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detectron2.config.yaml +495 -0
model_final.pth +3 -0
outputs/coco_instances_results.json +1 -0
outputs/events.out.tfevents.1695454760.d2eb307f4199.23.0 +3 -0
outputs/instances_predictions.pth +3 -0
outputs/last_checkpoint +1 -0
outputs/metrics.json +50 -0
outputs/model_final.pth +3 -0
semantic-segmentation-of-plants-with-detectron-2.log +635 -0

detectron2.config.yaml ADDED Viewed

	@@ -0,0 +1,495 @@

+!!python/object/new:detectron2.config.config.CfgNode
+dictitems:
+  CUDNN_BENCHMARK: false
+  DATALOADER: !!python/object/new:detectron2.config.config.CfgNode
+    dictitems:
+      ASPECT_RATIO_GROUPING: true
+      FILTER_EMPTY_ANNOTATIONS: true
+      NUM_WORKERS: 2
+      REPEAT_THRESHOLD: 0.0
+      SAMPLER_TRAIN: TrainingSampler
+    state:
+      __deprecated_keys__: !!set {}
+      __immutable__: false
+      __new_allowed__: false
+      __renamed_keys__: {}
+  DATASETS: !!python/object/new:detectron2.config.config.CfgNode
+    dictitems:
+      PRECOMPUTED_PROPOSAL_TOPK_TEST: 1000
+      PRECOMPUTED_PROPOSAL_TOPK_TRAIN: 2000
+      PROPOSAL_FILES_TEST: !!python/tuple []
+      PROPOSAL_FILES_TRAIN: !!python/tuple []
+      TEST: !!python/tuple []
+      TRAIN: !!python/tuple
+      - my_dataset_train
+    state:
+      __deprecated_keys__: !!set {}
+      __immutable__: false
+      __new_allowed__: false
+      __renamed_keys__: {}
+  GLOBAL: !!python/object/new:detectron2.config.config.CfgNode
+    dictitems:
+      HACK: 1.0
+    state:
+      __deprecated_keys__: !!set {}
+      __immutable__: false
+      __new_allowed__: false
+      __renamed_keys__: {}
+  INPUT: !!python/object/new:detectron2.config.config.CfgNode
+    dictitems:
+      CROP: !!python/object/new:detectron2.config.config.CfgNode
+        dictitems:
+          ENABLED: false
+          SIZE:
+          - 0.9
+          - 0.9
+          TYPE: relative_range
+        state:
+          __deprecated_keys__: !!set {}
+          __immutable__: false
+          __new_allowed__: false
+          __renamed_keys__: {}
+      FORMAT: BGR
+      MASK_FORMAT: polygon
+      MAX_SIZE_TEST: 1333
+      MAX_SIZE_TRAIN: 1333
+      MIN_SIZE_TEST: 800
+      MIN_SIZE_TRAIN: !!python/tuple
+      - 640
+      - 672
+      - 704
+      - 736
+      - 768
+      - 800
+      MIN_SIZE_TRAIN_SAMPLING: choice
+      RANDOM_FLIP: horizontal
+    state:
+      __deprecated_keys__: !!set {}
+      __immutable__: false
+      __new_allowed__: false
+      __renamed_keys__: {}
+  MODEL: !!python/object/new:detectron2.config.config.CfgNode
+    dictitems:
+      ANCHOR_GENERATOR: !!python/object/new:detectron2.config.config.CfgNode
+        dictitems:
+          ANGLES:
+          - - -90
+            - 0
+            - 90
+          ASPECT_RATIOS:
+          - - 0.5
+            - 1.0
+            - 2.0
+          NAME: DefaultAnchorGenerator
+          OFFSET: 0.0
+          SIZES:
+          - - 32
+          - - 64
+          - - 128
+          - - 256
+          - - 512
+        state:
+          __deprecated_keys__: !!set {}
+          __immutable__: false
+          __new_allowed__: false
+          __renamed_keys__: {}
+      BACKBONE: !!python/object/new:detectron2.config.config.CfgNode
+        dictitems:
+          FREEZE_AT: 2
+          NAME: build_resnet_fpn_backbone
+        state:
+          __deprecated_keys__: !!set {}
+          __immutable__: false
+          __new_allowed__: false
+          __renamed_keys__: {}
+      DEVICE: cuda
+      FPN: !!python/object/new:detectron2.config.config.CfgNode
+        dictitems:
+          FUSE_TYPE: sum
+          IN_FEATURES:
+          - res2
+          - res3
+          - res4
+          - res5
+          NORM: ''
+          OUT_CHANNELS: 256
+        state:
+          __deprecated_keys__: !!set {}
+          __immutable__: false
+          __new_allowed__: false
+          __renamed_keys__: {}
+      KEYPOINT_ON: false
+      LOAD_PROPOSALS: false
+      MASK_ON: true
+      META_ARCHITECTURE: GeneralizedRCNN
+      PANOPTIC_FPN: !!python/object/new:detectron2.config.config.CfgNode
+        dictitems:
+          COMBINE: !!python/object/new:detectron2.config.config.CfgNode
+            dictitems:
+              ENABLED: true
+              INSTANCES_CONFIDENCE_THRESH: 0.5
+              OVERLAP_THRESH: 0.5
+              STUFF_AREA_LIMIT: 4096
+            state:
+              __deprecated_keys__: !!set {}
+              __immutable__: false
+              __new_allowed__: false
+              __renamed_keys__: {}
+          INSTANCE_LOSS_WEIGHT: 1.0
+        state:
+          __deprecated_keys__: !!set {}
+          __immutable__: false
+          __new_allowed__: false
+          __renamed_keys__: {}
+      PIXEL_MEAN:
+      - 103.53
+      - 116.28
+      - 123.675
+      PIXEL_STD:
+      - 1.0
+      - 1.0
+      - 1.0
+      PROPOSAL_GENERATOR: !!python/object/new:detectron2.config.config.CfgNode
+        dictitems:
+          MIN_SIZE: 0
+          NAME: RPN
+        state:
+          __deprecated_keys__: !!set {}
+          __immutable__: false
+          __new_allowed__: false
+          __renamed_keys__: {}
