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1 Parent(s): 79940b6

Delete segmentator

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  1. segmentator/.DS_Store +0 -0
  2. segmentator/segmentator2D/.DS_Store +0 -0
  3. segmentator/segmentator2D/dataset.json +0 -42
  4. segmentator/segmentator2D/dataset_fingerprint.json +0 -0
  5. segmentator/segmentator2D/fold_all/.DS_Store +0 -0
  6. segmentator/segmentator2D/fold_all/checkpoint_final.pth +0 -3
  7. segmentator/segmentator2D/fold_all/debug.json +0 -53
  8. segmentator/segmentator2D/plans.json +0 -532
  9. segmentator/segmentator3D/dataset.json +0 -39
  10. segmentator/segmentator3D/dataset_fingerprint.json +0 -0
  11. segmentator/segmentator3D/fold_all/checkpoint_final.pth +0 -3
  12. segmentator/segmentator3D/fold_all/debug.json +0 -53
  13. segmentator/segmentator3D/plans.json +0 -532
segmentator/.DS_Store DELETED
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segmentator/segmentator2D/.DS_Store DELETED
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segmentator/segmentator2D/dataset.json DELETED
@@ -1,42 +0,0 @@
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- {
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- "name": "JHH-Train-test",
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- "description": "3151 cases for training; 1958 cases for testing",
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- "reference": "ScaleMAI",
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- "licence": "CC-BY-SA 4.0",
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- "relase": "1.0 10/28/2024",
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- "tensorImageSize": "3D",
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- "labels": {
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- "background": 0,
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- "aorta": 1,
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- "adrenal_gland_left": 2,
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- "adrenal_gland_right": 3,
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- "common_bile_duct": 4,
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- "celiac_aa": 5,
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- "colon": 6,
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- "duodenum": 7,
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- "gall_bladder": 8,
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- "postcava": 9,
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- "kidney_left": 10,
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- "kidney_right": 11,
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- "liver": 12,
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- "pancreas": 13,
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- "pancreatic_duct": 14,
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- "superior_mesenteric_artery": 15,
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- "intestine": 16,
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- "spleen": 17,
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- "stomach": 18,
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- "veins": 19,
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- "renal_vein_left": 20,
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- "renal_vein_right": 21,
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- "cbd_stent": 22,
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- "pancreatic_pdac": 23,
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- "pancreatic_cyst": 24,
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- "pancreatic_pnet": 25
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- },
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- "numTraining": 3151,
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- "numTest": 1958,
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- "file_ending": ".nii.gz",
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- "channel_names": {
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- "0": "CT"
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- }
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- }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
segmentator/segmentator2D/dataset_fingerprint.json DELETED
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segmentator/segmentator2D/fold_all/.DS_Store DELETED
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segmentator/segmentator2D/fold_all/checkpoint_final.pth DELETED
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segmentator/segmentator2D/fold_all/debug.json DELETED
@@ -1,53 +0,0 @@
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- {
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- "_best_ema": "0.7794641",
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- "batch_size": "43",
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- "configuration_manager": "{'data_identifier': 'nnUNetPlans_2d', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 43, 'patch_size': [640, 640], 'median_image_size_in_voxels': [613.0, 513.0], 'spacing': [0.5, 0.7109375], 'normalization_schemes': ['CTNormalization'], 'use_mask_for_norm': [False], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.ResidualEncoderUNet', 'arch_kwargs': {'n_stages': 8, 'features_per_stage': [32, 64, 128, 256, 512, 512, 512, 512], 'conv_op': 'torch.nn.modules.conv.Conv2d', 'kernel_sizes': [[3, 3], [3, 3], [3, 3], [3, 3], [3, 3], [3, 3], [3, 3], [3, 3]], 'strides': [[1, 1], [2, 2], [2, 2], [2, 2], [2, 2], [2, 2], [2, 2], [2, 2]], 'n_blocks_per_stage': [1, 3, 4, 6, 6, 6, 6, 6], 'n_conv_per_stage_decoder': [1, 1, 1, 1, 1, 1, 1], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm2d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': True}",
