| 8 | import numpy as np |
| 9 | |
| 10 | def nms(dets, thresh): |
| 11 | x1 = dets[:, 0] |
| 12 | y1 = dets[:, 1] |
| 13 | x2 = dets[:, 2] |
| 14 | y2 = dets[:, 3] |
| 15 | scores = dets[:, 4] |
| 16 | |
| 17 | areas = (x2 - x1 + 1) * (y2 - y1 + 1) |
| 18 | order = scores.argsort()[::-1] |
| 19 | |
| 20 | keep = [] |
| 21 | while order.size > 0: |
| 22 | i = order[0] |
| 23 | keep.append(i) |
| 24 | xx1 = np.maximum(x1[i], x1[order[1:]]) |
| 25 | yy1 = np.maximum(y1[i], y1[order[1:]]) |
| 26 | xx2 = np.minimum(x2[i], x2[order[1:]]) |
| 27 | yy2 = np.minimum(y2[i], y2[order[1:]]) |
| 28 | |
| 29 | w = np.maximum(0.0, xx2 - xx1 + 1) |
| 30 | h = np.maximum(0.0, yy2 - yy1 + 1) |
| 31 | inter = w * h |
| 32 | ovr = inter / (areas[i] + areas[order[1:]] - inter) |
| 33 | |
| 34 | inds = np.where(ovr <= thresh)[0] |
| 35 | order = order[inds + 1] |
| 36 | |
| 37 | return keep |