+      RESNETS: !!python/object/new:detectron2.config.config.CfgNode
+        dictitems:
+          DEFORM_MODULATED: false
+          DEFORM_NUM_GROUPS: 1
+          DEFORM_ON_PER_STAGE:
+          - false
+          - false
+          - false
+          - false
+          DEPTH: 50
+          NORM: FrozenBN
+          NUM_GROUPS: 1
+          OUT_FEATURES:
+          - res2
+          - res3
+          - res4
+          - res5
+          RES2_OUT_CHANNELS: 256
+          RES5_DILATION: 1
+          STEM_OUT_CHANNELS: 64
+          STRIDE_IN_1X1: true
+          WIDTH_PER_GROUP: 64
+        state:
+          __deprecated_keys__: !!set {}
+          __immutable__: false
+          __new_allowed__: false
+          __renamed_keys__: {}
+      RETINANET: !!python/object/new:detectron2.config.config.CfgNode
+        dictitems:
+          BBOX_REG_LOSS_TYPE: smooth_l1
+          BBOX_REG_WEIGHTS: &id002 !!python/tuple
+          - 1.0
+          - 1.0
+          - 1.0
+          - 1.0
+          FOCAL_LOSS_ALPHA: 0.25
+          FOCAL_LOSS_GAMMA: 2.0
+          IN_FEATURES:
+          - p3
+          - p4
+          - p5
+          - p6
+          - p7
+          IOU_LABELS:
+          - 0
+          - -1
+          - 1
+          IOU_THRESHOLDS:
+          - 0.4
+          - 0.5
+          NMS_THRESH_TEST: 0.5
+          NORM: ''
+          NUM_CLASSES: 80
+          NUM_CONVS: 4
+          PRIOR_PROB: 0.01
+          SCORE_THRESH_TEST: 0.05
+          SMOOTH_L1_LOSS_BETA: 0.1
+          TOPK_CANDIDATES_TEST: 1000
+        state:
+          __deprecated_keys__: !!set {}
+          __immutable__: false
+          __new_allowed__: false
+          __renamed_keys__: {}
+      ROI_BOX_CASCADE_HEAD: !!python/object/new:detectron2.config.config.CfgNode
+        dictitems:
+          BBOX_REG_WEIGHTS: !!python/tuple
+          - &id001 !!python/tuple
+            - 10.0
+            - 10.0
+            - 5.0
+            - 5.0
+          - !!python/tuple
+            - 20.0
+            - 20.0
+            - 10.0
+            - 10.0
+          - !!python/tuple
+            - 30.0
+            - 30.0
+            - 15.0
+            - 15.0
+          IOUS: !!python/tuple
+          - 0.5
+          - 0.6
+          - 0.7
+        state:
+          __deprecated_keys__: !!set {}
+          __immutable__: false
+          __new_allowed__: false
+          __renamed_keys__: {}
+      ROI_BOX_HEAD: !!python/object/new:detectron2.config.config.CfgNode
+        dictitems:
+          BBOX_REG_LOSS_TYPE: smooth_l1
+          BBOX_REG_LOSS_WEIGHT: 1.0
+          BBOX_REG_WEIGHTS: *id001
+          CLS_AGNOSTIC_BBOX_REG: false
+          CONV_DIM: 256
+          FC_DIM: 1024
+          FED_LOSS_FREQ_WEIGHT_POWER: 0.5
+          FED_LOSS_NUM_CLASSES: 50
+          NAME: FastRCNNConvFCHead
+          NORM: ''
+          NUM_CONV: 0
+          NUM_FC: 2
+          POOLER_RESOLUTION: 7
+          POOLER_SAMPLING_RATIO: 0
+          POOLER_TYPE: ROIAlignV2
+          SMOOTH_L1_BETA: 0.0
+          TRAIN_ON_PRED_BOXES: false
+          USE_FED_LOSS: false
+          USE_SIGMOID_CE: false
+        state:
+          __deprecated_keys__: !!set {}
+          __immutable__: false
+          __new_allowed__: false
+          __renamed_keys__: {}
+      ROI_HEADS: !!python/object/new:detectron2.config.config.CfgNode
+        dictitems:
+          BATCH_SIZE_PER_IMAGE: 256
+          IN_FEATURES:
+          - p2
+          - p3
+          - p4
+          - p5
+          IOU_LABELS:
+          - 0
+          - 1
+          IOU_THRESHOLDS:
+          - 0.5
+          NAME: StandardROIHeads
+          NMS_THRESH_TEST: 0.5
+          NUM_CLASSES: 4
+          POSITIVE_FRACTION: 0.25
+          PROPOSAL_APPEND_GT: true
+          SCORE_THRESH_TEST: 0.05
+        state:
+          __deprecated_keys__: !!set {}
+          __immutable__: false
+          __new_allowed__: false
+          __renamed_keys__: {}
+      ROI_KEYPOINT_HEAD: !!python/object/new:detectron2.config.config.CfgNode
+        dictitems:
+          CONV_DIMS: !!python/tuple
+          - 512
+          - 512
+          - 512
+          - 512
+          - 512
+          - 512
+          - 512
+          - 512
+          LOSS_WEIGHT: 1.0
+          MIN_KEYPOINTS_PER_IMAGE: 1
+          NAME: KRCNNConvDeconvUpsampleHead
+          NORMALIZE_LOSS_BY_VISIBLE_KEYPOINTS: true
+          NUM_KEYPOINTS: 17
+          POOLER_RESOLUTION: 14
+          POOLER_SAMPLING_RATIO: 0
+          POOLER_TYPE: ROIAlignV2
+        state:
+          __deprecated_keys__: !!set {}
+          __immutable__: false
+          __new_allowed__: false
+          __renamed_keys__: {}
+      ROI_MASK_HEAD: !!python/object/new:detectron2.config.config.CfgNode
+        dictitems:
+          CLS_AGNOSTIC_MASK: false
+          CONV_DIM: 256
+          NAME: MaskRCNNConvUpsampleHead
+          NORM: ''
+          NUM_CONV: 4
+          POOLER_RESOLUTION: 14
+          POOLER_SAMPLING_RATIO: 0
+          POOLER_TYPE: ROIAlignV2
+        state:
+          __deprecated_keys__: !!set {}
+          __immutable__: false
+          __new_allowed__: false
+          __renamed_keys__: {}
+      RPN: !!python/object/new:detectron2.config.config.CfgNode
