# vim: expandtab:ts=4:sw=4
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import numpy as np
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import cv2
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def non_max_suppression(boxes, max_bbox_overlap, scores=None):
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if len(boxes) == 0:
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return []
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boxes = boxes.astype(np.float)
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pick = []
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x1 = boxes[:, 0]
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y1 = boxes[:, 1]
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x2 = boxes[:, 2] + boxes[:, 0]
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y2 = boxes[:, 3] + boxes[:, 1]
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area = (x2 - x1 + 1) * (y2 - y1 + 1)
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if scores is not None:
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idxs = np.argsort(scores)
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else:
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idxs = np.argsort(y2)
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while len(idxs) > 0:
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last = len(idxs) - 1
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i = idxs[last]
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pick.append(i)
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xx1 = np.maximum(x1[i], x1[idxs[:last]])
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yy1 = np.maximum(y1[i], y1[idxs[:last]])
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xx2 = np.minimum(x2[i], x2[idxs[:last]])
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yy2 = np.minimum(y2[i], y2[idxs[:last]])
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w = np.maximum(0, xx2 - xx1 + 1)
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h = np.maximum(0, yy2 - yy1 + 1)
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overlap = (w * h) / area[idxs[:last]]
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idxs = np.delete(
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idxs, np.concatenate(
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([last], np.where(overlap > max_bbox_overlap)[0])))
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return pick
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