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{
"imports": [
"$import glob",
"$import os",
"$import skimage"
],
"bundle_root": "$os.getcwd()",
"ckpt_dir_stage0": "$os.path.join(@bundle_root, 'models', 'stage0')",
"ckpt_dir_stage1": "$os.path.join(@bundle_root, 'models')",
"ckpt_path_stage0": "$os.path.join(@ckpt_dir_stage0, 'model.pt')",
"output_dir": "$os.path.join(@bundle_root, 'eval')",
"dataset_dir": "/workspace/Data/Pathology/CoNSeP/Prepared/",
"train_images": "$list(sorted(glob.glob(@dataset_dir + '/Train/*image.npy')))",
"val_images": "$list(sorted(glob.glob(@dataset_dir + '/Test/*image.npy')))",
"train_inst_map": "$list(sorted(glob.glob(@dataset_dir + '/Train/*inst_map.npy')))",
"val_inst_map": "$list(sorted(glob.glob(@dataset_dir + '/Test/*inst_map.npy')))",
"train_type_map": "$list(sorted(glob.glob(@dataset_dir + '/Train/*type_map.npy')))",
"val_type_map": "$list(sorted(glob.glob(@dataset_dir + '/Test/*type_map.npy')))",
"device": "$torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')",
"stage": 0,
"epochs": 50,
"val_interval": 1,
"learning_rate": 0.0001,
"amp": true,
"hovernet_mode": "fast",
"patch_size": 256,
"out_size": 164,
"ckpt_dir": "$@ckpt_dir_stage0 if @stage == 0 else @ckpt_dir_stage1",
"network_def": {
"_target_": "HoVerNet",
"mode": "@hovernet_mode",
"in_channels": 3,
"out_classes": 5,
"adapt_standard_resnet": true,
"pretrained_url": "$None",
"freeze_encoder": true
},
"network": "$@network_def.to(@device)",
"loss": {
"_target_": "HoVerNetLoss",
"lambda_hv_mse": 1.0
},
"optimizer": {
"_target_": "torch.optim.Adam",
"params": "$filter(lambda p: p.requires_grad, @network.parameters())",
"lr": "@learning_rate",
"weight_decay": 1e-05
},
"lr_scheduler": {
"_target_": "torch.optim.lr_scheduler.StepLR",
"optimizer": "@optimizer",
"step_size": 25
},
"train": {
"preprocessing_transforms": [
{
"_target_": "LoadImaged",
"keys": [
"image",
"label_inst",
"label_type"
]
},
{
"_target_": "EnsureChannelFirstd",
"keys": [
"image",
"label_inst",
"label_type"
],
"channel_dim": -1
},
{
"_target_": "Lambdad",
"keys": "label_inst",
"func": "$lambda x: skimage.measure.label(x)"
},
{
"_target_": "RandAffined",
"keys": [
"image",
"label_inst",
"label_type"
],
"prob": 1.0,
"rotate_range": [
"$np.pi"
],
"scale_range": [
[
-0.2,
0.2
],
[
-0.2,
0.2
]
],
"shear_range": [
[
-0.05,
0.05
],
[
-0.05,
0.05
]
],
"translate_range": [
[
-6,
6
],
[
-6,
6
]
],
"padding_mode": "zeros",
"mode": "nearest"
},
{
"_target_": "CenterSpatialCropd",
"keys": [
"image"
],
"roi_size": [
"@patch_size",
"@patch_size"
]
},
{
"_target_": "RandFlipd",
"keys": [
"image",
"label_inst",
"label_type"
],
"prob": 0.5,
"spatial_axis": 0
},
{
"_target_": "RandFlipd",
"keys": [
"image",
"label_inst",
"label_type"
],
"prob": 0.5,
"spatial_axis": 1
},
{
"_target_": "OneOf",
"transforms": [
{
"_target_": "RandGaussianSmoothd",
"keys": [
"image"
],
"sigma_x": [
0.1,
1.1
],
"sigma_y": [
0.1,
1.1
],
"prob": 1.0
},
{
"_target_": "MedianSmoothd",
"keys": [
"image"
],
"radius": 1
},
{
"_target_": "RandGaussianNoised",