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- "configuration_name": "2d",
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- "cudnn_version": 90100,
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- "current_epoch": "650",
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- "dataloader_train": "<batchgenerators.dataloading.nondet_multi_threaded_augmenter.NonDetMultiThreadedAugmenter object at 0x7123f53afe50>",
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- "dataloader_train.generator": "<nnunetv2.training.dataloading.data_loader_2d.nnUNetDataLoader2D object at 0x7123f40ede10>",
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- "dataloader_train.num_processes": "32",
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- "dataloader_train.transform": "None",
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- "dataloader_val": "<batchgenerators.dataloading.nondet_multi_threaded_augmenter.NonDetMultiThreadedAugmenter object at 0x7123f4150350>",
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- "dataloader_val.generator": "<nnunetv2.training.dataloading.data_loader_2d.nnUNetDataLoader2D object at 0x7123f417b050>",
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- "dataloader_val.num_processes": "16",
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- "dataloader_val.transform": "None",
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- "dataset_json": "{'name': 'JHH-Train-test', 'description': '3151 cases for training; 1958 cases for testing', 'reference': 'ScaleMAI', 'licence': 'CC-BY-SA 4.0', 'relase': '1.0 10/28/2024', 'tensorImageSize': '3D', 'labels': {'background': 0, 'aorta': 1, 'adrenal_gland_left': 2, 'adrenal_gland_right': 3, 'common_bile_duct': 4, 'celiac_aa': 5, 'colon': 6, 'duodenum': 7, 'gall_bladder': 8, 'postcava': 9, 'kidney_left': 10, 'kidney_right': 11, 'liver': 12, 'pancreas': 13, 'pancreatic_duct': 14, 'superior_mesenteric_artery': 15, 'intestine': 16, 'spleen': 17, 'stomach': 18, 'veins': 19, 'renal_vein_left': 20, 'renal_vein_right': 21, 'cbd_stent': 22, 'pancreatic_pdac': 23, 'pancreatic_cyst': 24, 'pancreatic_pnet': 25}, 'numTraining': 3151, 'numTest': 1958, 'file_ending': '.nii.gz', 'channel_names': {'0': 'CT'}}",
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- "device": "cuda:0",
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- "disable_checkpointing": "False",
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- "enable_deep_supervision": "True",
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- "fold": "all",
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- "folder_with_segs_from_previous_stage": "None",
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- "gpu_name": "NVIDIA RTX 6000 Ada Generation",
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- "grad_scaler": "<torch.cuda.amp.grad_scaler.GradScaler object at 0x7123f69a1ed0>",
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- "hostname": "ccvl42",
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- "inference_allowed_mirroring_axes": "(0, 1)",
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- "initial_lr": "0.01",
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- "is_cascaded": "False",
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- "is_ddp": "False",
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- "label_manager": "<nnunetv2.utilities.label_handling.label_handling.LabelManager object at 0x7123f61d3ed0>",
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- "local_rank": "0",
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- "log_file": "/mnt/data/tlin67/nnUNet/nnUNet_results/Dataset808_AbdomenAtlasF/nnUNetTrainer__nnUNetResEncUNetLPlans__2d/fold_all/training_log_2025_5_3_12_54_52.txt",
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- "logger": "<nnunetv2.training.logging.nnunet_logger.nnUNetLogger object at 0x7123f6981f10>",
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- "loss": "DeepSupervisionWrapper(\n (loss): DC_and_CE_loss(\n (ce): RobustCrossEntropyLoss()\n (dc): OptimizedModule(\n (_orig_mod): MemoryEfficientSoftDiceLoss()\n )\n )\n)",
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- "lr_scheduler": "<nnunetv2.training.lr_scheduler.polylr.PolyLRScheduler object at 0x7123f72c8590>",
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- "my_init_kwargs": "{'plans': {'dataset_name': 'Dataset808_AbdomenAtlasF', 'plans_name': 'nnUNetResEncUNetLPlans', 'original_median_spacing_after_transp': [0.7109375, 0.5, 0.7109375], 'original_median_shape_after_transp': [512, 608, 512], 'image_reader_writer': 'SimpleITKIO', 'transpose_forward': [1, 0, 2], 'transpose_backward': [1, 0, 2], 'configurations': {'2d': {'data_identifier': 'nnUNetPlans_2d', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 43, 'patch_size': [640, 640], 'median_image_size_in_voxels': [613.0, 513.0], 'spacing': [0.5, 0.7109375], 'normalization_schemes': ['CTNormalization'], 'use_mask_for_norm': [False], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.ResidualEncoderUNet', 'arch_kwargs': {'n_stages': 8, 'features_per_stage': [32, 64, 128, 256, 512, 512, 512, 512], 