+        dictitems:
+          BATCH_SIZE_PER_IMAGE: 256
+          BBOX_REG_LOSS_TYPE: smooth_l1
+          BBOX_REG_LOSS_WEIGHT: 1.0
+          BBOX_REG_WEIGHTS: *id002
+          BOUNDARY_THRESH: -1
+          CONV_DIMS:
+          - -1
+          HEAD_NAME: StandardRPNHead
+          IN_FEATURES:
+          - p2
+          - p3
+          - p4
+          - p5
+          - p6
+          IOU_LABELS:
+          - 0
+          - -1
+          - 1
+          IOU_THRESHOLDS:
+          - 0.3
+          - 0.7
+          LOSS_WEIGHT: 1.0
+          NMS_THRESH: 0.7
+          POSITIVE_FRACTION: 0.5
+          POST_NMS_TOPK_TEST: 1000
+          POST_NMS_TOPK_TRAIN: 1000
+          PRE_NMS_TOPK_TEST: 1000
+          PRE_NMS_TOPK_TRAIN: 2000
+          SMOOTH_L1_BETA: 0.0
+        state:
+          __deprecated_keys__: !!set {}
+          __immutable__: false
+          __new_allowed__: false
+          __renamed_keys__: {}
+      SEM_SEG_HEAD: !!python/object/new:detectron2.config.config.CfgNode
+        dictitems:
+          COMMON_STRIDE: 4
+          CONVS_DIM: 128
+          IGNORE_VALUE: 255
+          IN_FEATURES:
+          - p2
+          - p3
+          - p4
+          - p5
+          LOSS_WEIGHT: 1.0
+          NAME: SemSegFPNHead
+          NORM: GN
+          NUM_CLASSES: 54
+        state:
+          __deprecated_keys__: !!set {}
+          __immutable__: false
+          __new_allowed__: false
+          __renamed_keys__: {}
+      WEIGHTS: https://dl.fbaipublicfiles.com/detectron2/COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x/137849600/model_final_f10217.pkl
+    state:
+      __deprecated_keys__: !!set {}
+      __immutable__: false
+      __new_allowed__: false
+      __renamed_keys__: {}
+  OUTPUT_DIR: /kaggle/working/outputs
+  SEED: -1
+  SOLVER: !!python/object/new:detectron2.config.config.CfgNode
+    dictitems:
+      AMP: !!python/object/new:detectron2.config.config.CfgNode
+        dictitems:
+          ENABLED: false
+        state:
+          __deprecated_keys__: !!set {}
+          __immutable__: false
+          __new_allowed__: false
+          __renamed_keys__: {}
+      BASE_LR: 0.00025
+      BASE_LR_END: 0.0
+      BIAS_LR_FACTOR: 1.0
+      CHECKPOINT_PERIOD: 5000
+      CLIP_GRADIENTS: !!python/object/new:detectron2.config.config.CfgNode
+        dictitems:
+          CLIP_TYPE: value
+          CLIP_VALUE: 1.0
+          ENABLED: false
+          NORM_TYPE: 2.0
+        state:
+          __deprecated_keys__: !!set {}
+          __immutable__: false
+          __new_allowed__: false
+          __renamed_keys__: {}
+      GAMMA: 0.1
+      IMS_PER_BATCH: 2
+      LR_SCHEDULER_NAME: WarmupMultiStepLR
+      MAX_ITER: 1000
+      MOMENTUM: 0.9
+      NESTEROV: false
+      NUM_DECAYS: 3
+      REFERENCE_WORLD_SIZE: 0
+      RESCALE_INTERVAL: false
+      STEPS: []
+      WARMUP_FACTOR: 0.001
+      WARMUP_ITERS: 1000
+      WARMUP_METHOD: linear
+      WEIGHT_DECAY: 0.0001
+      WEIGHT_DECAY_BIAS: null
+      WEIGHT_DECAY_NORM: 0.0
+    state:
+      __deprecated_keys__: !!set {}
+      __immutable__: false
+      __new_allowed__: false
+      __renamed_keys__: {}
+  TEST: !!python/object/new:detectron2.config.config.CfgNode
+    dictitems:
+      AUG: !!python/object/new:detectron2.config.config.CfgNode
+        dictitems:
+          ENABLED: false
+          FLIP: true
+          MAX_SIZE: 4000
+          MIN_SIZES: !!python/tuple
+          - 400
+          - 500
+          - 600
+          - 700
+          - 800
+          - 900
+          - 1000
+          - 1100
+          - 1200
+        state:
+          __deprecated_keys__: !!set {}
+          __immutable__: false
+          __new_allowed__: false
+          __renamed_keys__: {}
+      DETECTIONS_PER_IMAGE: 100
+      EVAL_PERIOD: 0
+      EXPECTED_RESULTS: []
+      KEYPOINT_OKS_SIGMAS: []
+      PRECISE_BN: !!python/object/new:detectron2.config.config.CfgNode
+        dictitems:
+          ENABLED: false
+          NUM_ITER: 200
+        state:
+          __deprecated_keys__: !!set {}
+          __immutable__: false
+          __new_allowed__: false
+          __renamed_keys__: {}
+    state:
+      __deprecated_keys__: !!set {}
+      __immutable__: false
+      __new_allowed__: false
+      __renamed_keys__: {}
+  VERSION: 2
+  VIS_PERIOD: 0
+state:
+  __deprecated_keys__: !!set {}
+  __immutable__: false
+  __new_allowed__: false
+  __renamed_keys__: {}

model_final.pth ADDED Viewed

	@@ -0,0 +1,3 @@

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+size 351146483

outputs/coco_instances_results.json ADDED Viewed

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outputs/model_final.pth ADDED Viewed

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semantic-segmentation-of-plants-with-detectron-2.log ADDED Viewed

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+,{"stream_name":"stdout","time":203.802910449,"data":"Successfully built detectron2 fvcore antlr4-python3-runtime\r\n"}
+,{"stream_name":"stdout","time":215.46712805,"data":"Installing collected packages: antlr4-python3-runtime, yacs, portalocker, pathspec, packaging, omegaconf, iopath, hydra-core, black, pycocotools, fvcore, detectron2\r\n"}
