Delete options

options/options.py

@@ -1,44 +0,0 @@
-import os
-import os.path as osp
-import logging
-import yaml
-from collections import OrderedDict
-try:
-    from yaml import CLoader as Loader, CDumper as Dumper
-except ImportError:
-    from yaml import Loader, Dumper
-
-
-def OrderedYaml():
-    '''yaml orderedDict support'''
-    _mapping_tag = yaml.resolver.BaseResolver.DEFAULT_MAPPING_TAG
-
-    def dict_representer(dumper, data):
-        return dumper.represent_dict(data.items())
-
-    def dict_constructor(loader, node):
-        return OrderedDict(loader.construct_pairs(node))
-
-    Dumper.add_representer(OrderedDict, dict_representer)
-    Loader.add_constructor(_mapping_tag, dict_constructor)
-    return Loader, Dumper
-
-#-----------------------
-Loader, Dumper = OrderedYaml()
-
-def parse(opt_path):
-    with open(opt_path, mode='r') as f:
-        opt = yaml.load(f, Loader=Loader)
-    return opt
-
-
-
-if __name__ == '__main__':
-    
-    path_yaml = './train/NBDN.yml'
-    with open(path_yaml, mode='r') as f:
-        opt = yaml.load(f, Loader=Loader)
-    opt = parse(path_yaml)
-    # print(opt)
-    print(type(opt['network']['width']))
-    # print(opt['gpu'])

options/predict/LOLBlur.yml

@@ -1,27 +0,0 @@
-#### network structures
-network:
-  name: Network
-  img_channels: 3
-  width: 32
-  middle_blk_num_enc: 2
-  middle_blk_num_dec: 2
-  enc_blk_nums: [1, 2, 3]
-  dec_blk_nums: [3, 1, 1]
-  enc_blk_nums_map: None
-  middle_blk_num_map: None
-  residual_layers: None
-  dilations: [1, 4, 9]
-  spatial: False
-  extra_depth_wise: True
-
-#### save model
-save:
-  best: ./models/bests/Network_noFAC_LOLBlur.pt
-  path: ./models/Network_noFAC_LOLBlur.pt
-
-LOLBlur:
-  inputs_path: ./inputs/synthetic
-  results_path: ./results/synthetic
-RealBlur:
-  inputs_path: ./inputs/real
-  results_path: ./results/real

options/train/All_LOL.yml

@@ -1,82 +0,0 @@
-#### general settings
-resume_training:
-  resume_training: True
-  resume: must
-  id: 2oceqxkt
-
-#### training devices
-device:
-  cuda: True
-  gpus: 0
-
-#### datasets
-datasets:
-  name: All_LOL
-  train:
-    train_path: /home/leadergpu/Datasets
-
-    n_workers: 4  # per GPU
-    batch_size_train: 12
-    cropsize: 256   # size you want to crop out as input sample.
-    flips: True
-    verbose: True
-    crop_type: Random
-  val:
-    test_path: /home/leadergpu/Datasets
-    batch_size_test: 1
-
-#### network structures
-network:
-  name: Network
-  img_channels: 3
-  width: 32
-  middle_blk_num: 3
-  enc_blk_nums: [1, 2, 3]
-  dec_blk_nums: [3, 1, 1]
-  enc_blk_nums_map: None
-  middle_blk_num_map: None
-  residual_layers: 2
-  dilations: [1, 4, 9]
-  spatial: None
-  extra_depth_wise: True
-
-
-#### training settings: learning rate scheme, loss
-train:
-  lr_initial: !!float 5e-4
-  lr_scheme: CosineAnnealing
-  betas: [0.9, 0.9]
-  epochs: 500
-  lr_gamma: 0.5
-  weight_decay: !!float 1e-3
-  eta_min: !!float 1e-6
-
-  pixel_criterion: l1
-  pixel_weight: 1.0
-
-  perceptual: True
-  perceptual_criterion: l1
-  perceptual_weight: 0.01
-  perceptual_reduction: mean
-
-  edge: True 
-  edge_criterion: l2
-  edge_weight: 50.0
-  edge_reduction: mean
-
-  frequency: True
-  frequency_criterion: l2
-  frequency_weight: 0.01
-  frequency_reduction: mean
-
-#### save model
-save:
-  path: ./models/Network_all_LOL.pt
-  best: ./models/bests/
-#### wandb:
-wandb:
-  init: True
-  project: LOLBlur
-  entity: cidautai
-  name: Network_all_LOL
-  save_code: True

