monai
medical
katielink's picture
unify naming
710f62b
{
"imports": [
"$import pandas as pd",
"$import os",
"$import ignite"
],
"bundle_root": "/wokspace/model-zoo/models/prostate_mri_anatomy",
"ckpt_dir": "$@bundle_root + '/models'",
"output_dir": "$@bundle_root + '/eval'",
"dataset_dir": "/workspace/data/prostate158/prostate158_train/",
"images": "$list(@dataset_dir + pd.read_csv(@dataset_dir + 'train.csv').t2)",
"labels": "$list(@dataset_dir + pd.read_csv(@dataset_dir + 'train.csv').t2_anatomy_reader1)",
"val_images": "$list(@dataset_dir + pd.read_csv(@dataset_dir + 'valid.csv').t2)",
"val_labels": "$list(@dataset_dir + pd.read_csv(@dataset_dir + 'valid.csv').t2_anatomy_reader1)",
"val_interval": 5,
"device": "$torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')",
"network_def": {
"_target_": "UNet",
"spatial_dims": 3,
"in_channels": 1,
"out_channels": 3,
"channels": [
16,
32,
64,
128,
256,
512
],
"strides": [
2,
2,
2,
2,
2
],
"num_res_units": 4,
"norm": "batch",
"act": "prelu",
"dropout": 0.15
},
"network": "$@network_def.to(@device)",
"loss": {
"_target_": "DiceFocalLoss",
"to_onehot_y": true,
"softmax": true,
"include_background": false
},
"optimizer": {
"_target_": "Novograd",
"params": "$@network.parameters()",
"lr": 0.001,
"amsgrad": true,
"weight_decay": 0.01
},
"train": {
"deterministic_transforms": [
{
"_target_": "LoadImaged",
"keys": [
"image",
"label"
]
},
{
"_target_": "EnsureChannelFirstd",
"keys": [
"image",
"label"
]
},
{
"_target_": "Orientationd",
"keys": [
"image",
"label"
],
"axcodes": "RAS"
},
{
"_target_": "Spacingd",
"keys": [
"image",
"label"
],
"pixdim": [
0.5,
0.5,
0.5
],
"mode": [
"bilinear",
"nearest"
]
},
{
"_target_": "ScaleIntensityd",
"keys": "image",
"minv": 0,
"maxv": 1
},
{
"_target_": "NormalizeIntensityd",
"keys": "image"
},
{
"_target_": "EnsureTyped",
"keys": [
"image",
"label"
]
}
],
"random_transforms": [
{
"_target_": "RandAdjustContrastd",
"keys": "image",
"prob": 0.15,
"gamma": 2.0
},
{
"_target_": "RandGaussianNoised",
"keys": "image",
"prob": 0.15,
"mean": 0.1,
"std": 0.25
},
{
"_target_": "RandAffined",
"keys": [
"image",
"label"
],
"prob": 0.15,
"rotate_range": 5,
"shear_range": 0.5,
"translate_range": 25
},
{
"_target_": "RandBiasFieldd",
"keys": "image",
"prob": 0.15,
"coeff_range": [
0.0,
0.01
],
"degree": 10
},
{
"_target_": "Rand3DElasticd",
"keys": [
"image",
"label"
],
"prob": 0.15,
"magnitude_range": [
0.5,
1.5
],
"rotate_range": 5,
"shear_range": 0.5,
"sigma_range": [
0.5,
1.5
],
"translate_range": 25
},
{
"_target_": "RandZoomd",
"keys": [
"image",
"label"
],
"prob": 0.15,
"max": 1.1,
"min": 0.9
},
{
"_target_": "RandCropByPosNegLabeld",
"keys": [
"image",
"label"
],
"label_key": "label",
"spatial_size": [
96,
96,
96
],
"pos": 1,
"neg": 1,
"num_samples": 4,
"image_key": "image",
"image_threshold": 0
},
{
"_target_": "RandShiftIntensityd",
"keys": "image",
"prob": 0.15,
"offsets": 0.2
}
],
"preprocessing": {
"_target_": "Compose",
"transforms": "$@train#deterministic_transforms + @train#random_transforms"
},
"dataset": {
"_target_": "PersistentDataset",
"data": "$[{'image': i, 'label': l} for i, l in zip(@images, @labels)]",
"transform": "@train#preprocessing",
"cache_dir": "$@bundle_root + '/cache'"
},
"dataloader": {
"_target_": "DataLoader",
"dataset": "@train#dataset",