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+,{"stream_name":"stdout","time":215.669311267,"data":"    Found existing installation: packaging 21.3\r\n"}
+,{"stream_name":"stdout","time":215.66931776,"data":"    Uninstalling packaging-21.3:\r\n"}
+,{"stream_name":"stdout","time":215.72093058,"data":"      Successfully uninstalled packaging-21.3\r\n"}
+,{"stream_name":"stdout","time":217.038332118,"data":"\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\r\n"}
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+,{"stream_name":"stdout","time":217.038427905,"data":"distributed 2023.7.1 requires dask==2023.7.1, but you have dask 2023.9.0 which is incompatible.\r\n"}
+,{"stream_name":"stdout","time":217.038433206,"data":"google-cloud-bigquery 2.34.4 requires packaging\u003c22.0dev,\u003e=14.3, but you have packaging 23.1 which is incompatible.\r\n"}
+,{"stream_name":"stdout","time":217.038438437,"data":"jupyterlab-lsp 4.2.0 requires jupyter-lsp\u003e=2.0.0, but you have jupyter-lsp 1.5.1 which is incompatible.\r\n"}
+,{"stream_name":"stdout","time":217.038443813,"data":"momepy 0.6.0 requires shapely\u003e=2, but you have shapely 1.8.5.post1 which is incompatible.\r\n"}
+,{"stream_name":"stdout","time":217.038449692,"data":"pymc3 3.11.5 requires numpy\u003c1.22.2,\u003e=1.15.0, but you have numpy 1.23.5 which is incompatible.\r\n"}
+,{"stream_name":"stdout","time":217.038459679,"data":"pymc3 3.11.5 requires scipy\u003c1.8.0,\u003e=1.7.3, but you have scipy 1.11.2 which is incompatible.\r\n"}
+,{"stream_name":"stdout","time":217.038469082,"data":"raft-dask 23.8.0 requires dask==2023.7.1, but you have dask 2023.9.0 which is incompatible.\r\n"}
+,{"stream_name":"stdout","time":217.038487331,"data":"ydata-profiling 4.3.1 requires scipy\u003c1.11,\u003e=1.4.1, but you have scipy 1.11.2 which is incompatible.\u001b[0m\u001b[31m\r\n"}
+,{"stream_name":"stdout","time":217.038494464,"data":"\u001b[0mSuccessfully installed antlr4-python3-runtime-4.9.3 black-23.9.1 detectron2-0.6 fvcore-0.1.5.post20221221 hydra-core-1.3.2 iopath-0.1.9 omegaconf-2.3.0 packaging-23.1 pathspec-0.11.2 portalocker-2.8.2 pycocotools-2.0.7 yacs-0.1.8\r\n"}
+,{"stream_name":"stdout","time":219.774063631,"data":"2.0.0 True\n"}
+,{"stream_name":"stdout","time":220.700549514,"data":"\u001b[5m\u001b[31mWARNING\u001b[0m \u001b[32m[09/23 07:38:36 d2.data.datasets.coco]: \u001b[0m\n"}
+,{"stream_name":"stdout","time":220.700602938,"data":"Category ids in annotations are not in [1, #categories]! We'll apply a mapping for you.\n"}
+,{"stream_name":"stdout","time":220.700611439,"data":"\n"}
+,{"stream_name":"stdout","time":220.702501643,"data":"\u001b[32m[09/23 07:38:36 d2.data.datasets.coco]: \u001b[0mLoaded 123 images in COCO format from /kaggle/input/leaf-flower-fruit-annotation/semantic-segmentation-of-plants.v2i.coco-segmentation/train/train.json\n"}
+,{"stream_name":"stdout","time":220.744890243,"data":"\u001b[5m\u001b[31mWARNING\u001b[0m \u001b[32m[09/23 07:38:36 d2.data.datasets.coco]: \u001b[0m\n"}
+,{"stream_name":"stdout","time":220.744911035,"data":"Category ids in annotations are not in [1, #categories]! We'll apply a mapping for you.\n"}
+,{"stream_name":"stdout","time":220.744927809,"data":"\n"}
+,{"stream_name":"stdout","time":220.746546326,"data":"\u001b[32m[09/23 07:38:36 d2.data.datasets.coco]: \u001b[0mLoaded 123 images in COCO format from /kaggle/input/leaf-flower-fruit-annotation/semantic-segmentation-of-plants.v2i.coco-segmentation/train/train.json\n"}
+,{"stream_name":"stdout","time":220.788803161,"data":"\u001b[5m\u001b[31mWARNING\u001b[0m \u001b[32m[09/23 07:38:36 d2.data.datasets.coco]: \u001b[0m\n"}
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+,{"stream_name":"stdout","time":220.788830261,"data":"\n"}
+,{"stream_name":"stdout","time":220.789918143,"data":"\u001b[32m[09/23 07:38:36 d2.data.datasets.coco]: \u001b[0mLoaded 18 images in COCO format from /kaggle/input/leaf-flower-fruit-annotation/semantic-segmentation-of-plants.v2i.coco-segmentation/valid/valid.json\n"}
+,{"stream_name":"stdout","time":227.179968614,"data":"\u001b[32m[09/23 07:38:42 d2.engine.defaults]: \u001b[0mModel:\n"}
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+,{"stream_name":"stdout","time":227.18267819,"data":")\n"}
+,{"stream_name":"stdout","time":227.194125733,"data":"\u001b[5m\u001b[31mWARNING\u001b[0m \u001b[32m[09/23 07:38:42 d2.data.datasets.coco]: \u001b[0m\n"}
+,{"stream_name":"stdout","time":227.194167193,"data":"Category ids in annotations are not in [1, #categories]! We'll apply a mapping for you.\n"}
+,{"stream_name":"stdout","time":227.194180416,"data":"\n"}
+,{"stream_name":"stdout","time":227.196109555,"data":"\u001b[32m[09/23 07:38:42 d2.data.datasets.coco]: \u001b[0mLoaded 123 images in COCO format from /kaggle/input/leaf-flower-fruit-annotation/semantic-segmentation-of-plants.v2i.coco-segmentation/train/train.json\n"}
+,{"stream_name":"stdout","time":227.202177857,"data":"\u001b[32m[09/23 07:38:42 d2.data.build]: \u001b[0mRemoved 0 images with no usable annotations. 123 images left.\n"}
