Path | qsyao/attack_landmark_detection | 3,377 |
qureshi-mi/S-ADDOPT | ['stochastic optimization'] | ['S-ADDOPT: Decentralized stochastic first-order optimization over directed graphs'] | LogisticRegression/cifar10.py LogisticRegression/Problems/log_reg_cifar.py NeuralNetwork/graph.py LogisticRegression/ExponentialNetwork.py LogisticRegression/download.py NeuralNetwork/Optimizers/COPTIMIZER.py NeuralNetwork/cifar10.py LogisticRegression/utilities.py NeuralNetwork/Problems/centralized/problem.py NeuralNetwork/cache.py LogisticRegression/Optimizers/COPTIMIZER.py NeuralNetwork/NeuralNetwork.py LogisticRegression/Problems/logistic_regression.py NeuralNetwork/dataset.py NeuralNetwork/Problems/centralized/neural_network_mnist.py NeuralNetwork/Problems/my_neural_network_cifar.py LogisticRegression/Optimizers/DOPTIMIZER.py LogisticRegression/graph.py NeuralNetwork/Problems/centralized/neural_network_cifar.py LogisticRegression/cache.py LogisticRegression/GeometricNetwork.py NeuralNetwork/download.py NeuralNetwork/Optimizers/DOPTIMIZER.py NeuralNetwork/Problems/my_neural_network_mnist.py NeuralNetwork/utilities.py LogisticRegression/analysis.py LogisticRegression/dataset.py error cache ExpensiveClass expensive_function convert_numpy2pickle load_class_names _load_data load_test_data _get_file_path _convert_images load_training_data _unpickle maybe_download_and_extract load_cached one_hot_encoded DataSet _print_download_progress download maybe_download_and_extract Geometric_graph Weight_matrix Exponential_graph nx_options monitor CSGD CNGD CGD SGP ADDOPT GP SADDOPT LR_L2 LR_L4 cache ExpensiveClass expensive_function convert_numpy2pickle load_class_names _load_data load_test_data _get_file_path _convert_images load_training_data _unpickle maybe_download_and_extract load_cached one_hot_encoded DataSet _print_download_progress download maybe_download_and_extract Geometric_graph Weight_matrix Exponential_graph nx_options monitor CSGD CNGD CGD SGP ADDOPT GP SADDOPT NN_cifar NN_mnist sigmoid softmax NN softmax_loss sigmoid softmax NN softmax_loss Problem print fn exists load print _get_file_path reshape transpose array array _unpickle _convert_images zeros len range _load_data _load_data max print cache format min write float flush print join urlretrieve makedirs join urlretrieve print endswith extractall makedirs print int monitor F_val grad append range deepcopy monitor grad F_val append range deepcopy monitor grad randint append N range networkgrad monitor ones inv matmul append range diag networkgrad deepcopy monitor ones inv matmul append range diag deepcopy networkgrad monitor ones inv matmul append range array diag deepcopy networkgrad monitor ones inv matmul append range array diag exp | # S-ADDOPT The code demonstrates the performance of SADDOPT with other comparable algorithms over directed graphs including GP, SGP, ADDOPT and SADDOPT presented in the paper: "https://arxiv.org/abs/2005.07785". We include the experiments for classification using logistic regression and neural networks. ## Dependencies and Setup All code runs on Python 3.6.7. We use some code from: "https://github.com/Hvass-Labs/TensorFlow-Tutorials" to download the CIFAR-10 dataset. ## Running Experiments There are three main scripts: 1) LogisticRegression/ExponentialNetwork.py 2) LogisticRegression/GeometricNetwork.py 3) NeuralNetwork/NeuralNetwork.py The rest of the files contain the classes and methods used to implement these files. The user needs to run "LogisticRegression/ExponentialNetwork.py" to simulate the results for classification of MNIST and CIFAR-10 datasets using logistic regression over an exponential graph of 16 nodes. Run "LogisticRegression/GeometricNetwork.py" to simulate the classification of MNIST and CIFAR-10 datasets using logistic regression over a 500 node geometric graph. Simulate "NeuralNetwork/NeuralNetwork.py" to get the results for classification using neural networks distributed over a geometric graph of 500 nodes. | 3,378 |
qureshi-mi/SADDOPT | ['stochastic optimization'] | ['S-ADDOPT: Decentralized stochastic first-order optimization over directed graphs'] | LogisticRegression/cifar10.py LogisticRegression/Problems/log_reg_cifar.py NeuralNetwork/graph.py LogisticRegression/ExponentialNetwork.py LogisticRegression/download.py NeuralNetwork/Optimizers/COPTIMIZER.py NeuralNetwork/cifar10.py LogisticRegression/utilities.py NeuralNetwork/Problems/centralized/problem.py NeuralNetwork/cache.py LogisticRegression/Optimizers/COPTIMIZER.py NeuralNetwork/NeuralNetwork.py LogisticRegression/Problems/logistic_regression.py NeuralNetwork/dataset.py NeuralNetwork/Problems/centralized/neural_network_mnist.py NeuralNetwork/Problems/my_neural_network_cifar.py LogisticRegression/Optimizers/DOPTIMIZER.py LogisticRegression/graph.py NeuralNetwork/Problems/centralized/neural_network_cifar.py LogisticRegression/cache.py LogisticRegression/GeometricNetwork.py NeuralNetwork/download.py NeuralNetwork/Optimizers/DOPTIMIZER.py NeuralNetwork/Problems/my_neural_network_mnist.py NeuralNetwork/utilities.py LogisticRegression/analysis.py LogisticRegression/dataset.py error cache ExpensiveClass expensive_function convert_numpy2pickle load_class_names _load_data load_test_data _get_file_path _convert_images load_training_data _unpickle maybe_download_and_extract load_cached one_hot_encoded DataSet _print_download_progress download maybe_download_and_extract Geometric_graph Weight_matrix Exponential_graph nx_options monitor CSGD CNGD CGD SGP ADDOPT GP SADDOPT LR_L2 LR_L4 cache ExpensiveClass expensive_function convert_numpy2pickle load_class_names _load_data load_test_data _get_file_path _convert_images load_training_data _unpickle maybe_download_and_extract load_cached one_hot_encoded DataSet _print_download_progress download maybe_download_and_extract Geometric_graph Weight_matrix Exponential_graph nx_options monitor CSGD CNGD CGD SGP ADDOPT GP SADDOPT NN_cifar NN_mnist sigmoid softmax NN softmax_loss sigmoid softmax NN softmax_loss Problem print fn exists load print _get_file_path reshape transpose array array _unpickle _convert_images zeros len range _load_data _load_data max print cache format min write float flush print join urlretrieve makedirs join urlretrieve print endswith extractall makedirs print int monitor F_val grad append range deepcopy monitor grad F_val append range deepcopy monitor grad randint append N range networkgrad monitor ones inv matmul append range diag networkgrad deepcopy monitor ones inv matmul append range diag deepcopy networkgrad monitor ones inv matmul append range array diag deepcopy networkgrad monitor ones inv matmul append range array diag exp | # S-ADDOPT The code demonstrates the performance of SADDOPT with other comparable algorithms over directed graphs including GP, SGP, ADDOPT and SADDOPT presented in the paper: "https://arxiv.org/abs/2005.07785". We include the experiments for classification using logistic regression and neural networks. ## Dependencies and Setup All code runs on Python 3.6.7. We use some code from: "https://github.com/Hvass-Labs/TensorFlow-Tutorials" to download the CIFAR-10 dataset. ## Running Experiments There are three main scripts: 1) LogisticRegression/ExponentialNetwork.py 2) LogisticRegression/GeometricNetwork.py 3) NeuralNetwork/NeuralNetwork.py The rest of the files contain the classes and methods used to implement these files. The user needs to run "LogisticRegression/ExponentialNetwork.py" to simulate the results for classification of MNIST and CIFAR-10 datasets using logistic regression over an exponential graph of 16 nodes. Run "LogisticRegression/GeometricNetwork.py" to simulate the classification of MNIST and CIFAR-10 datasets using logistic regression over a 500 node geometric graph. Simulate "NeuralNetwork/NeuralNetwork.py" to get the results for classification using neural networks distributed over a geometric graph of 500 nodes. | 3,379 |
qwarts/video_classification | ['action recognition'] | ['Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet?'] | generate_result_video/generate_result_video.py train.py validation.py temporal_transforms.py spatial_transforms.py test.py dataset.py TEST.py utils.py opts.py mean.py classify.py main.py target_transforms.py model.py classify_video Video get_class_labels load_annotation_data video_loader make_dataset accimage_loader get_default_image_loader get_default_video_loader pil_loader get_video_names_and_annotations get_mean generate_model parse_opts CenterCrop ToTensor Compose Scale Normalize ClassLabel VideoID Compose LoopPadding TemporalCenterCrop calculate_video_results test train_main train_main_multi_batch train_epoch binary_cross_entropy calculate_accuracy AverageMeter calculate_accuracy_mse load_value_file calculate_accuracy_single_target Logger get_fps data Video model Variable size Compose tolist DataLoader sample_duration append LoopPadding max range cat enumerate join format image_loader append exists get_default_image_loader append items list format deepcopy list IntTensor append listdir range len densenet169 densenet201 resnet50 densenet264 DataParallel resnet101 resnet34 resnet200 resnet18 resnet152 resnet10 cuda densenet121 parse_args set_defaults add_argument ArgumentParser topk size mean stack append range update time format model print Variable cpu AverageMeter size eval calculate_video_results append range enumerate len model zero_grad save cuda log range update format size calculate_accuracy_single_target enumerate join time result_path criterion backward print Variable AverageMeter t zeros train step len str print range max log len getLogger endswith model JsonFormatter calculate_accuracy_mse zero_grad DataLoader save cuda log addHandler exit Adam MSELoss call range state_dict update setFormatter format size Compose StreamHandler sample_duration listdir LoopPadding enumerate join time Video criterion backward print Variable AverageMeter t parameters zeros train step len getLogger batch_size model JsonFormatter calculate_accuracy_mse zero_grad DataLoader save cuda log str addHandler exit Adam MSELoss call range state_dict update setFormatter format size Compose StreamHandler sample_duration listdir LoopPadding enumerate join time int Video criterion backward print Variable AverageMeter t parameters zeros train step len data topk view print size t eq float sum data topk print size t eq topk view print size t sum decode format communicate len round float listdir Popen find | # Video Classification Using 3D ResNet This is a pytorch code for video (action) classification using 3D ResNet trained by [this code](https://github.com/kenshohara/3D-ResNets-PyTorch). The 3D ResNet is trained on the Kinetics dataset, which includes 400 action classes. This code uses videos as inputs and outputs class names and predicted class scores for each 16 frames in the score mode. In the feature mode, this code outputs features of 512 dims (after global average pooling) for each 16 frames. **Torch (Lua) version of this code is available [here](https://github.com/kenshohara/video-classification-3d-cnn).** ## Requirements * [PyTorch](http://pytorch.org/) ``` conda install pytorch torchvision cuda80 -c soumith | 3,380 |
qwopqwop200/SoftPool | ['action recognition'] | ['Refining activation downsampling with SoftPool'] | tensorflow_softpool.py torch_softpool.py SoftPooling3D SoftPooling1D SoftPooling2D test SoftPooling3D SoftPooling1D SoftPooling2D test ones | qwopqwop200/SoftPool | 3,381 |
qxcv/magical | ['imitation learning'] | ['The MAGICAL Benchmark for Robust Imitation'] | magical/version.py magical/__init__.py magical/base_env.py magical/geom.py magical/benchmarks/move_to_corner.py magical/benchmarks/move_to_region.py magical/benchmarks/__init__.py magical/reference_demos.py magical/pyglet_backport/image/imagebuffer.py magical/pyglet_backport/image/__init__.py magical/misc/re_record_demos.py magical/misc/render_demos.py magical/entities.py tests/test_rollout_preproc.py magical/evaluation.py magical/benchmarks/cluster.py magical/misc/benchmark_env_perf.py magical/benchmarks/find_dupe.py magical/benchmarks/match_regions.py magical/misc/convert_demos_to_new_act_format.py magical/gym_render.py magical/benchmarks/make_line.py magical/benchmarks/fix_colour.py magical/style.py magical/__main__.py setup.py magical/phys_vars.py magical/saved_trajectories.py get_version readme ez_init BaseEnv PhysicsVariables ArenaBoundaries Entity RobotAction ShapeType ShapeColour Shape make_finger_vertices EntityIndex GoalRegion Robot latexify_results EvaluationProtocol pm_randomise_all_poses pm_shift_bodies _listify add_vecs regular_poly_circ_rad_to_side_length rect_verts _convert_vec compute_star_verts regular_poly_circumrad mul_vecs rotate_vec PlacementError randomise_hw regular_poly_apothem_to_side_legnth regular_poly_side_length_to_apothem pm_randomise_pose compute_regular_poly_verts Transform PolyLine Image _add_attrs Point make_polyline Geom get_display make_square SimpleImageViewer LineStyle Line make_polygon get_offscreen_fbo FilledPolygon Viewer Compound TransformEgocentric Color Attr make_rect blit_fbo LineWidth make_capsule make_circle _is_var_name PhysicsVariablesBase _PhysicsVariablesMeta PhysVar _recursive_extract DownloadError _main try_download_demos _download_file _MockDemoEnv MAGICALTrajectory splice_in_preproc_name load_demos preprocess_demos_with_wrapper _TrajRewriteUnpickler rgb lighten_rgb darken_rgb main Accumulator get_unique_fn ClusterShapeEnv BaseClusterEnv ClusterColourEnv FindDupeEnv FixColourEnv MakeLineEnv longest_line MatchRegionsEnv MoveToCornerEnv MoveToRegionEnv update_magical_env_name EnvName _gym_tree_map register_envs EagerDictFrameStack lores_stack_entry_point ResizeDictObservation ChannelsFirst FlattenFrameStack lores_ea_entry_point get_cls main do_eval main main get_frames main get_max_color_attachments Renderbuffer Framebuffer Texture AbstractImage test_rollouts test_registered_envs PhysVar max pi rect_verts rotated pi Vec2d join list iterrows print unique append StringIO len pi Vec2d regular_poly_circumrad pi rotated append range Vec2d pi rotated append range isinstance Vec2d _convert_vec _convert_vec rotated Vec2d update int reindex_shapes_for_body pm_shift_bodies zip Vec2d angle pi set shape_query shapes uniform warn position float list isinstance _listify bodies _replace filter pm_randomise_pose zip append shapes range len minimum uniform asarray maximum reindex_shapes_for_body Vec2d angle rotated position float string_types isinstance GL_DEPTH_COMPONENT attach_renderbuffer create GL_COLOR_ATTACHMENT0 _depth_rb GL_TEXTURE_2D_MULTISAMPLE attach_texture glTexImage2D GL_UNSIGNED_BYTE GL_FRAMEBUFFER GL_TEXTURE_2D _colour_texture Renderbuffer GL_DEPTH_ATTACHMENT GL_RGB Framebuffer glTexImage2DMultisample GL_DRAW_FRAMEBUFFER GL_READ_FRAMEBUFFER GL_NEAREST glBindFramebuffer GL_COLOR_BUFFER_BIT glBlitFramebuffer glDrawBuffer set_linewidth set_color append range pi Transform add_attr Compound make_circle make_polygon join exists info get print write raise_for_status float iter_content sep len split basicConfig add_argument try_download_demos ArgumentParser parse_args print enumerate len get make wrapper reset wrapped_constructor append step rgb_to_hls rgb_to_hls now strftime KeyStateHandler debug_print_entity_spec UP register_envs finish_trajectory abspath add_step Accumulator isopen flags_to_action push_handlers render get_unique_fn sleep RIGHT DOWN LEFT fps CLOSE make time join print reset step makedirs groupby norm asarray sort squeeze min diff nonzero abs max range len isinstance cls_lookup isinstance EnvName task variant version append preproc update_magical_env_name items list EnvName sorted update setdefault extend set dict add env_name append is_test register keys demo_env_name sample reset range step seed runctx locals strftime globals asarray MAGICALTrajectory relpath acts tuple load_demos append walk sorted defaultdict obs concatenate append keys list FFmpegWriter writeFrame map dirname get basename replace zip enumerate GLint GL_MAX_COLOR_ATTACHMENTS glGetIntegerv get_max_color_attachments GL_LINEAR seed make reset sample step range | # Multitask Assessment of Generalisation in Imitative Control Algorithms (MAGICAL) [](https://badge.fury.io/py/magical-il) [](https://app.circleci.com/pipelines/github/qxcv/magical) [](https://colab.research.google.com/github/qxcv/magical/blob/pyglet1.5/demo-notebook.ipynb) [](https://arxiv.org/abs/2011.00401) ## A Benchmark Suite for Robust imitation Learning MAGICAL is a benchmark suite to evaluate the generalisation capabilities of imitation learning algorithms. Rather than using the same setting for training and testing, MAGICAL provides one set of "training" environments where demonstrations are observed, and another, distinct set of "testing" environments | 3,382 |
qychen13/ClusterAlignReID | ['person re identification'] | ['Cluster-level Feature Alignment for Person Re-identification'] | utils/center.py datasets/msmt17.py utils/rank_cylib/test_cython.py datasets/dukemtm.py models/model_abd/branches.py utils/metrics.py models/model_layumi.py models/model_abd/resnet.py models/model_strong_baseline/resnet_ibn_a.py arguments/arguments_train.py models/model_strong_baseline/senet.py arguments/arguments_test.py arguments/arguments_base.py models/model_strong_baseline/resnet.py models/__init__.py models/model_strong_baseline/baseline.py models/utils.py utils/evaluation.py utils/rank_cylib/setup.py models/model_base.py trainval.py utils/distance.py models/model_abd/attention.py utils/lr_scheduler.py test.py models/model_abd/__init__.py datasets/sampler.py datasets/market1501.py datasets/__init__.py models/model_abd/shallow_cam.py models/model_mgn/mgn.py datasets/dataset_bases.py utils/construct_engine.py models/model_strong_baseline/__init__.py arguments/__init__.py models/model_mgn/__init__.py utils/rank.py utils/rerank.py config.py datasets/cuhk03.py datasets/utils.py utils/engine.py utils/loss.py get_config get_test_config get_optimizer_config get_metrics_config get_loss_config get_dataset_config get_model_config main main ArgumentsBase ArgumentsTest ArgumentsTrainVal check_isfile CUHK03 CUHK03Detected read_json CUHK03Labeled write_json mkdir_if_missing BaseDataset BaseImageDataset BaseVideoDataset DukeMTMCreID Market1501 MSMT17 RandomIdentitySampler RandomIdentitySampler_alignedreid RandomErasing Random2DTranslation construct_dataset ImageDataset read_image split_train_val BaselineClassifier PersonReidModelNeck resnet50_feature_extractor BottleNeckClassifier resnet50_feature_extractor_v1 weights_init_classifier weight_initialization Identity BNNeckClassifer PersonReidModel ft_net_dense ClassBlock ft_net PCB_test weights_init_classifier ft_net_middle PCB weights_init_kaiming construct_model CAM_Module PAM_Module get_attention_module_instance Identity DANetHead NPBranch Sequential MultiBranchNetwork DANBranch ABDBranch GlobalBranch init_params MultiBranchMGNLikeResNet resnet50_backbone ResNet resnet50 init_pretrained_weights ResNetDeepBranch Bottleneck ResNetMGNLikeCommonBranch ResNetCommonBranch resnet50_mgn_like conv3x3 ResNetMGNLikeDeepBranch MultiBranchResNet BasicBlock ShallowCAM MGN Baseline PCBClassifier weights_init_classifier SqueezeNeck weights_init_kaiming ResNet conv3x3 BasicBlock Bottleneck resnet152_ibn_a resnet50_ibn_a Bottleneck_IBN ResNet_IBN IBN resnet101_ibn_a SENet SEResNetBottleneck SEBottleneck SEResNeXtBottleneck Bottleneck SEModule resnet50v1 resnet50_pcb resnet50 resnet50_pcb_v1 resnet50_ibn_av1 resnet50_ibn_a resnet50v2 calculate_id_features extract_features_for_id update_id_features construct_engine cosine_distance euclidean_squared_distance compute_distance_matrix Engine compute_test_metrics evaluate compute_mAP test test_external evaluate_gpu extract_features fliplr hard_example_mining euclidean_dist CrossEntropyLabelSmooth TripletLoss normalize TripletIDLoss hard_id_mining WarmupMultiStepLR AverageValueMeter ClassAccuracy MetricBase KeyLossMetric eval_market1501 evaluate_py eval_cuhk03 evaluate_rank re_ranking numpy_include update list namedtuple func Configuration keys dict dict dict update items list format isinstance KeyLossMetric key range ClassAccuracy l1_loss CrossEntropyLabelSmooth TripletLoss TripletIDLoss mse_loss resume_epoch StepLR Adam SGD dict MultiStepLR resume_iteration WarmupMultiStepLR load construct_model format print get_config construct_dataset test feature_extractor eval load_state_dict restore_file parse_args cuda gpu_ids resume_iteration lr_scheduler_func construct_engine check_log_dir optimizer_func len base maxepoch resume_epoch param_groups resume join learning_rate lr_scheduler_iter_func dict makedirs makedirs print format isfile dirname mkdir_if_missing RandomErasing gallery RandomIdentitySampler Compose data_directory ImageDataset DataLoader query Normalize append train split_train_val list format defaultdict print append keys len convert data isinstance Conv2d bias normal_ weight kaiming_normal_ constant_ Linear data normal_ __name__ constant_ resnet50 Identity Sequential resnet50_feature_extractor Linear apply BatchNorm1d Dropout data normal_ kaiming_normal_ __name__ constant_ PersonReidModel PersonReidModelNeck lower data isinstance Conv2d bias normal_ weight kaiming_normal_ constant_ Linear load update format print load_state_dict state_dict ResNet init_pretrained_weights resnet50_backbone resnet50_backbone affine bias weight bias weight ResNet_IBN load_url load_state_dict ResNet_IBN load_url load_state_dict ResNet_IBN load_url load_state_dict print isinstance defaultdict isinstance eval cuda cat SummaryWriter Engine cosine_distance euclidean_squared_distance view expand t normalize addmm_ t normalize mm view norm compute_test_metrics print evaluate_gpu div savemat expand_as extract_features FloatTensor evaluate_gpu dict IntTensor loadmat index_select long is_cuda cuda defaultdict isinstance eval cuda cat format re_ranking print strftime from_numpy cpu compute_distance_matrix norm view evaluate div zero_ expand_as cpu float cuda range len setdiff1d view compute_mAP argsort intersect1d numpy argwhere cpu mm append flatten argwhere in1d zero_ range len expand_as t sqrt addmm_ expand data ne view size min squeeze expand t eq gather max bool size type masked_select cumsum list defaultdict shape append sum range format asarray astype choice mean enumerate invert items print float32 argsort int32 zeros len invert format asarray print cumsum astype float32 argsort shape mean int32 append sum range cpu evaluate_py asarray evaluate_cy minimum exp zeros_like concatenate transpose astype float32 mean int32 unique append zeros sum max range len get_include | # Cluster-Level Feature Alignment for Person Re-Identificaiton The proposed anchor loss is simple and highly effective with additional serveral epochs fine-tuning after traditional training stage and brings sigfinicant performance boost. It achieves state-of-the-art based on a simple and strong baseline, [Bag of Tricks and a Strong Baseline for Deep Person Re-Identification](https://openaccess.thecvf.com/content_CVPR_2019/papers/Wang_Ranked_List_Loss_for_Deep_Metric_Learning_CVPR_2019_paper.pdf). Check out our [technical report](https://arxiv.org/abs/2008.06810) for more details.  If you find the technical report or repository is useful, please kindly cite: ``` @article{chen2020cluster-reid, title={Cluster-level Feature Alignment for Person Re-identification}, author={Chen, Qiuyu and Zhang, Wei and Fan, Jianping}, journal={arXiv preprint arXiv:2008.06810}, year={2020} | 3,383 |
qzhang95/SAR-DRN | ['sar image despeckling'] | ['Learning a Dilated Residual Network for SAR Image Despeckling'] | utils.py batch_PSNR data_augmentation weights_init_kaiming data constant clamp_ __name__ kaiming_normal range astype float32 transpose rot90 flipud | # SAR-DRN Learning a Dilated Residual Network for SAR Image Despeckling. http://arxiv.org/abs/1709.02898 | 3,384 |
