| # Evaluation |
|
|
| `evaluate.py` evaluates a fine-tuned checkpoint against labelled test images. |
| Use `inference.py` instead for images without ground truth. |
|
|
| ## Segmentation |
|
|
| ```bash |
| python evaluate.py \ |
| --config configs/aff_base_finetune_512_fpw.yaml \ |
| --checkpoint AFFMAE_BASE_FT_512 |
| ``` |
|
|
| The paper reports mean Intersection over Union (mIoU) and the filtration-slits |
| class IoU. Results are summarized as mean ± standard deviation across four |
| random seeds. |
|
|
| ## FPW geometry |
|
|
| ```bash |
| python evaluate.py \ |
| --config configs/aff_base_finetune_512_fpw.yaml \ |
| --checkpoint AFFMAE_BASE_FT_512 \ |
| --mode fpw --eval-grid-size 1024 \ |
| --out-json output/fpw.json |
| ``` |
|
|
| The geometry pass recovers connected PGBMI segments from the segmentation, |
| forms a one-pixel-wide ordered centerline for each segment, detects filtration |
| slits, and projects the slit locations onto that centerline. Arc length between |
| successive slit locations represents foot-process width. Predicted and |
| ground-truth segments are paired geometrically before their mean widths are |
| compared. FPW MAE: the mean per-image absolute pixel error |
| `|FPW_pred - FPW_GT|`, with distances scaled to a 1024×1024 reference grid. |
|
|
| ```bash |
| python evaluate.py --config configs/aff_base_finetune_512_fpw.yaml \ |
| --mode fpw --seeds 42,77,2026,31415 \ |
| --checkpoint 'output/fpw_seed{seed}/last_model.pth' |
| ``` |
|
|
| Use `--vis-dir output/fpw_geometry` to render matched PGBMI centerlines and slit |
| locations. |
