| """Classical difference baseline — the floor every learned model must beat. |
| |
| Measured on the first 40 training pairs: recall 0.57, precision 0.015, F1 0.03. |
| """ |
| from __future__ import annotations |
|
|
| import cv2 |
| import numpy as np |
|
|
| from .preprocess import load_prepared |
|
|
|
|
| def baseline_pair(split: str, idx: int, diff_thr: float = 25.0, min_area: int = 12, |
| prep_root=None): |
| _, _, tn, pn = load_prepared(split, idx, prep_root) |
| diff = np.abs(pn.astype(np.float32) - tn.astype(np.float32)) |
| mask = (diff > diff_thr).astype(np.uint8) |
| mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, np.ones((3, 3), np.uint8)) |
| n, _, stats, _ = cv2.connectedComponentsWithStats(mask, 8) |
| boxes, scores = [], [] |
| for i in range(1, n): |
| x, y, w, h, area = stats[i] |
| if area < min_area: |
| continue |
| boxes.append([x, y, x + w, y + h]) |
| scores.append(min(1.0, area / 200.0)) |
| if not boxes: |
| return np.zeros((0, 4), np.float32), np.zeros(0, np.float32) |
| return np.asarray(boxes, np.float32), np.asarray(scores, np.float32) |
|
|
