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{
"imports": [
"$import glob",
"$import os",
"$import torch",
"$import numpy as np"
],
"bundle_root": ".",
"use_imagenet_pretrain": false,
"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": "$torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')",
"network_def": {
"_target_": "FlexibleUNet",
"in_channels": 3,
"out_channels": 2,
"backbone": "efficientnet-b2",
"spatial_dims": 2,
"dropout": 0.6,
"pretrained": "@use_imagenet_pretrain",
"is_pad": false,
"pre_conv": null
},
"network": "$@network_def.to(@device)",
"loss": {
"_target_": "DiceFocalLoss",
"include_background": false,
"to_onehot_y": true,
"softmax": true,
"jaccard": true
},
"optimizer": {
"_target_": "torch.optim.Adam",
"params": "$@network.parameters()",
"lr": 0.0001
},
"lr_scheduler": {
"_target_": "torch.optim.lr_scheduler.CosineAnnealingWarmRestarts",
"optimizer": "@optimizer",
"T_0": 100,
"T_mult": 1
},
"train": {
"deterministic_transforms": [
{
"_target_": "LoadImaged",
"keys": [
"image",
"label"
],
"image_only": false
},
{
"_target_": "EnsureChannelFirstd",
"keys": "image",
"channel_dim": -1
},
{
"_target_": "EnsureChannelFirstd",
"keys": "label",
"channel_dim": "no_channel"
},
{
"_target_": "Resized",
"keys": [
"image",
"label"
],
"spatial_size": [
736,
480
],
"mode": [
"bilinear",
"nearest"
]
},
{
"_target_": "ScaleIntensityd",
"keys": [
"image",
"label"
]
}
],
"random_transforms": [
{
"_target_": "RandRotated",
"keys": [
"image",
"label"
],
"range_x": "$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": 0.5,
"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": 1.0
},
"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"
}
},
"initialize": [
"$monai.utils.set_determinism(seed=123)"
],
"run": [
"$@train#trainer.run()"
]
}
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