options/train/LOL.yml

@@ -1,79 +0,0 @@
-#### general settings
-resume_training:
-  resume_training: True
-  resume: must
-  id: waye95l7
-
-
-#### datasets
-datasets:
-  name: LOL
-  train:
-    train_path: /mnt/valab-datasets/LOL/train
-
-    n_workers: 4  # per GPU
-    batch_size_train: 4
-    cropsize: 256   # size you want to crop out as input sample.
-    flips: True
-    verbose: True
-    crop_type: Random
-  val:
-    test_path: /mnt/valab-datasets/LOL/test
-    cropsize: 256
-    batch_size_test: 1
-
-#### network structures
-network:
-  name: Network_v3
-  img_channels: 3
-  width: 32
-  middle_blk_num: 3
-  enc_blk_nums: [1, 2, 3]
-  dec_blk_nums: [3, 1, 1]
-  enc_blk_nums_map: None
-  middle_blk_num_map: None
-  residual_layers: 1
-  dilations: [1, 4]
-  spatial: None
-  extra_depth_wise: False
-
-
-#### training settings: learning rate scheme, loss
-train:
-  lr_initial: !!float 5e-4
-  lr_scheme: CosineAnnealing
-  betas: [0.9, 0.9]
-  epochs: 500
-  lr_gamma: 0.5
-  weight_decay: !!float 1e-3
-  eta_min: !!float 1e-6
-
-  pixel_criterion: l1
-  pixel_weight: 1.0
-
-  perceptual: True
-  perceptual_criterion: l1
-  perceptual_weight: 0.01
-  perceptual_reduction: mean
-
-  edge: True 
-  edge_criterion: l2
-  edge_weight: 50.0
-  edge_reduction: mean
-
-  frequency: True
-  frequency_criterion: l2
-  frequency_weight: 0.01
-  frequency_reduction: mean
-
-#### save model
-save:
-  path: ./models/Network_v3_interpolate.pt
-  best: ./models/bests/
-#### wandb:
-wandb:
-  init: True
-  project: LOLBlur
-  entity: cidautai
-  name: Network_v3_interpolate_extraDW_LOLBlur
-  save_code: True

options/train/LOLBlur.yml

@@ -1,86 +0,0 @@
-#### general settings
-resume_training:
-  resume_training: True
-  resume: must
-  id: qa5ramgk
-
-#### training devices
-device:
-  cuda: True
-  gpus: 0
-
-#### datasets
-datasets:
-  name: LOLBlur
-  train:
-    train_path: /home/leadergpu/Datasets/LOLBlur_temp/train
-
-    n_workers: 4  # per GPU
-    batch_size_train: 12
-    cropsize: 256   # size you want to crop out as input sample.
-    flips: True
-    verbose: True
-    crop_type: Random
-  val:
-    test_path: /home/leadergpu/Datasets/LOLBlur_temp/test
-    batch_size_test: 1
-
-#### network structures
-network:
-  name: Network
-  img_channels: 3
-  width: 32
-  middle_blk_num_enc: 2
-  middle_blk_num_dec: 2
-  enc_blk_nums: [1, 2, 3]
-  dec_blk_nums: [3, 1, 1]
-  enc_blk_nums_map: None
-  middle_blk_num_map: None
-  residual_layers: None
-  dilations: [1, 4, 9]
-  spatial: None
-  extra_depth_wise: True
-
-
-#### training settings: learning rate scheme, loss
-train:
-  lr_initial: !!float 5e-4
-  lr_scheme: CosineAnnealing
-  betas: [0.9, 0.9]
-  epochs: 500
-  lr_gamma: 0.5
-  weight_decay: !!float 1e-3
-  eta_min: !!float 1e-6
-
-  pixel_criterion: l1
-  pixel_weight: 1.0
-
-  perceptual: True
-  perceptual_criterion: l1
-  perceptual_weight: 0.01
-  perceptual_reduction: mean
-
-  edge: True 
-  edge_criterion: l2
-  edge_weight: 50.0
-  edge_reduction: mean
-
-  frequency: True
-  frequency_criterion: l2
-  frequency_weight: 0.01
-  frequency_reduction: sum
-
-#### save model
-save:
-  path: ./models/Network_noFAC_LOLBlur.pt
-  best: ./models/bests/
-  new: ./models/Network_noFAC_LOLBlur.pt 
-#### wandb:
-wandb:
-  init: True
-  project: LOLBlur
-  entity: cidautai
-  name: Network_v3_noFAC_LOLBlur
-  save_code: True
-
-