radhen/BebionicFingerSensor | ['time series'] | ['Real-time regression analysis with deep convolutional neural networks'] | AIME_journal_files/AIME_data/calibDATA_deadWeights/ir_baro_dragon_calibTest/ir+baro_Dragon_calibtest_06_15/Finger_2/readskin_raw.py AIME_journal_files/scripts/GP/GP_sklearn.py AIME_journal_files/AIME_data/calibDATA_deadWeights/ir_baro_dragon_calibTest/ir+baro_Dragon_calibtest_06_15/Thumb/readskin_raw.py AIME_journal_files/scripts/ML/classify_SpatialLoc/svm_spatial.py AIME_journal_files/scripts/plot.py AIME_journal_files/scripts/ML/classify_SpatialLoc/cnn_spatial.py AIME_journal_files/scripts/ML/classify_ProbeAngle/regression.py nn_c/example_usage/radhensNN.py AIME_journal_files/AIME_data/calibDATA_deadWeights/ir_baro_dragon_calibTest/ir+baro_Dragon_calibtest_06_15/finger_1/readskin_raw.py nn_c/modelWeg_textfile.py AIME_journal_files/AIME_data/calibDATA_deadWeights/ir_baro_dragon_calibTest/ir+baro_Dragon_calibTest_05_23/readskin_raw.py AIME_journal_files/AIME_data/calibDATA_deadWeights/ir_baro_calibTest/ir+baro_calibTest_05_19/readskin_raw.py AIME_journal_files/scripts/GP/GPs.py scripts/motor_functions.py AIME_journal_files/AIME_data/calibDATA_deadWeights/ir_baro_dragon_calibTest/ir+baro_Dragon_calibTest_05_19/readskin_raw.py scripts/get_data.py scripts/prox_control.py scripts/motor_control.py AIME_journal_files/scripts/ML/classify_ProbeAngle/plotting.py AIME_journal_files/scripts/ML/classify_ProbeAngle/cnn_angle.py AIME_journal_files/scripts/ML/classify_SpatialLoc/test_svm.py AIME_journal_files/scripts/ML/classify_ProbeAngle/svm_angle.py AIME_journal_files/scripts/readskin_raw.py error kernel load_data preprocessData sortData split_train_test plot_2d split_train_test_SINGLE load_data plot_3d preprocessData gaussian_process sortData NN plot make_patch_spines_invisible load_data preprocessData make_meshgrid plot_contours series_to_supervised make_meshgrid preprocessData load_data FeatureEng preprocessData load_data NN preprocessData load_data FeatureEng GetData push pid_callback MotorFunctions push pid_callback dot reshape T sum float min max sort tolist read_excel reshape sortData show plot concatenate xlabel ylabel figure legend fill show plot set_pane_color set_xlabel set_ylabel figure legend set_zlabel gca RationalQuadratic GaussianProcessRegressor print mean sqrt predict fit concatenate print reshape tolist shuffle shape append preprocessData array reshape preprocessData concatenate list set_frame_on set_visible values show format subplots set_position make_patch_spines_invisible tight_layout set_visible set_ylabel twinx title Figure tick_params format tolist as_matrix zeros range print Series transform StandardScaler range values fit meshgrid arange reshape contourf predict shape concat shift append dropna DataFrame range append zeros max range len int nsecs print get_rostime append secs sum array push | # BebionicFingerSensor Contains python/MATLAB/C script and data files for the paper "Multi-Modal Fingertip Sensor with Proximity, Contact, and Force Localization Capabilities" submitted at AIME journal (link coming soon...) In the top level of the GitHub repository radhen/Bebionics_FungerSensor There is a /scripts folder. It has a /GP (gaussianprocesses) and /ML (machine learning) folder. For /GP these two python files are relevant GP_sklearn.py and GPs.py. GP_sklearn.py is implemned uisng sklearn library. It has some good alrgorithms based on probabilistic and machine learning theory. Try to explore the API online. For /ML, go inside classify_Probangle, that contains files for CNN and SVM to classify probing angle. Three angular locations (0, 20, -20 degree) from the paper I sent. Relevant pythons files are cnn_angle.py and svm_angle.py. Similarly in classify_SpatialLoc the relevant pythons files to classify five spatial locations (ref. paper) are cnn_spatial.py and svm_spatial.py. I am using alignpeaks.m MATALAB files to preprocess the data for the above models. Recall the experimental setup I described to you last time we met. Excel files contains data for different peak loads (1N, 30N, 50N) appllied to the sensor. Python files are calling these Excel files and are further processesing the data for the models. | 3,385 |
raghavchalapathy/Bidirectional-LSTM-CRF-for-Clinical-Concept-Extraction | ['word embeddings'] | ['Bidirectional LSTM-CRF for Clinical Concept Extraction', 'Bidirectional LSTM-CRF for Clinical Concept Extraction'] | tagger/nn.py tagger/optimization.py prepare_i2b2_CoNLL2003_data.py tagger/conceptExtractor.py tagger/train.py tagger/train_loop.py tagger/utils.py tagger/loader.py prepare_i2b2_CoNLL2003_data_ignore_OneWordSentence.py tagger/model.py tagger/compute_vector_embeddings.py createTrain_Valid_Set create_validationDataSet computeConceptDict countNumberOfFiles loadword2VecModel divideDataIntotrain_valid create_testDataSet generateRandomGloveVector count_entitiesWithinDict create_pretrained_EmbeddingFile createCONLL2003Data countEntities prepareIOB_wordList removefilesInDirectoryPath save_train_validDatasets loadGloveModel createTrain_Valid_Set create_validationDataSet computeConceptDict pad_OneWordSentences countNumberOfFiles divideDataIntotrain_valid create_testDataSet count_entitiesWithinDict createCONLL2003Data save_ignoredSentences countEntities prepareIOB_wordList removefilesInDirectoryPath save_train_validDatasets loadword2VecModel loadGloveModel update_tag_scheme prepare_dataset word_mapping load_sentences char_mapping augment_with_pretrained prepare_sentence tag_mapping cap_feature Model HiddenLayer DropoutLayer log_sum_exp LSTM EmbeddingLayer forward Optimization runModelInLoop create_input get_name iob_iobes iob2 pad_word_chars evaluate iobes_iob insert_singletons create_dico set_values zero_digits create_mapping shared iglob iglob split replace open update replace readlines dict open append split int list len append range split update computeConceptDict readlines write len open prepareIOB_wordList removefilesInDirectoryPath range append split int round len Set list shuffle difference append range chdir remove write open removefilesInDirectoryPath range len createTrain_Valid_Set print divideDataIntotrain_valid save_train_validDatasets len join random shuffle open split write open removefilesInDirectoryPath range len print join items len print load_word2vec_format print len split open join print len write loadword2VecModel loadGloveModel open append pad_OneWordSentences len write range open append open split join enumerate zip iob_iobes print create_dico create_mapping print create_dico create_mapping len print create_dico create_mapping len append print create_mapping set max scan concatenate permutation load_sentences dev tag_mapping save_mappings str build Model append range update_tag_scheme create_input word_mapping test copy set model_path enumerate prepare_dataset char_mapping evaluate print augment_with_pretrained f_train reload train len append items list join float32 set_value astype get_value sqrt uniform sum zeros list items sorted enumerate split append replace enumerate append replace enumerate append append max len append pad_word_chars insert_singletons join str format create_input sum print astype randint iobes_iob system int32 zip append zeros argmax range enumerate len | # Bidirectional-LSTM-CRF-for-Clinical-Concept-Extraction Extraction of concepts present in patient clinical records is an essential step in clinical research. The 2010 i2b2/VA Workshop on Natural Language Processing Challenges for clinical records presented concept extraction (CE) task, with aim to identify concepts (such as treatments, tests, problems) and classify them into predefined categories. State-of-the-art CE approaches heavily rely on hand crafted features and domain specific resources which are hard to collect and tune. For this reason, this paper employs bidirectional LSTM with CRF decoding initialized with general purpose off-the-shelf word embeddings for CE. The experimental results achieved on 2010 i2b2/VA reference standard corpora using bidirectional LSTM CRF ranks closely with top ranked systems. | 3,386 |
raghavchalapathy/gad | ['anomaly detection'] | ['Group Anomaly Detection using Deep Generative Models'] | experiments/Stitched_scene/vae/scene_train.py experiments/synthetic_data/vae/cifar10_train.py experiments/cats_n_dogs/vae/cifar10_generate.py experiments/synthetic_data/vae/cifar10_generate.py experiments/Stitched_scene/vae/cifar10_params.py experiments/cats_vs_rotated_cats/aae/aae_keras.py experiments/synthetic_data/rcae/syn_rcae.py experiments/Stitched_scene/rcae/scene_rcae.py experiments/cats_n_dogs/vae/cifar10_train.py experiments/cats_vs_rotated_cats/vae/cifar10_params.py experiments/synthetic_data/vae/cifar10_params.py experiments/Stitched_scene/aae/aae_keras.py experiments/cats_vs_rotated_cats/vae/cifar10_train.py experiments/cats_n_dogs/aae/aae_keras.py experiments/cats_n_dogs/rcae/rcae.py experiments/cats_vs_rotated_cats/vae/cifar10_generate.py experiments/Stitched_scene/vae/scene_generate.py experiments/cats_n_dogs/vae/cifar10_params.py experiments/synthetic_data/aae/aae_keras.py experiments/cats_vs_rotated_cats/rcae/rcae.py experiments/Stitched_scene/rcae/rcae.py evalPred compute_mse visualise_anamolies_detected AdversarialAutoencoder compute_best_worst_rank add_Salt_Pepper_Noise func_slice_stich prepare_cifar_data_with_anamolies precAtK au_roc compute_mse soft_threshold compute_precAtK encoder evalPred compute_softhreshold prepare_cifar_data_with_noise_injection fit_auto_conv_AE loadData load_cifar10catsdogs loadtrainTestData au_prc apk decoder addNoise visualise_anamolies_detected mapk compute_best_worst_rank evalPred compute_mse visualise_anamolies_detected func_slice_stich prepare_cifar_data_with_anamolies compute_best_worst_rank CustomVariationalLayer prepare_cifar_data_with_anamolies sampling func_slice_stich CustomVariationalLayer evalPred compute_mse visualise_anamolies_detected AdversarialAutoencoder compute_best_worst_rank add_Salt_Pepper_Noise func_slice_stich prepare_cifar_data_with_anamolies precAtK au_roc compute_mse soft_threshold compute_precAtK encoder evalPred compute_softhreshold prepare_cifar_data_with_noise_injection fit_auto_conv_AE loadData load_cifar10catsdogs loadtrainTestData au_prc apk decoder addNoise visualise_anamolies_detected mapk compute_best_worst_rank evalPred compute_mse visualise_anamolies_detected func_slice_stich prepare_cifar_data_with_anamolies compute_best_worst_rank CustomVariationalLayer prepare_cifar_data_with_anamolies sampling func_slice_stich CustomVariationalLayer evalPred compute_mse visualise_anamolies_detected precAtK AdversarialAutoencoder compute_best_worst_rank add_Salt_Pepper_Noise prepare_scene_data_with_anomalies func_slice_stich prepare_cifar_data_with_anamolies precAtK au_roc compute_mse soft_threshold compute_precAtK readjpegimages2Array encoder evalPred compute_softhreshold prepare_cifar_data_with_noise_injection fit_auto_conv_AE loadData load_cifar10catsdogs loadtrainTestData au_prc apk decoder addNoise visualise_anamolies_detected mapk compute_best_worst_rank add_Salt_Pepper_Noise evalPred decoder compute_mse addNoise prepare_scene_data_with_anomalies compute_softhreshold prepare_cifar_data_with_noise_injection func_slice_stich_scene fit_auto_conv_AE prepare_cifar_data_with_anamolies visualise_anamolies_detected load_cifar10catsdogs soft_threshold readjpegimages2Array encoder precAtK compute_best_worst_rank evalPred compute_mse prepare_scene_data_with_anomalies visualise_anamolies_detected readjpegimages2Array func_slice_stich prepare_cifar_data_with_anamolies precAtK compute_best_worst_rank CustomVariationalLayer prepare_scene_data_with_anomalies readjpegimages2Array sampling func_slice_stich prepare_cifar_data_with_anamolies CustomVariationalLayer evalPred compute_mse visualise_anamolies_detected AdversarialAutoencoder compute_best_worst_rank add_Salt_Pepper_Noise prepare_synthetic_data_with_anamolies func_slice_stich prepare_cifar_data_with_anamolies precAtK au_roc compute_mse soft_threshold compute_precAtK encoder evalPred compute_softhreshold prepare_cifar_data_with_noise_injection fit_auto_conv_AE loadData load_cifar10catsdogs loadtrainTestData au_prc apk decoder addNoise visualise_anamolies_detected mapk compute_best_worst_rank prepare_synthetic_data_with_anamolies evalPred compute_mse visualise_anamolies_detected func_slice_stich prepare_cifar_data_with_anamolies compute_best_worst_rank CustomVariationalLayer prepare_synthetic_data_with_anamolies sampling func_slice_stich prepare_cifar_data_with_anamolies CustomVariationalLayer update list asarray print reshape shape mean_squared_error values update sorted asarray list reshape shape keys range len uint8 ndarray imsave print astype range print reshape ones average_precision_score precision_score roc_auc_score len print format average_precision_score print format roc_auc_score argsort zeros precision_score shape get_shape conv_2d print fully_connected flatten sigmoid batch_normalization elu W get_shape conv_2d print fully_connected transpose reshape conv_2d_transpose batch_normalization elu W normal random_noise int array_split print hstack where update uint8 concatenate ones print Sequential astype exit where shape savemat array func_slice_stich augment_images full len where print where shape zeros float reshape predict fit asarray print reshape fit_auto_conv_AE soft_threshold range str reshape shape enumerate argsort precision_score print loadmat ravel append loadmat range asarray append loadmat range asarray random_normal precAtK sum append asarray range len concatenate print shape readjpegimages2Array full len hstack array_split func_slice_stich_scene readjpegimages2Array print shape asarray transpose print loadmat ones concatenate | # gad This repository contains experiments conducted for the paper submitted to ECML-2018 Group Anomaly detection using deep generative models. The datasets used in the experiments can be found here : [Datasets](https://drive.google.com/open?id=1KE-mqKd1pVYt9WjV-ojaYPsNVVhX-Ybe) | 3,387 |
raghavchalapathy/oc-nn | ['anomaly detection'] | ['Anomaly Detection using One-Class Neural Networks', 'Robust, Deep and Inductive Anomaly Detection'] | src/models/RCAE_Cifar10.py src/data/modules.py src/data/base.py src/data/main.py src/utils/misc.py src/utils/visualization/filters_plot.py models/LSTM_AE_OCSVM_models.py models/CAE_OCSVM_models.py models/synthetic_models.py src/data/cifar10.py models/sklearn_OCSVM_explicit_model.py src/utils/visualization/line_plot.py models/mnist_ae2.py models/models.py src/models/Fake_Noise_FF_NN.py models/keras_tl_oc_nn_cifar.py src/models/FF_NN.py models/tf_OneClass_NN_model_plot_scores.py models/plot_syn_scores.py models/sklearn_isolation_forest.py models/spam_models.py src/models/Deep_SVDD.py setup.py models/OCSVM_dogs_vs_cats.py models/plot_mnist_scores.py models/OCSVM_cifar.py models/sklearn_OCSVM_explicit_plot_scores.py models/tf_OneClass_NN_model.py models/DBN2_OCSVM_models.py models/OneClass_NN_model.py models/img_to_vec.py src/utils/visualization/five_number_plot.py src/models/svm.py models/AE_SVDD_models.py models/tflearn_OneClass_NN_model_plot_scores.py models/plot_scores.py models/test2.py models/plot_pfam_scores.py src/data/preprocessing.py src/models/Lenet.py src/models/RCAE_Verion1.py src/utils/visualization/mosaic_plot.py models/mnist_models.py models/cifar10vgg.py models/plot_cifar_scores.py src/data/iterator.py src/utils/pickle.py src/models/OC_NN.py models/dataset.py src/models/RCAE.py models/tf_OneClass_CNN_model.py src/models/Copy of OneClass_SVDD.py models/RDA_models.py src/models/ocnn.py models/sklearn_OCSVM_model.py src/models/OneClass_SVDD.py src/models/isoForest.py src/models/ocsvmSklearn.py src/utils/__init__.py src/data/Copy of mnist.py models/OneClass_NN_model_plot_scores.py src/utils/monitoring.py models/RCAE_models.py src/config.py src/data/__local__.py models/plot_spam_scores.py models/tf_Cifar_OC_NN_Models.py models/test.py src/debug/debug_mnist.py models/fake_news_models.py models/plot_fake_news_scores.py src/models/kernels/__init__.py src/models/kernels/weighted_degree.py src/models/SupervisedNN.py src/models/fakeNoiseNN.py models/OCSVM_Autoencoder_model.py models/plot_synthetic_scores_old.py models/pfam_models.py src/models/ocnnFakeNoise.py models/test_without_OC_nn.py src/data/GTSRB.py src/utils/visualization/diagnostics_plot.py models/plot_synthetic_scores.py models/tflearn_OneClass_NN_model.py src/debug/debug_ocnn.py models/plot_syn_scores_with_subplots.py models/cifar_models.py src/models/kernels/degree.py src/utils/diag.py models/usps_models.py models/sklearn_OCSVM_rpca.py src/models/config.py src/utils/log.py src/data/make_dataset.py src/data/mnist.py models/r_pca.py src/models/kde.py models/plot_usps_scores.py src/utils/visualization/scatter_plot.py src/utils/visualization/images_plot.py src/models/DCAE.py add_new_last_layer nnScore relu add_new_last_layer nnScore relu prepare_cifar_data_for_cae_ocsvm AE2_SVDD_Linear add_new_last_layer prepare_usps_data_for_cae_ocsvm prepare_mnist_data_for_cae_ocsvm AE2_SVDD_RBF prepare_cifar_data_for_cae_ocsvm add_new_last_layer CAE_OCSVM_RBF prepare_usps_data_for_cae_ocsvm write_decisionScores2Csv prepare_mnist_data_for_cae_ocsvm plotNNFilter CAE_OCSVM_Linear prepare_cifar_data_with_anamolies cifar10vgg func_getDecision_Scores_cifar write_training_test_results load_test load_train DataSet read_test_set read_train_sets add_new_last_layer nnScore relu func_getDecision_Scores_fake_news Img2Vec add_new_last_layer nnScore relu tf_OneClass_LSTM_AE_NN_sigmoid LSTMAE_OCSVM_Linear tf_OneClass_LSTM_AE_NN_linear AE_OCSVM_Linear add_new_last_layer AE_OCSVM_RBF LSTMAE_OCSVM_RBF prepare_data_LSTM_AE_OCSVM build_deep_autoencoder prepare_mnist_mlfetch tf_mnist_OneClass_NN_linear AE2_SVDD_Linear func_getDecision_Scores_usps_old CAE_OCSVM_RBF usps_autoencoder_representation CAE_OCSVM_Linear write_decisionScores2Csv prepare_usps_mlfetch tf_mnist_OneClass_NN_sigmoid write_training_test_results tf_mnist_OneClass_NN_Relu func_getDecision_Scores_mnist AE2_SVDD_RBF func_getDecision_Scores_CIFAR_10 func_getDecision_Scores_FAKE_NEWS func_getDecision_Scores_USPS func_getDecision_Scores_SPAM_VS_HAM add_new_last_layer nnScore relu add_new_last_layer nnScore relu ocnn_obj One_Class_NN_explicit_linear relu ocnn_grad nnScore One_Class_NN_explicit_sigmoid dRelu func_getDecision_Scores_One_Class_NN_explicit plot_decision_scores_One_Class_NN_explicit tf_OneClass_LSTM_AE_NN_sigmoid LSTMAE_OCSVM_Linear tf_OneClass_LSTM_AE_NN_linear prepare_pfam_data_for_ocsvm_isolationForest add_new_last_layer write_decisionScores2Csv encode_pfam_data_for_ae_ocsvm LSTMAE_OCSVM_RBF tf_OneClass_LSTM_AE_NN_Relu prepare_data_LSTM_AE_OCSVM write_training_test_results func_getDecision_Scores_pfam plot_decision_scores_CIFAR_10 plot_decision_scores_CIFAR plot_decision_scores_FAKE_NEWS plot_decision_scores_MNIST plot_decision_scores_pfam plot_decision_scores_USPS plot_decision_scores plot_decision_scores_SPAM plot_decision_scores plot_decision_scores_SYNTHETIC plot_decision_scores_USPS plot_decision_scores plot_decision_scores_SYN_new plot_decision_scores plot_decision_scores_Synthetic plot_decision_scores_SYN plot_decision_scores plot_decision_scores_USPS plot_decision_scores_USPS_new plot_decision_scores add_new_last_layer nnScore relu R_pca sklearn_IsolationForest func_getDecision_Scores_sklearn_OCSVM_explicit ocsvm_obj sklearn_OCSVM_explicit_sigmoid relu sklearn_OCSVM_explicit_linear ocsvm_grad svmScore dRelu plot_decision_scores_sklearn_OCSVM_explicit sklearn_OCSVM_linear write_decisionScores2Csv sklearn_OCSVM_rbf func_getKerasModelfeatures func_getDecision_Scores_sklearn_OCSVM sklearn_RPCA_OCSVM_Linear sklearn_RPCA_OCSVM_rbf sklearn__RPCA_OCSVM func_getDecision_Scores_spam prepare_usps_mlfetch func_getDecision_Scores_synthetic write_decisionScores2Csv plotNNFilter plotNNFilter tflearn_OneClass_NN_linear func_getDecision_Scores_tflearn_OneClass_NN tflearn_OneClass_NN_Sigmoid plot_decision_scores_tflearn_OneClass_NN tf_OneClass_NN_linear relu nnScore write_decisionScores2Csv tf_OneClass_NN_relu tf_OneClass_NN_sigmoid func_get_ImageVectors ocnn_obj g relu nnScore getConv_features init_weights tf_OneClass_CNN_linear init_weights_2 create_ConvFeatureInputs func_getKerasModelfeatures init_weights_1 tf_OneClass_CNN_sigmoid forwardprop write_decisionScores2Csv tf_OneClass_NN_linear tf_OneClass_NN_Relu tf_OneClass_NN_sigmoid plot_decision_scores_tf_One_Class_NN AE2_SVDD_Linear func_getDecision_Scores_usps_old func_getDecision_Scores_usps CAE_OCSVM_RBF usps_autoencoder_representation CAE_OCSVM_Linear write_decisionScores2Csv prepare_usps_mlfetch write_training_test_results AE2_SVDD_RBF Configuration DataLoader CIFAR_10_DataLoader debug_visualise_anamolies_detected load_mnist_images MNIST_DataLoader RcaeParamSaver load_mnist_labels readTrafficSigns_asnparray PIL2array GTSRB_DataLoader debug_visualise_anamolies_detected readTrafficSigns plot_cifar indices_generator iterate_batches MyScheme load_dataset CreateDataSet load_mnist_images MNIST_DataLoader RcaeParamSaver load_mnist_labels addConvModule crop_to_square learn_dictionary extract_norm_and_out zca_whitening center_data rescale_to_unit_interval normalize_data pca gcn make_unit_norm global_contrast_normalization downscale Configuration Adjust_svdd_Radius OneClass_SVDD DCAE Deep_SVDD SupervisedFakeNoiseNN Fake_Noise_FF_NN FF_NN IsoForest KDE LeNet OCNN OCNNFakeNoiseNN OCSVM OC_NN Adjust_svdd_Radius OneClass_SVDD debug_visualise_anamolies_detected RCAE_AD debug_visualise_anamolies_detected RCAE_AD debug_visualise_anamolies_detected RCAE_AD SupervisedNN SVM degree_kernel weighted_degree_kernel NNetParamDiag NNetDataDiag log_isoForest AD_Log Log log_NeuralNet log_exp_config log_AD_results log_SVM log_KDE flush_last_line get_five_number_summary performance print_obj_and_acc ae_performance load_isoForest dump_svm load_svm dump_kde load_weights load_kde dump_isoForest dump_weights plot_random_reconstructions plot_parameter_norms plot_diagnostics plot_ae_diagnostics plot_accuracy plot_scores plot_objective_with_parts plot_representation_norms plot_auc plot_center_c_diagnostics plot_objectives plot_filters plot_five_number_summary plot_outliers_and_most_normal plot_line plot_mosaic plot_2Dscatter print output shape Model input layers to_categorical decision_function resize sorted list load_model shape Model OneClassSVM list_images input append imread predict update img_to_array add_new_last_layer get_layer time print fit output summary array len layers to_categorical decision_function resize sorted list load_model shape Model OneClassSVM list_images input append imread predict update img_to_array add_new_last_layer get_layer time print fit output summary array len layers to_categorical resize sorted list load_model Model list_images input append imread predict update img_to_array add_new_last_layer get_layer print output summary array len layers to_categorical resize sorted list load_model Model list_images input append imread predict update img_to_array add_new_last_layer get_layer print output summary array len layers to_categorical resize sorted list load_model Model list_images input append imread predict update img_to_array add_new_last_layer get_layer print output summary array len print tolist close zip_longest subplot print reshape axis imshow savefig figure ceil range time print OneClassSVM decision_function write_decisionScores2Csv savemat fit time print OneClassSVM decision_function write_decisionScores2Csv fit where concatenate tf_OneClass_NN_linear sklearn_IsolationForest sklearn_OCSVM_linear print AE2_SVDD_Linear CAE_OCSVM_RBF sklearn__RPCA_OCSVM tf_OneClass_NN_relu sklearn_OCSVM_rbf write_training_test_results tf_OneClass_NN_sigmoid CAE_OCSVM_Linear AE2_SVDD_RBF print str write open join format basename print glob len index resize append zeros imread array INTER_LINEAR join sorted basename glob print astype resize append imread array INTER_LINEAR load_train print shuffle DataSets len load_test sklearn_OCSVM_explicit_sigmoid One_Class_NN_explicit_linear tf_OneClass_NN_linear sklearn_OCSVM_explicit_linear print sklearn_OCSVM_linear One_Class_NN_explicit_sigmoid sklearn_OCSVM_rbf tf_OneClass_NN_sigmoid time print OneClassSVM decision_function fit time print OneClassSVM decision_function fit load asarray print reshape shape OneClassSVM decision_function append fit load asarray print reshape shape OneClassSVM decision_function append fit load asarray print reshape shape append normal ocnn_obj global_variables_initializer minimize print close nnScore placeholder set_random_seed init_weights run reset_default_graph range Session get_variable forwardprop normal ocnn_obj global_variables_initializer minimize print close nnScore placeholder set_random_seed range init_weights run reset_default_graph argmax Session get_variable load_data where concatenate Reshape Sequential add Dense InputLayer Flatten where concatenate tf_mnist_OneClass_NN_linear sklearn_IsolationForest sklearn_OCSVM_linear print AE2_SVDD_Linear CAE_OCSVM_RBF sklearn__RPCA_OCSVM tf_mnist_OneClass_NN_sigmoid sklearn_OCSVM_rbf write_training_test_results tf_mnist_OneClass_NN_Relu CAE_OCSVM_Linear AE2_SVDD_RBF print reshape astype predict shape Model summary append Input compile fit sklearn_OCSVM_explicit_sigmoid One_Class_NN_explicit_linear tf_OneClass_NN_linear sklearn_OCSVM_explicit_linear print sklearn_OCSVM_linear One_Class_NN_explicit_sigmoid sklearn_OCSVM_rbf tf_OneClass_NN_sigmoid nnScore set_random_seed reset_default_graph argmax Session forwardprop run ocnn_obj get_variable placeholder write_decisionScores2Csv range normal close init_weights time minimize print global_variables_initializer nnScore set_random_seed reset_default_graph argmax Session forwardprop run ocnn_obj get_variable placeholder write_decisionScores2Csv range normal close init_weights time minimize print global_variables_initializer forwardprop normal ocnn_obj global_variables_initializer minimize print close nnScore placeholder set_random_seed range init_weights run reset_default_graph argmax Session get_variable print print print print ones relu reshape nnScore mean sum reshape concatenate nnScore dRelu seed normal minimize print check_grad reshape sort nnScore x seed normal minimize print check_grad reshape sort nnScore x One_Class_NN_explicit_sigmoid One_Class_NN_explicit_linear add_subplot tight_layout title hist figure legend tf_OneClass_LSTM_AE_NN_sigmoid sklearn_RPCA_OCSVM_Linear tf_OneClass_LSTM_AE_NN_linear LSTMAE_OCSVM_Linear sklearn_IsolationForest sklearn_OCSVM_linear print AE_OCSVM_Linear sklearn_RPCA_OCSVM_rbf AE_OCSVM_RBF LSTMAE_OCSVM_RBF tf_OneClass_LSTM_AE_NN_Relu sklearn_OCSVM_rbf