+,{"stream_name":"stdout","time":227.21499769,"data":"\u001b[32m[09/23 07:38:42 d2.data.build]: \u001b[0mDistribution of instances among all 4 categories:\n"}
+,{"stream_name":"stdout","time":227.215031132,"data":"\u001b[36m|   category    | #instances   | category   | #instances   | category   | #instances   |\n"}
+,{"stream_name":"stdout","time":227.2150391,"data":"|:-------------:|:-------------|:-----------|:-------------|:-----------|:-------------|\n"}
+,{"stream_name":"stdout","time":227.215057176,"data":"| leaf, flowe.. | 0            | 0          | 440          | 1          | 164          |\n"}
+,{"stream_name":"stdout","time":227.215063542,"data":"|       2       | 114          |            |              |            |              |\n"}
+,{"stream_name":"stdout","time":227.215069607,"data":"|     total     | 718          |            |              |            |              |\u001b[0m\n"}
+,{"stream_name":"stdout","time":227.21704684,"data":"\u001b[32m[09/23 07:38:42 d2.data.dataset_mapper]: \u001b[0m[DatasetMapper] Augmentations used in training: [ResizeShortestEdge(short_edge_length=(640, 672, 704, 736, 768, 800), max_size=1333, sample_style='choice'), RandomFlip()]\n"}
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+,{"stream_name":"stdout","time":228.653681696,"data":"\u001b[32m[09/23 07:38:44 d2.engine.train_loop]: \u001b[0mStarting training from iteration 0\n"}
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+,{"stream_name":"stdout","time":539.851856257,"data":"\u001b[32m[09/23 07:43:55 d2.utils.events]: \u001b[0m eta: 0:01:27  iter: 759  total_loss: 0.7775  loss_cls: 0.1542  loss_box_reg: 0.2954  loss_mask: 0.2675  loss_rpn_cls: 0.006361  loss_rpn_loc: 0.03081    time: 0.3703  last_time: 0.3897  data_time: 0.0079  last_data_time: 0.0067   lr: 0.00018981  max_mem: 1777M\n"}
+,{"stream_name":"stdout","time":547.255724779,"data":"\u001b[32m[09/23 07:44:02 d2.utils.events]: \u001b[0m eta: 0:01:20  iter: 779  total_loss: 0.5322  loss_cls: 0.07315  loss_box_reg: 0.2183  loss_mask: 0.2537  loss_rpn_cls: 0.002045  loss_rpn_loc: 0.01187    time: 0.3703  last_time: 0.3445  data_time: 0.0081  last_data_time: 0.0062   lr: 0.00019481  max_mem: 1777M\n"}
+,{"stream_name":"stdout","time":554.533396611,"data":"\u001b[32m[09/23 07:44:10 d2.utils.events]: \u001b[0m eta: 0:01:13  iter: 799  total_loss: 0.583  loss_cls: 0.1178  loss_box_reg: 0.2244  loss_mask: 0.2243  loss_rpn_cls: 0.002606  loss_rpn_loc: 0.01259    time: 0.3701  last_time: 0.3479  data_time: 0.0088  last_data_time: 0.0061   lr: 0.0001998  max_mem: 1777M\n"}
+,{"stream_name":"stdout","time":562.09889552,"data":"\u001b[32m[09/23 07:44:17 d2.utils.events]: \u001b[0m eta: 0:01:05  iter: 819  total_loss: 0.6812  loss_cls: 0.1063  loss_box_reg: 0.2592  loss_mask: 0.2674  loss_rpn_cls: 0.005045  loss_rpn_loc: 0.01705    time: 0.3703  last_time: 0.3368  data_time: 0.0104  last_data_time: 0.0068   lr: 0.0002048  max_mem: 1777M\n"}
+,{"stream_name":"stdout","time":569.577541326,"data":"\u001b[32m[09/23 07:44:25 d2.utils.events]: \u001b[0m eta: 0:00:58  iter: 839  total_loss: 0.6475  loss_cls: 0.1354  loss_box_reg: 0.2331  loss_mask: 0.2683  loss_rpn_cls: 0.003228  loss_rpn_loc: 0.01554    time: 0.3703  last_time: 0.3450  data_time: 0.0073  last_data_time: 0.0085   lr: 0.00020979  max_mem: 1777M\n"}
+,{"stream_name":"stdout","time":577.105613046,"data":"\u001b[32m[09/23 07:44:32 d2.utils.events]: \u001b[0m eta: 0:00:51  iter: 859  total_loss: 0.5261  loss_cls: 0.08092  loss_box_reg: 0.2062  loss_mask: 0.2242  loss_rpn_cls: 0.001237  loss_rpn_loc: 0.01276    time: 0.3705  last_time: 0.4097  data_time: 0.0084  last_data_time: 0.0081   lr: 0.00021479  max_mem: 1777M\n"}
+,{"stream_name":"stdout","time":584.639586156,"data":"\u001b[32m[09/23 07:44:40 d2.utils.events]: \u001b[0m eta: 0:00:43  iter: 879  total_loss: 0.5345  loss_cls: 0.07986  loss_box_reg: 0.2093  loss_mask: 0.1887  loss_rpn_cls: 0.0009999  loss_rpn_loc: 0.008154    time: 0.3706  last_time: 0.3908  data_time: 0.0076  last_data_time: 0.0079   lr: 0.00021978  max_mem: 1777M\n"}
+,{"stream_name":"stdout","time":592.133724965,"data":"\u001b[32m[09/23 07:44:47 d2.utils.events]: \u001b[0m eta: 0:00:36  iter: 899  total_loss: 0.6179  loss_cls: 0.1105  loss_box_reg: 0.2395  loss_mask: 0.2561  loss_rpn_cls: 0.008318  loss_rpn_loc: 0.01785    time: 0.3707  last_time: 0.3466  data_time: 0.0090  last_data_time: 0.0072   lr: 0.00022478  max_mem: 1777M\n"}
+,{"stream_name":"stdout","time":599.759886771,"data":"\u001b[32m[09/23 07:44:55 d2.utils.events]: \u001b[0m eta: 0:00:29  iter: 919  total_loss: 0.4821  loss_cls: 0.07783  loss_box_reg: 0.1655  loss_mask: 0.2053  loss_rpn_cls: 0.0013  loss_rpn_loc: 0.01239    time: 0.3709  last_time: 0.4113  data_time: 0.0079  last_data_time: 0.0068   lr: 0.00022977  max_mem: 1777M\n"}
+,{"stream_name":"stdout","time":607.564687644,"data":"\u001b[32m[09/23 07:45:03 d2.utils.events]: \u001b[0m eta: 0:00:22  iter: 939  total_loss: 0.5789  loss_cls: 0.1175  loss_box_reg: 0.2348  loss_mask: 0.2183  loss_rpn_cls: 0.002596  loss_rpn_loc: 0.01899    time: 0.3713  last_time: 0.3916  data_time: 0.0087  last_data_time: 0.0098   lr: 0.00023477  max_mem: 1777M\n"}
