| # Default configuration for WireSegHR (segmentation-only) | |
| backbone: mit_b2 | |
| pretrained: true # Uses HF SegFormer weights if available | |
| coarse: | |
| train_size: 512 | |
| test_size: 1024 | |
| fine: | |
| patch_size: 512 | |
| overlap: 128 | |
| conditioning: | |
| cond_from: coarse_logits_1x1 | |
| cond_crop: patch # per published method (method_yq) | |
| minmax: | |
| enable: true | |
| kernel: 6 # fixed 6x6 luminance min/max | |
| label: | |
| coarse_downsample: maxpool | |
| inference: | |
| alpha: 0.01 | |
| prob_threshold: 0.5 # default inference threshold per paper tuning | |
| fine_patch_size: 1024 | |
| stitch: avg_logits | |
| eval: | |
| max_samples: 12 | |
| fine_batch: 16 | |
| optim: | |
| iters: 5000 | |
| batch_size: 4 | |
| lr: 6e-5 | |
| weight_decay: 0.01 | |
| schedule: poly | |
| power: 1.0 | |
| precision: bf16 # one of: fp32, fp16, bf16 | |
| # training housekeeping | |
| seed: 42 | |
| out_dir: runs/wireseghr | |
| eval_interval: 200 | |
| ckpt_interval: 400 | |
| resume: runs/wireseghr/ckpt_4800.pt # optional | |
| # dataset paths (placeholders) | |
| data: | |
| train_images: dataset/train/images | |
| train_masks: dataset/train/gts | |
| val_images: dataset/val/images | |
| val_masks: dataset/val/gts | |
| test_images: dataset/test/images | |
| test_masks: dataset/test/gts | |