| { | |
| "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()" | |
| ] | |
| } | |