write_training_test_results time write_decisionScores2Csv time write_decisionScores2Csv time write_decisionScores2Csv write_decisionScores2Csv time forwardprop normal ocnn_obj global_variables_initializer minimize print close nnScore placeholder set_random_seed range init_weights run reset_default_graph argmax Session get_variable to_vecs asarray print load_protvec shape append range read_csv len layers load_model print add_new_last_layer output Model get_layer summary input predict len subplots set_title suptitle hist legend setp subplots set_title suptitle hist legend setp subplots set_title suptitle title hist legend setp subplots set_title suptitle print hist legend setp subplots set_title suptitle hist legend setp subplots set_title suptitle title hist legend setp items list title hist legend DataFrame subplots set_title suptitle title hist legend setp subplots set_title suptitle hist legend setp subplots arange set_title hist legend setp xticks list subplots title hist savefig legend xticks range yticks subplots set_title suptitle hist legend setp list subplots title hist savefig legend xticks range yticks time print shape IsolationForest predict fit mean sum svmScore relu append mean svmScore dRelu seed normal minimize print check_grad svmScore seed normal minimize print check_grad svmScore sklearn_OCSVM_explicit_sigmoid sklearn_OCSVM_explicit_linear add_subplot tight_layout title hist figure legend format print File close shape type array time print OneClassSVM decision_function write_decisionScores2Csv fit time print OneClassSVM decision_function write_decisionScores2Csv fit sklearn_OCSVM_rbf sklearn_OCSVM_linear R_pca time print shape OneClassSVM predict fit R_pca time print shape OneClassSVM predict fit R_pca time print shape OneClassSVM predict fit print sklearn_OCSVM_rbf sklearn_OCSVM_linear sklearn_OCSVM_explicit_sigmoid One_Class_NN_explicit_linear tf_OneClass_NN_linear sklearn_IsolationForest sklearn_OCSVM_explicit_linear print sklearn_OCSVM_linear CAE_OCSVM_RBF tf_OneClass_NN_Relu sklearn__RPCA_OCSVM One_Class_NN_explicit_sigmoid sklearn_OCSVM_rbf tf_OneClass_NN_sigmoid CAE_OCSVM_Linear fully_connected variable get_value input_data nnScore DNN is_training reset_default_graph Session W set_weights seed run percentile set_value get_training_mode append initialize_all_variables get_weights predict normal astype eval constant_initializer print reshape float32 oneClassNN fit fully_connected variable get_value input_data nnScore DNN is_training reset_default_graph Session W set_weights seed run percentile set_value get_training_mode append initialize_all_variables get_weights predict normal astype eval constant_initializer print reshape float32 oneClassNN fit tflearn_OneClass_NN_linear tolist tflearn_OneClass_NN_Sigmoid add_subplot tight_layout title hist figure legend normal ocnn_obj time global_variables_initializer minimize print close nnScore placeholder set_random_seed init_weights run reset_default_graph range Session get_variable nnScore set_random_seed reset_default_graph argmax Session forwardprop run ocnn_obj get_variable placeholder range normal close init_weights time minimize print data_rep savemat global_variables_initializer forwardprop normal ocnn_obj global_variables_initializer minimize print close nnScore placeholder set_random_seed range init_weights run reset_default_graph argmax Session get_variable asarray iglob print get_vec Img2Vec append open wrap train infer random_normal load load get_shape print float32 matmul cast cast float32 float32 reduce_sum reduce_mean cast ocnn_obj minimize print close nnScore range set_random_seed shape init_weights_2 run global_variables_initializer func_getKerasModelfeatures argmax Session init_weights_1 forwardprop ocnn_obj minimize print close nnScore range set_random_seed init_weights_2 run global_variables_initializer func_getKerasModelfeatures argmax Session init_weights_1 forwardprop argmax forwardprop write_decisionScores2Csv write_decisionScores2Csv forwardprop normal ocnn_obj global_variables_initializer minimize print close nnScore placeholder set_random_seed range init_weights run reset_default_graph argmax Session get_variable add_subplot tight_layout title hist figure legend tf_OneClass_NN_linear sklearn_IsolationForest sklearn_OCSVM_linear print AE2_SVDD_Linear CAE_OCSVM_RBF tf_OneClass_NN_Relu sklearn__RPCA_OCSVM sklearn_OCSVM_rbf write_training_test_results tf_OneClass_NN_sigmoid CAE_OCSVM_Linear AE2_SVDD_RBF float32 floatX str list uint8 ndarray imsave print reshape astype range astype float32 int sum format reader rollaxis len close float32 resize append zeros imread next range open int format asarray reader ANTIALIAS close PIL2array resize append next open uint8 subplots divmod astype axis tight_layout imshow savefig range indices_generator len int arange min shuffle ceil check_all load_data StandardScaler leaky_relu addConvLayer addDropoutLayer addLeakyReLU GlorotUniform Constant addMaxPool addReLU addUpscale mean reshape reshape std max min array newaxis array svd T reshape mean shape dot sqrt prod diag newaxis print reshape PCA transform fit shape min fromarray rollaxis newaxis ones reshape any zeros sum len print reshape components_ MiniBatchDictionaryLearning shuffle choice transform len StandardScaler StandardScaler cifar10_normal ones logical_and shape newaxis sum range ones zeros logical_and shape newaxis sum range zca_whitening out_frac mnist_normal pca gcn mnist_outlier open seed str mnist_rep_dim cifar10_normal format mnist_bias cifar10_rep_dim close gtsrb_rep_dim unit_norm_used mnist_architecture cifar10_architecture cifar10_outlier weight_dict_init write cifar10_bias leaky_relu batch_size R_update_solver c_mean_init_n_batches get_value ae_lr_drop block_coordinate lr_drop weight_decay ae_loss open lr_decay_after_epoch dropout_architecture lr_decay hard_margin R_update_lp_obj R_update_scalar_method reconstruction_penalty format pretrain lr_drop_in_epoch dropout close center_fixed ae_weight_decay k_update_epochs lr_drop_factor use_batch_norm warm_up_n_epochs ae_lr_drop_factor write c_mean_init ae_lr_drop_in_epoch svm_GridSearchCV format write close open format write close kde_GridSearchCV open format write close open format test_time write close train_time round open write range flush percentile median min max print title format save_objective_and_accuracy softmax_loss floatX batch_size forward n_val get_epoch min n_train track_best_results flatten print_obj_and_acc save_diagnostics n_test save_network_diagnostics svdd_loss empty get_epoch batch_size n_val min n_train ae_forward save_ae_diagnostics flatten n_test empty trainable_layers print get_value all_layers dict pickle_filename isbatchnorm trainable_layers set_value print all_layers pickle_filename svdd_loss isbatchnorm print print print print print print plot_random_reconstructions reconstruction_penalty plot_parameter_norms plot_accuracy plot_scores plot_objective_with_parts plot_representation_norms svdd_loss plot_auc plot_center_c_diagnostics plot_objectives plot_scores plot_objective_with_parts plot_auc plot_objectives OrderedDict plot_line OrderedDict title plot_line OrderedDict plot_line _y_test OrderedDict plot_line _y_train _y_val OrderedDict plot_line trainable_layers str isdense isconv OrderedDict plot_line num_units range _y_test OrderedDict plot_five_number_summary _y_train _y_val _y_test OrderedDict plot_five_number_summary _y_train _y_val str n_train choice plot_mosaic forward auc_best_epoch str plot_mosaic get_value set_palette arange grid clf max percentile show ylabel ylim title savefig legend plot xlim zeros yscale xlabel min set_style median fill_between len str int _X_test _X_val n_val n_train _X_train argsort auc_best_epoch title load_data n_test plot_mosaic yscale show plot xlabel min grid ylabel set ylim title savefig clf legend zeros max len show int ones squeeze range shape imshow set_visible floor title savefig clf gca newaxis moveaxis zeros show set title scatter savefig clf legend | # Keras-Tensorflow Implementation of One Class Neural Networks. This repository provides a Keras-Tensorflow implementation of the One Class Neural Network method presented in our paper ”Anomaly Detection using One Class Neural Networks”. # Citations and Contact. You find a PDF of the **One Class Neural Network paper** at: https://arxiv.org/pdf/1802.06360.pdf If you use our work, please also cite the paper: ``` @article{chalapathy2018anomaly, title={Anomaly Detection using One-Class Neural Networks}, author={Chalapathy, Raghavendra and Menon, Aditya Krishna and Chawla, Sanjay}, | 3,388 |
raghavchalapathy/oc-nn_old | ['anomaly detection'] | ['Robust, Deep and Inductive Anomaly Detection'] | models/sklearn_OCSVM_explicit_plot_scores.py models/OCSVM_Autoencoder_model.py models/sklearn_OCSVM_model.py models/tf_OneClass_NN_model.py models/plot_synthetic_scores_old.py models/DBN2_OCSVM_models.py models/pfam_models.py models/OneClass_NN_model.py models/img_to_vec.py models/LSTM_AE_OCSVM_models.py data_load/cifar10.py models/CAE_OCSVM_models.py models/synthetic_models.py models/test_without_OC_nn.py models/AE_SVDD_models.py models/plot_synthetic_scores.py data_load/load_datasets.py metrics/metrics.py models/sklearn_OCSVM_explicit_model.py models/tflearn_OneClass_NN_model.py models/tflearn_OneClass_NN_model_plot_scores.py models/OneClass_NN_model_plot_scores.py models/plot_scores.py models/test2.py models/RCAE_models.py models/plot_syn_scores_with_subplots.py models/plot_pfam_scores.py models/cifar_models.py models/mnist_ae2.py data_load/convert.py models/models.py data_load/download.py models/keras_tl_oc_nn_cifar.py models/usps_models.py models/plot_spam_scores.py models/mnist_models.py models/tf_Cifar_OC_NN_Models.py models/sklearn_OCSVM_rpca.py metrics/metrics_lstm_ae_oc_nn.py models/tf_OneClass_NN_model_plot_scores.py models/cifar10vgg.py data_load/dataset.py models/plot_cifar_scores.py models/plot_syn_scores.py models/sklearn_isolation_forest.py models/test.py models/r_pca.py models/fake_news_models.py models/spam_models.py models/plot_usps_scores.py models/dataset.py models/tf_OneClass_CNN_model.py models/plot_fake_news_scores.py models/OCSVM_dogs_vs_cats.py models/RDA_models.py models/plot_mnist_scores.py models/OCSVM_cifar.py load_class_names _load_data load_test_data _get_file_path _convert_images load_training_data _unpickle maybe_download_and_extract video2images load_test load_train DataSet read_test_set read_train_sets _print_download_progress maybe_download_and_extract prepare_cifar_data_for_ae2_svdd prepare_spam_vs_ham_data prepare_scene_data_with_anamolies prepare_mnist_data_for_ae2_svdd prepare_cifar_10_data_for_conv_net prepare_usps_data_for_cae_svdd prepare_mnist_mlfetch prepare_cifar_data_for_cae_ocsvm prepare_usps_data_for_ae2_svdd readjpegimages2Array prepare_mnist_data_for_cae_svdd prepare_synthetic_data prepare_cifar_10_data add_new_last_layer prepare_usps_mlfetch prepare_mnist_with_anomalies prepare_pfam_data_for_lstm_ae prepare_pfam_data_for_ocsvm_isolationForest func_slice_stich_scene prepare_fake_news_data prepare_cifar_data_for_rpca_forest_ocsvm compute_prec_at_10 au_roc au_prc compute_precAtK compute_au_prc compute_au_roc compute_prec_at_10 au_roc au_prc compute_precAtK compute_au_prc compute_au_roc add_new_last_layer nnScore relu add_new_last_layer nnScore relu prepare_cifar_data_for_cae_ocsvm AE2_SVDD_Linear add_new_last_layer prepare_usps_data_for_cae_ocsvm prepare_mnist_data_for_cae_ocsvm AE2_SVDD_RBF prepare_cifar_data_for_cae_ocsvm add_new_last_layer CAE_OCSVM_RBF prepare_usps_data_for_cae_ocsvm write_decisionScores2Csv prepare_mnist_data_for_cae_ocsvm plotNNFilter CAE_OCSVM_Linear prepare_cifar_data_with_anamolies cifar10vgg func_getDecision_Scores_cifar write_training_test_results load_test load_train DataSet read_test_set read_train_sets add_new_last_layer nnScore relu func_getDecision_Scores_fake_news Img2Vec add_new_last_layer nnScore relu tf_OneClass_LSTM_AE_NN_sigmoid LSTMAE_OCSVM_Linear tf_OneClass_LSTM_AE_NN_linear AE_OCSVM_Linear add_new_last_layer AE_OCSVM_RBF LSTMAE_OCSVM_RBF prepare_data_LSTM_AE_OCSVM build_deep_autoencoder prepare_mnist_mlfetch tf_mnist_OneClass_NN_linear AE2_SVDD_Linear func_getDecision_Scores_usps_old CAE_OCSVM_RBF usps_autoencoder_representation CAE_OCSVM_Linear write_decisionScores2Csv prepare_usps_mlfetch tf_mnist_OneClass_NN_sigmoid write_training_test_results tf_mnist_OneClass_NN_Relu func_getDecision_Scores_mnist AE2_SVDD_RBF func_getDecision_Scores_CIFAR_10 func_getDecision_Scores_FAKE_NEWS func_getDecision_Scores_USPS func_getDecision_Scores_SPAM_VS_HAM add_new_last_layer nnScore relu add_new_last_layer nnScore relu ocnn_obj One_Class_NN_explicit_linear relu ocnn_grad nnScore One_Class_NN_explicit_sigmoid dRelu func_getDecision_Scores_One_Class_NN_explicit plot_decision_scores_One_Class_NN_explicit tf_OneClass_LSTM_AE_NN_sigmoid LSTMAE_OCSVM_Linear tf_OneClass_LSTM_AE_NN_linear prepare_pfam_data_for_ocsvm_isolationForest add_new_last_layer write_decisionScores2Csv encode_pfam_data_for_ae_ocsvm LSTMAE_OCSVM_RBF tf_OneClass_LSTM_AE_NN_Relu prepare_data_LSTM_AE_OCSVM write_training_test_results func_getDecision_Scores_pfam plot_decision_scores_CIFAR_10 plot_decision_scores_CIFAR plot_decision_scores_FAKE_NEWS plot_decision_scores_MNIST plot_decision_scores_pfam plot_decision_scores_USPS plot_decision_scores plot_decision_scores_SPAM plot_decision_scores plot_decision_scores_SYNTHETIC plot_decision_scores_USPS plot_decision_scores plot_decision_scores_SYN_new plot_decision_scores plot_decision_scores_Synthetic plot_decision_scores_SYN plot_decision_scores plot_decision_scores_USPS plot_decision_scores_USPS_new plot_decision_scores add_new_last_layer nnScore relu R_pca sklearn_IsolationForest func_getDecision_Scores_sklearn_OCSVM_explicit ocsvm_obj sklearn_OCSVM_explicit_sigmoid relu sklearn_OCSVM_explicit_linear ocsvm_grad svmScore dRelu plot_decision_scores_sklearn_OCSVM_explicit sklearn_OCSVM_linear write_decisionScores2Csv sklearn_OCSVM_rbf func_getKerasModelfeatures func_getDecision_Scores_sklearn_OCSVM sklearn_RPCA_OCSVM_Linear sklearn_RPCA_OCSVM_rbf sklearn__RPCA_OCSVM func_getDecision_Scores_spam prepare_usps_mlfetch func_getDecision_Scores_synthetic write_decisionScores2Csv plotNNFilter plotNNFilter tflearn_OneClass_NN_linear func_getDecision_Scores_tflearn_OneClass_NN tflearn_OneClass_NN_Sigmoid plot_decision_scores_tflearn_OneClass_NN tf_OneClass_NN_linear relu nnScore write_decisionScores2Csv tf_OneClass_NN_relu tf_OneClass_NN_sigmoid func_get_ImageVectors ocnn_obj g relu nnScore getConv_features init_weights tf_OneClass_CNN_linear init_weights_2 create_ConvFeatureInputs func_getKerasModelfeatures init_weights_1 tf_OneClass_CNN_sigmoid forwardprop write_decisionScores2Csv tf_OneClass_NN_linear tf_OneClass_NN_Relu tf_OneClass_NN_sigmoid plot_decision_scores_tf_One_Class_NN AE2_SVDD_Linear func_getDecision_Scores_usps_old func_getDecision_Scores_usps CAE_OCSVM_RBF usps_autoencoder_representation CAE_OCSVM_Linear write_decisionScores2Csv prepare_usps_mlfetch write_training_test_results AE2_SVDD_RBF print _get_file_path reshape transpose array array _unpickle _convert_images zeros len range _load_data _load_data join format relpath endswith tuple print call splitext normpath walk makedirs join format basename print glob index resize append zeros imread array len join sorted basename glob print astype resize append imread array int load_train isinstance DataSet shuffle DataSets load_test float format write flush join urlretrieve print endswith extractall makedirs append asarray range len hstack array_split concatenate print reshape shape readjpegimages2Array full len reshape load_data where concatenate normal concatenate make_blobs print shape fill empty load_data where concatenate where concatenate fillna transform English display values concatenate SelectPercentile toarray tolist apply TfidfVectorizer append fit_transform read_csv HTML fit asarray reshape tolist load_data prepare_cifar_data_with_anamolies concatenate tolist shape TfidfVectorizer transform head read_csv values fit_transform read_test_set read_train_sets len print shape Model update sorted list img_to_array print reshape to_categorical list_images append imread array clear_session layers to_categorical resize sorted list load_model shape Model list_images input append imread predict update img_to_array add_new_last_layer get_layer print output summary array len to_vecs asarray print load_protvec shape append range read_csv len layers max sorted list load_model len add shape append range asarray concatenate set encode_sequence print reshape dict summary zeros split clear_session layers to_categorical resize sorted list load_model shape Model list_images input append imread predict update img_to_array add_new_last_layer get_layer print output summary array len clear_session layers load_model print reshape add_new_last_layer astype output shape Model get_layer summary input predict len clear_session layers load_model print reshape add_new_last_layer astype output shape Model get_layer summary input predict len clear_session layers load_model print reshape add_new_last_layer astype output shape Model get_layer summary input predict len clear_session layers load_model print reshape add_new_last_layer astype output shape Model get_layer summary input predict len print format average_precision_score print format roc_auc_score au_prc concatenate au_roc concatenate compute_precAtK concatenate argsort zeros precision_score shape layers to_categorical decision_function resize sorted list load_model shape Model OneClassSVM list_images input append imread predict update img_to_array add_new_last_layer get_layer time print fit output summary array len layers to_categorical decision_function resize sorted list load_model shape Model OneClassSVM list_images input append imread predict update img_to_array add_new_last_layer get_layer time print fit output summary array len layers to_categorical resize sorted list load_model Model list_images input append imread predict update img_to_array add_new_last_layer get_layer print output summary array len layers to_categorical resize sorted list load_model Model list_images input append imread predict update img_to_array add_new_last_layer get_layer print output summary array len print tolist close zip_longest subplot print reshape axis imshow savefig figure ceil range time print OneClassSVM decision_function write_decisionScores2Csv savemat fit time print OneClassSVM decision_function write_decisionScores2Csv fit where concatenate tf_OneClass_NN_linear sklearn_IsolationForest sklearn_OCSVM_linear print AE2_SVDD_Linear CAE_OCSVM_RBF sklearn__RPCA_OCSVM tf_OneClass_NN_relu sklearn_OCSVM_rbf write_training_test_results tf_OneClass_NN_sigmoid CAE_OCSVM_Linear AE2_SVDD_RBF print str write open INTER_LINEAR INTER_LINEAR print len sklearn_OCSVM_explicit_sigmoid One_Class_NN_explicit_linear tf_OneClass_NN_linear sklearn_OCSVM_explicit_linear print sklearn_OCSVM_linear One_Class_NN_explicit_sigmoid sklearn_OCSVM_rbf tf_OneClass_NN_sigmoid output input time print OneClassSVM decision_function fit time print OneClassSVM decision_function fit load asarray print reshape shape OneClassSVM decision_function append fit load asarray print reshape shape OneClassSVM decision_function append fit load asarray print reshape shape append normal ocnn_obj global_variables_initializer minimize print close nnScore placeholder set_random_seed init_weights run reset_default_graph range Session get_variable forwardprop normal ocnn_obj global_variables_initializer minimize print close nnScore placeholder set_random_seed range init_weights run reset_default_graph argmax Session get_variable Reshape Sequential add Dense InputLayer Flatten tf_mnist_OneClass_NN_linear sklearn_IsolationForest sklearn_OCSVM_linear print AE2_SVDD_Linear CAE_OCSVM_RBF sklearn__RPCA_OCSVM tf_mnist_OneClass_NN_sigmoid sklearn_OCSVM_rbf write_training_test_results tf_mnist_OneClass_NN_Relu CAE_OCSVM_Linear AE2_SVDD_RBF print reshape astype predict shape Model summary append Input compile fit sklearn_OCSVM_explicit_sigmoid One_Class_NN_explicit_linear tf_OneClass_NN_linear sklearn_OCSVM_explicit_linear print sklearn_OCSVM_linear One_Class_NN_explicit_sigmoid sklearn_OCSVM_rbf tf_OneClass_NN_sigmoid nnScore set_random_seed reset_default_graph argmax Session forwardprop run ocnn_obj get_variable placeholder write_decisionScores2Csv range normal close init_weights time minimize print global_variables_initializer nnScore set_random_seed reset_default_graph argmax Session forwardprop run ocnn_obj get_variable placeholder write_decisionScores2Csv range normal close init_weights time minimize print global_variables_initializer forwardprop normal ocnn_obj global_variables_initializer minimize print close nnScore placeholder set_random_seed range init_weights run reset_default_graph argmax Session get_variable print print print print ones relu reshape nnScore mean sum reshape concatenate nnScore dRelu seed normal minimize print check_grad reshape sort nnScore x seed normal minimize print check_grad reshape sort nnScore x One_Class_NN_explicit_sigmoid One_Class_NN_explicit_linear add_subplot tight_layout title hist figure legend tf_OneClass_LSTM_AE_NN_sigmoid sklearn_RPCA_OCSVM_Linear tf_OneClass_LSTM_AE_NN_linear LSTMAE_OCSVM_Linear sklearn_IsolationForest sklearn_OCSVM_linear print AE_OCSVM_Linear sklearn_RPCA_OCSVM_rbf AE_OCSVM_RBF LSTMAE_OCSVM_RBF tf_OneClass_LSTM_AE_NN_Relu sklearn_OCSVM_rbf write_training_test_results time write_decisionScores2Csv time write_decisionScores2Csv time write_decisionScores2Csv write_decisionScores2Csv time forwardprop normal ocnn_obj global_variables_initializer minimize print close nnScore placeholder set_random_seed range init_weights run reset_default_graph argmax Session get_variable layers load_model print add_new_last_layer output Model get_layer summary input predict len subplots set_title suptitle hist legend setp subplots set_title suptitle hist legend setp subplots set_title suptitle title hist legend setp subplots set_title suptitle print hist legend setp subplots set_title suptitle hist legend setp subplots set_title suptitle title hist legend setp items list title hist legend DataFrame subplots set_title suptitle title hist legend setp subplots set_title suptitle hist legend setp subplots arange set_title hist legend setp xticks list subplots title hist savefig legend xticks range yticks subplots set_title suptitle hist legend setp list subplots title hist savefig legend xticks range yticks time print shape IsolationForest predict fit mean sum svmScore relu append mean svmScore dRelu seed normal minimize print check_grad svmScore seed normal minimize print check_grad svmScore sklearn_OCSVM_explicit_sigmoid sklearn_OCSVM_explicit_linear add_subplot tight_layout title hist figure legend format print File close shape type array time print OneClassSVM decision_function write_decisionScores2Csv fit time print OneClassSVM decision_function write_decisionScores2Csv fit sklearn_OCSVM_rbf sklearn_OCSVM_linear R_pca time print shape OneClassSVM predict fit R_pca time print shape OneClassSVM predict fit R_pca time print shape OneClassSVM predict fit print sklearn_OCSVM_rbf sklearn_OCSVM_linear sklearn_OCSVM_explicit_sigmoid One_Class_NN_explicit_linear tf_OneClass_NN_linear sklearn_IsolationForest sklearn_OCSVM_explicit_linear print sklearn_OCSVM_linear CAE_OCSVM_RBF tf_OneClass_NN_Relu sklearn__RPCA_OCSVM One_Class_NN_explicit_sigmoid sklearn_OCSVM_rbf tf_OneClass_NN_sigmoid CAE_OCSVM_Linear fully_connected variable get_value input_data nnScore DNN is_training reset_default_graph Session W set_weights seed run percentile set_value get_training_mode append initialize_all_variables get_weights predict normal astype eval constant_initializer print reshape float32 oneClassNN fit fully_connected variable get_value input_data nnScore DNN is_training reset_default_graph Session W set_weights seed run percentile set_value get_training_mode append initialize_all_variables get_weights predict normal astype eval constant_initializer print reshape float32 oneClassNN fit tflearn_OneClass_NN_linear tolist tflearn_OneClass_NN_Sigmoid add_subplot tight_layout title hist figure legend normal ocnn_obj time global_variables_initializer minimize print close nnScore placeholder set_random_seed init_weights run reset_default_graph range Session get_variable nnScore set_random_seed reset_default_graph argmax Session forwardprop run ocnn_obj get_variable placeholder range normal close init_weights time minimize print data_rep savemat global_variables_initializer forwardprop normal ocnn_obj global_variables_initializer minimize print close nnScore placeholder set_random_seed range init_weights run reset_default_graph argmax Session get_variable asarray iglob print get_vec Img2Vec append open wrap train infer random_normal load load get_shape print float32 matmul cast cast float32 float32 reduce_sum reduce_mean cast ocnn_obj minimize print close nnScore range set_random_seed shape init_weights_2 run global_variables_initializer func_getKerasModelfeatures argmax Session init_weights_1 forwardprop ocnn_obj minimize print close nnScore range set_random_seed init_weights_2 run global_variables_initializer func_getKerasModelfeatures argmax Session init_weights_1 forwardprop argmax forwardprop write_decisionScores2Csv write_decisionScores2Csv forwardprop normal ocnn_obj global_variables_initializer minimize print close nnScore placeholder set_random_seed range init_weights run reset_default_graph argmax Session get_variable add_subplot tight_layout title hist figure legend tf_OneClass_NN_linear sklearn_IsolationForest sklearn_OCSVM_linear print AE2_SVDD_Linear CAE_OCSVM_RBF tf_OneClass_NN_Relu sklearn__RPCA_OCSVM sklearn_OCSVM_rbf write_training_test_results tf_OneClass_NN_sigmoid CAE_OCSVM_Linear AE2_SVDD_RBF | # Keras-Tensorflow Implementation of One Class Neural Networks. This repository provides a Keras-Tensorflow implementation of the One Class Neural Network method presented in our paper ”Anomaly Detection using One Class Neural Networks”. # Citations and Contact. You find a PDF of the **One Class Neural Network paper** at: If you use our work, please also cite the paper: ``` @inproceedings{chalapathy2017robust, title={Robust, deep and inductive anomaly detection}, author={Chalapathy, Raghavendra and Menon, Aditya Krishna and Chawla, Sanjay}, booktitle={Joint European Conference on Machine Learning and Knowledge Discovery in Databases}, | 3,389 |