+,{"stream_name":"stdout","time":614.932708254,"data":"\u001b[32m[09/23 07:45:10 d2.utils.events]: \u001b[0m eta: 0:00:14  iter: 959  total_loss: 0.5084  loss_cls: 0.08297  loss_box_reg: 0.1746  loss_mask: 0.235  loss_rpn_cls: 0.002214  loss_rpn_loc: 0.01299    time: 0.3713  last_time: 0.3617  data_time: 0.0084  last_data_time: 0.0086   lr: 0.00023976  max_mem: 1777M\n"}
+,{"stream_name":"stdout","time":622.746722669,"data":"\u001b[32m[09/23 07:45:18 d2.utils.events]: \u001b[0m eta: 0:00:07  iter: 979  total_loss: 0.5914  loss_cls: 0.08434  loss_box_reg: 0.235  loss_mask: 0.2241  loss_rpn_cls: 0.002513  loss_rpn_loc: 0.01149    time: 0.3716  last_time: 0.3726  data_time: 0.0085  last_data_time: 0.0177   lr: 0.00024476  max_mem: 1777M\n"}
+,{"stream_name":"stdout","time":630.929186452,"data":"\u001b[32m[09/23 07:45:26 d2.utils.events]: \u001b[0m eta: 0:00:00  iter: 999  total_loss: 0.6494  loss_cls: 0.1022  loss_box_reg: 0.2411  loss_mask: 0.252  loss_rpn_cls: 0.002364  loss_rpn_loc: 0.0139    time: 0.3716  last_time: 0.3077  data_time: 0.0075  last_data_time: 0.0069   lr: 0.00024975  max_mem: 1777M\n"}
+,{"stream_name":"stdout","time":630.930411314,"data":"\u001b[32m[09/23 07:45:26 d2.engine.hooks]: \u001b[0mOverall training speed: 998 iterations in 0:06:10 (0.3716 s / it)\n"}
+,{"stream_name":"stdout","time":630.932104437,"data":"\u001b[32m[09/23 07:45:26 d2.engine.hooks]: \u001b[0mTotal training time: 0:06:25 (0:00:14 on hooks)\n"}
+,{"stream_name":"stdout","time":631.852853369,"data":"\u001b[32m[09/23 07:45:27 d2.checkpoint.detection_checkpoint]: \u001b[0m[DetectionCheckpointer] Loading from /kaggle/working/outputs/model_final.pth ...\n"}
+,{"stream_name":"stdout","time":633.854559424,"data":"\u001b[5m\u001b[31mWARNING\u001b[0m \u001b[32m[09/23 07:45:29 d2.data.datasets.coco]: \u001b[0m\n"}
+,{"stream_name":"stdout","time":633.854596514,"data":"Category ids in annotations are not in [1, #categories]! We'll apply a mapping for you.\n"}
+,{"stream_name":"stdout","time":633.854603187,"data":"\n"}
+,{"stream_name":"stdout","time":633.855964849,"data":"\u001b[32m[09/23 07:45:29 d2.data.datasets.coco]: \u001b[0mLoaded 18 images in COCO format from /kaggle/input/leaf-flower-fruit-annotation/semantic-segmentation-of-plants.v2i.coco-segmentation/valid/valid.json\n"}
+,{"stream_name":"stdout","time":633.862563388,"data":"\u001b[32m[09/23 07:45:29 d2.data.build]: \u001b[0mDistribution of instances among all 4 categories:\n"}
+,{"stream_name":"stdout","time":633.862601189,"data":"\u001b[36m|   category    | #instances   | category   | #instances   | category   | #instances   |\n"}
+,{"stream_name":"stdout","time":633.862608844,"data":"|:-------------:|:-------------|:-----------|:-------------|:-----------|:-------------|\n"}
+,{"stream_name":"stdout","time":633.862614688,"data":"| leaf, flowe.. | 0            | 0          | 27           | 1          | 19           |\n"}
+,{"stream_name":"stdout","time":633.862620603,"data":"|       2       | 36           |            |              |            |              |\n"}
+,{"stream_name":"stdout","time":633.862626214,"data":"|     total     | 82           |            |              |            |              |\u001b[0m\n"}
+,{"stream_name":"stdout","time":633.864171798,"data":"\u001b[32m[09/23 07:45:29 d2.data.dataset_mapper]: \u001b[0m[DatasetMapper] Augmentations used in inference: [ResizeShortestEdge(short_edge_length=(800, 800), max_size=1333, sample_style='choice')]\n"}
+,{"stream_name":"stdout","time":633.865624594,"data":"\u001b[32m[09/23 07:45:29 d2.data.common]: \u001b[0mSerializing the dataset using: \u003cclass 'detectron2.data.common._TorchSerializedList'\u003e\n"}
+,{"stream_name":"stdout","time":633.867186249,"data":"\u001b[32m[09/23 07:45:29 d2.data.common]: \u001b[0mSerializing 18 elements to byte tensors and concatenating them all ...\n"}
+,{"stream_name":"stdout","time":633.868659769,"data":"\u001b[32m[09/23 07:45:29 d2.data.common]: \u001b[0mSerialized dataset takes 0.02 MiB\n"}
+,{"stream_name":"stdout","time":633.870068823,"data":"\u001b[32m[09/23 07:45:29 d2.evaluation.evaluator]: \u001b[0mStart inference on 18 batches\n"}
+,{"stream_name":"stdout","time":635.094665576,"data":"\u001b[32m[09/23 07:45:30 d2.evaluation.evaluator]: \u001b[0mInference done 11/18. Dataloading: 0.0016 s/iter. Inference: 0.0821 s/iter. Eval: 0.0064 s/iter. Total: 0.0901 s/iter. ETA=0:00:00\n"}
+,{"stream_name":"stdout","time":635.766430367,"data":"\u001b[32m[09/23 07:45:31 d2.evaluation.evaluator]: \u001b[0mTotal inference time: 0:00:01.213719 (0.093363 s / iter per device, on 1 devices)\n"}
+,{"stream_name":"stdout","time":635.769214269,"data":"\u001b[32m[09/23 07:45:31 d2.evaluation.evaluator]: \u001b[0mTotal inference pure compute time: 0:00:01 (0.080777 s / iter per device, on 1 devices)\n"}
+,{"stream_name":"stdout","time":635.771225527,"data":"\u001b[32m[09/23 07:45:31 d2.evaluation.coco_evaluation]: \u001b[0mPreparing results for COCO format ...\n"}
+,{"stream_name":"stdout","time":635.773198027,"data":"\u001b[32m[09/23 07:45:31 d2.evaluation.coco_evaluation]: \u001b[0mSaving results to ./outputs/coco_instances_results.json\n"}