"keys": [
"image"
],
"std": 0.05,
"prob": 1.0
}
]
},
{
"_target_": "CastToTyped",
"keys": "image",
"dtype": "$np.uint8"
},
{
"_target_": "TorchVisiond",
"keys": "image",
"name": "ColorJitter",
"brightness": [
0.9,
1.0
],
"contrast": [
0.95,
1.1
],
"saturation": [
0.8,
1.2
],
"hue": [
-0.04,
0.04
]
},
{
"_target_": "AsDiscreted",
"keys": "label_type",
"to_onehot": 5
},
{
"_target_": "ScaleIntensityRanged",
"keys": "image",
"a_min": 0.0,
"a_max": 255.0,
"b_min": 0.0,
"b_max": 1.0,
"clip": true
},
{
"_target_": "CastToTyped",
"keys": "label_inst",
"dtype": "$torch.int"
},
{
"_target_": "ComputeHoVerMapsd",
"keys": "label_inst"
},
{
"_target_": "Lambdad",
"keys": "label_inst",
"func": "$lambda x: x > 0",
"overwrite": "label"
},
{
"_target_": "CenterSpatialCropd",
"keys": [
"label",
"hover_label_inst",
"label_inst",
"label_type"
],
"roi_size": [
"@out_size",
"@out_size"
]
},
{
"_target_": "AsDiscreted",
"keys": "label",
"to_onehot": 2
},
{
"_target_": "CastToTyped",
"keys": [
"image",
"label_inst",
"label_type"
],
"dtype": "$torch.float32"
}
],
"preprocessing": {
"_target_": "Compose",
"transforms": "$@train#preprocessing_transforms"
},
"dataset": {
"_target_": "Dataset",
"data": "$[{'image': i, 'label_inst': j, 'label_type': k} for i, j, k in zip(@train_images, @train_inst_map, @train_type_map)]",
"transform": "@train#preprocessing"
},
"dataloader": {
"_target_": "DataLoader",
"dataset": "@train#dataset",
"batch_size": 16,
"shuffle": true,
"num_workers": 4
},
"inferer": {
"_target_": "SimpleInferer"
},
"postprocessing_np": {
"_target_": "Compose",
"transforms": [
{
"_target_": "Activationsd",
"keys": "nucleus_prediction",
"softmax": true
},
{
"_target_": "AsDiscreted",
"keys": "nucleus_prediction",
"argmax": true
}
]
},
"postprocessing": {
"_target_": "Lambdad",
"keys": "pred",
"func": "$@train#postprocessing_np"
},
"handlers": [
{
"_target_": "LrScheduleHandler",
"lr_scheduler": "@lr_scheduler",
"print_lr": true
},
{
"_target_": "ValidationHandler",
"validator": "@validate#evaluator",
"epoch_level": true,
"interval": "@val_interval"
},
{
"_target_": "CheckpointSaver",
"save_dir": "@ckpt_dir",
"save_dict": {
"model": "@network"
},
"save_interval": 10,
"epoch_level": true,
"save_final": true,
"final_filename": "model.pt"
},
{
"_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)"
}
],
"extra_handlers": [
{
"_target_": "CheckpointLoader",
"load_path": "$os.path.join(@ckpt_dir_stage0, 'model.pt')",
"load_dict": {
"model": "@network"
}
}
],
"train_handlers": "$@train#extra_handlers + @train#handlers if @stage==1 else @train#handlers",
"key_metric": {
"train_mean_dice": {
"_target_": "MeanDice",
"include_background": false,
"output_transform": "$monai.apps.pathology.handlers.utils.from_engine_hovernet(keys=['pred', 'label'], nested_key='nucleus_prediction')"
}
},
"trainer": {
"_target_": "SupervisedTrainer",
"max_epochs": "@epochs",
"device": "@device",
"train_data_loader": "@train#dataloader",
"prepare_batch": "$monai.apps.pathology.engines.utils.PrepareBatchHoVerNet(extra_keys=['label_type', 'hover_label_inst'])",