'conv_op': 'torch.nn.modules.conv.Conv2d', 'kernel_sizes': [[3, 3], [3, 3], [3, 3], [3, 3], [3, 3], [3, 3], [3, 3], [3, 3]], 'strides': [[1, 1], [2, 2], [2, 2], [2, 2], [2, 2], [2, 2], [2, 2], [2, 2]], 'n_blocks_per_stage': [1, 3, 4, 6, 6, 6, 6, 6], 'n_conv_per_stage_decoder': [1, 1, 1, 1, 1, 1, 1], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm2d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': True}, '3d_lowres': {'data_identifier': 'nnUNetResEncUNetLPlans_3d_lowres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': [224, 256, 224], 'median_image_size_in_voxels': [349, 417, 349], 'spacing': [1.044035686906972, 0.7342668567257824, 1.044035686906972], 'normalization_schemes': ['CTNormalization'], 'use_mask_for_norm': [False], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.ResidualEncoderUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 320, 320], 'conv_op': 'torch.nn.modules.conv.Conv3d', 'kernel_sizes': [[3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3]], 'strides': [[1, 1, 1], [2, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2]], 'n_blocks_per_stage': [1, 3, 4, 6, 6, 6], 'n_conv_per_stage_decoder': [1, 1, 1, 1, 1], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm3d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': False, 'next_stage': '3d_cascade_fullres'}, '3d_fullres': {'data_identifier': 'nnUNetPlans_3d_fullres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': [224, 256, 224], 'median_image_size_in_voxels': [512.0, 613.0, 513.0], 'spacing': [0.7109375, 0.5, 0.7109375], 'normalization_schemes': ['CTNormalization'], 'use_mask_for_norm': [False], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.ResidualEncoderUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 320, 320], 'conv_op': 'torch.nn.modules.conv.Conv3d', 'kernel_sizes': [[3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3]], 'strides': [[1, 1, 1], [2, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2]], 'n_blocks_per_stage': [1, 3, 4, 6, 6, 6], 'n_conv_per_stage_decoder': [1, 1, 1, 1, 1], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm3d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': True}, '3d_cascade_fullres': {'inherits_from': '3d_fullres', 'previous_stage': '3d_lowres'}}, 'experiment_planner_used': 'nnUNetPlannerResEncL', 'label_manager': 'LabelManager', 'foreground_intensity_properties_per_channel': {'0': {'max': 1000.0, 'mean': 21.503620147705078, 'median': 63.0, 'min': -1000.0, 'percentile_00_5': -1000.0, 'percentile_99_5': 361.0, 'std': 215.7941131591797}}}, 'configuration': '2d', 'fold': 'all', 'dataset_json': {'name': 'JHH-Train-test', 'description': '3151 cases for training; 1958 cases for testing', 'reference': 'ScaleMAI', 'licence': 'CC-BY-SA 4.0', 'relase': '1.0 10/28/2024', 'tensorImageSize': '3D', 'labels': {'background': 0, 'aorta': 1, 'adrenal_gland_left': 2, 'adrenal_gland_right': 3, 'common_bile_duct': 4, 'celiac_aa': 5, 'colon': 6, 'duodenum': 7, 'gall_bladder': 8, 'postcava': 9, 'kidney_left': 10, 'kidney_right': 11, 'liver': 12, 'pancreas': 13, 'pancreatic_duct': 14, 'superior_mesenteric_artery': 15, 'intestine': 16, 'spleen': 17, 'stomach': 18, 'veins': 19, 'renal_vein_left': 20, 'renal_vein_right': 21, 'cbd_stent': 22, 'pancreatic_pdac': 23, 'pancreatic_cyst': 24, 'pancreatic_pnet': 25}, 'numTraining': 3151, 'numTest': 1958, 'file_ending': '.nii.gz', 'channel_names': {'0': 'CT'}}, 'unpack_dataset': True, 'device': device(type='cuda')}",
36
- "network": "OptimizedModule",
37
- "num_epochs": "1000",
38
- "num_input_channels": "1",
39
- "num_iterations_per_epoch": "250",
40
- "num_val_iterations_per_epoch": "50",
41
- "optimizer": "SGD (\nParameter Group 0\n dampening: 0\n differentiable: False\n foreach: None\n fused: None\n initial_lr: 0.01\n lr: 0.003897412779133726\n maximize: False\n momentum: 0.99\n nesterov: True\n weight_decay: 3e-05\n)",
42
- "output_folder": "/mnt/data/tlin67/nnUNet/nnUNet_results/Dataset808_AbdomenAtlasF/nnUNetTrainer__nnUNetResEncUNetLPlans__2d/fold_all",
43
- "output_folder_base": "/mnt/data/tlin67/nnUNet/nnUNet_results/Dataset808_AbdomenAtlasF/nnUNetTrainer__nnUNetResEncUNetLPlans__2d",
44
- "oversample_foreground_percent": "0.33",
45
- "plans_manager": "{'dataset_name': 'Dataset808_AbdomenAtlasF', 'plans_name': 'nnUNetResEncUNetLPlans', 'original_median_spacing_after_transp': [0.7109375, 0.5, 0.7109375], 'original_median_shape_after_transp': [512, 608, 512], 'image_reader_writer': 'SimpleITKIO', 'transpose_forward': [1, 0, 2], 'transpose_backward': [1, 0, 2], 'configurations': {'2d': {'data_identifier': 'nnUNetPlans_2d', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 43, 'patch_size': [640, 640], 'median_image_size_in_voxels': [613.0, 513.0], 'spacing': [0.5, 0.7109375], 'normalization_schemes': ['CTNormalization'], 'use_mask_for_norm': [False], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.ResidualEncoderUNet', 'arch_kwargs': {'n_stages': 8, 'features_per_stage': [32, 64, 128, 256, 512, 512, 512, 512], 'conv_op': 'torch.nn.modules.conv.Conv2d', 'kernel_sizes': [[3, 3], [3, 3], [3, 3], [3, 3], [3, 3], [3, 3], [3, 3], [3, 3]], 'strides': [[1, 1], [2, 2], [2, 2], [2, 2], [2, 2], [2, 2], [2, 2], [2, 2]], 'n_blocks_per_stage': [1, 3, 4, 6, 6, 6, 6, 6], 'n_conv_per_stage_decoder': [1, 1, 1, 1, 1, 1, 1], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm2d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': True}, '3d_lowres': 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