+,{"stream_name":"stdout","time":635.778019995,"data":"\u001b[32m[09/23 07:45:31 d2.evaluation.coco_evaluation]: \u001b[0mEvaluating predictions with unofficial COCO API...\n"}
+,{"stream_name":"stdout","time":635.779417428,"data":"Loading and preparing results...\n"}
+,{"stream_name":"stdout","time":635.779434434,"data":"DONE (t=0.00s)\n"}
+,{"stream_name":"stdout","time":635.779440883,"data":"creating index...\n"}
+,{"stream_name":"stdout","time":635.77944617,"data":"index created!\n"}
+,{"stream_name":"stdout","time":635.779451855,"data":"\u001b[32m[09/23 07:45:31 d2.evaluation.fast_eval_api]: \u001b[0mEvaluate annotation type *bbox*\n"}
+,{"stream_name":"stdout","time":635.789318341,"data":"\u001b[32m[09/23 07:45:31 d2.evaluation.fast_eval_api]: \u001b[0mCOCOeval_opt.evaluate() finished in 0.01 seconds.\n"}
+,{"stream_name":"stdout","time":635.797159053,"data":"\u001b[32m[09/23 07:45:31 d2.evaluation.fast_eval_api]: \u001b[0mAccumulating evaluation results...\n"}
+,{"stream_name":"stdout","time":635.807632373,"data":"\u001b[32m[09/23 07:45:31 d2.evaluation.fast_eval_api]: \u001b[0mCOCOeval_opt.accumulate() finished in 0.02 seconds.\n"}
+,{"stream_name":"stdout","time":635.810643959,"data":" Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.302\n"}
+,{"stream_name":"stdout","time":635.810661179,"data":" Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.474\n"}
+,{"stream_name":"stdout","time":635.810671544,"data":" Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.357\n"}
+,{"stream_name":"stdout","time":635.810677171,"data":" Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = -1.000\n"}
+,{"stream_name":"stdout","time":635.810682026,"data":" Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.304\n"}
+,{"stream_name":"stdout","time":635.810686646,"data":" Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.263\n"}
+,{"stream_name":"stdout","time":635.810691178,"data":" Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.138\n"}
+,{"stream_name":"stdout","time":635.810695681,"data":" Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.391\n"}
+,{"stream_name":"stdout","time":635.810700604,"data":" Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.392\n"}
+,{"stream_name":"stdout","time":635.810705254,"data":" Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = -1.000\n"}
+,{"stream_name":"stdout","time":635.810710319,"data":" Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.371\n"}
+,{"stream_name":"stdout","time":635.810714862,"data":" Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.364\n"}
+,{"stream_name":"stdout","time":635.810719904,"data":"\u001b[32m[09/23 07:45:31 d2.evaluation.coco_evaluation]: \u001b[0mEvaluation results for bbox: \n"}
+,{"stream_name":"stdout","time":635.810725438,"data":"|   AP   |  AP50  |  AP75  |  APs  |  APm   |  APl   |\n"}
+,{"stream_name":"stdout","time":635.81073265,"data":"|:------:|:------:|:------:|:-----:|:------:|:------:|\n"}
+,{"stream_name":"stdout","time":635.81074006,"data":"| 30.219 | 47.387 | 35.729 |  nan  | 30.435 | 26.317 |\n"}
+,{"stream_name":"stdout","time":635.812444438,"data":"\u001b[32m[09/23 07:45:31 d2.evaluation.coco_evaluation]: \u001b[0mSome metrics cannot be computed and is shown as NaN.\n"}
+,{"stream_name":"stdout","time":635.814914009,"data":"\u001b[32m[09/23 07:45:31 d2.evaluation.coco_evaluation]: \u001b[0mPer-category bbox AP: \n"}
+,{"stream_name":"stdout","time":635.814931885,"data":"| category               | AP     | category   | AP     | category   | AP     |\n"}
+,{"stream_name":"stdout","time":635.814941054,"data":"|:-----------------------|:-------|:-----------|:-------|:-----------|:-------|\n"}
+,{"stream_name":"stdout","time":635.814950236,"data":"| leaf, flower and fruit | nan    | 0          | 11.429 | 1          | 39.127 |\n"}
+,{"stream_name":"stdout","time":635.814955966,"data":"| 2                      | 40.100 |            |        |            |        |\n"}
+,{"stream_name":"stdout","time":635.831025164,"data":"Loading and preparing results...\n"}
+,{"stream_name":"stdout","time":635.831060554,"data":"DONE (t=0.00s)\n"}
+,{"stream_name":"stdout","time":635.831066509,"data":"creating index...\n"}
+,{"stream_name":"stdout","time":635.831071302,"data":"index created!\n"}
+,{"stream_name":"stdout","time":635.831076148,"data":"\u001b[32m[09/23 07:45:31 d2.evaluation.fast_eval_api]: \u001b[0mEvaluate annotation type *segm*\n"}
+,{"stream_name":"stdout","time":635.832967364,"data":"\u001b[32m[09/23 07:45:31 d2.evaluation.fast_eval_api]: \u001b[0mCOCOeval_opt.evaluate() finished in 0.01 seconds.\n"}
+,{"stream_name":"stdout","time":635.834387149,"data":"\u001b[32m[09/23 07:45:31 d2.evaluation.fast_eval_api]: \u001b[0mAccumulating evaluation results...\n"}
+,{"stream_name":"stdout","time":635.849730149,"data":"\u001b[32m[09/23 07:45:31 d2.evaluation.fast_eval_api]: \u001b[0mCOCOeval_opt.accumulate() finished in 0.02 seconds.\n"}
+,{"stream_name":"stdout","time":635.852968257,"data":" Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.268\n"}
+,{"stream_name":"stdout","time":635.853013325,"data":" Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.482\n"}
+,{"stream_name":"stdout","time":635.85302032,"data":" Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.266\n"}
