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
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
|
#!/usr/bin/env python
'''
example to detect upright people in images using HOG features
Usage:
peopledetect.py <image_names>
Press any key to continue, ESC to stop.
'''
# Python 2/3 compatibility
from __future__ import print_function
import numpy as np
import cv2 as cv
def inside(r, q):
rx, ry, rw, rh = r
qx, qy, qw, qh = q
return rx > qx and ry > qy and rx + rw < qx + qw and ry + rh < qy + qh
def draw_detections(img, rects, thickness = 1):
for x, y, w, h in rects:
# the HOG detector returns slightly larger rectangles than the real objects.
# so we slightly shrink the rectangles to get a nicer output.
pad_w, pad_h = int(0.15*w), int(0.05*h)
cv.rectangle(img, (x+pad_w, y+pad_h), (x+w-pad_w, y+h-pad_h), (0, 255, 0), thickness)
def main():
import sys
from glob import glob
import itertools as it
hog = cv.HOGDescriptor()
hog.setSVMDetector( cv.HOGDescriptor_getDefaultPeopleDetector() )
default = [cv.samples.findFile('basketball2.png')] if len(sys.argv[1:]) == 0 else []
for fn in it.chain(*map(glob, default + sys.argv[1:])):
print(fn, ' - ',)
try:
img = cv.imread(fn)
if img is None:
print('Failed to load image file:', fn)
continue
except:
print('loading error')
continue
found, _w = hog.detectMultiScale(img, winStride=(8,8), padding=(32,32), scale=1.05)
found_filtered = []
for ri, r in enumerate(found):
for qi, q in enumerate(found):
if ri != qi and inside(r, q):
break
else:
found_filtered.append(r)
draw_detections(img, found)
draw_detections(img, found_filtered, 3)
print('%d (%d) found' % (len(found_filtered), len(found)))
cv.imshow('img', img)
ch = cv.waitKey()
if ch == 27:
break
print('Done')
if __name__ == '__main__':
print(__doc__)
main()
cv.destroyAllWindows()
|