"network": "@network",
"loss_function": "@loss",
"optimizer": "@optimizer",
"inferer": "@train#inferer",
"postprocessing": "@train#postprocessing",
"key_train_metric": "@train#key_metric",
"train_handlers": "@train#train_handlers",
"amp": "@amp"
}
},
"validate": {
"preprocessing_transforms": [
{
"_target_": "LoadImaged",
"keys": [
"image",
"label_inst",
"label_type"
]
},
{
"_target_": "EnsureChannelFirstd",
"keys": [
"image",
"label_inst",
"label_type"
],
"channel_dim": -1
},
{
"_target_": "Lambdad",
"keys": "label_inst",
"func": "$lambda x: skimage.measure.label(x)"
},
{
"_target_": "CastToTyped",
"keys": [
"image",
"label_inst"
],
"dtype": "$torch.int"
},
{
"_target_": "CenterSpatialCropd",
"keys": [
"image"
],
"roi_size": [
"@patch_size",
"@patch_size"
]
},
{
"_target_": "ScaleIntensityRanged",
"keys": "image",
"a_min": 0.0,
"a_max": 255.0,
"b_min": 0.0,
"b_max": 1.0,
"clip": true
},
{
"_target_": "ComputeHoVerMapsd",
"keys": "label_inst"
},
{
"_target_": "Lambdad",
"keys": "label_inst",
"func": "$lambda x: x > 0",
"overwrite": "label"
},
{
"_target_": "CenterSpatialCropd",
"keys": [
"label",
"hover_label_inst",
"label_inst",
"label_type"
],
"roi_size": [
"@out_size",
"@out_size"
]
},
{
"_target_": "CastToTyped",
"keys": [
"image",
"label_inst",
"label_type"
],
"dtype": "$torch.float32"
}
],
"preprocessing": {
"_target_": "Compose",
"transforms": "$@validate#preprocessing_transforms"
},
"dataset": {
"_target_": "Dataset",
"data": "$[{'image': i, 'label_inst': j, 'label_type': k} for i, j, k in zip(@val_images, @val_inst_map, @val_type_map)]",
"transform": "@validate#preprocessing"
},
"dataloader": {
"_target_": "DataLoader",
"dataset": "@validate#dataset",
"batch_size": 16,
"shuffle": false,
"num_workers": 4
},
"inferer": {
"_target_": "SimpleInferer"
},
"postprocessing": "$@train#postprocessing",
"handlers": [
{
"_target_": "StatsHandler",
"iteration_log": false
},
{
"_target_": "TensorBoardStatsHandler",
"log_dir": "@output_dir",
"iteration_log": false
},
{
"_target_": "CheckpointSaver",
"save_dir": "@ckpt_dir",
"save_dict": {
"model": "@network"
},
"save_key_metric": true
}
],
"key_metric": {
"val_mean_dice": {
"_target_": "MeanDice",
"include_background": false,
"output_transform": "$monai.apps.pathology.handlers.utils.from_engine_hovernet(keys=['pred', 'label'], nested_key='nucleus_prediction')"
}
},
"evaluator": {
"_target_": "SupervisedEvaluator",
"device": "@device",
"val_data_loader": "@validate#dataloader",
"prepare_batch": "$monai.apps.pathology.engines.utils.PrepareBatchHoVerNet(extra_keys=['label_type', 'hover_label_inst'])",
"network": "@network",
"inferer": "@validate#inferer",
"postprocessing": "@validate#postprocessing",
"key_val_metric": "@validate#key_metric",
"val_handlers": "@validate#handlers",
"amp": "@amp"
}
},
"training": [
"$monai.utils.set_determinism(seed=321)",
"$setattr(torch.backends.cudnn, 'benchmark', True)",
"$@train#trainer.run()"
]
}
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