mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
76 lines
2.0 KiB
76 lines
2.0 KiB
#!/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 as cv |
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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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cv.rectangle(img, (x+pad_w, y+pad_h), (x+w-pad_w, y+h-pad_h), (0, 255, 0), thickness) |
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def 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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hog = cv.HOGDescriptor() |
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hog.setSVMDetector( cv.HOGDescriptor_getDefaultPeopleDetector() ) |
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default = [cv.samples.findFile('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 = cv.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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cv.imshow('img', img) |
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ch = cv.waitKey() |
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if ch == 27: |
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break |
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print('Done') |
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if __name__ == '__main__': |
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print(__doc__) |
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main() |
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cv.destroyAllWindows()
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