+,{"stream_name":"stdout","time":635.853026725,"data":" Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = -1.000\n"}
+,{"stream_name":"stdout","time":635.853032566,"data":" Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.290\n"}
+,{"stream_name":"stdout","time":635.853037529,"data":" Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.233\n"}
+,{"stream_name":"stdout","time":635.853043059,"data":" Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.134\n"}
+,{"stream_name":"stdout","time":635.853052344,"data":" Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.349\n"}
+,{"stream_name":"stdout","time":635.853058969,"data":" Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.350\n"}
+,{"stream_name":"stdout","time":635.853080544,"data":" Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = -1.000\n"}
+,{"stream_name":"stdout","time":635.853086828,"data":" Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.347\n"}
+,{"stream_name":"stdout","time":635.853104345,"data":" Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.324\n"}
+,{"stream_name":"stdout","time":635.853111104,"data":"\u001b[32m[09/23 07:45:31 d2.evaluation.coco_evaluation]: \u001b[0mEvaluation results for segm: \n"}
+,{"stream_name":"stdout","time":635.853117005,"data":"|   AP   |  AP50  |  AP75  |  APs  |  APm   |  APl   |\n"}
+,{"stream_name":"stdout","time":635.853122229,"data":"|:------:|:------:|:------:|:-----:|:------:|:------:|\n"}
+,{"stream_name":"stdout","time":635.853127204,"data":"| 26.769 | 48.197 | 26.573 |  nan  | 29.003 | 23.334 |\n"}
+,{"stream_name":"stdout","time":635.854207133,"data":"\u001b[32m[09/23 07:45:31 d2.evaluation.coco_evaluation]: \u001b[0mSome metrics cannot be computed and is shown as NaN.\n"}
+,{"stream_name":"stdout","time":635.85871157,"data":"\u001b[32m[09/23 07:45:31 d2.evaluation.coco_evaluation]: \u001b[0mPer-category segm AP: \n"}
+,{"stream_name":"stdout","time":635.858754408,"data":"| category               | AP     | category   | AP     | category   | AP     |\n"}
+,{"stream_name":"stdout","time":635.858761686,"data":"|:-----------------------|:-------|:-----------|:-------|:-----------|:-------|\n"}
+,{"stream_name":"stdout","time":635.858767208,"data":"| leaf, flower and fruit | nan    | 0          | 11.675 | 1          | 31.041 |\n"}
+,{"stream_name":"stdout","time":635.858772523,"data":"| 2                      | 37.590 |            |        |            |        |\n"}
+,{"stream_name":"stdout","time":635.860120683,"data":"OrderedDict([('bbox', {'AP': 30.218943392039694, 'AP50': 47.386900130198846, 'AP75': 35.72921800473737, 'APs': nan, 'APm': 30.43451625382318, 'APl': 26.31694060377811, 'AP-leaf, flower and fruit': nan, 'AP-0': 11.42892373885882, 'AP-1': 39.12745560270313, 'AP-2': 40.10045083455714}), ('segm', {'AP': 26.768528027464377, 'AP50': 48.19729533929002, 'AP75': 26.573458292849743, 'APs': nan, 'APm': 29.0032162556915, 'APl': 23.334085433968955, 'AP-leaf, flower and fruit': nan, 'AP-0': 11.674782020116336, 'AP-1': 31.04055405540554, 'AP-2': 37.59024800687124})])\n"}
+,{"stream_name":"stderr","time":641.251753977,"data":"/opt/conda/lib/python3.10/site-packages/traitlets/traitlets.py:2930: FutureWarning: --Exporter.preprocessors=[\"remove_papermill_header.RemovePapermillHeader\"] for containers is deprecated in traitlets 5.0. You can pass `--Exporter.preprocessors item` ... multiple times to add items to a list.\n"}
+,{"stream_name":"stderr","time":641.252033612,"data":"  warn(\n"}
+,{"stream_name":"stderr","time":641.271251502,"data":"[NbConvertApp] WARNING | Config option `kernel_spec_manager_class` not recognized by `NbConvertApp`.\n"}
+,{"stream_name":"stderr","time":641.299639329,"data":"[NbConvertApp] Converting notebook __notebook__.ipynb to notebook\n"}
+,{"stream_name":"stderr","time":641.812192464,"data":"[NbConvertApp] Writing 1563115 bytes to __notebook__.ipynb\n"}
+,{"stream_name":"stderr","time":643.508675438,"data":"/opt/conda/lib/python3.10/site-packages/traitlets/traitlets.py:2930: FutureWarning: --Exporter.preprocessors=[\"nbconvert.preprocessors.ExtractOutputPreprocessor\"] for containers is deprecated in traitlets 5.0. You can pass `--Exporter.preprocessors item` ... multiple times to add items to a list.\n"}
+,{"stream_name":"stderr","time":643.508732164,"data":"  warn(\n"}
+,{"stream_name":"stderr","time":643.511626803,"data":"[NbConvertApp] WARNING | Config option `kernel_spec_manager_class` not recognized by `NbConvertApp`.\n"}
+,{"stream_name":"stderr","time":643.556443524,"data":"[NbConvertApp] Converting notebook __notebook__.ipynb to html\n"}
+,{"stream_name":"stderr","time":644.538437008,"data":"[NbConvertApp] Support files will be in __results___files/\n"}
+,{"stream_name":"stderr","time":644.538518612,"data":"[NbConvertApp] Making directory __results___files\n"}
+,{"stream_name":"stderr","time":644.539060619,"data":"[NbConvertApp] Making directory __results___files\n"}
+,{"stream_name":"stderr","time":644.539504448,"data":"[NbConvertApp] Making directory __results___files\n"}
+,{"stream_name":"stderr","time":644.540311438,"data":"[NbConvertApp] Writing 357130 bytes to __results__.html\n"}
+]