raghavchalapathy/rcae | ['anomaly detection'] | ['Robust, Deep and Inductive Anomaly Detection'] | section_5.1_anomaly_detection_CIFAR_10_AE.py section_5.1_anomaly_detection_Restaurant_AE.py section_5.1_anomaly_detection_CIFAR_10.py section_5.2_inductive_anomaly_detection_results_script_AE.py section_5.2_inductive_anomaly_detection_results_script_CAE.py section_5.1_anomaly_detection_Restaurant_cae.py section_5.3_image_denoising_results_script_CAE.py add_Salt_Pepper_Noise evalPred decoder compute_mse addNoise compute_softhreshold prepare_cifar_data_with_noise_injection fit_auto_conv_AE visualise_anamolies_detected load_cifar10catsdogs soft_threshold prepare_cifar_data_with_anamolies encoder precAtK compute_best_worst_rank add_Salt_Pepper_Noise evalPred compute_mse addNoise compute_softhreshold prepare_cifar_data_with_noise_injection fit_auto_DAE visualise_anamolies_detected soft_threshold prepare_cifar_data_with_anamolies compute_best_worst_rank prepare_fgbg_restraurantData add_Salt_Pepper_Noise compute_mse addNoise compute_softhreshold fit_auto_DAE visualise_anamolies_detected fit_auto soft_threshold prepare_cifar_data_with_anamolies compute_best_worst_rank prepare_fgbg_restraurantData add_Salt_Pepper_Noise compute_mse decoder addNoise compute_softhreshold fit_auto_DAE visualise_anamolies_detected fit_auto soft_threshold prepare_cifar_data_with_anamolies encoder compute_best_worst_rank add_Salt_Pepper_Noise evalPred compute_mse addNoise compute_softhreshold prepare_cifar_data_with_noise_injection fit_auto_DAE visualise_anamolies_detected soft_threshold prepare_cifar_data_with_anamolies precAtK compute_best_worst_rank add_Salt_Pepper_Noise evalPred decoder compute_mse addNoise compute_softhreshold prepare_cifar_data_with_noise_injection fit_auto_conv_AE visualise_anamolies_detected load_cifar10catsdogs soft_threshold prepare_cifar_data_with_anamolies encoder precAtK compute_best_worst_rank add_Salt_Pepper_Noise evalPred decoder compute_mse addNoise compute_softhreshold prepare_cifar_data_with_noise_injection fit_auto_conv_AE visualise_anamolies_detected load_cifar10catsdogs soft_threshold prepare_cifar_data_with_anamolies encoder precAtK compute_best_worst_rank get_shape conv_2d print fully_connected flatten sigmoid batch_normalization elu get_shape conv_2d print fully_connected reshape conv_2d_transpose batch_normalization elu normal random_noise where concatenate update list asarray print reshape shape mean_squared_error values where print where shape zeros float update sorted asarray list reshape shape keys range len reshape predict fit asarray print reshape fit_auto_conv_AE soft_threshold range str uint8 ndarray imsave print reshape astype shape range reshape average_precision_score precAtK sum roc_auc_score argsort precision_score loadmat ravel reshape predict fit fit_auto_DAE predict fit shape type transpose list print shape loadmat values | # Robust Convolution AutoEncoder for Anomaly detection [rcae] contains the code and datasets used for models in the paper [Robust, Deep and Inductive Anomaly Detection](https://arxiv.org/pdf/1704.06743.pdf) The python files with _CAE.py contains Convolution Autoencoder network architecture while python files with _AE contains Autoencoder network architecture used for models in the paper | 3,390 |
raghavian/cFlow | ['medical image segmentation', 'semantic segmentation'] | ['Uncertainty quantification in medical image segmentation with normalizing flows'] | models/layers.py nflib/spline_flows.py nflib/flows.py utils/utils.py train_model.py models/flows.py utils/tools.py nflib/nets.py data/dataset.py nflib/made.py models/unet.py models/cflownet.py models/unet_blocks.py LIDC Drive glowDensity AxisAlignedConvGaussian cFlowNet Encoder Fcomb planarFlowDensity Sylvester TriangularSylvester Planar IAF GatedConvTranspose2d MaskedConv2d MaskedLinear Identity GatedConv2d Unet UpConvBlock DownConvBlock ActNorm IAF NormalizingFlow Invertible1x1Conv SlowMAF CondInvertible1x1Conv AffineHalfFlow CondActNorm AffineConstantFlow MAF NormalizingFlowModel CondAffineHalfFlow MADE MaskedLinear MLP LeafParam PosEncMLP ARMLP PositionalEncoder NSF_CL searchsorted NSF_AR RQS unconstrained_RQS GaussianFilter makeBatchAdj multiClassAccuracy makeAdj to_linear_idx GaussianLayer binary_accuracy dice_loss computeAuc plotLearningCurve wBCE to_2d_idx makeRegAdj wCELoss regrAcc rescaledRegAcc transformers writeLog makeAdjWithInvNgbrs dice makeLogFile hingeLoss row_normalize sparse_mx_to_torch_sparse_tensor focalCE focalLoss save_mask_prediction_example ged ncc init_weights pdist l2_regularisation truncated_normal_ init_weights_orthogonal_normal variance_ncc_dist exp zeros_like pad RQS log softplus cumsum pow pad sqrt softmax gather log roc_curve auc _nnz LongTensor _values _indices zeros type range row_normalize arange toarray ones reshape size csr_matrix sparse_mx_to_torch_sparse_tensor shape repeat eye zeros mod range seed row_normalize toarray coalesce ones reshape size csr_matrix sparse_mx_to_torch_sparse_tensor shape eye randint array values arange _nnz FloatTensor ones _indices stack data Size astype float32 from_numpy shape long array diags flatten dot sum array floor float array sum double float argmax float type_as float type_as type_as print rename isfile print format show plot grid clf legend flatten mean std len pixel_wise_xent mean ncc append zeros range mean transpose sum view ByteTensor pdist type type_as squeeze add_ copy_ shape normal_ bias kaiming_normal_ weight truncated_normal_ bias weight orthogonal_ truncated_normal_ parameters norm imshow savefig str | # README # This is official Pytorch implementation of "[Uncertainty quantification in medical image segmentation with Normalizing Flows](https://arxiv.org/abs/2006.02683)", Raghavendra Selvan et al. 2020  ### What is this repository for? ### * Train the proposed model on LIDC and Retina datasets * Reproduce the reported numbers in the paper * v1.0 ### How do I get set up? ### | 3,391 |
rahulbhalley/cyclegan-qp | ['style transfer'] | ['Artist Style Transfer Via Quadratic Potential'] | main.py networks.py config.py data.py get_infinite_Y_data get_infinite_X_data safe_sampling load_data train infer Generator Critic ConvTranspose2d ResidualBlock print ImageFolder Compose DataLoader print next zero_grad l1_loss safe_sampling save load_state_dict C_X F range state_dict mean requires_grad_ sqrt load join C_Y G backward print parameters step load join int image_loader print Compose eval load_state_dict save_image | # Artist Style Transfer Via Quadratic Potential [**Rahul Bhalley**](https://github.com/rahulbhalley) and [Jianlin Su](https://github.com/bojone) [arXiv paper](https://arxiv.org/abs/1902.11108) ### Abstract In this paper we address the problem of artist style transfer where the painting style of a given artist is applied on a real world photograph. We train our neural networks in adversarial setting via recently introduced quadratic potential divergence for stable learning process. To further improve the quality of generated artist stylized images we also integrate some of the recently introduced deep learning techniques in our method. To our best knowledge this is the first attempt towards artist style transfer via quadratic potential divergence. We provide some stylized image samples in the supplementary material. The source code for experimentation was written in [PyTorch](https://pytorch.org) and is available online in my [GitHub repository](https://github.com/rahulbhalley/cyclegan-qp). If you find our work, or this repository helpful, please consider citing our work with the following BibTex: ``` @article{bhalley2019artist, title={Artist Style Transfer Via Quadratic Potential}, author={Bhalley, Rahul and Su, Jianlin}, | 3,392 |
rahulkidambi/AccSGD | ['stochastic optimization'] | ['On the insufficiency of existing momentum schemes for Stochastic Optimization'] | AccSGD.py AccSGD | # AccSGD This is the code associated with Accelerated SGD algorithm used in the paper [On the insufficiency of existing momentum schemes for Stochastic Optimization](https://openreview.net/forum?id=rJTutzbA-), selected to appear at ICLR 2018. ## Usage: The code can be downloaded and placed in a given local directory. In a manner similar to using any usual optimizer from the pytorch toolkit, it is also possible to use the AccSGD optimizer with little effort. First, we require importing the optimizer through the following command: ``` from AccSGD import * ``` Next, an ASGD optimizer working with a given pytorch `model` can be invoked using the following command: ``` | 3,393 |
rahulmaz/L0BnB | ['sparse learning'] | ['Sparse Regression at Scale: Branch-and-Bound rooted in First-Order Optimization'] | l0bnb/relaxation.py l0bnb/_third_party.py profiler.py l0bnb/__init__.py l0bnb/regpath.py l0bnb/viz.py l0bnb/utilities.py l0bnb/gensynthetic.py setup.py l0bnb/tree.py l0bnb/node.py profile readme gen_synthetic Node process_data fit_path _coordinate_descent_loop _above_threshold_indices _calculate_cost relaxation_solve initial_active_set _calculate_dual_cost coordinate_descent BNBTree branch is_integral strong_branching new_z max_fraction_branching graph_plot show_plots l0gurobi l0mosek read remove close Stats run print_stats __name__ open seed normal ones dot sqrt zeros std masked argmax abs max lsq_linear solve identity BNBTree append concatenate square sqrt print min dot process_data zeros array x len norm ones square mean zeros minimum abs maximum maximum sign zeros abs len set_add add dot dot_product sign abs _coordinate_descent_loop list sorted List _calculate_cost abs _coordinate_descent_loop int list deepcopy List matmul argpartition len minimum _above_threshold_indices maximum matmul set _calculate_cost initial_active_set _calculate_dual_cost zeros coordinate_descent abs argmax astype deepcopy zub int zlb list min set new_z max strong_branch_solve lower_bound_z zlb Node strong_branching new_z max_fraction_branching zub xlabel ylabel scatter func figure show update addTerms optimize addVar LinExpr addConstr setObjective MINIMIZE Model setParam zeros QuadExpr range x len unbounded mul Minimize variable setLogHandler greaterThan ones solve add Model setSolverParam constraint sum hstack dense stdout equalsTo inRange sub inRotatedQCone constTerm objective | # L0BnB: Sparse Regression at Scale ### Hussein Hazimeh, Rahul Mazumder, and Ali Saab ### Massachusetts Institute of Technology ## Introduction L0BnB is a scalable global optimization framework for solving linear regression problems penalized with a combination of the L0 and L2 norms. More concretely, given a data matrix X (with n samples and p features) and a response vector y, L0BnB solves the following problem to optimality: <img src="https://raw.githubusercontent.com/alisaab/l0bnb/master/formulation.png" width = 300> where the L0 norm counts the number of nonzeros in the coefficients vector B. Here the L0 norm performs variable selection, while the L2 norm adds shrinkage which can be effective in low-signal settings. L0BnB implements a custom branch-and-bound (BnB) framework that leverages a highly specialized first-order method to solve the node subproblems. It achieves over 3600x speed-ups compared to the state-of-the-art mixed integer programming (MIP) solvers, and can scale to problems where the number of features p ~ 10^7. For more details, check out our paper *Sparse Regression at Scale: Branch-and-Bound rooted in First Order Optimization* ([arXiv link](https://arxiv.org/abs/2004.06152)). ## Installation The toolkit is implemented in Python 3. To install it, run the following command: ```bash | 3,394 |
rahulvigneswaran/Lottery-Ticket-Hypothesis-in-Pytorch | ['network pruning'] | ['The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks'] | archs/cifar100/resnet.py archs/cifar100/vgg.py archs/mnist/AlexNet.py archs/cifar10/AlexNet.py archs/cifar10/LeNet5.py archs/cifar10/resnet.py archs/mnist/resnet.py archs/cifar100/AlexNet.py archs/cifar10/vgg.py utils.py archs/mnist/vgg.py combine_plots.py archs/cifar100/fc1.py archs/cifar10/fc1.py archs/cifar10/densenet.py main.py archs/mnist/LeNet5.py archs/mnist/fc1.py archs/cifar100/LeNet5.py make_mask test prune_by_percentile weight_init main train original_initialization checkdir original_initialization plot_train_test_stats print_nonzeros AlexNet _bn_function_factory densenet161 _load_state_dict DenseNet densenet169 densenet201 _DenseLayer _DenseBlock _densenet _Transition densenet121 fc1 LeNet5 ResNet ResNet34 Bottleneck ResNet101 test ResNet50 resnet18 BasicBlock ResNet152 vgg19 VGG vgg16_bn _vgg vgg19_bn vgg11_bn vgg13 vgg11 make_layers vgg13_bn vgg16 AlexNet fc1 LeNet5 conv1x1 resnext50_32x4d wide_resnet50_2 ResNet resnet50 resnext101_32x8d Bottleneck resnet152 wide_resnet101_2 conv3x3 _resnet resnet34 resnet18 BasicBlock resnet101 vgg19 VGG vgg16_bn _vgg vgg19_bn vgg11_bn vgg13 vgg11 make_layers vgg13_bn vgg16 AlexNet fc1 LeNet5 conv1x1 resnext50_32x4d wide_resnet50_2 ResNet resnet50 resnext101_32x8d Bottleneck resnet152 wide_resnet101_2 conv3x3 _resnet resnet34 resnet18 BasicBlock resnet101 vgg_block vgg16 prune_iterations arange make_mask grid DataLoader set_description save device xticks original_initialization list prune_percent FashionMNIST exit Adam ylabel apply checkdir title ylim savefig legend to CIFAR100 CrossEntropyLoss range state_dict dump plot print_nonzeros Compose astype close test CIFAR10 start_iter MNIST deepcopy print end_iter xlabel min named_parameters prune_by_percentile parameters tqdm zeros train add_scalar criterion model backward to step zero_grad where named_parameters device numpy enumerate eval device percentile where named_parameters numpy device to abs ones_like numpy named_parameters to named_parameters device data constant_ ConvTranspose3d BatchNorm3d Conv3d normal_ BatchNorm1d xavier_normal_ GRUCell GRU BatchNorm2d ConvTranspose1d LSTMCell Conv1d ConvTranspose2d Linear isinstance orthogonal_ Conv2d parameters LSTM count_nonzero print named_parameters shape numpy prod makedirs yscale show arange plot xlabel ylabel title clf set_style ylim legend savefig list group match load_state_dict load_state_dict_from_url keys compile _load_state_dict DenseNet randn print ResNet18 size net Conv2d make_layers VGG ResNet range | # Lottery Ticket Hypothesis in Pytorch []() []() []() This repository contains a **Pytorch** implementation of the paper [The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks](https://arxiv.org/abs/1803.03635) by [Jonathan Frankle](https://github.com/jfrankle) and [Michael Carbin](https://people.csail.mit.edu/mcarbin/) that can be **easily adapted to any model/dataset**. ## Requirements ``` pip3 install -r requirements.txt ``` ## How to run the code ? ### Using datasets/architectures included with this repository : | 3,395 |
rajammanabrolu/StoryRealization | ['text generation', 'story generation'] | ['Story Realization: Expanding Plot Events into Sentences'] | RetEdit/gtd/ml/torch/multilayered_decoder_cell.py FSM/constrained_beam_search.py parse.py RetEdit/train_ctx_vae.py avg_sent_length.py RetEdit/gtd/ml/torch/tests/test_recurrent.py RetEdit/gtd/ml/torch/tests/test_utils.py RetEdit/gtd/utils.py mcts/evaluation_metrics.py RetEdit/train_noret.py RetEdit/editor_code/copy_editor/tests/test_editor.py Templates/weight_drop.py RetEdit/gtd/ml/tests/test_vocab.py data.py FSM/decode_fsm.py FSM/evaluate.py RetEdit/gtd/ml/torch/tests/test_source_encoder.py RetEdit/editor_code/copy_editor/editor.py FSM/beam_search_fsm.py RetEdit/hstone_eval_ctxvae.py RetEdit/gtd/tests/test_utils.py Templates/evaluation_metrics.py RetEdit/editor_code/copy_editor/tests/test_attention_decoder.py RetEdit/test_server.py RetEdit/paths.py Templates/locked_dropout.py FSM/data_utils.py strip_drl_input.py RetEdit/gtd/ml/torch/seq_batch.py EventCreation/memoryGraph_scifi.py Templates/templates_decode.py RetEdit/gtd/ml/utils.py RetEdit/editor_code/copy_editor/encoder.py RetEdit/gtd/ml/tf/tests/test_model.py RetEdit/github_ctxvae_eval.py RetEdit/github_valid_print.py RetEdit/gtd/ml/torch/tests/test_alignments.py RetEdit/gtd/ml/torch/decoder_cell.py Templates/model.py RetEdit/editor_code/copy_editor/datasets.py RetEdit/gtd/codalab.py Templates/abstract_dataset.py mcts/decode.py model_lib.py RetEdit/train_seq2seq.py RetEdit/editor_code/copy_editor/utils.py RetEdit/run_docker.py RetEdit/editor_code/copy_editor/vocab.py RetEdit/gtd/ml/torch/tests/test_attention.py RetEdit/gtd/ml/tf/seq_batch.py RetEdit/gtd/ml/tf/tests/test_utils.py RetEdit/eval/evaluation_metrics.py RetEdit/prepare_data.py RetEdit/gtd/ml/tf/training_run.py RetEdit/gtd/chrono.py RetEdit/editor_code/copy_editor/vae_encoder.py mcts/monte_carlo.py RetEdit/editor_code/copy_editor/context_vae_training_run.py RetEdit/hstone_valid_ex_print.py RetEdit/gtd/tests/test_graph.py Templates/extract_sentences.py RetEdit/gtd/profile_imports.py RetEdit/gtd/ml/training_run.py rebuild_drl_output.py Templates/main.py RetEdit/gtd/ml/tests/test_utils.py model.py RetEdit/editor_code/copy_editor/edit_training_run.py RetEdit/gtd/ml/torch/decoder.py Templates/finetune.py RetEdit/editor_code/copy_editor/vae_editret.py RetEdit/gtd/tests/test_persist.py RetEdit/scifi_valid_print.py RetEdit/editor_code/run_docker.py RetEdit/gtd/tests/test_io.py RetEdit/gtd/ml/torch/feed_forward.py RetEdit/editor_code/copy_editor/data.py EventCreation/run_event.py mcts/evaluate.py RetEdit/gtd/ml/torch/recurrent.py Templates/frames_with_loss.py RetEdit/gtd/turk.py RetEdit/gtd/ml/torch/alignments.py Templates/test_frames_with_loss.py RetEdit/gtd/ml/torch/attention.py Templates/backwards_forwards_events.py RetEdit/github_eval.py Templates/val_frames_with_loss.py EventCreation/eventmaker_singleSent.py weight_drop.py Templates/embed_regularize.py RetEdit/gtd/ml/vocab.py FSM/model.py take_out_outputs.py RetEdit/gtd/text.py RetEdit/editor_code/copy_editor/edit_retriever.py FSM/padremover.py Templates/utils.py mcts/original_decode.py RetEdit/gtd/graph.py EventCreation/corenlp.py Slotfilling/lm.py ensemble_main.py RetEdit/gtd/ml/torch/checkpoints.py RetEdit/gtd/ml/torch/source_encoder.py RetEdit/gtd/ml/torch/tests/test_token_embedder.py RetEdit/gtd/tests/test_lm.py mcts/model.py RetEdit/gtd/log.py Templates/data.py RetEdit/editor_code/copy_editor/attention_decoder.py RetEdit/editor_code/copy_editor/tests/test_vocab.py FSM/evaluation_metrics.py Templates/pointer.py Templates/TahaManipulateState.py Templates/use_frames_refactor.py RetEdit/word_vectors/create_vectors.py RetEdit/gtd/git_utils.py mcts/data_utils.py Slotfilling/fillIn_class.py RetEdit/gtd/ml/training_run_viewer.py Slotfilling/memoryGraph_scifi.py RetEdit/gtd/ml/torch/token_embedder.py RetEdit/gtd/retrieval_func.py RetEdit/run_server.py RetEdit/gtd/ml/tf/tests/test_seq_batch.py RetEdit/gtd/ml/tf/profile.py RetEdit/editor_code/copy_editor/retrieve_edit_run.py RetEdit/gtd/ml/torch/utils.py mcts/new_monte_carlo.py RetEdit/gtd/ml/torch/tests/test_seq_batch.py Slotfilling/fillSentsFromFile_comparison.py check_file_ok.py RetEdit/gtd/tests/test_log.py TemplateDecoder.py RetEdit/gtd/persist.py RetEdit/gtd/ml/torch/training_run.py RetEdit/gtd/plot.py mcts/beam_search.py RetEdit/gtd/ml/tf/tests/test_framework.py RetEdit/gtd/io.py FSM/avglen.py RetEdit/plot.py RetEdit/gtd/ml/tf/model.py Templates/splitcross.py reweight_ensemble.py RetEdit/gtd/postgres.py RetEdit/gtd/ml/tf/utils.py EventCreation/eventmaker_preparsed.py RetEdit/gtd/ml/torch/simple_decoder_cell.py percent.py RetEdit/gtd/lm.py RetEdit/gtd/ml/tf/framework.py locked_dropout.py Dictionary Corpus templates_thread mcts_thread vanilla_thread fsm_thread retedit_thread LockedDropout RNNModel MCTSBeamSearchDecoder BeamSearchDecoder GreedyDecoder FSMBeamSearchDecoder TemplateDecoder WeightDrop removePunct callStanford getPrimaryFrame eventMaker levenshtein getPOSs allXinY simplifyFrame getPrimaryFrame eventMaker levenshtein getPOSs allXinY simplifyFrame MemoryGraph isVerbNet allXinY Beam FSMBeamSearch read_summarization_data read_data_pipeline read_dialog_summarization_data construct_vocab read_config read_nmt_data get_autoencode_minibatch get_minibatch hyperparam_string evaluate_autoencode_model get_bleu get_bleu_moses model_perplexity decode_minibatch bleu bleu_stats evaluate_model finish_model main Ngrams Wrapper parse_args DeepBidirectionalLSTM StackedAttentionLSTM Seq2SeqFastAttention Seq2Seq LSTMAttentionDot Seq2SeqAutoencoder Seq2SeqAttentionSharedEmbedding SoftDotAttention Seq2SeqAttention LSTMAttention read_summarization_data read_data_pipeline read_dialog_summarization_data construct_vocab read_config read_nmt_data get_autoencode_minibatch get_minibatch hyperparam_string evaluate_autoencode_model get_bleu get_bleu_moses model_perplexity decode_minibatch bleu bleu_stats evaluate_model finish_model main Ngrams Wrapper parse_args DeepBidirectionalLSTM StackedAttentionLSTM Seq2SeqFastAttention Seq2Seq LSTMAttentionDot Seq2SeqAutoencoder Seq2SeqAttentionSharedEmbedding SoftDotAttention Seq2SeqAttention LSTMAttention BeamSearchDecoder GreedyDecoder pipeline_predict avg_runlen correct_runlen set_output_encoding btok eval_batch_noret agree_vec eval_batch_ret tokenize_for_bleu_eval rle avg_runlen correct_runlen set_output_encoding btok eval_batch_noret agree_vec tokenize_for_bleu_eval rle set_output_encoding make_eexs cut_by_substring proc_str load_input format_ex tok_wrapper invert_str map_vocab tokenize_for_bleu_eval tok_str print_card make_eexs cut_by_substring proc_str load_input format_ex tok_wrapper invert_str map_vocab tokenize_for_bleu_eval tok_str install set_output_encoding edit set_output_encoding set_output_encoding edit AttentionRNNInput AttentionTrace AttentionRNNState AttentionDecoderCellOutput AttentionDecoderCell AttentionContextCombiner ContextVAETrainingRuns ContextVAETrainingRunsViewer ContextVAETrainingRun unicode_csv_reader RuleCandidates file_rows create_splits Example utf_8_encoder Examples EditExample LossTrace EditTrace HardCopyTrainDecoderInput decoder_inputs_and_outputs Editor EditRetriever EditDataSplits EditTrainingRunsViewer EditTrainingRun EditTrainingRuns VMFVAEWrapper AgendaMaker Encoder GaussianVAEWrapper EncoderOutput RetrieveEditTrainingRun RetrieveEditTrainingRunsViewer RetrieveEditTrainingRuns edit_dist EditPath CustomEditDistance VAERetriever TargetVAEEncoder MultiVocabIndices load_embeddings HardCopyVocab HardCopyDynamicVocab DynamicMultiVocabTokenEmbedder base_plus_copy_indices LexicalWhitelister TestAttentionDecoderCellOutput TestHardCopyTrainDecoderInput TestHardCopyVocab TestHardCopyDynamicVocab TestLemmatizedVocabWhitelist TestDynamicMultiVocabTokenEmbedder finish_model main Ngrams Wrapper parse_args Profiling FunctionStats monitor_call_stack time_limit ProfilerStats timer Pulse Profiler verboserate profile function_label TimeoutException open_file tensorboard in_codalab get_uuids configure_matplotlib download_logs report launch_job Bundle monitor_jobs upload add_to_sys_path commit_diff Graph JSONPicklable redirect_stream split_path read_files save EmptyFile shell IntegerDirectories Tmux lines_in_file Process redirect_stdout sub_dirs local_bash tunnel MultiFileWriter utfopen reset_state rsync InitPicklable MultiStream load work_in_sandbox open_or_create num_lines save_stdout Workspace redirect_stderr TmuxSessionExists makedirs DistributionStats normalize_counts LMSampler Generator CountLM LM replace_parens last_k KNNLM LMSamplerWithStats in_ipython print_with_fonts print_list jupyter_no_margins SyncedMetadata set_log_level TraceSession print_no_newline Metadata gb_used Tracer indent EagerSequence FileSequence SimpleAppendableSequence ORMColumn ShardedSequence FileSequenceOffsets SimpleORM FileSerializer LazyIterator UnicodeSerializer TableMapping FileMapping ORM FileSequenceMetaData JSONPicklableSerializer BatchMapping LazyMapping SimpleFileSequence CustomSerializer sqlalchemy_metadata AppendableSequence EagerMapping BatchIterator CacheWrapperMixin Closeable Shard BatchMutableMapping SimpleBatchMapping CustomORM SequenceSlice show rgb_to_hex hinton plot_pdf Postgres table_to_dict dict_to_table stack_add