72 lines
2.0 KiB
Python
Executable File
72 lines
2.0 KiB
Python
Executable File
#!/usr/bin/env python
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'''
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example to detect upright people in images using HOG features
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Usage:
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peopledetect.py <image_names>
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Press any key to continue, ESC to stop.
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'''
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# Python 2/3 compatibility
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from __future__ import print_function
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import numpy as np
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import cv2
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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(__doc__)
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hog = cv2.HOGDescriptor()
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hog.setSVMDetector( cv2.HOGDescriptor_getDefaultPeopleDetector() )
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default = ['../data/basketball2.png '] if len(sys.argv[1:]) == 0 else []
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for fn in it.chain(*map(glob, default + 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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if img is None:
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print('Failed to load image file:', fn)
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continue
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except:
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print('loading error')
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continue
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found, w = 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 = 0xFF & cv2.waitKey()
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if ch == 27:
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break
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cv2.destroyAllWindows()
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