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‎models/swin_unetr_btcv_segmentation/configs/evaluate.json‎

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{
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"validate#postprocessing":{
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"validate#postprocessing": {
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"_target_": "Compose",
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"transforms": [
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{
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},
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{
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"_target_": "Invertd",
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"keys": ["pred", "label"],
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"keys": [
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"pred",
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"label"
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],
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"transform": "@validate#preprocessing",
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"orig_keys": "image",
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"meta_key_postfix": "meta_dict",
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"nearest_interp": [false, true],
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"nearest_interp": [
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false,
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true
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],
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"to_tensor": true
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},
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{
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"_target_": "AsDiscreted",
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"keys": ["pred", "label"],
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"argmax": [true, false],
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"_target_": "AsDiscreted",
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"keys": [
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"pred",
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"label"
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],
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"argmax": [
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true,
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false
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],
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"to_onehot": 14
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},
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{
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"_target_": "SaveImaged",
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"_target_": "SaveImaged",
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"keys": "pred",
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"meta_keys": "pred_meta_dict",
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"output_dir": "@output_dir",
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{
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"_target_": "CheckpointLoader",
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"load_path": "$@ckpt_dir + '/model.pt'",
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"load_dict": {"model": "@network"}
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"load_dict": {
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"model": "@network"
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}
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},
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{
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"_target_": "StatsHandler",
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{
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"_target_": "MetricsSaver",
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"save_dir": "@output_dir",
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"metrics": ["val_mean_dice", "val_acc"],
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"metric_details": ["val_mean_dice"],
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"metrics": [
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"val_mean_dice",
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"val_acc"
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],
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"metric_details": [
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"val_mean_dice"
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],
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"batch_transform": "$monai.handlers.from_engine(['image_meta_dict'])",
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"summary_ops": "*"
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}
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],
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],
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"evaluating": [
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"$setattr(torch.backends.cudnn, 'benchmark', True)",
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"$@validate#evaluator.run()"

‎models/swin_unetr_btcv_segmentation/configs/inference.json‎

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{
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"_target_": "Spacingd",
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"keys": "image",
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"pixdim": [1.5, 1.5, 2.0],
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"pixdim": [
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1.5,
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1.5,
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2.0
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],
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"mode": "bilinear"
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},
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{
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},
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"inferer": {
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"_target_": "SlidingWindowInferer",
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"roi_size": [96, 96, 96],
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"roi_size": [
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],
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"sw_batch_size": 4,
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"overlap": 0.5
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},
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{
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"_target_": "CheckpointLoader",
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"load_path": "$@bundle_root + '/models/model.pt'",
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"load_dict": {"model": "@network"}
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"load_dict": {
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"model": "@network"
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}
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},
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{
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"_target_": "StatsHandler",

‎models/swin_unetr_btcv_segmentation/configs/multi_gpu_train.json‎

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"network": {
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"_target_": "torch.nn.parallel.DistributedDataParallel",
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"module": "$@network_def.to(@device)",
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"device_ids": ["@device"]
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"device_ids": [
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"@device"
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]
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},
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"train#sampler": {
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"_target_": "DistributedSampler",

‎models/swin_unetr_btcv_segmentation/configs/train.json‎

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"optimizer": {
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"_target_": "torch.optim.Adam",
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"params": "[email protected]()",
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"lr": 2e-4
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"lr": 0.0002
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},
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"train": {
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"deterministic_transforms": [
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{
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"_target_": "LoadImaged",
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"keys": ["image", "label"]
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"keys": [
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"image",
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"label"
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]
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},
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{
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"_target_": "EnsureChannelFirstd",
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"keys": ["image", "label"]
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"keys": [
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"image",
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"label"
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]
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},
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{
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"_target_": "Orientationd",
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"keys": ["image", "label"],
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"keys": [
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"image",
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"label"
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],
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"axcodes": "RAS"
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},
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{
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"_target_": "Spacingd",
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"keys": ["image", "label"],
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"pixdim": [1.5, 1.5, 2.0],
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"mode": ["bilinear", "nearest"]
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"keys": [
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"image",
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"label"
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],
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"pixdim": [
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1.5,
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1.5,
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2.0
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],
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"mode": [
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"bilinear",
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"nearest"
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]
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},
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{
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"_target_": "ScaleIntensityRanged",
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},
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{
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"_target_": "EnsureTyped",
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"keys": ["image", "label"]
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"keys": [
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"image",
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"label"
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]
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}
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],
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"random_transforms": [
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{
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"_target_": "RandCropByPosNegLabeld",
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"keys": ["image", "label"],
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"keys": [
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"image",
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"label"
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],
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"label_key": "label",
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"spatial_size": [96, 96, 96],
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"spatial_size": [
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],
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"pos": 1,
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"neg": 1,
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"num_samples": 4,
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},
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{
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"_target_": "RandFlipd",
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"keys": ["image", "label"],
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"spatial_axis": [0],
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"prob": 0.10
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"keys": [
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"image",
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"label"
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],
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"spatial_axis": [
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],
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"prob": 0.1
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},
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{
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"_target_": "RandFlipd",
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"keys": ["image", "label"],
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"spatial_axis": [1],
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"prob": 0.10
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"keys": [
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"image",
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"label"
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],
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"spatial_axis": [
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],
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"prob": 0.1
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},
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{
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"_target_": "RandFlipd",
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"keys": ["image", "label"],
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"spatial_axis": [2],
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"prob": 0.10
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"keys": [
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"image",
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"label"
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],
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"spatial_axis": [
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],
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"prob": 0.1
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},
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{
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"_target_": "RandRotate90d",
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"keys": ["image", "label"],
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"keys": [
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"image",
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"label"
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],
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"max_k": 3,
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"prob": 0.10
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"prob": 0.1
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},
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{
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"_target_": "RandShiftIntensityd",
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},
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{
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"_target_": "AsDiscreted",
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"keys": ["pred", "label"],
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"argmax": [true, false],
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"keys": [
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"pred",
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"label"
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],
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"argmax": [
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true,
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false
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],
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"to_onehot": 14
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}
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]
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},
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"inferer": {
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"_target_": "SlidingWindowInferer",
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"roi_size": [96, 96, 96],
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"roi_size": [
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],
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"sw_batch_size": 4,
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"overlap": 0.5
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},
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{
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"_target_": "CheckpointSaver",
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"save_dir": "@ckpt_dir",
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"save_dict": {"model": "@network"},
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"save_dict": {
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"model": "@network"
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},
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"save_key_metric": true,
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"key_metric_filename": "model.pt"
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}

‎models/swin_unetr_btcv_segmentation/docs/README.md‎

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- Target: Multi-organs
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- Task: Segmentation
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- Modality: CT
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- Modality: CT
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- Size: 30 3D volumes (24 Training + 6 Testing)
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## Training configuration

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