log_stack_info uninstall stack_finish timed_import timed_compile install grab_nbs generate_predictions make_hash make_hash_from_vec grab_nbs_from_vec map_sent get_spacy Trie get_ngrams NER lemmatize PhraseMatcher longest_common_subsequence ngram_precision_recall lemma_to_forms word_to_forms camel_to_snake_case _get_all_hits ExternalQuestionTask get_mturk_connection Task standard_quals Config parallel_call memoize_with_key_fxn Bunch flatten ensure_unicode truncated FunctionWrapper Frozen NestedDict Memoized UnicodeMixin set_once_attribute HomogeneousBatchSampler ranks SimpleExecutor fixed_length batch_compute bleu EqualityMixin sample_if_large map_array quantiles get_batch sorted_by_value args_as_string EqualityMixinSlots ComparableMixin group DictMemoized Failure compute_if_absent softmax generator_ignore_errors random_seed as_batches data_split chunks sigmoid FileMemoized file_memoize sample_excluding best_threshold ClassCounter cached_property memoize TrainingRun TrainingRuns TrainingRunWorkspace num_checkpoints TrainingRunViewer NumSteps Renderer Commit checkpoint_numbers JSONSelector run_name Owner temperature_smooth CasedWordVocab emulate_distribution WordVocab SimpleEmbeddings Vocab SimpleVocab test_temperature_smooth vocab embeds TestSimpleVocab Feedable KerasTrainer Batch KerasObjective Model KerasModel Optimizable Attention SoftCopyScorer BidiLSTMSequenceEmbedder Scorer LSTMSequenceEmbedder TokenEmbedder MeanSequenceEmbedder Embedder CandidateScorer MaxSequenceEmbedder ConcatSequenceEmbedder SequenceEmbedder ProfiledSession change_pad_value weighted_sum reduce_max SequenceBatch reduce_sum FeedSequenceBatch reduce_mean embed TFTrainingRun guarantee_initialized_variables gather_2d assert_broadcastable expand_dims_for_broadcast assert_shape Saver clean_session TensorDebugger TensorBoardLogger broadcast clean_test_session FeedableTester KerasModelTester TestFeedableExample KerasLayersModelExample assert_array_collections_equal TestKerasLayersModel FeedableExample TestConcatSequenceEmbedder VocabExample TestCandidateScorer TestLSTMSequenceEmbedder TestSoftCopyScorer TestAttention TestTokenEmbedder TestBidiLSTMSequenceEmbedder TestSequenceEmbedder TestFixedLengthConcatEmbedder TestFeedSequenceBatch TestSequenceBatch TestReduceMean TestReduceSum TestReduceMax TestTensorDebugger test_broadcast TestSaver test_expand_dims_for_broadcast TestGather2D Alignments SoftCopyAttentionOutput DummyAttention AttentionOutput SentinelAttention SoftCopyAttentionTrace Attention SoftCopyAttention TrainState Checkpoints SampleDecoder BeamDuplicator BeamDecoder BeamTrace BeamDecoderTrace DecoderState PenalizeExtensionsByRank ExtensionProbsModifier PredictionTrace BeamCandidate RNNContextCombiner TrainDecoder TrainDecoderInput BatchSelector Candidate LeftRightDecoder WeightByValueEstimates BeamDuplicatable BasicTrainDecoderInput TestDecoder DecoderCellOutput DecoderCell PredictionBatch RNNState RNNInput FeedForwardNetwork MultilayeredRNNState MultilayeredRNNInput MultilayeredDecoderCell AdditionCell gated_update tile_state SequenceBatch SimpleRNNInput SimpleRNNState SimpleDecoderCell BidirectionalSourceEncoder SimpleSourceEncoder SourceEncoder MultiLayerSourceEncoder BidirectionalEncoderOutput TrainFlagEmbedding TokenEmbedder TorchTrainingRun random_seed assert_tensor_equal is_binary try_gpu RandomState random_state GPUVariable similar_size_batches expand_dims_for_broadcast conditional batch_tile print_module_parameters to_numpy NamedTupleLike TestAlignments TestAttention TestSoftCopyAttention AttentionExample test_tile_state test_gated_update TestSequenceBatch TestBidirectionalSourceEncoder TestTokenEmbedder test_is_binary test_batch_tile test_expand_dims_for_broadcast TestGraph test_split_path TestIntegerDirectories test_normalize_counts lm test_sample_from_distribution test_get_contexts test_sequence_probability lm_sampler test_last_k test_largest_known_context TestSyncedMetadata TestMetadata TestLazyMapping BatchMappingTester TestShardedSequence ORMTester TestLazyIterator ExampleKeyORM TestBatchIterator TestSequenceSlice MetaDataExample TestTableMappingSpeed LazyMappingExample ExampleValORM ExampleBatchIterator TestExampleKeyORM test_eager_mapping EagerMappingExample TableMappingExample FileSequenceExample AppendableSequenceTester TestFileSequence FileSerializerTester LazyIteratorExample FileSerializerExample BatchMutableMappingTester TestTableMapping DummySlotsObject test_ranks MemoizedClass2 TestFailure test_as_batches TestEqualityMixinSlot Dummy TestUtils test_truncated TestClassCounter MemoizedClass TestNestedDict test_file_memoized_represent_args TestSimpleExecutor TestMemoizeWithKey TestDictMemoized loadWords loadGloveModel FillIn getAgentTurn LM MemoryGraph Dictionary Corpus embedded_dropout finish_model main Ngrams Wrapper parse_args train evaluate predict_beam mean main isNoun sample_for_word LockedDropout model_save train model_load evaluate RNNModel one_hot evaluate SplitCrossEntropyLoss ManipulateState main predict_beam isNoun sample_for_word predict_beam mean main isNoun sample_for_word main predict_beam isNoun sample_for_word repackage_hidden get_batch batchify predict_beam mean main isNoun sample_for_word WeightDrop print translate print translate print translate print template_main print text loads append strip replace split unlink join name config_java split list min append range enumerate len list index len isdigit index load open list items sorted enumerate print construct_vocab print construct_vocab print construct_vocab append split construct_vocab max cuda max cuda Counter append max range len sum array zip join close write Popen decode model argmax cuda range cat data view model Variable size get_minibatch loss_criterion range append len join print index decode_minibatch zip get_minibatch numpy cuda range append len decode join model print index numpy get_autoencode_minibatch zip append argmax cuda range cat len int training_set error add_argument add_mutually_exclusive_group eval output_file ArgumentParser input classify laplace_unigrams occurrenceToBiTuring laplace_ngrams occurrenceToUniTuring turing finish_model open str training_set types bleu parse_args test_set readlines bi_perplex init zip perplexity uni_perplex n print processFile n_laplace_perplex_help sentence_bleu Ngrams split join read_data_pipeline BeamSearchDecoder GreedyDecoder read_config translate stdout stderr encoding encoder_input sum vocab_probs train_decoder train_decoder_input base_vocab word2index copy len preprocess zip append encoder numpy range UNK split base_vocab copy_lens input_words word2index append encoder sum range UNK encoder_input train_decoder_input copy HardCopyDynamicVocab preprocess zip vocab_probs train_decoder split numpy len append max range len asarray where append diff array len append float sum array rle append max rle sub replace append len find replace append range len join EditExample sub zip append split append range len join invert_str target_words split append extend str join print target_words invert_str call str list grab_nbs prob make_hash dist tqdm ret_and_make_ex append train range generate_predictions len print split seed int list shuffle len utf_8_encoder reader append float min range list tokens concatenate from_file extend HardCopyVocab shape sample_embeds SPECIAL_TOKENS len get assert_tensor_equal from_sequences mask word_to_copy_token stack zip append UNK corpus_bleu float __code__ isinstance add_function print time format flush progress SIGALRM alarm signal in_ipython format print __stderr__ stderr getpid register SIGUSR1 format shell split remove format name close NamedTemporaryFile shell open join format isinstance print uuid shell Bundle Bundle render get_uuids format print rmtree report input exists makedirs print format shell insert format shell split print join format shell set add_path b_blob a_blob diff chdir print getcwd rmtree exists makedirs seed reset_default_graph set_random_seed format print EmptyFile append enumerate open pop Process read print wait write append flush append join listdir isdir join isdir format_address local append Tmux format run append split num_lines min items list Counter sum values join format HTML display ru_maxrss print write flush setLevel isinstance getLogger HTML display URL create_engine arange set_yticklabels abs max log set_aspect set_major_locator NullLocator ndenumerate ceil set_xticklabels sqrt invert_yaxis set_yticks add_patch set_xticks set_facecolor Rectangle autoscale_view in_ipython join close savefig makedirs _compute_covariance plot gaussian_kde min density linspace max append pop append pop sort write extend reverse append get stack_add list f_lineno _timer _real_import endswith _getframe keys find get stack_add _timer endswith repr _real_compile _getframe f_lineno zeros seed AnnoyIndex defaultdict add_item tqdm build map_sent seed AnnoyIndex add_item tqdm build enumerate len append tqdm map_sent append tqdm English info sub LCS len list get_ngrams set zip append float len update items list add set add WordNetLemmatizer set update lemmatize lemma_to_forms set MTurkConnection Qualifications NumberHitsApprovedRequirement add Requirement LocaleRequirement PercentAssignmentsApprovedRequirement int list get_page TotalNumResults bool range join len choice range len str Missing int list format print shuffle set len get keyfunc show list plot_pdf plot sort figure zip append len append get_batch append batch_fxn range len list isnan isinstance arange isinstance argsort shape empty array len int sorted append round len list shuffle append tolist ndarray isinstance append defaultdict grouper seed get_state getstate set_state setstate max exp array sum tuple min max len enumerate join checkpoint_numbers sum exp log mean std same exp smooth eye len ones select expand_dims_for_broadcast shape cast bool broadcast verify_tensor_all_finite mask expand_dims_for_broadcast gather values ones select reduce_sum shape equal ones expand_dims_for_broadcast mask reduce_sum assert_is_compatible_with variables_initializer list run slice shape rank assert_equal get_shape list TensorShape dims shape rank set_shape ndims assert_broadcastable get_shape ones select shape set_shape tile equal get_shape list reshape concat TensorShape shape rank set_shape gather split Graph zip isinstance assert_equal ones GPUVariable size expand numpy isinstance to_numpy assert_array_almost_equal size unsqueeze range len data prod isinstance list sorted format print shuffle chunks sum total_cost items list named_children print is_available RandomState set_global RandomState set_global manual_seed size extend tile_state assert_tensor_equal GPUVariable FloatTensor gated_update GPUVariable assert_tensor_equal FloatTensor assert_tensor_equal FloatTensor squeeze expand_dims_for_broadcast zeros FloatTensor batch_tile assert_tensor_equal LongTensor FloatTensor Counter list assert_approx_equal normalize_counts Counter keys range record_counts CountLM sequence_probability split EagerMappingExample str join _cache_key dict FileMemoized DictMemoized print split array open print split open rfind fillIn replace embedding max_norm sparse padding_idx norm_type scale_grad_by_freq expand_as weight repackage_hidden get_batch bptt view model size dictionary eval reset range init_hidden len repackage_hidden batch_size model zero_grad max clip exp bptt view dictionary sum normal format get_batch clip_grad_norm int time log_interval criterion backward print min parameters reset step init_hidden len topk max append model Variable insert pos_ range nlp cuda cpu sum long init_hidden sample_for_word seed error cpu close sample input_event_file eval manual_seed is_available cuda init_hidden clip_grad_norm_ log alpha item beta Variable float32 from_numpy zeros cuda lambdasm theta squeeze softmax enumerate print mv Tensor isinstance size cuda narrow contiguous min view len | # Event-to-Sentence Ensemble Code for the paper "Story Realization: Expanding Plot Events into Sentences" Prithviraj Ammanabrolu, Ethan Tien, Wesley Cheung, Zhaochen Luo, William Ma, Lara J. Martin, and Mark O. Riedl https://ojs.aaai.org//index.php/AAAI/article/view/6232 On arXiv: https://arxiv.org/abs/1909.03480 **Disclaimer:** Code is not upkept BibTex Citation: ``` @inproceedings{ammanabrolu-storyrealize, title = "Story Realization: Expanding Plot Events into Sentences", author = "Ammanabrolu, Prithviraj and Tien, Ethan and Cheung, Wesley and Luo, Zhaochen and Ma, William and Martin, Lara J. and Riedl, Mark O.", | 3,396 |
rajammanabrolu/WorldGeneration | ['text generation'] | ['Bringing Stories Alive: Generating Interactive Fiction Worlds'] | evennia-engine/evennia/evennia/server/deprecations.py evennia-engine/evennia/evennia/scripts/scripts.py evennia-engine/evennia/evennia/locks/lockfuncs.py evennia-engine/evennia/evennia/commands/default/system.py evennia-engine/evennia/evennia/typeclasses/migrations/0010_delete_old_player_tables.py evennia-engine/evennia/evennia/objects/migrations/0009_remove_objectdb_db_player.py evennia-engine/evennia/evennia/accounts/migrations/0007_copy_player_to_account.py evennia-engine/evennia/evennia/server/validators.py evennia-engine/evennia/evennia/utils/create.py evennia-engine/evennia/evennia/commands/default/tests.py evennia-engine/engine/server/conf/cmdparser.py evennia-engine/evennia/evennia/server/portal/suppress_ga.py evennia-engine/evennia/evennia/scripts/manager.py evennia-engine/evennia/evennia/game_template/typeclasses/channels.py evennia-engine/evennia/evennia/locks/tests.py neural-based/scrape-wikipedia/scrape/get_plot.py evennia-engine/evennia/evennia/server/signals.py evennia-engine/evennia/evennia/game_template/server/conf/web_plugins.py evennia-engine/evennia/evennia/contrib/barter.py evennia-engine/evennia/evennia/server/migrations/0002_auto_20190128_2311.py evennia-engine/evennia/evennia/server/portal/telnet_oob.py evennia-engine/evennia/evennia/utils/dbserialize.py evennia-engine/evenv/share/doc/networkx-2.4/examples/graph/plot_roget.py evennia-engine/evenv/share/doc/networkx-2.4/examples/jit/plot_rgraph.py evennia-engine/engine/server/conf/server_services_plugins.py evennia-engine/evennia/evennia/objects/migrations/0001_initial.py evennia-engine/evenv/share/doc/networkx-2.4/examples/drawing/plot_atlas.py evennia-engine/evenv/share/doc/networkx-2.4/examples/drawing/plot_sampson.py evennia-engine/evenv/share/doc/networkx-2.4/examples/graph/plot_karate_club.py evennia-engine/evenv/share/doc/networkx-2.4/examples/advanced/plot_heavy_metal_umlaut.py evennia-engine/evennia/evennia/game_template/typeclasses/exits.py evennia-engine/evennia/evennia/commands/default/__init__.py evennia-engine/engine/server/conf/settings.py evennia-engine/evennia/evennia/contrib/rpsystem.py evennia-engine/evennia/evennia/server/tests/test_initial_setup.py evennia-engine/evennia/evennia/utils/tests/data/prototypes_example.py evennia-engine/evennia/evennia/scripts/migrations/0008_auto_20170606_1731.py evennia-engine/evennia/evennia/contrib/turnbattle/tb_magic.py evennia-engine/evennia/evennia/game_template/__init__.py neural-based/scrape-wikipedia/main.py evennia-engine/engine/server/conf/web_plugins.py evennia-engine/evennia/evennia/web/webclient/views.py evennia-engine/evennia/evennia/utils/validatorfuncs.py evennia-engine/evennia/evennia/utils/ansi.py evennia-engine/evennia/evennia/contrib/evscaperoom/tests.py evennia-engine/evennia/evennia/contrib/ingame_python/scripts.py evennia-engine/evennia/evennia/scripts/migrations/0009_scriptdb_db_account.py evennia-engine/evennia/evennia/contrib/dice.py evennia-engine/engine/server/conf/serversession.py neural-based/flavortext-generation/flavortext.py evennia-engine/evennia/evennia/server/models.py evennia-engine/evennia/evennia/utils/inlinefuncs.py evennia-engine/evenv/share/doc/networkx-2.4/examples/advanced/plot_parallel_betweenness.py evennia-engine/evennia/evennia/server/profiling/memplot.py evennia-engine/evennia/evennia/scripts/tests.py evennia-engine/evennia/evennia/contrib/ingame_python/typeclasses.py evennia-engine/evennia/.travis/mysql_settings.py evennia-engine/evennia/evennia/typeclasses/migrations/0007_tag_migrations_may_be_slow.py evennia-engine/evennia/evennia/web/utils/tests.py evennia-engine/evennia/evennia/comms/tests.py evennia-engine/evennia/evennia/objects/migrations/0004_auto_20150118_1622.py evennia-engine/evenv/share/doc/networkx-2.4/examples/drawing/plot_knuth_miles.py evennia-engine/evennia/evennia/game_template/commands/default_cmdsets.py evennia-engine/evenv/share/doc/networkx-2.4/examples/drawing/plot_node_colormap.py evennia-engine/evennia/evennia/locks/lockhandler.py evennia-engine/evennia/evennia/game_template/server/conf/lockfuncs.py evennia-engine/evennia/evennia/server/portal/amp.py evennia-engine/evennia/evennia/commands/cmdset.py evennia-engine/evennia/evennia/web/website/urls.py evennia-engine/evennia/evennia/typeclasses/migrations/0003_defaultcharacter_defaultexit_defaultguest_defaultobject_defaultplayer_defaultroom_defaultscript_dono.py evennia-engine/evennia/evennia/comms/migrations/0012_merge_20170617_2017.py evennia-engine/evennia/evennia/comms/migrations/0011_auto_20170606_1731.py evennia-engine/evennia/evennia/scripts/migrations/0005_auto_20150306_1441.py evennia-engine/evennia/evennia/accounts/bots.py evennia-engine/evennia/evennia/server/evennia_runner.py evennia-engine/evennia/evennia/contrib/mapbuilder.py evennia-engine/evennia/evennia/scripts/migrations/0001_initial.py evennia-engine/evennia/evennia/objects/__init__.py evennia-engine/evennia/evennia/server/portal/portal.py evennia-engine/engine/server/conf/at_initial_setup.py evennia-engine/evennia/evennia/contrib/fieldfill.py evennia-engine/evenv/Scripts/activate_this.py evennia-engine/evennia/evennia/typeclasses/admin.py evennia-engine/evenv/share/doc/networkx-2.4/examples/graph/plot_degree_sequence.py evennia-engine/evennia/evennia/server/portal/tests.py evennia-engine/engine/web/urls.py neural-based/flavortext-generation/finetune.py evennia-engine/evennia/evennia/server/tests/test_launcher.py evennia-engine/evennia/evennia/contrib/tutorial_world/objects.py evennia-engine/evennia/evennia/contrib/clothing.py evennia-engine/evennia/evennia/accounts/__init__.py evennia-engine/engine/typeclasses/rooms.py evennia-engine/evennia/evennia/scripts/scripthandler.py evennia-engine/evennia/evennia/server/portal/__init__.py evennia-engine/evennia/evennia/comms/migrations/__init__.py evennia-engine/evenv/share/doc/networkx-2.4/examples/graph/dot_atlas.py evennia-engine/evennia/evennia/game_template/server/conf/connection_screens.py evennia-engine/evennia/evennia/server/portal/mxp.py evennia-engine/evennia/evennia/contrib/turnbattle/tb_items.py evennia-engine/evennia/evennia/server/portal/ttype.py evennia-engine/evennia/evennia/typeclasses/migrations/0012_attrs_to_picklev4_may_be_slow.py evennia-engine/evennia/evennia/contrib/tree_select.py evennia-engine/evennia/evennia/typeclasses/models.py evennia-engine/evennia/evennia/comms/managers.py evennia-engine/evennia/evennia/scripts/taskhandler.py evennia-engine/evennia/evennia/scripts/migrations/0002_auto_20150118_1625.py evennia-engine/evenv/share/doc/networkx-2.4/examples/advanced/plot_eigenvalues.py evennia-engine/evennia/setup.py evennia-engine/evennia/evennia/help/migrations/0002_auto_20170606_1731.py evennia-engine/evenv/share/doc/networkx-2.4/examples/drawing/plot_weighted_graph.py evennia-engine/evennia/evennia/server/profiling/test_queries.py evennia-engine/evennia/evennia/commands/cmdhandler.py evennia-engine/evennia/evennia/contrib/multidescer.py evennia-engine/evennia/evennia/accounts/migrations/0006_auto_20170606_1731.py evennia-engine/evennia/evennia/web/website/templatetags/addclass.py evennia-engine/evennia/evennia/utils/__init__.py evennia-engine/evennia/evennia/server/portal/amp_server.py evennia-engine/evennia/evennia/typeclasses/migrations/0004_auto_20151101_1759.py evennia-engine/engine/server/__init__.py evennia-engine/evenv/share/doc/networkx-2.4/examples/algorithms/plot_davis_club.py evennia-engine/evennia/evennia/help/migrations/__init__.py evennia-engine/evennia/evennia/server/sessionhandler.py evennia-engine/evenv/share/doc/networkx-2.4/examples/drawing/plot_giant_component.py evennia-engine/evennia/evennia/scripts/migrations/0003_checksessions_defaultscript_donothing_scriptbase_store_validatechannelhandler_validateidmappercache_.py evennia-engine/evennia/evennia/help/models.py evennia-engine/evennia/evennia/contrib/turnbattle/tb_range.py evennia-engine/evennia/evennia/server/game_index_client/__init__.py evennia-engine/evenv/share/doc/networkx-2.4/examples/graph/plot_napoleon_russian_campaign.py evennia-engine/evennia/evennia/server/tests/test_server.py evennia-engine/evennia/evennia/utils/evmore.py evennia-engine/evenv/share/doc/networkx-2.4/examples/algorithms/plot_rcm.py evennia-engine/evenv/share/doc/networkx-2.4/examples/subclass/plot_antigraph.py evennia-engine/evenv/share/doc/networkx-2.4/examples/algorithms/plot_beam_search.py evennia-engine/evennia/evennia/accounts/accounts.py evennia-engine/evennia/evennia/scripts/migrations/__init__.py evennia-engine/evennia/evennia/contrib/puzzles.py evennia-engine/evennia/evennia/locks/__init__.py evennia-engine/evennia/evennia/contrib/gendersub.py evennia-engine/evennia/evennia/game_template/server/conf/mssp.py evennia-engine/evenv/share/doc/networkx-2.4/examples/drawing/plot_random_geometric_graph.py evennia-engine/evennia/evennia/objects/models.py evennia-engine/evennia/evennia/contrib/evscaperoom/room.py evennia-engine/evennia/evennia/utils/tests/test_gametime.py evennia-engine/evennia/evennia/accounts/migrations/__init__.py evennia-engine/evennia/evennia/comms/migrations/0014_auto_20170705_1736.py evennia-engine/evennia/evennia/server/__init__.py evennia-engine/evennia/evennia/objects/migrations/0007_objectdb_db_account.py evennia-engine/evennia/evennia/utils/search.py evennia-engine/evennia/evennia/typeclasses/migrations/0009_rename_player_cmdsets_typeclasses.py evennia-engine/evennia/evennia/objects/migrations/0006_auto_20170606_1731.py evennia-engine/evennia/evennia/contrib/evscaperoom/objects.py evennia-engine/evennia/evennia/contrib/email_login.py evennia-engine/evennia/evennia/typeclasses/migrations/0008_lock_and_perm_rename.py evennia-engine/evennia/evennia/contrib/tutorial_world/rooms.py evennia-engine/evennia/evennia/web/urls.py evennia-engine/engine/server/conf/lockfuncs.py evennia-engine/evennia/evennia/typeclasses/__init__.py evennia-engine/evennia/evennia/utils/tests/test_evmenu.py evennia-engine/evennia/evennia/server/profiling/dummyrunner_settings.py evennia-engine/evennia/evennia/contrib/random_string_generator.py evennia-engine/evennia/evennia/web/website/tests.py evennia-engine/evennia/evennia/typeclasses/migrations/__init__.py evennia-engine/evennia/evennia/accounts/migrations/0001_initial.py evennia-engine/evennia/evennia/prototypes/tests.py evennia-engine/evenv/Scripts/pywin32_postinstall.py evennia-engine/evennia/evennia/web/webclient/urls.py evennia-engine/evenv/share/doc/networkx-2.4/examples/graph/plot_erdos_renyi.py evennia-engine/evennia/evennia/__init__.py evennia-engine/evennia/evennia/web/__init__.py evennia-engine/evennia/evennia/game_template/server/conf/cmdparser.py evennia-engine/evennia/evennia/web/utils/general_context.py evennia-engine/evennia/evennia/prototypes/menus.py evennia-engine/evennia/evennia/web/utils/middleware.py evennia-engine/evennia/evennia/comms/admin.py evennia-engine/evennia/evennia/server/portal/irc.py evennia-engine/evennia/evennia/comms/channelhandler.py evennia-engine/evennia/evennia/contrib/evscaperoom/states/state_001_start.py evennia-engine/evennia/evennia/server/tests/testrunner.py evennia-engine/evennia/evennia/accounts/migrations/0002_move_defaults.py evennia-engine/evennia/evennia/web/utils/backends.py evennia-engine/evennia/evennia/contrib/ingame_python/tests.py evennia-engine/evennia/evennia/contrib/security/auditing/outputs.py evennia-engine/evennia/evennia/game_template/typeclasses/objects.py evennia-engine/evennia/evennia/typeclasses/tags.py evennia-engine/evennia/evennia/accounts/admin.py evennia-engine/evennia/evennia/comms/migrations/0005_auto_20150223_1517.py evennia-engine/evennia/evennia/utils/logger.py evennia-engine/evennia/evennia/objects/migrations/0005_auto_20150403_2339.py evennia-engine/evenv/share/doc/networkx-2.4/examples/drawing/plot_house_with_colors.py evennia-engine/engine/typeclasses/exits.py evennia-engine/evennia/evennia/game_template/server/conf/server_services_plugins.py evennia-engine/evennia/evennia/comms/migrations/0015_auto_20170706_2041.py evennia-engine/evenv/share/doc/networkx-2.4/examples/basic/plot_read_write.py evennia-engine/evennia/evennia/server/game_index_client/client.py evennia-engine/evennia/evennia/game_template/server/conf/inlinefuncs.py evennia-engine/evennia/evennia/accounts/migrations/0008_auto_20190128_1820.py evennia-engine/evennia/evennia/contrib/tutorial_world/__init__.py evennia-engine/evennia/evennia/objects/migrations/0003_defaultcharacter_defaultexit_defaultobject_defaultroom.py evennia-engine/evennia/evennia/accounts/manager.py evennia-engine/evennia/evennia/utils/batchprocessors.py evennia-engine/evennia/evennia/utils/idmapper/__init__.py evennia-engine/evennia/evennia/commands/command.py