{ "command": "train", "gpu_ids": [0], "path_output": "tumor_segmentation", "model_name": "seg_tumor_t2", "debugging": true, "object_detection_params": { "object_detection_path": null, "safety_factor": [1.1, 1.1, 1.0] }, "wandb": { "wandb_api_key": "", "project_name": "my_project", "group_name": "my_group", "run_name": "run-1", "log_grads_every": 100 }, "loader_parameters": { "path_data": ["/home/andreanne/Documents/dataset/toy_dataset"], "target_suffix": ["_seg-tumor"], "extensions": [".nii.gz"], "roi_params": { "suffix": null, "slice_filter_roi": null }, "contrast_params": { "training_validation": ["T2w"], "testing": ["T2w"], "balance": {} }, "slice_filter_params": { "filter_empty_mask": false, "filter_empty_input": true }, "slice_axis": "sagittal", "multichannel": false, "soft_gt": false }, "split_dataset": { "fname_split": null, "random_seed": 6, "split_method" : "participant_id", "data_testing": {"data_type": null, "data_value":[]}, "balance": null, "train_fraction": 0.6, "test_fraction": 0.2 }, "training_parameters": { "batch_size": 1, "loss": { "name": "DiceLoss" }, "training_time": { "num_epochs": 10, "early_stopping_patience": 50, "early_stopping_epsilon": 0.001 }, "scheduler": { "initial_lr": 0.001, "lr_scheduler": { "name": "CosineAnnealingLR", "base_lr": 1e-5, "max_lr": 1e-2 } }, "balance_samples": false, "mixup_alpha": null, "transfer_learning": { "retrain_model": null, "retrain_fraction": 1.0, "reset": true } }, "default_model": { "name": "Unet", "dropout_rate": 0.3, "bn_momentum": 0.9, "depth": 4 }, "Modified3DUNet": { "applied": true, "length_3D": [512, 256, 16], "stride_3D": [512, 256, 16], "attention": false, "n_filters": 8 }, "uncertainty": { "epistemic": false, "aleatoric": false, "n_it": 0 }, "postprocessing": { "remove_noise": {"thr": -1}, "binarize_prediction": {"thr": 0.5}, "uncertainty": {"thr": -1, "suffix": "_unc-vox.nii.gz"}, "remove_small": {"unit": "vox", "thr": 3} }, "evaluation_parameters": { "target_size": {"unit": "vox", "thr": [20, 100]}, "overlap": {"unit": "vox", "thr": 3} }, "transformation": { "Resample": { "hspace": 1, "wspace": 1, "dspace": 2 }, "CenterCrop": {"size": [512, 256, 16]}, "RandomAffine": { "degrees": 5, "scale": [0.1, 0.1, 0.1], "translate": [0.03, 0.03], "dataset_type": ["training"] }, "NormalizeInstance": {"applied_to": ["im"]} } }