"batch_size": 2,
"shuffle": true,
"num_workers": 4
},
"inferer": {
"_target_": "SimpleInferer"
},
"postprocessing": {
"_target_": "Compose",
"transforms": [
{
"_target_": "Activationsd",
"keys": "pred",
"softmax": true
},
{
"_target_": "AsDiscreted",
"keys": [
"pred",
"label"
],
"argmax": [
true,
false
],
"to_onehot": 3
}
]
},
"handlers": [
{
"_target_": "ValidationHandler",
"validator": "@validate#evaluator",
"epoch_level": true,
"interval": "@val_interval"
},
{
"_target_": "StatsHandler",
"tag_name": "train_loss",
"output_transform": "$monai.handlers.from_engine(['loss'], first=True)"
},
{
"_target_": "TensorBoardStatsHandler",
"log_dir": "@output_dir",
"tag_name": "train_loss",
"output_transform": "$monai.handlers.from_engine(['loss'], first=True)"
}
],
"key_metric": {
"train_dice": {
"_target_": "MeanDice",
"include_background": false,
"output_transform": "$monai.handlers.from_engine(['pred', 'label'])"
}
},
"trainer": {
"_target_": "SupervisedTrainer",
"max_epochs": 100,
"device": "@device",
"train_data_loader": "@train#dataloader",
"network": "@network",
"loss_function": "@loss",
"optimizer": "@optimizer",
"inferer": "@train#inferer",
"postprocessing": "@train#postprocessing",
"key_train_metric": "@train#key_metric",
"train_handlers": "@train#handlers",
"amp": true
}
},
"validate": {
"preprocessing": {
"_target_": "Compose",
"transforms": "%train#deterministic_transforms"
},
"dataset": {
"_target_": "PersistentDataset",
"data": "$[{'image': i, 'label': l} for i, l in zip(@val_images, @val_labels)]",
"transform": "@validate#preprocessing",
"cache_dir": "$@bundle_root + '/cache'"
},
"dataloader": {
"_target_": "DataLoader",
"dataset": "@validate#dataset",
"batch_size": 1,
"shuffle": false,
"num_workers": 4
},
"inferer": {
"_target_": "SlidingWindowInferer",
"roi_size": [
96,
96,
96
],
"sw_batch_size": 16,
"overlap": 0.5
},
"postprocessing": "%train#postprocessing",
"handlers": [
{
"_target_": "StatsHandler",
"iteration_log": false
},
{
"_target_": "TensorBoardStatsHandler",
"log_dir": "@output_dir",
"iteration_log": false
},
{
"_target_": "CheckpointSaver",
"save_dir": "@ckpt_dir",
"save_dict": {
"model": "@network"
},
"save_key_metric": true,
"key_metric_filename": "model.pt"
}
],
"key_metric": {
"val_mean_dice": {
"_target_": "MeanDice",
"include_background": false,
"output_transform": "$monai.handlers.from_engine(['pred', 'label'])"
}
},
"additional_metrics": {
"val_hausdorff_distance": {
"_target_": "HausdorffDistance",
"include_background": false,
"reduction": "mean",
"output_transform": "$monai.handlers.from_engine(['pred', 'label'])"
},
"val_surface_distance": {
"_target_": "SurfaceDistance",
"include_background": false,
"reduction": "mean",
"output_transform": "$monai.handlers.from_engine(['pred', 'label'])"
}
},
"evaluator": {
"_target_": "SupervisedEvaluator",
"device": "@device",
"val_data_loader": "@validate#dataloader",
"network": "@network",
"inferer": "@validate#inferer",
"postprocessing": "@validate#postprocessing",
"key_val_metric": "@validate#key_metric",
"additional_metrics": "@validate#additional_metrics",
"val_handlers": "@validate#handlers",
"amp": true
}
},
"training": [
"$monai.utils.set_determinism(seed=42)",
"$setattr(torch.backends.cudnn, 'benchmark', True)",
"$@train#trainer.run()"
]
}