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56 lines
1.7 KiB
Python
56 lines
1.7 KiB
Python
import numpy as np
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import cv2
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help_message = '''
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USAGE: peopledetect.py <image_names> ...
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Press any key to continue, ESC to stop.
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'''
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def inside(r, q):
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rx, ry, rw, rh = r
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qx, qy, qw, qh = q
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return rx > qx and ry > qy and rx + rw < qx + qw and ry + rh < qy + qh
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def draw_detections(img, rects, thickness = 1):
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for x, y, w, h in rects:
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# the HOG detector returns slightly larger rectangles than the real objects.
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# so we slightly shrink the rectangles to get a nicer output.
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pad_w, pad_h = int(0.15*w), int(0.05*h)
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cv2.rectangle(img, (x+pad_w, y+pad_h), (x+w-pad_w, y+h-pad_h), (0, 255, 0), thickness)
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if __name__ == '__main__':
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import sys
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from glob import glob
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import itertools as it
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print help_message
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hog = cv2.HOGDescriptor()
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hog.setSVMDetector( cv2.HOGDescriptor_getDefaultPeopleDetector() )
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for fn in it.chain(*map(glob, sys.argv[1:])):
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print fn, ' - ',
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try:
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img = cv2.imread(fn)
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except:
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print 'loading error'
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continue
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found = hog.detectMultiScale(img, winStride=(8,8), padding=(32,32), scale=1.05)
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found_filtered = []
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for ri, r in enumerate(found):
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for qi, q in enumerate(found):
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if ri != qi and inside(r, q):
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break
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else:
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found_filtered.append(r)
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draw_detections(img, found)
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draw_detections(img, found_filtered, 3)
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print '%d (%d) found' % (len(found_filtered), len(found))
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cv2.imshow('img', img)
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ch = cv2.waitKey()
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if ch == 27:
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break
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