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Runtime error
| defaults: | |
| - _self_ | |
| data: | |
| num_classes: 14 | |
| image_size: [512, 512] | |
| mean: [0.4810, 0.4810, 0.4810] #[0.4513, 0.4513, 0.4513] | |
| std: [0.2492, 0.2492, 0.2492] #[0.1879, 0.1879, 0.1879] | |
| background_cls_id: 0 | |
| split_ratio: 0.8 | |
| base_dir: 'E:\Seg\Test\medical_segmentation\Bitewing' | |
| mask_dir: "${data.base_dir}/newAnnotations/" | |
| original_dir: "${data.base_dir}/Images/" | |
| dataset_path: "${hydra:runtime.cwd}/Bitwening_dataset1" | |
| # Normalization settings | |
| normalization: | |
| always_apply: true | |
| # Image resize configuration | |
| resize: | |
| interpolation: "INTER_NEAREST" # CV2 interpolation method | |
| # Complete augmentation configuration with all parameters | |
| augmentation: | |
| # HorizontalFlip | |
| use_horizontal_flip: true | |
| horizontal_flip_prob: 0.5 | |
| # VerticalFlip | |
| use_vertical_flip: true | |
| vertical_flip_prob: 0.5 | |
| # ShiftScaleRotate | |
| use_shift_scale_rotate: true | |
| shift_scale_rotate_prob: 0.5 | |
| rotate_limit: 0.15 | |
| scale_limit: 0.12 | |
| shift_limit: 0.12 | |
| border_mode: 4 # cv2.BORDER_REFLECT_101 | |
| # RandomBrightnessContrast | |
| use_brightness_contrast: true | |
| brightness_contrast_prob: 0.5 | |
| brightness_limit: 0.2 | |
| contrast_limit: 0.2 | |
| # CoarseDropout | |
| use_coarse_dropout: true | |
| coarse_dropout: | |
| max_holes: 8 | |
| min_holes: 5 | |
| max_height: 25 | |
| max_width: 25 | |
| fill_value: 0 | |
| mask_fill_value: 0 | |
| prob: 0.5 | |
| training: | |
| batch_size: 10 | |
| num_epochs: 1 | |
| init_lr: 3e-4 | |
| optimizer_name: "AdamW" | |
| weight_decay: 0.1 | |
| use_scheduler: true | |
| scheduler: "MultiStepLR" | |
| model_name: "nvidia/segformer-b4-finetuned-ade-512-512" | |
| num_workers: 0 | |
| pin_memory: true | |
| drop_last: true | |
| shuffle_train: true | |
| shuffle_valid: false | |
| inference: | |
| batch_size: 10 | |
| num_batches: 3 | |
| wandb: | |
| project: "UM_medical_segmentation" | |
| log_model: true | |
| trainer: | |
| accelerator: "gpu" | |
| devices: "1" | |
| strategy: "auto" | |
| precision: "16-mixed" | |
| enable_model_summary: false | |
| id2color: | |
| 0: [0, 0, 0] # Black | |
| 1: [0, 0, 255] # Blue | |
| 2: [0, 255, 0] # Green | |
| 3: [255, 0, 0] # Red | |
| 4: [255, 255, 0] # Yellow | |
| 5: [255, 165, 0] # Orange | |
| 6: [128, 0, 128] # Purple | |
| 7: [0, 255, 255] # Cyan | |
| 8: [255, 20, 147] # Deep Pink | |
| 9: [75, 0, 130] # Indigo | |
| 10: [139, 69, 19] # Saddle Brown | |
| 11: [255, 192, 203] # Pink | |
| 12: [47, 79, 79] # Dark Slate Gray | |
| 13: [173, 255, 47] # Green Yellow | |
| 14: [0, 128, 128] # Teal | |
| experiment: | |
| name: "EXPERIMENT_1 bitewing dataset" # Descriptive name for the experiment | |
| description: "Testing on 14 classes dataset with no layers and just fine tuning the model " # What this experiment is testing | |
| goal: "to check the performance of the model on 100 epochs" # What you hope to achieve |