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#!/usr/bin/env python
import numpy as np
import cv2
help_message = '''
USAGE: peopledetect.py <image_names> ...
Press any key to continue, ESC to stop.
'''
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)
cv2.rectangle(img, (x+pad_w, y+pad_h), (x+w-pad_w, y+h-pad_h), (0, 255, 0), thickness)
if __name__ == '__main__':
import sys
from glob import glob
import itertools as it
print help_message
hog = cv2.HOGDescriptor()
hog.setSVMDetector( cv2.HOGDescriptor_getDefaultPeopleDetector() )
for fn in it.chain(*map(glob, sys.argv[1:])):
print fn, ' - ',
try:
img = cv2.imread(fn)
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))
cv2.imshow('img', img)
ch = 0xFF & cv2.waitKey()
if ch == 27:
break
cv2.destroyAllWindows()
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