| { | |
| "imports": [ | |
| "$import glob", | |
| "$import os", | |
| "$import torch", | |
| "$import numpy as np" | |
| ], | |
| "bundle_root": "/workspace/bundle/endoscopic_tool_segmentation", | |
| "ckpt_dir": "$@bundle_root + '/models'", | |
| "output_dir": "$@bundle_root + '/eval'", | |
| "dataset_dir": "/workspace/data/endoscopic_tool_dataset", | |
| "images": "$list(sorted(glob.glob(os.path.join(@dataset_dir,'train', '*', '*[!seg].jpg'))))", | |
| "labels": "$[x.replace('.jpg', '_seg.jpg') for x in @images]", | |
| "val_images": "$list(sorted(glob.glob(os.path.join(@dataset_dir,'val', '*', '*[!seg].jpg'))))", | |
| "val_labels": "$[x.replace('.jpg', '_seg.jpg') for x in @val_images]", | |
| "val_interval": 1, | |
| "device": "$torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')", | |
| "network_def": { | |
| "_target_": "FlexibleUNet", | |
| "in_channels": 3, | |
| "out_channels": 2, | |
| "backbone": "efficientnet-b2", | |
| "spatial_dims": 2, | |
| "dropout": 0.5, | |
| "pretrained": true, | |
| "is_pad": false, | |
| "pre_conv": null | |
| }, | |
| "network": "$@network_def.to(@device)", | |
| "loss": { | |
| "_target_": "DiceLoss", | |
| "include_background": false, | |
| "to_onehot_y": true, | |
| "softmax": true, | |
| "jaccard": true | |
| }, | |
| "optimizer": { | |
| "_target_": "torch.optim.Adam", | |
| "params": "$@network.parameters()", | |
| "lr": 0.0001 | |
| }, | |
| "lr_scheduler": { | |
| "_target_": "torch.optim.lr_scheduler.CosineAnnealingWarmRestarts", | |
| "optimizer": "@optimizer", | |
| "T_0": 100, | |
| "T_mult": 1 | |
| }, | |
| "train": { | |
| "deterministic_transforms": [ | |
| { | |
| "_target_": "LoadImaged", | |
| "keys": [ | |
| "image", | |
| "label" | |
| ] | |
| }, | |
| { | |
| "_target_": "AsChannelFirstd", | |
| "keys": "image" | |
| }, | |
| { | |
| "_target_": "AddChanneld", | |
| "keys": "label" | |
| }, | |
| { | |
| "_target_": "Resized", | |
| "keys": [ | |
| "image", | |
| "label" | |
| ], | |
| "spatial_size": [ | |
| 736, | |
| 480 | |
| ], | |
| "mode": [ | |
| "bilinear", | |
| "nearest" | |
| ] | |
| }, | |
| { | |
| "_target_": "ScaleIntensityd", | |
| "keys": [ | |
| "image", | |
| "label" | |
| ] | |
| } | |
| ], | |
| "random_transforms": [ | |
| { | |
| "_target_": "RandRotated", | |
| "keys": [ | |
| "image", | |
| "label" | |
| ], | |
| "range_x": "$np.pi", | |
| "prob": 0.8, | |
| "mode": [ | |
| "bilinear", | |
| "nearest" | |
| ] | |
| }, | |
| { | |
| "_target_": "RandZoomd", | |
| "keys": [ | |
| "image", | |
| "label" | |
| ], | |
| "min_zoom": 0.8, | |
| "max_zoom": 1.2, | |
| "prob": 0.2, | |
| "mode": [ | |
| "bilinear", | |
| "nearest" | |
| ] | |
| } | |
| ], | |
| "preprocessing": { | |
| "_target_": "Compose", | |
| "transforms": "$@train#deterministic_transforms + @train#random_transforms" | |
| }, | |
| "dataset": { | |
| "_target_": "CacheDataset", | |
| "data": "$[{'image': i, 'label': l} for i, l in zip(@images, @labels)]", | |
| "transform": "@train#preprocessing", | |
| "cache_rate": 0.1, | |
| "num_workers": 4 | |
| }, | |
| "dataloader": { | |
| "_target_": "DataLoader", | |
| "dataset": "@train#dataset", | |
| "batch_size": 8, | |
| "shuffle": true, | |
| "num_workers": 4 | |
| }, | |
| "inferer": { | |
| "_target_": "SimpleInferer" | |
| }, | |
| "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)" | |
| }, | |
| { | |
| "_target_": "LrScheduleHandler", | |
| "lr_scheduler": "@lr_scheduler", | |
| "print_lr": true | |
| } | |
| ], | |
| "key_metric": { | |
| "train_iou": { | |
| "_target_": "MeanIoUHandler", | |
| "include_background": false, | |
| "reduction": "mean", | |
| "output_transform": "$monai.handlers.from_engine(['pred', 'label'])" | |
| } | |
| }, | |
| "postprocessing": { | |
| "_target_": "Compose", | |
| "transforms": [ | |
| { | |
| "_target_": "AsDiscreted", | |
| "argmax": [ | |
| true, | |
| false | |
| ], | |
| "to_onehot": [ | |
| 2, | |
| 2 | |
| ], | |
| "keys": [ | |
| "pred", | |
| "label" | |
| ] | |
| } | |
| ] | |
| }, | |
| "trainer": { | |
| "_target_": "SupervisedTrainer", | |
| "max_epochs": 100, | |
| "device": "@device", | |
| "train_data_loader": "@train#dataloader", | |
| "network": "@network", | |
| "loss_function": "@loss", | |
| "optimizer": "@optimizer", | |
| "inferer": "@train#inferer", | |
| "postprocessing": "@train#postprocessing", | |
| "key_train_metric": "@train#key_metric", | |
| "train_handlers": "@train#handlers" | |
| } | |
| }, | |
| "validate": { | |
| "preprocessing": { | |
| "_target_": "Compose", | |
| "transforms": "%train#deterministic_transforms" | |
| }, | |
| "dataset": { | |
| "_target_": "CacheDataset", | |
| "data": "$[{'image': i, 'label': l} for i, l in zip(@val_images, @val_labels)]", | |
| "transform": "@validate#preprocessing", | |
| "cache_rate": 0.1 | |
| }, | |
| "dataloader": { | |
| "_target_": "DataLoader", | |
| "dataset": "@validate#dataset", | |
| "batch_size": 8, | |
| "shuffle": false, | |
| "num_workers": 4 | |
| }, | |
| "inferer": { | |
| "_target_": "SimpleInferer" | |
| }, | |
| "postprocessing": { | |
| "_target_": "Compose", | |
| "transforms": "%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" | |
| } | |
| ], | |
| "additional_metrics": { | |
| "val_mean_dice": { | |
| "_target_": "MeanDice", | |
| "include_background": false, | |
| "reduction": "mean", | |
| "output_transform": "$monai.handlers.from_engine(['pred', 'label'])" | |
| } | |
| }, | |
| "key_metric": { | |
| "val_iou": { | |
| "_target_": "MeanIoUHandler", | |
| "include_background": false, | |
| "reduction": "mean", | |
| "output_transform": "$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" | |
| } | |
| }, | |
| "training": [ | |
| "$monai.utils.set_determinism(seed=0)", | |
| "$setattr(torch.backends.cudnn, 'benchmark', True)", | |
| "$@train#trainer.run()" | |
| ] | |
| } | |