evennia-engine/evennia/evennia/server/throttle.py evennia-engine/engine/server/conf/portal_services_plugins.py evennia-engine/evennia/evennia/typeclasses/migrations/0006_auto_add_dbmodel_value_for_tags_attributes.py neural-based/KG-extraction/bert.py evennia-engine/evennia/evennia/contrib/evscaperoom/menu.py evennia-engine/evennia/evennia/server/manager.py evennia-engine/evennia/evennia/server/portal/webclient.py evennia-engine/evennia/evennia/game_template/world/prototypes.py evennia-engine/evennia/evennia/commands/default/cmdset_unloggedin.py evennia-engine/evennia/evennia/contrib/tutorial_examples/bodyfunctions.py evennia-engine/evenv/Scripts/pywin32_testall.py evennia-engine/evennia/evennia/contrib/evscaperoom/scripts.py evennia-engine/evenv/share/doc/networkx-2.4/examples/drawing/plot_lanl_routes.py evennia-engine/evennia/evennia/game_template/server/conf/at_search.py evennia-engine/evennia/evennia/commands/default/cmdset_session.py evennia-engine/evenv/share/doc/networkx-2.4/examples/drawing/plot_four_grids.py evennia-engine/engine/server/conf/mssp.py evennia-engine/engine/server/conf/inlinefuncs.py evennia-engine/evenv/share/doc/networkx-2.4/examples/drawing/plot_unix_email.py evennia-engine/evennia/evennia/contrib/turnbattle/tb_basic.py evennia-engine/evennia/evennia/contrib/building_menu.py evennia-engine/evennia/evennia/server/session.py evennia-engine/evennia/evennia/web/website/__init__.py rule-based/describe_graph.py evennia-engine/evennia/evennia/objects/manager.py evennia-engine/evennia/evennia/comms/migrations/0008_auto_20160905_0902.py evennia-engine/evennia/evennia/contrib/mail.py evennia-engine/evennia/evennia/objects/migrations/0002_auto_20140917_0756.py evennia-engine/evennia/evennia/server/admin.py evennia-engine/evennia/evennia/utils/test_resources.py evennia-engine/evennia/evennia/comms/comms.py evennia-engine/evenv/share/doc/networkx-2.4/examples/drawing/plot_degree_histogram.py evennia-engine/evennia/evennia/comms/migrations/0003_auto_20140917_0756.py evennia-engine/evennia/evennia/commands/default/account.py evennia-engine/evennia/evennia/objects/migrations/0008_auto_20170705_1736.py evennia-engine/evennia/evennia/contrib/security/auditing/server.py evennia-engine/evennia/evennia/game_template/server/conf/secret_settings.py evennia-engine/evennia/evennia/server/profiling/tests.py evennia-engine/evennia/evennia/help/migrations/0003_auto_20190128_1820.py neural-based/KG-extraction/utils_squad_evaluate.py evennia-engine/evennia/evennia/server/inputfuncs.py evennia-engine/evennia/evennia/comms/migrations/0004_auto_20150118_1631.py evennia-engine/evennia/evennia/contrib/ingame_python/eventfuncs.py evennia-engine/evennia/evennia/commands/default/muxcommand.py evennia-engine/engine/typeclasses/channels.py evennia-engine/evennia/evennia/utils/evmenu.py evennia-engine/engine/server/conf/at_server_startstop.py evennia-engine/evennia/evennia/server/portal/ssl.py evennia-engine/evennia/evennia/game_template/server/conf/portal_services_plugins.py evennia-engine/evennia/evennia/contrib/turnbattle/tb_equip.py evennia-engine/evennia/evennia/typeclasses/tests.py evennia-engine/evennia/evennia/contrib/tests.py evennia-engine/evennia/evennia/help/admin.py evennia-engine/evenv/Scripts/evennia_launcher.py evennia-engine/evenv/share/doc/networkx-2.4/examples/drawing/plot_circular_tree.py evennia-engine/evennia/evennia/objects/admin.py evennia-engine/evennia/evennia/comms/__init__.py neural-based/KG-extraction/run_squad.py evennia-engine/evennia/evennia/accounts/migrations/0004_auto_20150403_2339.py evennia-engine/evennia/evennia/contrib/tutorial_world/mob.py evennia-engine/evennia/evennia/typeclasses/migrations/0001_initial.py neural-based/KG-extraction/kg-extraction.py evennia-engine/evenv/share/doc/networkx-2.4/examples/drawing/plot_ego_graph.py evennia-engine/evennia/evennia/contrib/ingame_python/utils.py evennia-engine/evennia/evennia/contrib/chargen.py evennia-engine/evennia/evennia/server/profiling/timetrace.py evennia-engine/evennia/evennia/contrib/simpledoor.py evennia-engine/evennia/evennia/utils/evtable.py evennia-engine/evennia/evennia/contrib/slow_exit.py evennia-engine/graph2world/generator.py evennia-engine/engine/typeclasses/accounts.py evennia-engine/evennia/evennia/commands/default/admin.py evennia-engine/evennia/evennia/scripts/monitorhandler.py evennia-engine/evennia/evennia/utils/gametime.py evennia-engine/graph2world/main.py evennia-engine/evennia/evennia/server/game_index_client/service.py evennia-engine/evennia/evennia/server/migrations/__init__.py evennia-engine/evennia/evennia/utils/picklefield.py evennia-engine/evennia/evennia/game_template/server/__init__.py evennia-engine/evennia/evennia/server/migrations/0001_initial.py evennia-engine/evennia/evennia/typeclasses/migrations/0002_auto_20150109_0913.py evennia-engine/evenv/share/doc/networkx-2.4/examples/algorithms/plot_blockmodel.py evennia-engine/evennia/evennia/typeclasses/migrations/0011_auto_20190128_1820.py evennia-engine/evennia/evennia/accounts/tests.py evennia-engine/evennia/evennia/commands/default/comms.py evennia-engine/evennia/evennia/help/__init__.py evennia-engine/evennia/evennia/commands/default/unloggedin.py evennia-engine/evennia/evennia/comms/migrations/0009_auto_20160921_1731.py evennia-engine/evennia/evennia/scripts/__init__.py evennia-engine/evennia/evennia/scripts/migrations/0010_auto_20170705_1736.py evennia-engine/evennia/evennia/game_template/server/conf/inputfuncs.py evennia-engine/evennia/.travis/postgresql_settings.py evennia-engine/evennia/evennia/objects/tests.py evennia-engine/evennia/evennia/server/portal/telnet_ssl.py evennia-engine/evennia/evennia/server/evennia_launcher.py evennia-engine/evennia/evennia/game_template/typeclasses/scripts.py evennia-engine/evennia/evennia/server/portal/telnet.py neural-based/KG-extraction/utils_squad.py evennia-engine/evenv/share/doc/networkx-2.4/examples/graph/plot_words.py evennia-engine/evennia/evennia/utils/utils.py evennia-engine/evennia/evennia/objects/objects.py evennia-engine/evennia/evennia/contrib/wilderness.py evennia-engine/engine/__init__.py evennia-engine/evenv/share/doc/networkx-2.4/examples/javascript/force.py evennia-engine/evennia/evennia/commands/default/building.py evennia-engine/engine/server/conf/connection_screens.py rule-based/process_story.py evennia-engine/evennia/evennia/comms/migrations/0002_msg_db_hide_from_objects.py evennia-engine/evennia/evennia/contrib/security/auditing/tests.py evennia-engine/evennia/evennia/utils/optionhandler.py evennia-engine/evennia/evennia/commands/cmdparser.py evennia-engine/evennia/evennia/server/portal/ssh.py evennia-engine/evennia/evennia/comms/migrations/0013_auto_20170705_1726.py evennia-engine/evennia/evennia/contrib/__init__.py evennia-engine/evennia/evennia/utils/idmapper/manager.py evennia-engine/evennia/evennia/server/portal/portalsessionhandler.py evennia-engine/evennia/evennia/game_template/server/conf/at_server_startstop.py evennia-engine/evennia/evennia/settings_default.py evennia-engine/evennia/evennia/commands/default/batchprocess.py evennia-engine/evenv/share/doc/networkx-2.4/examples/pygraphviz/plot_write_dotfile.py evennia-engine/evennia/evennia/game_template/typeclasses/accounts.py evennia-engine/evennia/evennia/server/portal/webclient_ajax.py evennia-engine/engine/server/conf/inputfuncs.py evennia-engine/evennia/evennia/utils/text2html.py evennia-engine/evennia/bin/project_rename.py evennia-engine/evennia/evennia/utils/eveditor.py evennia-engine/evennia/evennia/commands/default/general.py evennia-engine/evennia/evennia/help/manager.py evennia-engine/evennia/evennia/comms/migrations/0001_initial.py evennia-engine/evenv/share/doc/networkx-2.4/examples/3d_drawing/mayavi2_spring.py evennia-engine/evennia/evennia/contrib/tutorial_examples/red_button.py evennia-engine/evennia/evennia/contrib/tutorial_examples/red_button_scripts.py evennia-engine/engine/server/conf/__init__.py evennia-engine/evennia/evennia/contrib/ingame_python/callbackhandler.py evennia-engine/evennia/evennia/comms/models.py evennia-engine/engine/commands/default_cmdsets.py evennia-engine/evennia/evennia/scripts/tickerhandler.py evennia-engine/engine/world/prototypes.py evennia-engine/evennia/evennia/game_template/typeclasses/characters.py evennia-engine/evennia/evennia/scripts/migrations/0006_auto_20150310_2249.py evennia-engine/evennia/evennia/typeclasses/migrations/0005_auto_20160625_1812.py evennia-engine/evenv/share/doc/networkx-2.4/examples/drawing/plot_labels_and_colors.py evennia-engine/evenv/Scripts/django-admin.py evennia-engine/evennia/evennia/prototypes/protfuncs.py evennia-engine/graph2world/function_words.py evennia-engine/evennia/evennia/scripts/migrations/0011_remove_scriptdb_db_player.py evennia-engine/evennia/evennia/contrib/custom_gametime.py evennia-engine/evennia/evennia/scripts/migrations/0007_auto_20150403_2339.py evennia-engine/evenv/share/doc/networkx-2.4/examples/graph/plot_football.py evennia-engine/engine/typeclasses/characters.py evennia-engine/evenv/share/doc/networkx-2.4/examples/pygraphviz/plot_pygraphviz_attributes.py evennia-engine/evennia/evennia/contrib/evscaperoom/state.py evennia-engine/evennia/evennia/utils/tests/test_create_functions.py evennia-engine/evennia/evennia/comms/migrations/0007_msg_db_tags.py evennia-engine/evennia/evennia/comms/migrations/0006_channeldb_db_object_subscriptions.py evennia-engine/evennia/evennia/utils/evform.py evennia-engine/evennia/evennia/contrib/tutorial_examples/tests.py evennia-engine/evennia/evennia/utils/idmapper/models.py rule-based/draw_graph.py evennia-engine/evennia/evennia/typeclasses/attributes.py evennia-engine/evennia/evennia/server/profiling/settings_mixin.py evennia-engine/evennia/evennia/server/server.py evennia-engine/evennia/evennia/game_template/web/urls.py evennia-engine/evennia/evennia/commands/default/cmdset_character.py evennia-engine/evennia/evennia/contrib/health_bar.py evennia-engine/evennia/evennia/contrib/evscaperoom/commands.py evennia-engine/evennia/evennia/contrib/evscaperoom/utils.py evennia-engine/evennia/evennia/utils/tests/test_tagparsing.py evennia-engine/evennia/evennia/accounts/models.py evennia-engine/evennia/evennia/comms/migrations/0011_auto_20170217_2039.py evennia-engine/evenv/share/doc/networkx-2.4/examples/drawing/plot_degree_rank.py evennia-engine/evennia/evennia/server/portal/naws.py evennia-engine/evennia/evennia/server/amp_client.py evennia-engine/evennia/evennia/utils/tests/data/evform_example.py evennia-engine/evenv/share/doc/networkx-2.4/examples/drawing/plot_directed.py evennia-engine/evennia/evennia/contrib/color_markups.py evennia-engine/evennia/evennia/server/tests/test_misc.py evennia-engine/evennia/evennia/utils/optionclasses.py evennia-engine/evennia/evennia/contrib/talking_npc.py evennia-engine/evennia/evennia/game_template/server/conf/at_initial_setup.py evennia-engine/evennia/evennia/game_template/server/conf/__init__.py evennia-engine/evennia/evennia/utils/tests/test_eveditor.py evennia-engine/engine/server/conf/at_search.py evennia-engine/evennia/evennia/server/connection_wizard.py evennia-engine/evennia/evennia/commands/tests.py evennia-engine/evennia/evennia/comms/migrations/0010_auto_20161206_1912.py evennia-engine/engine/typeclasses/scripts.py evennia-engine/evennia/evennia/commands/default/cmdset_account.py evennia-engine/evennia/evennia/game_template/server/conf/serversession.py evennia-engine/evennia/evennia/server/serversession.py evennia-engine/evenv/share/doc/networkx-2.4/examples/drawing/plot_edge_colormap.py evennia-engine/evennia/evennia/accounts/migrations/0005_auto_20160905_0902.py neural-based/scrape-wikipedia/demo_load.py evennia-engine/evennia/evennia/web/website/forms.py evennia-engine/evennia/evennia/game_template/server/conf/settings.py evennia-engine/evennia/evennia/server/profiling/dummyrunner.py evennia-engine/evenv/share/doc/networkx-2.4/examples/subclass/plot_printgraph.py evennia-engine/evennia/evennia/comms/migrations/0016_auto_20180925_1735.py evennia-engine/evennia/evennia/server/portal/mssp.py evennia-engine/evennia/evennia/contrib/rplanguage.py evennia-engine/graph2world/g2w.py evennia-engine/evennia/evennia/commands/__init__.py evennia-engine/evennia/evennia/scripts/admin.py evennia-engine/evennia/evennia/server/portal/rss.py evennia-engine/evennia/evennia/commands/default/help.py evennia-engine/evenv/share/doc/networkx-2.4/examples/algorithms/plot_krackhardt_centrality.py evennia-engine/evennia/evennia/contrib/tutorial_examples/cmdset_red_button.py evennia-engine/evennia/evennia/help/migrations/0001_initial.py evennia-engine/evenv/share/doc/networkx-2.4/examples/drawing/plot_simple_path.py evennia-engine/evennia/evennia/server/portal/mccp.py evennia-engine/evenv/share/doc/networkx-2.4/examples/graph/plot_expected_degree_sequence.py evennia-engine/evennia/evennia/accounts/migrations/0003_auto_20150209_2234.py evennia-engine/evenv/share/doc/networkx-2.4/examples/drawing/plot_chess_masters.py evennia-engine/evennia/evennia/scripts/models.py evennia-engine/evennia/evennia/contrib/extended_room.py evennia-engine/evennia/.travis/sqlite3_settings.py neural-based/scrape-wikipedia/scrape/get_page.py evennia-engine/evennia/evennia/web/website/views.py evennia-engine/evennia/evennia/comms/migrations/0017_auto_20190128_1820.py evennia-engine/evennia/evennia/game_template/commands/command.py evennia-engine/evennia/evennia/contrib/tutorial_examples/example_batch_code.py evennia-engine/evennia/evennia/server/initial_setup.py evennia-engine/evenv/share/doc/networkx-2.4/examples/advanced/plot_iterated_dynamical_systems.py evennia-engine/evennia/evennia/server/webserver.py evennia-engine/evennia/evennia/game_template/typeclasses/rooms.py evennia-engine/evennia/evennia/utils/idmapper/tests.py evennia-engine/evennia/evennia/commands/default/syscommands.py evennia-engine/evenv/share/doc/networkx-2.4/examples/drawing/plot_spectral_grid.py evennia-engine/evennia/evennia/scripts/migrations/0004_auto_20150306_1354.py evennia-engine/evennia/evennia/scripts/migrations/0012_auto_20190128_1820.py evennia-engine/evennia/evennia/contrib/menu_login.py evennia-engine/evennia/evennia/utils/containers.py evennia-engine/evennia/evennia/contrib/unixcommand.py evennia-engine/evennia/evennia/commands/cmdsethandler.py evennia-engine/evenv/share/doc/networkx-2.4/examples/pygraphviz/plot_pygraphviz_draw.py evennia-engine/evennia/evennia/utils/tests/test_evform.py evennia-engine/evennia/evennia/server/tests/test_amp_connection.py evennia-engine/evennia/evennia/utils/tests/test_utils.py evennia-engine/engine/commands/command.py evennia-engine/evennia/evennia/server/portal/grapevine.py evennia-engine/evennia/evennia/contrib/ingame_python/commands.py evennia-engine/evennia/evennia/prototypes/prototypes.py evennia-engine/evenv/share/doc/networkx-2.4/examples/basic/plot_properties.py evennia-engine/evennia/evennia/typeclasses/managers.py evennia-engine/evennia/evennia/prototypes/spawner.py evennia-engine/evenv/share/doc/networkx-2.4/examples/pygraphviz/plot_pygraphviz_simple.py evennia-engine/engine/typeclasses/objects.py evennia-engine/evennia/bin/windows/evennia_launcher.py evennia-engine/evennia/evennia/objects/migrations/0010_auto_20190128_1820.py Command SessionCmdSet AccountCmdSet UnloggedinCmdSet CharacterCmdSet at_initial_setup at_search_result at_server_stop at_server_reload_start at_server_start at_server_reload_stop at_server_cold_start at_server_cold_stop cmdparser start_plugin_services ServerSession start_plugin_services at_webserver_root_creation Guest Account Channel Character Exit Object Room Script package_data get_version get_requirements get_scripts rename_in_file _red _green _case_sensitive_replace _yellow rename_in_tree _create_version _init set_trace DefaultAccount AccountSessionHandler DefaultGuest AccountForm AccountAttributeInline AccountTagInline AccountInline AccountDBCreationForm AccountDBChangeForm AccountDBAdmin RSSBot GrapevineBot BotStarter Bot IRCBot AccountManager AccountDBManager AccountDB TestDefaultAccount TestDefaultAccountAuth TestDefaultAccountEv TestDefaultGuest TestAccountPuppetDeletion TestAccountSessionHandler Migration convert_defaults Migration Migration Migration Migration Migration Migration forwards Migration _progressive_cmd_run _process_input NoCmdSets get_and_merge_cmdsets ErrorReported ExecSystemCommand cmdhandler _msg_err try_num_prefixes build_matches create_match cmdparser _CmdSetMeta CmdSet _EmptyCmdSet import_cmdset CmdSetHandler _ErrorCmdSet InterruptCommand _init_command Command CommandMeta _CmdSetC _CmdSetTest _CmdB _CmdSetA TestGetAndMergeCmdSets _CmdC _CmdD _mockdelay _CmdSetB TestCmdParser AccessableCommand _CmdSetD _CmdA _CmdTest1 TestCmdSetMergers _CmdTest3 _CmdTest2 _CmdTest4 CmdQuell CmdQuit CmdIC CmdCharDelete CmdStyle CmdCharCreate CmdWho CmdColorTest CmdOOCLook MuxAccountLookCommand CmdOption CmdPassword CmdOOC CmdSessions CmdWall CmdNewPassword CmdBoot CmdForce CmdBan CmdEmit CmdPerm list_bans CmdUnban CmdStateNN show_curr CmdStateBL CmdBatchCode BatchSafeCmdSet CmdStateJJ CmdStateSS format_header CmdBatchCommands CmdStateCC format_code CmdStateLL CmdStateQQ CmdStateAbort batch_cmd_exec CmdStateRRR CmdStatePP CmdStateSL BatchInteractiveCmdSet purge_processor CmdStateBB step_pointer batch_code_exec CmdStateRR CmdStateJL CmdStateNL CmdStateHH CmdExamine _desc_load CmdLink _desc_save CmdSpawn CmdDig ObjManipCommand CmdCopy CmdOpen CmdTag CmdTunnel CmdTeleport CmdDesc CmdTypeclass CmdFind CmdCpAttr CmdMvAttr CmdWipe CmdUnLink CmdDestroy CmdSetObjAlias CmdCreate CmdScript _desc_quit CmdSetAttribute CmdName CmdListCmdSets _convert_from_string CmdSetHome CmdLock AccountCmdSet CharacterCmdSet SessionCmdSet UnloggedinCmdSet CmdLook CmdMove CmdGet CmdDrop CmdInventory CmdGive _loadhelp CmdHelp _quithelp _savehelp CmdSetHelp MuxCommand MuxAccountCommand SystemNoMatch SystemMultimatch SystemNoInput SystemSendToChannel CmdAbout _py_load CmdTickers format_script_list CmdShutdown _py_code _py_quit CmdAccounts CmdTime CmdReload CmdService CmdServerLoad CmdObjects _run_code_snippet CmdPy CmdScripts evennia_local_vars EvenniaPythonConsole CmdReset CommandTest TestHelp TestUnconnectedCommand TestGeneral TestAdmin TestBatchProcess TestBuilding TestInterruptCommand TestAccount TestComms TestSystemCommands CmdInterrupt TestSystem _create_account CmdUnconnectedConnect create_guest_account CmdUnconnectedHelp CmdUnconnectedEncoding _create_character CmdUnconnectedQuit create_normal_account CmdUnconnectedInfo CmdUnconnectedLook CmdUnconnectedScreenreader ChannelAttributeInline ChannelTagInline ChannelAdmin MsgAdmin ChannelCommand ChannelHandler DefaultChannel ChannelManager identify_object CommError ChannelDBManager dbref to_object MsgManager TempMsg ChannelDB SubscriptionHandler Msg ObjectCreationTest Migration Migration Migration convert_defaults Migration convert_channelnames Migration Migration Migration Migration Migration Migration Migration Migration Migration _table_exists Migration Migration forwards _table_exists Migration Migration Migration TradeTimeout CmdAccept CmdEvaluate CmdTradeHelp CmdStatus CmdFinish CmdTrade CmdDecline TradeHandler CmdTradeBase CmdOffer CmdsetTrade _menu_quitfunc GenericBuildingCmd BuildingMenuCmdSet CmdNoMatch menu_edit BuildingMenu _menu_loadfunc _call_or_get Choice _menu_savefunc menu_quit GenericBuildingMenu menu_setattr CmdNoInput OOCCmdSetCharGen CmdOOCCharacterCreate CmdOOCLook ClothedCharacter CmdCover CmdUncover get_worn_clothes Clothing clothing_type_count ClothedCharacterCmdSet CmdDrop order_clothes_list single_type_count CmdRemove CmdInventory CmdWear CmdGive realtime_to_gametime real_seconds_until gametime_to_realtime time_to_tuple schedule GametimeScript custom_gametime roll_dice DiceCmdSet CmdDice CmdUnconnectedCreate CmdUnconnectedConnect UnloggedinCmdSet CmdUnconnectedHelp CmdUnconnectedQuit CmdUnconnectedLook CmdExtendedRoomDetail CmdExtendedRoomLook ExtendedRoom CmdExtendedRoomDesc ExtendedRoomCmdSet CmdExtendedRoomGameTime init_fill_field sendmessage FieldEvMenu menunode_fieldfill verify_online_player form_template_to_dict init_delayed_message display_formdata CmdTestMenu GenderCharacter SetGender display_meter CmdMail CmdMailCharacter build_map _map_to_list example2_build_verticle_exit example2_build_horizontal_exit example1_build_temple example2_build_forest example1_build_mountains example1_build_forest CmdMapBuilder node_enter_username node_enter_password CmdUnloggedinLook node_quit_or_login _show_help UnloggedinCmdSet _node_formatter _load_editor _update_store _quit_editor CmdMultiDesc _save_editor DescValidateError CmdArmPuzzle CmdCreatePuzzleRecipe CmdListPuzzleRecipes maskout_protodef CmdListArmedPuzzles PuzzleSystemCmdSet _matching_puzzles CmdUsePuzzleParts PuzzleRecipe _lookups_parts_puzzlenames_protodefs proto_def CmdEditPuzzle _colorize_message _puzzles_by_names ExhaustedGenerator RandomStringGeneratorScript RejectedRegex RandomStringGenerator LanguageHandler LanguageError LanguageExistsError add_language available_languages obfuscate_language obfuscate_whisper CmdSay CmdEmote SdescError ContribRPCharacter RecogError regex_tuple_from_key_alias RPCommand CmdRecog ContribRPObject SdescHandler RPSystemCmdSet RecogHandler parse_sdescs_and_recogs EmoteError CmdSdesc parse_language LanguageError CmdPose ContribRPRoom send_emote CmdMask _dummy_process ordered_permutation_regex SimpleDoor CmdOpen CmdOpenCloseDoor CmdStop CmdSetSpeed SlowExit TalkingNPC END TalkingCmdSet info1 info2 menu_start_node info3 CmdTalk _cancellable_mockdelay TestCustomGameTime TestMail TestTurnBattleItemsCmd TestBarter TestTalkingNPC TestTreeSelectFunc TestTutorialWorldMob TestTurnBattleBasicCmd TestLanguage TestExtendedRoom TestMapBuilder TestTurnBattleBasicFunc TestChargen TestTutorialWorldRooms TestEmailLogin TestMenuLogin TestColorMarkup _testcallback TestTurnBattleMagicFunc TestDice TestSlowExit TestGenderSub TestTurnBattleEquipCmd TestRPSystem TestTutorialWorldObjects TestMultidescer CmdDummy TestFieldFillFunc TestUnixCommand TestTurnBattleRangeFunc TestPuzzles TestSimpleDoor TestRandomStringGenerator TestTurnBattleMagicCmd TestTurnBattleEquipFunc TestTurnBattleItemsFunc TestTurnBattleRangeCmd TestBuildingMenu ForceUTCDatetime Submenu TestWilderness TestHealthBar TestClothingFunc TestClothingCmd init_tree_selection parse_opts index_to_selection CmdNameColor change_name_color dashcount is_category go_up_one_category optlist_to_menuoptions menunode_treeselect ParseError HelpAction UnixCommandParser UnixCommand WildernessExit WildernessMapProvider WildernessRoom create_wilderness enter_wilderness get_new_coordinates WildernessScript CmdLook CmdEvscapeRoom CmdRerouter CmdOptions CmdWho CmdHelp CmdJumpState CmdEmote CmdGet CmdEvscapeRoomStart CmdGiveUp CmdSetFlag CmdFocusInteraction CmdStand CmdCreateObj CmdSpeak CmdSetEvScapeRoom CmdFocus _select_room run_evscaperoom_menu node_create_room OptionsMenu run_option_menu node_set_desc EvscaperoomMenu _get_all_rooms node_quit node_start node_options _set_thing_style _toggle_screen_reader _create_new_room _move_to_room node_join_room CodeInput Mixable Kneelable EvscaperoomObject Positionable BaseConsumable Rotatable IndexReadable Liable Edible Combinable Usable Insertable Listenable HasButtons Openable BaseApplicable Smellable Feelable Climbable Readable Movable Sittable BasePositionable Drinkable EvscapeRoom CleanupScript StateHandler BaseState TestUtils TestEvScapeRoom TestStates TestEvscaperoomCommands msg_cinematic add_msg_borders parse_for_things create_evscaperoom_object parse_for_perspectives create_fantasy_word HelpButton Key State Door CallbackHandler _ev_save _ev_load CmdCallback _ev_quit get deny call_event complete_task TimeEventScript EventHandler EventRoom EventCharacter EventObject EventExit get_event_handler InterruptEvent get_next_wait register_events time_event keyword_event phrase_event to_file to_syslog AuditedServerSession AuditingTest is_in_combat CmdAttack roll_init TBBasicTurnHandler resolve_attack spend_action combat_cleanup CmdRest apply_damage CmdPass get_damage is_turn TBBasicCharacter CmdDisengage get_defense BattleCmdSet CmdCombatHelp get_attack at_defeat CmdFight is_in_combat CmdAttack roll_init CmdWield TBEquipCharacter CmdDoff resolve_attack spend_action combat_cleanup TBEWeapon CmdRest CmdDon apply_damage CmdPass get_damage is_turn CmdDisengage get_defense CmdUnwield BattleCmdSet TBEquipTurnHandler CmdCombatHelp get_attack at_defeat CmdFight TBEArmor add_condition is_in_combat CmdAttack roll_init condition_tickdown itemfunc_add_condition resolve_attack spend_action combat_cleanup CmdRest TBItemsCharacterTest apply_damage itemfunc_cure_condition CmdPass TBItemsCharacter get_damage is_turn CmdDisengage get_defense TBItemsTurnHandler CmdUse BattleCmdSet CmdCombatHelp get_attack use_item spend_item_use itemfunc_heal at_defeat CmdFight itemfunc_attack CmdStatus is_in_combat CmdAttack roll_init CmdCast spell_healing resolve_attack spend_action combat_cleanup CmdRest apply_damage TBMagicCharacter CmdPass CmdLearnSpell spell_conjure get_damage is_turn CmdDisengage get_defense BattleCmdSet spell_attack CmdCombatHelp get_attack TBMagicTurnHandler at_defeat CmdFight CmdStatus distance_inc is_in_combat roll_init TBRangeTurnHandler combat_status_message CmdAttack CmdApproach get_range resolve_attack spend_action combat_cleanup CmdRest