-
Notifications
You must be signed in to change notification settings - Fork 1
/
nms.py
51 lines (43 loc) · 1.6 KB
/
nms.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
# --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick
# --------------------------------------------------------
'''
nms.py: CPU implementation of non maximal supression modified from Ross's code.
Authors : svp
Modified from https://github.com/rbgirshick/fast-rcnn/blob/master/lib/utils/nms.py
to accommodate a corner case which handles one box lying completely inside another.
'''
import numpy as np
def is_square(inter, areas):
truth_val = np.logical_not((np.logical_and((np.sqrt(areas) **2 == areas), (np.sqrt(inter) **2 == inter))))
return np.float32(truth_val)
def nms(dets, thresh):
x1 = dets[:, 0]
y1 = dets[:, 1]
x2 = dets[:, 2]
y2 = dets[:, 3]
scores = dets[:, 4]
areas = (x2 - x1 +1) * (y2 - y1 +1)
order = scores.argsort()[::-1]
keep = []
while order.size > 0:
i = order[0]
keep.append(i)
xx1 = np.maximum(x1[i], x1[order[1:]])
yy1 = np.maximum(y1[i], y1[order[1:]])
xx2 = np.minimum(x2[i], x2[order[1:]])
yy2 = np.minimum(y2[i], y2[order[1:]])
w = np.maximum(0.0, xx2 - xx1 +1)
h = np.maximum(0.0, yy2 - yy1 +1)
inter = w * h
remove_index_1 = np.where(areas[i] == inter)
remove_index_2 = np.where(areas[order[1:]] == inter)
ovr = inter / (areas[i] + areas[order[1:]] - inter)
ovr[remove_index_1] = 1.0
ovr[remove_index_2] = 1.0
inds = np.where(ovr <= thresh)[0]
order = order[inds + 1]
return keep