62 lines
1.8 KiB
Python
62 lines
1.8 KiB
Python
#!/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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'''
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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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from tests_common import NewOpenCVTests, intersectionRate
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class peopledetect_test(NewOpenCVTests):
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def test_peopledetect(self):
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hog = cv2.HOGDescriptor()
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hog.setSVMDetector( cv2.HOGDescriptor_getDefaultPeopleDetector() )
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dirPath = 'samples/data/'
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samples = ['basketball1.png', 'basketball2.png']
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testPeople = [
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[[23, 76, 164, 477], [440, 22, 637, 478]],
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[[23, 76, 164, 477], [440, 22, 637, 478]]
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]
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eps = 0.5
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for sample in samples:
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img = self.get_sample(dirPath + sample, 0)
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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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matches = 0
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for i in range(len(found_filtered)):
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for j in range(len(testPeople)):
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found_rect = (found_filtered[i][0], found_filtered[i][1],
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found_filtered[i][0] + found_filtered[i][2],
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found_filtered[i][1] + found_filtered[i][3])
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if intersectionRate(found_rect, testPeople[j][0]) > eps or intersectionRate(found_rect, testPeople[j][1]) > eps:
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matches += 1
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self.assertGreater(matches, 0) |