apply_damage CmdPass CmdShoot get_damage is_turn withdraw TBRangeObject CmdWithdraw CmdDisengage get_defense approach BattleCmdSet CmdCombatHelp TBRangeCharacter get_attack at_defeat CmdFight BodyFunctions LidClosedCmdSet CmdPush CmdNudge CmdCloseLid CmdBlindLook BlindCmdSet CmdBlindHelp CmdSmashGlass DefaultCmdSet LidOpenCmdSet CmdOpenLid RedButton DeactivateButtonEvent CloseLidEvent ClosedLidState OpenLidState BlinkButtonEvent BlindedState TestBodyFunctions MobCmdSet Mob CmdMobOnOff CmdSetLight CmdRead CmdShiftRoot CmdAttack CrumblingWall Weapon CmdLight CmdPressButton CmdClimb TutorialObject TutorialClimbable CmdSetCrumblingWall CmdSetClimbable WeaponRack CmdSetWeaponRack TutorialReadable CmdSetReadable CmdSetWeapon Obelisk LightSource CmdGetWeapon BridgeRoom CmdTutorialLook CmdEast CmdTutorialSetDetail BridgeCmdSet CmdLookBridge CmdBridgeHelp CmdDarkHelp WeatherRoom TeleportRoom DarkRoom DarkCmdSet OutroRoom CmdDarkNoMatch IntroRoom TutorialRoomCmdSet CmdTutorial CmdLookDark TutorialRoom CmdWest Command SessionCmdSet AccountCmdSet UnloggedinCmdSet CharacterCmdSet at_initial_setup at_search_result at_server_stop at_server_reload_start at_server_start at_server_reload_stop at_server_cold_start at_server_cold_stop cmdparser start_plugin_services ServerSession start_plugin_services at_webserver_root_creation Guest Account Channel Character Exit Object Room Script HelpEntryAdmin HelpTagInline HelpEntryForm HelpEntryManager HelpEntry Migration Migration Migration pid attr_eq attr_gt id _to_account attr_lt objtag false superuser perm inside all serversetting attr_ge self perm_above has_account dbref locattr true holds tag objlocattr pdbref attr objattr attr_le pperm none pperm_above attr_ne validate_lockstring _test LockException check_lockstring _cache_lockfuncs _ObjDummy LockHandler get_all_lockfuncs TestLockCheck TestLockfuncs ObjectEditForm ObjectCreateForm ObjectTagInline ObjectDBAdmin ObjectAttributeInline ObjectManager ObjectDBManager ObjectDB ContentsHandler DefaultObject DefaultCharacter ExitCommand DefaultExit ObjectSessionHandler DefaultRoom DefaultObjectTest TestObjectManager Migration Migration Migration convert_defaults Migration Migration Migration _table_exists Migration Migration forwards _table_exists Migration Migration _add_attr node_destination node_aliases node_apply_diff _spawn start_olc _lock_add _set_prototype_value _get_tup_by_attrname node_examine_entity node_prototype_save node_key _set_actioninfo node_locks _attr_select _display_attribute _caller_attrs _format_lockfuncs _path_cropper _prototype_load_actions _display_perm _get_flat_menu_prototype _apply_diff node_prototype_locks _check_prototype_key _get_tup_by_tagname _typeclass_select node_prototype_parent _format_list_actions _lock_select node_prototype_key _prototype_parent_actions _set_menu_prototype _prototype_lock_add _caller_tags _caller_locks _tag_select _permission_select _get_menu_prototype node_location _caller_prototype_tags node_tags _search_object _add_tag node_prototype_spawn node_permissions node_search_object node_prototype_tags _attrs_actions _wizard_options node_typeclass OLCMenu _locks_display _format_diff_text_and_options _get_unchanged_inherited _keep_diff _object_search_actions _prototype_locks_actions _tags_actions node_attrs _all_prototype_parents _typeclass_actions node_prototype_desc _format_option_value node_home _prototype_tag_select _aliases_select _display_tag _set_property _prototype_lock_select _prototype_load_select node_validate_prototype _add_perm _format_protfuncs _default_parse _is_new_prototype node_prototype_load _add_prototype_tag _aliases_actions _caller_permissions node_index _object_search_select _locks_actions _permissions_actions _all_aliases _validate_prototype _get_current_value _prototype_parent_select _caller_prototype_locks _all_typeclasses _prototype_tags_actions _obj_search toint mult obj objlist random choice add div eval sub protkey full_justify randint dbref center_justify right_justify left_justify protfunc_parser init_spawn_value save_prototype homogenize_prototype value_to_obj_or_any search_objects_with_prototype format_available_protfuncs DbPrototype delete_prototype value_to_obj list_prototypes validate_prototype check_permission PermissionError prototype_to_str search_prototype ValidationError prototype_diff spawn prototype_from_object _get_prototype flatten_diff batch_update_objects_with_prototype batch_create_object flatten_prototype prototype_diff_from_object TestProtLib TestUtils TestPrototypeStorage TestSpawner TestMenuModule _MockMenu TestProtFuncs TestOLCMenu ScriptAttributeInline ScriptTagInline ScriptDBAdmin ScriptDBManager ScriptManager ScriptDB MonitorHandler ScriptHandler restart_scripts_after_flush DefaultScript DoNothing Store ExtendedLoopingCall ScriptBase TaskHandler TestScript TestScriptDB TickerPool TickerHandler Ticker Migration convert_defaults Migration Migration Migration remove_manage_scripts Migration Migration remove_manage_scripts Migration Migration _table_exists Migration Migration forwards _table_exists Migration Migration ServerConfigAdmin AMPServerClientProtocol AMPClientFactory node_view_and_apply_settings ConnectionWizard node_game_index_fields node_start node_game_index_start node_mssp_start _save_changes check_errors check_warnings wait_for_status_reply _get_twistd_cmdline create_superuser AMPLauncherProtocol MsgStatus MsgLauncher2Portal start_evennia evennia_version _parse_status run_menu stop_server_only create_game_directory collectstatic check_database reload_evennia create_secret_key show_version_info start_only_server start_portal_interactive init_game_directory run_dummyrunner run_connect_wizard getenv del_pid error_check_python_modules _file_names_compact create_settings_file start_server_interactive tail_log_files _print_info send_instruction list_settings stop_evennia main set_gamedir query_status get_pid kill _reactor_stop reboot_evennia wait_for_status _is_windows query_info check_main_evennia_dependencies set_restart_mode get_pid cycle_logfile start_services get_restart_mode getenv main create_objects reset_server create_channels get_god_account handle_setup at_initial_setup collectstatic monitor echo _NA get_value bot_data_in unrepeat login msdp_report external_discord_hello unmonitor msdp_unreport get_client_options client_options get_inputfuncs _testrepeat monitored _on_monitor_change webclient_options default text repeat _on_webclient_options_change msdp_list ServerConfigManager ServerConfig _server_maintenance Evennia NAttributeHandler NDbHolder ServerSession Session SessionHandler DummySession ServerSessionHandler delayed_import Throttle EvenniaPasswordValidator EvenniaUsernameAvailabilityValidator WSGIWebServer PrivateStaticRoot HTTPChannelWithXForwardedFor EvenniaReverseProxyResource Website DjangoWebRoot LockableThreadPool StringProducer QuietHTTP11ClientFactory EvenniaGameIndexClient SimpleResponseReceiver EvenniaGameIndexService Migration Migration forwards AMPMultiConnectionProtocol _get_logger AdminPortal2Server MsgPortal2Server dumps MsgServer2Portal Compressed FunctionCall loads MsgLauncher2Portal MsgStatus AdminServer2Portal catch_traceback getenv AMPServerProtocol _is_windows AMPServerFactory RestartingWebsocketServerFactory GrapevineClient IRCBot IRCBotFactory parse_irc_to_ansi parse_ansi_to_irc Mccp mccp_compress Mssp mxp_parse Mxp Naws Portal Websocket PortalSessionHandler RSSBotFactory RSSReader PassAvatarIdTerminalRealm ExtraInfoAuthServer SshProtocol getKeyPair SSHServerFactory AccountDBPasswordChecker TerminalSessionTransport_getPeer makeFactory verify_SSL_key_and_cert getSSLContext SSLProtocol SuppressGA TelnetProtocol TelnetServerFactory TelnetOOB verify_or_create_SSL_key_and_cert getSSLContext SSLProtocol TestTelnet TestAMPServer TestIRC Ttype WebSocketClient AjaxWebClient jsonify LazyEncoder AjaxWebClientSession DummyClient gidcounter makeiter idcounter start_all_dummy_clients DummyFactory c_moves_s c_logout c_help c_creates_button c_creates_obj c_login c_looks c_digs c_moves c_moves_n c_idles c_login_nodig c_socialize c_examines Memplot TestDummyrunnerSettings TestMemPlot count_queries timetrace EvenniaTestSuiteRunner TestAMPClientRecv TestAMPClientSend _TestAMP TestInitialSetup TestLauncher ValidatorTest TestDeprecations ThrottleTest MockSettings TestServer AttributeForm AttributeFormSet TagAdmin TagFormSet AttributeInline TagForm TagInline initialize_nick_templates parse_nick_template NickTemplateInvalid NickHandler Attribute NAttributeHandler AttributeHandler TypeclassManager TypedObjectManager TypedObject remove_attributes_on_delete TypeclassBase call_at_first_save DbHolder PermissionHandler Tag TagHandler AliasHandler TestAttributes TestTypedObjectManager Migration Migration Migration Migration update_nicks Migration update_tags_with_dbmodel Migration update_tags_with_dbmodel Migration update_perms_and_locks Migration update_typeclasses Migration _case_sensitive_replace _drop_table _table_exists drop_tables Migration Migration Migration forwards parse_ansi strip_raw_ansi _on_raw ANSIMeta strip_ansi ANSIString _transform _spacing_preflight _query_super raw ANSIParser tb_iter tb_filename read_batchfile BatchCodeProcessor BatchCommandProcessor GlobalScriptContainer OptionContainer Container create_message create_channel create_script create_help_entry create_account create_object _SaverMutable _TO_DATESTRING _SaverSet _SaverList _save _get_mysql_db_version _IS_PACKED_DBOBJ unpack_dbobj do_pickle dbunserialize _init_globals to_pickle unpack_session _SaverOrderedDict dbserialize do_unpickle from_pickle _SaverDeque deserialize pack_dbobj pack_session _SaverDict _IS_PACKED_SESSION _load_editor CmdEditorGroup EvEditorCmdSet CmdLineInput CmdEditorBase CmdSaveYesNo SaveYesNoCmdSet EvEditor EvForm _to_rect _test _to_ansi CmdGetInput test_look_node EvMenu CmdTestMenu _test_call test_view_node test_dynamic_node test_set_node CmdEvMenuNode get_input _Prompt test_start_node test_end_node test_displayinput_node _generate_goto list_node EvMenuError EvMenuCmdSet InputCmdSet CmdSetMore CmdMore CmdMoreLook msg EvMore _test2 ANSITextWrapper EvTable _test wrap EvCell _to_ansi fill EvColumn gametime real_seconds_until server_epoch runtime uptime reset_gametime game_epoch schedule TimeScript portal_uptime null InlinefuncError initialize_nick_templates clr parse_nick_template ParseStack NickTemplateInvalid pad parse_inlinefunc nomatch crop log_trace log_info _open_log_file WeeklyLogFile PortalLogObserver EvenniaLogFile log_server tail_log_file log_err timeformat log_file log_sec log_warn log_dep ServerLogObserver log_msg Boolean UnsignedInteger Duration Lock BaseOption Email Text SignedInteger Datetime Future PositiveInteger Color Timezone OptionHandler InMemorySaveHandler dbsafe_decode _ObjectWrapper PickledWidget wrap_conflictual_object PickledFormField PickledObjectField PickledObject dbsafe_encode search_script_attribute search_object_attribute search_account_attribute search_object_by_tag search_channel_tag search_account_tag search_script_tag search_channel_attribute _mock_deferlater unload_module EvenniaTest mockdelay mockdeferLater parse_html TextToHTMLparser inherits_from at_search_result init_new_account host_os_is latinify datetime_format fuzzy_import_from_module wildcard_to_regexp variable_from_module justify columnize class_from_module server_services uses_database pad m_len validate_email_address check_evennia_dependencies dbref has_parent time_format all_from_module LimitedSizeOrderedDict run_async mod_import get_evennia_version string_from_module deepsize pypath_to_realpath strip_control_sequences make_iter lazy_property to_str string_similarity get_all_typeclasses crop calledby get_game_dir_path interactive callables_from_module is_iter dbref_to_obj delay format_table mod_import_from_path string_suggestions get_evennia_pids list_to_string to_bytes wrap string_partial_matching random_string_from_module dedent duration text lock unsigned_integer color timezone email future boolean positive_integer signed_integer datetime SharedMemoryManager SharedMemoryModelBase cache_size flush_cache WeakSharedMemoryModelBase flush_cached_instance update_cached_instance WeakSharedMemoryModel SharedMemoryModel conditional_flush SharedMemorysTest RegularArticle RegularCategory Category Article TestCreateScript TestEvEditor TestEvForm TestEvMenu TestEvMenuExample TestGametime TestInlineFuncs ANSIStringTestCase TestTextToHTMLparser TestTimeformat TestMLen TestCrop TestIsIter TestDateTimeFormat LatinifyTest TestDedent TestImportFunctions TestListToString CaseInsensitiveModelBackend set_game_name_and_slogan general_context set_webclient_settings SharedLoginMiddleware TestGeneralContext webclient CharacterForm AccountForm EvenniaForm ObjectForm CharacterUpdateForm RegisterTest CharacterCreateView CharacterPuppetView LoginTest PasswordResetTest ChannelDetailTest ChannelListTest CharacterManageView CharacterUpdateView CharacterDeleteView EvenniaWebTest LogoutTest AdminTest WebclientTest IndexTest CharacterListView _gamestats CharacterPuppetView CharacterDetailView CharacterMixin EvenniaIndexView evennia_admin HelpMixin CharacterUpdateView TypeclassMixin to_be_implemented ObjectCreateView CharacterListView EvenniaUpdateView ChannelMixin HelpListView ObjectDeleteView admin_wrapper ObjectUpdateView CharacterCreateView AccountMixin ChannelDetailView EvenniaDetailView HelpDetailView AccountCreateView ChannelListView EvenniaCreateView CharacterManageView CharacterDeleteView ObjectDetailView EvenniaDeleteView addclass install verify_destination LoadSystemModule Tee uninstall get_shortcuts_folder get_system_dir RegisterCOMObjects RegisterPythonwin fixup_dbi SetPyKeyVal CopyTo find_and_run run_test sum_of_digits_graph powersum cubing_153_digraph digitsrep fixed_points collatz_problem_digraph attractor153_graph squaring_cycle_digraph squaring_cycle_graph_old discrete_dynamics_digraph _betmap chunks betweenness_centrality_parallel main progressive_widening_search create_hc iso atlas6 chess_pgn_graph miles_graph lanl_graph mbox_graph minard_graph roget_graph generate_graph words_graph static_proxy AntiGraph PrintGraph graph_to_world get_gml_graph get_dummy_graph Generator main parse_args get_data parse_args World QA parse_args World readGraph set_seed evaluate main to_list train load_and_cache_examples _check_is_max_context _compute_softmax convert_example_to_features write_predictions_extended InputFeatures get_final_text _improve_answer_span _get_best_indexes read_squad_examples read_squad_example convert_examples_to_features SquadExample to_list get_predictions write_predictions find_best_thresh find_all_best_thresh_v2 apply_no_ans_threshold make_qid_to_has_ans make_eval_dict plot_pr_curve parse_args make_precision_recall_eval find_all_best_thresh compute_exact main merge_eval EVAL_OPTS compute_f1 find_best_thresh_v2 normalize_answer run_precision_recall_analysis histogram_na_prob get_raw_scores get_tokens demo main_fairy_tale compile_pages main_detective scratch_work print_stories get_stories get_subcategories get_pages get_custom get_page get_section_links get_example_plots get_plot section generate_room_intro gen_desc gen_room_obj extract_tw_template walk_through_files construct_graph match_graph draw process_htl generate_loc_dict process_tag walk_through_files process_output append strip join prefix append join walk relpath escape compile I join list rename_in_file print _green eval any rename _case_sensitive_replace zip input walk pop items list sorted format isdir input print exit _green eval lower _case_sensitive_replace zip _yellow startswith enumerate split decode dirname abspath BASE_EXIT_TYPECLASS parse_ansi BASE_SCRIPT_TYPECLASS DBmanagers BASE_GUEST_TYPECLASS BASE_ACCOUNT_TYPECLASS start BASE_CHANNEL_TYPECLASS BASE_ROOM_TYPECLASS BASE_CHARACTER_TYPECLASS DefaultCmds BASE_OBJECT_TYPECLASS SystemCmds class_from_module f_back Pdb Debugger AccountManager property RegexField RegexField CharField RegexField through through BASE_SCRIPT_TYPECLASS property CharField AccountDBManager BooleanField get_model filter save all add save AccountDB get_model append is_installed log_trace strip msg timeformat format_exc next send deferLater old_duplicates tuple no_exits returnValue priority account get_all_cmd_keys_and_aliases puppet string_suggestions strip returnValue _ extend aliases lower create_match append match sorted try_num_prefixes build_matches get rsplit cmdsetclass strip msg import_module getattr log_err callable _ErrorCmdSet tuple permissions I locks list hasattr arg_regex len aliases append range UNICODE popitem set lower setattr compile _matchset join split COMMAND_DEFAULT_LOCKS COMMAND_DEFAULT_ARG_REGEX COMMAND_DEFAULT_HELP_CATEGORY COMMAND_DEFAULT_MSG_ALL_SESSIONS slice styled_table str add_row enumerate batch_stack replace strip batch_stackptr crop len split batch_stack execute_cmd msg batch_stackptr format_header batch_debug code_exec batch_stack msg format_code batch_stackptr format_header batch_stack min msg batch_stackptr max len batch_stack strip msg batch_stackptr split format_header len clear batch_cmdset_backup validate update msg remove msg object compile _editing_help msg _editing_help msg _run_code_snippet _py_clientraw msg _py_measure_time msg stdout time hasattr all stderr msg eval evennia_local_vars FakeStd compile repeats EvTable desc id time_until_next_repeat key add_row crop join address BASE_GUEST_TYPECLASS msg authenticate class_from_module GUEST_ENABLED join address msg BASE_ACCOUNT_TYPECLASS authenticate class_from_module create_account key get_channel log_err append add create_object through through ChannelManager lstrip isinstance dbref hasattr __name__ isinstance identify_object log_err DateTimeField property TextField CharField MsgManager ManyToManyField BASE_CHANNEL_TYPECLASS ManyToManyField ChannelDBManager get_model filter delete save _table_exists cursor get get getattr get remove setattr getattr move _building_menu add getargspec update dict keywords callable args setattr strip getattr format has close msg log_err EvEditor attr remove clothing_type remove reversed insert append worn order_clothes_list contents clothing_type clothing_type append int items list sorted values set gametime sorted values set gametime list sorted items time_to_tuple index set append values enumerate create_script real_seconds_until int sum tuple eval abs FieldEvMenu form_template_to_dict update int list pretext verifyfunc formcallback strip borderstyle list_to_string msg split submitcmd formhelptext posttext append keys formtemplate formdata update str reformat_column EvTable add_row len append get_puppet get_sessions msg msg delay str msg center int ljust rjust float round max len msg key dbref Room create_object choice msg randint key dbref range Room create_object msg key dbref Room create_object msg key dbref Room create_object Exit key msg create_object Exit key msg create_object items list _map_to_list len msg Exit range create_object msg callables_from_module format random_string_from_module get format get disconnect login msg CMD_LOGINSTART insert lower _update_store _multidesc_editkey msg _multidesc_editkey msg append all dict pop join len all dict proto_def dbref append extend list search_script_attribute list maskout_protodef remove dict append enumerate get get add get int min max join sorted product set sub split append enumerate list reversed groups sub finditer enumerate list format all group groups id reversed start sub append max finditer len get items list format process_recog id msg dict process_language sub process_sdesc parse_language key parse_sdescs_and_recogs __doc__ ExtendedRoom callback EvMenu split append dashcount split strip split dashcount reversed split append index_to_selection callback go_back parse_opts index_to_selection mark_category index treestr start_text optlist_to_menuoptions uncolored_name key msg create_script exists WildernessMapProvider get is_valid_coordinates move_obj CMD_NOMATCH msg_room at_object_receive location msg_char count log_info init_state log create_fantasy_word filter _move_to_room create_object get_all_characters int all append len strip format get desc format get _session evscaperoom_standalone cmdhandler EvscaperoomMenu location get add session_portal_sync location get OptionsMenu create_object append choice split sub max justify strip add_msg_borders format remove format get_event_handler edit_callback check_lockstring msg _callback remove _callback get_event_handler msg current_locals script call dict set_task get pop format call log_err get get items list isinstance __module__ add_event append class_from_module __name__ log_trace items sorted list format replace int join gametime_to_realtime reversed dict getattr log_err rsu append split create_script get_next_wait format append lower append lower replace split dumps strftime log_file pop dumps syslog randint randint msg_contents msg_contents get_damage apply_damage get_attack at_defeat get_defense remove all combat_turnhandler turn_end_check wielded_weapon worn_armor worn_armor wielded_weapon wielded_weapon weapon_type_name add_condition location capitalize delete msg item_uses is_in_combat msg spend_item_use item_kwargs spend_action msg_contents conditions update msg_contents msg_contents hp max_hp msg randint msg_contents add_condition msg msg_contents conditions msg randint msg_contents resolve_attack msg msg_contents hp is_in_combat max_hp randint spend_action update msg_contents insert is_in_combat apply_damage at_defeat get_defense randint spend_action range len msg_contents create_object distance_inc distance_dec contents distance_inc contents append combat_range msg CMD_NOMATCH through CharField HelpEntryManager TextField CharField BooleanField ManyToManyField account inherits_from pop get all index lower int strip hasattr get strip hasattr obj hasattr obj hasattr obj hasattr obj dbid check_holds len contents literal_eval update LOCK_FUNC_MODULES callables_from_module _ObjDummy LockHandler _ObjDummy LockHandler _cache_lockfuncs print check set_trace add LockHandler TestObj through through CharField CharField property ObjectDBManager ForeignKey CharField BASE_OBJECT_TYPECLASS property ObjectManager db_account olc_prototype hasattr _menutree _get_menu_prototype flatten_prototype olc_flat_prototype _get_menu_prototype _get_flat_menu_prototype get join format hasattr __name__ is_iter repr callable _get_menu_prototype get protfunc_parser join format _set_prototype_value dumps msg processor append type callable append prototype_to_str spawn append format append strip format get format append _get_flat_menu_prototype formatter strip _get_menu_prototype comparer get join list int strip group match keys get _wizard_options _get_flat_menu_prototype _validate_prototype append get _wizard_options append format Q strip search msg lstrip distinct startswith search_account dbref olc_search_object_matches prototype_from_object index msg prototype_to_str get olc_search_object_matches _set_menu_prototype prototype_from_object strip index msg _default_parse prototype_to_str get olc_search_object_matches format _wizard_options _format_list_actions _set_actioninfo append len get format _get_menu_prototype extend append format msg lower search_prototype _is_new_prototype append format _wizard_options get remove format _get_flat_menu_prototype _set_prototype_value _get_menu_prototype msg make_iter append _default_parse flatten_prototype prototype_to_str search_prototype flatten_prototype get format _wizard_options _get_menu_prototype _format_list_actions make_iter _set_actioninfo append search_prototype get pop format _set_menu_prototype _get_menu_prototype strip msg append _default_parse split format _set_property msg append format _wizard_options append format _wizard_options _get_menu_prototype str format _all_aliases _set_prototype_value index msg append get remove format _all_aliases _set_prototype_value strip msg append _default_parse format _wizard_options _format_list_actions _set_actioninfo append _get_menu_prototype get _get_menu_prototype index protfunc_parser type format get format _set_prototype_value strip _get_menu_prototype index lower split len _get_tup_by_attrname msg strip split get _add_attr _get_tup_by_attrname strip msg _default_parse split format _wizard_options _format_list_actions _set_actioninfo append _get_menu_prototype get _get_menu_prototype index format get pop format _set_prototype_value strip _get_menu_prototype index lower _get_tup_by_tagname split append len _get_tup_by_tagname msg get strip msg _get_tup_by_tagname _add_tag _default_parse format _wizard_options _format_list_actions _set_actioninfo append get _caller_locks pop join format _set_prototype_value index lower split get _default_parse _lock_add msg append format _wizard_options get _get_menu_prototype join lower format PERMISSION_HIERARCHY format _set_prototype_value index lower _caller_permissions append get strip msg _add_perm _default_parse format _wizard_options _format_list_actions _set_actioninfo append append format _wizard_options append format _wizard_options append format _wizard_options append format _wizard_options get _get_menu_prototype pop format _set_prototype_value index _caller_prototype_tags lower append format msg get strip msg _add_prototype_tag _default_parse format _wizard_options _format_list_actions _set_actioninfo append get pop join format _set_prototype_value index lower _caller_prototype_locks split get strip _prototype_lock_add msg _default_parse format _wizard_options _format_list_actions _set_actioninfo append get format batch_update_objects_with_prototype msg tuple list sorted format extend append _parse_diffpart get pop join _wizard_options _format_diff_text_and_options extend choice append prototype_diff_from_object get join format _wizard_options save_prototype _validate_prototype search_objects_with_prototype _get_menu_prototype append search_prototype count get format spawn copy get join _wizard_options _validate_prototype location _get_menu_prototype search_objects_with_prototype extend append count _set_menu_prototype search_prototype format msg get _default_parse delete_prototype prototype_to_str _format_list_actions _set_actioninfo _wizard_options append OLCMenu strip literal_eval strip literal_eval strip literal_eval strip literal_eval join format isinstance value_to_obj_or_any literal_eval get join account pop search_object append access _obj_search get items list format make_iter BASE_OBJECT_TYPECLASS append get validate_lockstring update clear batch_add homogenize_prototype create_script add lower filter get lower filter delete order_by get_by_tag set make_iter lower len get str sorted is_iter format reformat_column EvTable check_lockstring append search_prototype range len get pop join format id lower make_iter append class_from_module parse_inlinefunc literal_eval append items list format get join format homogenize_prototype append get format log_err search_prototype validator value callable dbid_to_obj type is_iter type is_iter get update pop _inherit_tags lower _inherit_attrs make_iter homogenize_prototype validate_prototype get str join format all sorted db_destination db_typeclass_path db_home db_location dbref make_iter key search_prototype _recursive_diff items list all _get_all_nested_diff_instructions homogenize_prototype prototype_diff prototype_from_object get clear remove init_spawn_value batch_add list get_by_tag isinstance homogenize_prototype items add flatten_diff BASE_OBJECT_TYPECLASS save search_prototype prototype_diff_from_object ObjectDB exec append save pop items list format init_spawn_value get _get_prototype dict lower make_iter BASE_OBJECT_TYPECLASS DEFAULT_HOME append validate_prototype through through BASE_SCRIPT_TYPECLASS property ForeignKey IntegerField ScriptDBManager CharField BooleanField validate ScriptManager get_model filter delete display ask_node node_start node_game_index_fields display get GAME_INDEX_LISTING display ask_choice ask_input node_start MSSP_META_MODULE mod_import ask_continue display __file__ node_start GAME_DIR join mod_import hasattr ask_continue display PrettyPrinter node_start game_index_listing pformat _save_changes CHANNEL_CONNECTINFO any hasattr print DEBUG IN_GAME_ERRORS basename dirname format print _strip_empty_lines _prepare_dict max append format extend stop TCP4ClientEndpoint print exit AMPLauncherProtocol connectProtocol addCallbacks send_instruction print wait_for_status call_command send_instruction _get_twistd_cmdline collectstatic send_instruction _get_twistd_cmdline collectstatic send_instruction send_instruction collectstatic format _get_twistd_cmdline print send_instruction collectstatic stop_server_only collectstatic send_instruction send_instruction send_instruction callLater decode __version__ join format print short exit join chdir getcwd print exit isfile range pardir shuffle join list replace join format print copy eval input exists join print exit rename abspath copytree exists create_settings_file print call_command get cursor _init get_table_list join path copy exists remove exists get_pid remove int format callback SetConsoleCtrlHandler print errback _is_windows GenerateConsoleCtrlEvent BASE_EXIT_TYPECLASS check_errors print COMMAND_PARSER BASE_SCRIPT_TYPECLASS check_warnings BASE_ACCOUNT_TYPECLASS LOCK_FUNC_MODULES BASE_ROOM_TYPECLASS BASE_CHARACTER_TYPECLASS BASE_OBJECT_TYPECLASS CONNECTION_SCREEN_MODULE _imp SEARCH_AT_RESULT AMP_PORT AMP_INTERFACE abspath check_database setup SERVER_LOG_FILE exit dirname format insert AMP_HOST PORTAL_LOG_FILE import_module HTTP_LOG_FILE set_gamedir pardir join print __file__ _is_windows call join extend exists node_start ConnectionWizard str list items EvTable print dict import_module add_row range len wait start_evennia stop_server_only reload_evennia basename show_version_info init_game_directory input _file_names_compact tail_log_files format eval stop_evennia query_status int kill reboot_evennia print _is_windows query_info len rstrip dummyrunner start_evennia ArgumentParser initmissing run_menu stop_server_only create_game_directory run reload_evennia show_version_info execute_from_command_line init_game_directory start_only_server exit listsetting start_portal_interactive run_dummyrunner parse_known_args run_connect_wizard altsettings operation error_check_python_modules _file_names_compact create_settings_file altgamedir start_server_interactive tail_log_files format show_version profiler list_settings init stop_evennia query_status join kill tail_log call_command reboot_evennia print add_argument _is_windows sub query_info initsettings check_main_evennia_dependencies makedirs insert exists remove rename exists get format start_new_thread print Queue Popen set_restart_mode iportal start_services slogfile twistdbinary doexit parse_args pportal insert plogfile noportal pserver get_pid cycle_logfile noserver gamedir extend hlogfile get at_account_creation log_info swap_typeclass strip add BASE_ACCOUNT_TYPECLASS get_god_account BASE_ROOM_TYPECLASS BASE_CHARACTER_TYPECLASS basetype_setup save append _ create_object create_channel DEFAULT_CHANNELS log_info CHANNEL_CONNECTINFO connect get_god_account CHANNEL_MUDINFO get log_info __import__ AT_INITIAL_SETUP_HOOK_MODULE log_info time portal_reset_server log_info conf setup_func enumerate conf pop account puppet cmdhandler nickreplace update_session_counters pop update_session_counters execute_cmd data_out get format log_err msg update items list format validate_bool validate_size msg dict lower session_portal_partial_sync to_str validate_encoding protocol_flags client_options dict msg create_normal_account get msg msg get int join remove msg add max repeat msg get remove puppet add kwargs monitor puppet all msg _GA msg account list items _saved_webclient_options copy msg add puppet all msg monitor unmonitor PickledObjectField property CharField ServerConfigManager update time validate _FLUSH_CACHE disconnect close SERVER_RUNTIME conf _ property property rsplit variable_from_module decode to_bytes loads db_value join to_str sub zip append split sub to_str hasattr sub replace toString Key generate Portal PassAvatarIdTerminalRealm ConchFactory getKeyPair registerChecker copy AccountDBPasswordChecker toString print write call Key generate verify_SSL_key_and_cert join PKey TYPE_RSA generate_key verify_or_create_SSL_key_and_cert int connectTCP print tuple ACTIONS zip DummyFactory sum range run counter extend gid gid counter extend counter append counter append exits print queries exec len print startswith split CharField PickledFormField CharField DateTimeField property TextField CharField PickledObjectField sub translate match at_first_save delete property DateTimeField property TextField TypedObjectManager CharField ManyToManyField CharField TextField get_model filter db_value update get_model all remove exclude add save Tag UNICODE filter sub save get_model IGNORECASE db_lock_storage compile db_cmdset_storage all db_typeclass_path filter _case_sensitive_replace save get_model db_lock_storage execute _table_exists format _drop_table cursor COLOR_ANSI_EXTRA_MAP join COLOR_XTERM256_EXTRA_GFG COLOR_XTERM256_EXTRA_GBG COLOR_ANSI_XTERM256_BRIGHT_BG_EXTRA_MAP COLOR_NO_DEFAULT dict COLOR_XTERM256_EXTRA_BG DOTALL COLOR_XTERM256_EXTRA_FG compile pypath_to_realpath BASE_BATCHPROCESS_PATHS tb_next OPTION_CLASS_MODULES dbid_to_obj typeclass isinstance dict save send class_from_module TYPECLASS_PATHS dbid_to_obj typeclass isinstance dict save send class_from_module TYPECLASS_PATHS _HelpEntry send save add make_iter _Msg save add typeclass isinstance dict save send class_from_module TYPECLASS_PATHS dbid_to_obj typeclass isinstance validate_password now set_password dict filter normalize_email save class_from_module TYPECLASS_PATHS execute cursor fetchone update get defaultdict dict ATTRIBUTE_STORED_MODEL_RENAME append property _init_globals _init_globals get _init_globals sessid get _init_globals update _SaverOrderedDict _SaverDict extend _SaverDeque _SaverSet _SaverList type get items remove list add EvEditor setattr len max is_iter sub isinstance EvForm map EvTable add msg _Prompt _menutree get key format msg rstrip get rstrip format msg format EvMore ANSITextWrapper ANSITextWrapper add_column str reformat_column reformat add_row add_row range EvTable TIME_GAME_EPOCH time server_epoch runtime fromtimestamp replace total_seconds datetime runtime conf len len strip len pop update pop finditer format groupdict log_info join print group copy ParseStack lstrip append callable findall len utcfromtimestamp fromtimestamp int seconds abs days msg str msg splitlines format_exc log_msg str splitlines log_msg str splitlines log_msg str splitlines log_msg str splitlines log_msg str splitlines log_msg str splitlines log_msg CHANNEL_LOG_NUM_TAIL_LINES join CHANNEL_LOG_ROTATE_SIZE close fromFullPath LOG_DIR addErrback _open_log_file _open_log_file _ObjectWrapper deepcopy compress dumps decode encode decompress b64decode dict default_error_messages callback callback hasattr __name__ isinstance __module__ callback S replace dict I DOTALL compile M isinstance lstrip len split pop extend _process_line split append MULTILINE enumerate int join divmod len append justify max range split int now strftime strip __version__ osjoin split dbref decode chr ord isinstance iter append str isinstance isinstance rsplit replace callable isinstance namedServices pop addCallback addErrback deferToThread callable strip words IRC_ENABLED log_err check_main_evennia_dependencies max rsplit sep rstrip abspath ModuleType isinstance getmembers mod_import getmembers mod_import append make_iter get mod_import variable_from_module make_iter import_module rsplit import_module getattr format log_dep list set defaultdict min split append enumerate append range len GAME_DIR join exists sum _recurse getsizeof join min stack max len get strip msg _ enumerate join chdir getcwd isfile range pardir strip_ansi UTC replace strptime localize strftime split lower match split datetime int signed_integer signed_integer upper list _partial keys _val_email strip split SharedMemoryManager flush_instance_cache class_hierarchy cache_instance time read mem2cachesize cache_size flush_cache log_warn float __subclasses__ get_recurse CharField CharField CharField ForeignKey CharField ForeignKey get_evennia_version strip get int WEBSOCKET_CLIENT_URL WEBSOCKET_CLIENT_PORT WEBSOCKET_CLIENT_ENABLED WEBCLIENT_ENABLED user int get is_authenticated next EmailField CharField BASE_EXIT_TYPECLASS BASE_SCRIPT_TYPECLASS BASE_ACCOUNT_TYPECLASS BASE_ROOM_TYPECLASS BASE_CHARACTER_TYPECLASS BASE_OBJECT_TYPECLASS BASE_CHANNEL_TYPECLASS BASE_EXIT_TYPECLASS account_count BASE_ROOM_TYPECLASS BASE_CHARACTER_TYPECLASS class_from_module count class_from_module BASE_OBJECT_TYPECLASS class_from_module BASE_OBJECT_TYPECLASS class_from_module BASE_OBJECT_TYPECLASS class_from_module BASE_OBJECT_TYPECLASS BASE_ACCOUNT_TYPECLASS class_from_module AccountForm reverse_lazy CharacterForm class_from_module BASE_CHARACTER_TYPECLASS reverse_lazy CharacterUpdateForm BASE_CHANNEL_TYPECLASS class_from_module get CopyFile join get_suffixes load_dynamic get_root_hkey CreateKey OpenKey print SetValueEx REG_SZ UnregisterClasses __import__ getattr func RegisterClasses join get_root_hkey CreateKey SetValueEx Close REG_SZ get_python_lib DeleteKey QueryValue get_special_folder_path get_root_hkey IsWow64Process join remove file_created print __file__ rename dirname isfile DeleteKey exists CopyTo basename LoadSystemModule CreateKey get_shortcuts_folder prefix RegisterCOMObjects append RegisterPythonwin create_shortcut glob unlink mkdir join get_root_hkey isdir winver print file_created directory_created isfile fixup_dbi SetPyKeyVal split join remove basename LoadSystemModule isdir print glob get_shortcuts_folder rmtree RegisterCOMObjects isfile RegisterPythonwin read chdir getcwd print readlines close executable write GetShortPathName popen3 split join abspath run_test isfile digitsrep powersum add_edge range DiGraph powersum add_edge DiGraph range add_node add_edge DiGraph f range add_node tuple islice iter int list _pool order nodes chunks map zip Pool len bfs_beam_edges pow condition ceil range log len get gnp_random_graph progressive_widening_search eigenvector_centrality sum values len items list defaultdict complete len all_pairs_shortest_path_length fcluster zip append zeros range squareform Graph remove_node disjoint_union append isomorphic pop add_edge MultiDiGraph strip BZ2File startswith split decode add_edge add_node Graph insert readlines match startswith split float compile open add_edge int Graph subgraph readlines open float split add_edge MultiDiGraph parseaddr mbox getaddresses get_all int add_edge Graph append split decode add_edge add_node DiGraph endswith print strip readlines startswith split compile open Graph add_nodes_from dict add_edge decode str readlines set add startswith open add_nodes_from add_edge DiGraph upper sorted relabel_nodes to_undirected to_file Generator load_graph add_argument ArgumentParser replace graph_to_world get_gml_graph load close open seed manual_seed_all manual_seed gradient_accumulation_steps model get_linear_schedule_with_warmup tuple clip_grad_norm_ zero_grad DataLoader DataParallel DistributedDataParallel max_grad_norm output_dir save max initialize list set_seed logging_steps master_params update SummaryWriter format close mean save_pretrained num_train_epochs info fp16 trange per_gpu_train_batch_size max_steps enumerate int items n_gpu join evaluate backward AdamW add_scalar makedirs tqdm parameters step train_batch_size len tuple RawResult DataLoader DataParallel end_n_top output_dir max_answer_length max eval_batch_size per_gpu_eval_batch_size default_timer write_predictions do_lower_case n_best_size append format write_predictions_extended eval evaluate_on_squad info verbose_logging RawResultExtended EVAL_OPTS enumerate start_n_top int join n_gpu predict_file makedirs tqdm version_2_with_negative null_score_diff_threshold unique_id load_and_cache_examples len pop join str format load arange max_seq_length size barrier read_squad_examples TensorDataset dirname convert_examples_to_features info save tensor enable_attach from_pretrained warning device do_train output_dir save eval_all_checkpoints setLevel basicConfig list set_seed set_device device_count to WARN update init_process_group lower register_half_function save_pretrained info fp16 wait_for_attach train n_gpu evaluate model_name_or_path barrier dict bool load_and_cache_examples local_rank join is_whitespace whitespace_tokenize warning SquadExample append len _DocSpan _improve_answer_span is_impossible orig_answer_text length convert_tokens_to_ids append range doc_tokens InputFeatures question_text start info tokenize enumerate join _check_is_max_context namedtuple tqdm len join tokenize range length start min enumerate strip end_logit _get_best_indexes sorted defaultdict get_final_text _NbestPrediction end_logits OrderedDict append start_logit replace _compute_softmax insert start_logits info enumerate join namedtuple text _PrelimPrediction split end_log_prob cls_logits strip find_all_best_thresh_v2 make_qid_to_has_ans sorted defaultdict get_final_text _NbestPrediction do_lower_case OrderedDict append range _compute_softmax info convert_tokens_to_string enumerate join namedtuple text min _PrelimPrediction get_raw_scores start_log_prob split join _strip_spaces list items BasicTokenizer len info tokenize find sorted append range enumerate len append exp strip end_logit _get_best_indexes sorted get_final_text _NbestPrediction end_logits OrderedDict append start_logit replace _compute_softmax start_logits enumerate join namedtuple text _PrelimPrediction split _DocSpan _check_is_max_context namedtuple doc_tokens orig_answer_text length question_text len convert_tokens_to_ids _improve_answer_span InputFeatures start is_impossible append tokenize range enumerate is_whitespace SquadExample append len exit print_help bool Counter get_tokens sum values len print max list items float len xlabel ylabel ylim title savefig clf fill_between xlim step sorted plot_pr_curve append float enumerate sum make_precision_recall_eval merge_eval makedirs join ones_like xlabel ylabel title hist savefig clf float len sorted sum enumerate sorted sum enumerate find_best_thresh find_best_thresh_v2 make_eval_dict na_prob_file find_all_best_thresh na_prob_thresh run_precision_recall_analysis histogram_na_prob dumps apply_no_ans_threshold get_raw_scores out_image_dir out_file make_qid_to_has_ans merge_eval load replace unquote print close open len list compile_pages extend set get_pages get_custom dump print get_plot close append open list compile_pages extend set get_custom get_page load print min close len range open print get_plot append find_all find get BeautifulSoup text get get_stories text get_subcategories extend BeautifulSoup append get_plot replace unquote WikipediaPage format index len items list copy range len items list replace strip choice findall keys append count list replace strip choice findall values count data gen_room_obj generate_room_intro uniform write_dot items list min copy choice range len add_edge list items word_tokenize write_gml DiGraph print len tag set add lower match_graph add_node check_output format write_dot endswith walk pos_tag word_tokenize items list format join remove print copy add set title intersection keys split join detokenize word_tokenize Graph data generate_loc_dict | # WorldGeneration Code accompanying the paper ["Bringing Stories Alive: Generating Interactive Fiction Worlds"](http://arxiv.org/abs/2001.10161). Neural PCG model (including AskBERT) is found in ```neural-based```, Rule-based PCG model is found in ```rule-based```, Evennia game generation framework is found in ```evennia-engine```. Each folder has its own README, follow the instructions in ```rule-based``` and ```neural-based``` to generate a ```*.dot``` file that can then be passed in the Evennia framework to create a playable game. # Dataset The data used for finetuning fairytale and mystery models can be collected through ```/neural-based/scrape-wikipedia``` BibTex ``` @article{ammanabrolu20world, title={Bringing Stories Alive: Generating Interactive Fiction Worlds}, | 3,397 |
rajdeep345/ABSA-Reproducibility | ['sentiment analysis', 'aspect based sentiment analysis'] | ['Reproducibility, Replicability and Beyond: Assessing Production Readiness of Aspect Based Sentiment Analysis in the Wild'] | results/process_results.py code/train_k_fold_cross_val.py code/models/aen.py code/layers/point_wise_feed_forward.py code/models/ram.py code/models/td_lstm.py code/models/tnet_lf.py code/layers/__init__.py code/models/atae_lstm.py code/data_utils.py code/models/bert_spc.py code/models/mgan.py code/infer_example.py code/train.py code/grid_search.py code/models/lcf_bert.py code/models/cabasc.py code/models/__init__.py code/layers/squeeze_embedding.py code/models/aoa.py code/models/lstm.py code/layers/attention.py code/infer_example_bert_models.py code/models/ian.py code/models/memnet.py code/layers/dynamic_rnn.py _load_word_vec build_embedding_matrix Tokenizer4Bert pad_and_truncate build_tokenizer ABSADataset Tokenizer Option Inferer pad_and_truncate prepare_data get_parameters main Instructor main Instructor NoQueryAttention Attention DynamicLSTM PositionwiseFeedForward SqueezeEmbedding AEN_BERT CrossEntropyLoss_LSR AEN_GloVe AOA ATAE_LSTM BERT_SPC Cabasc IAN LCF_BERT SelfAttention LSTM MemNet MGAN AlignmentMatrix LocationEncoding RAM TD_LSTM Absolute_Position_Embedding TNet_LF parse_fname parse_hardset parse_cdomain load dump print strip readlines close len fit_on_text range exists Tokenizer open join split asarray open get items list dump load print _load_word_vec zeros exists open asarray astype asarray text_to_sequence max_seq_len strip pad_and_truncate sum parse_args add_argument ArgumentParser seed format addHandler add_argument Instructor train_dataset strftime localtime model_name ArgumentParser manual_seed run parse_args dataset FileHandler float split join read_csv split genfromtxt join zip append accuracy_score argmax array split | # ABSA-Reproducibility Codes and Datasets for our ECIR 2021 Paper: "Reproducibility, Replicability and Beyond: Assessing Production Readiness of Aspect Based Sentiment Analysis in the Wild" ## Setup instructions * Create a conda environment using the requirements.txt file. * Alternately, one can use the ABSA.yml extracted from our conda environment to exactly replicate the environment. * Download and unzip the [GloVe embeddings](http://nlp.stanford.edu/data/glove.840B.300d.zip) into the current folder. ## Running experiments ```python python grid_search.py ``` | 3,398 |
rajeevyasarla/UMRL--using-Cycle-Spinning | ['single image deraining'] | ['Uncertainty Guided Multi-Scale Residual Learning-using a Cycle Spinning CNN for Single Image De-Raining'] | datasets/pix2pix_val.py umrl_cycspn_train.py datasets/pix2pix.py myutils/utils.py umrl_test.py transforms/pix2pix_val.py datasets/pix2pix2.py myutils/vgg16.py misc.py transforms/pix2pix_val3.py datasets/pix2pix_class.py models/derain_mulcmp.py datasets/util.py datasets/classification.py myutils/StyleLoader.py umrl_train.py transforms/pix2pix3.py transforms/pix2pix.py umrl_cycspn_test.py AverageMeter ImagePool create_exp_dir adjust_learning_rate weights_init getLoader norm_ip norm_range bceloss gradient norm_ip norm_range bceloss gradient is_image_file default_loader make_dataset classification is_image_file pix2pix default_loader make_dataset is_image_file pix2pix default_loader make_dataset is_image_file pix2pix default_loader make_dataset is_image_file pix2pix_val default_loader make_dataset u array2ntpl ntpl2array transpose_ntpl_list solve_status_str spnoise tiledict surf Timer ContextTimer convdicts imageblocks imview plot ExampleImages idle_cpu_count tikhonov_filter complex_randn grid_search rgb2gray netgetdata conv_block Multi_scale2 BottleneckBlock1 UMRL TransitionBlock BottleneckBlock scale_residue_est D1 blockUNet1 D deconv_block TransitionBlock1 BottleneckBlock2 TransitionBlock3 vgg19ca blockUNet scale_residue_conf StyleLoader add_imagenet_mean_batch subtract_imagenet_mean_batch init_vgg16 preprocess_batch gram_matrix tensor_load_rgbimage tensor_save_rgbimage imagenet_clamp_batch tensor_save_bgrimage Vgg16 Pad ToPILImage CenterCrop Lambda ToTensor Compose Scale RandomCrop Normalize RandomHorizontalFlip Pad ToPILImage CenterCrop Lambda ToTensor Compose Scale RandomCrop Normalize RandomHorizontalFlip Pad ToPILImage CenterCrop Lambda ToTensor Compose Scale RandomCrop Normalize RandomHorizontalFlip Pad ToPILImage CenterCrop Lambda ToTensor Compose Scale RandomCrop Normalize RandomHorizontalFlip print makedirs normal_ __name__ fill_ commonDataset DataLoader param_groups clamp_ div_ norm_ip max min abs log is_image_file join sorted append walk warn warn warn namedtuple _fields __name__ namedtuple tuple len int T ones reshape min shape sqrt floor tile ceil float max range amax itemsize as_strided rollaxis reshape ascontiguousarray dstack shape array atleast_nd array ndim shape uniform copy reshape ndim pad ifftn real fftn conj int cpu_count floor join list product isinstance slct reshape tuple argmin cpu_count map close shape array unravel_index argmax Pool len load join list dirname keys urlopen range read ValueError Dropout2d Sequential add_module Conv2d ReLU BatchNorm2d LeakyReLU ConvTranspose2d Dropout2d Sequential add_module Conv2d ReLU BatchNorm2d LeakyReLU ConvTranspose2d int ANTIALIAS transpose convert resize float fromarray numpy astype save chunk tensor_save_rgbimage cat bmm size transpose view data size type tensortype data size type tensortype clamp_ transpose chunk cat join Vgg16 load_lua system parameters save zip state_dict | # UMRL--using-Cycle-Spinning Uncertainty Guided Multi-Scale Residual Learning-using a Cycle Spinning CNN for Single Image De-Raining [Rajeev Yasarla](https://sites.google.com/view/rajeevyasarla/home), [Vishal M. Patel](https://engineering.jhu.edu/ece/faculty/vishal-m-patel/) [Paper Link](https://arxiv.org/abs/1906.11129) (CVPR'19) @InProceedings{Yasarla_2019_CVPR, author = {Yasarla, Rajeev and Patel, Vishal M.}, title = {Uncertainty Guided Multi-Scale Residual Learning-Using a Cycle Spinning CNN for Single Image De-Raining}, booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, month = {June}, year = {2019} | 3,399 |
Subsets and Splits
No saved queries yet
Save your SQL queries to embed, download, and access them later. Queries will appear here once saved.