62 lines
2.0 KiB
Python
62 lines
2.0 KiB
Python
import cv2
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import sys
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def blit(l_img, s_img, x_offset, y_offset):
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for c in range(0, 3):
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l_img[y_offset:y_offset+s_img.shape[0], x_offset:x_offset+s_img.shape[1], c] = s_img[:,:,c] * (s_img[:,:,3]/255.0) + l_img[y_offset:y_offset+s_img.shape[0], x_offset:x_offset+s_img.shape[1], c] * (1.0 - s_img[:,:,3]/255.0)
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def downscale(img, width, height):
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factor = min(1.0*height/img.shape[0], 1.0*width/img.shape[1])
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return cv2.resize(img, None, None, factor, factor)
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def popeize(faceCascade, image, papaj, faceScale=1.5):
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gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
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# Detect faces in the image
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faces = faceCascade.detectMultiScale(gray, faceScale, 5)
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print "Found {0} faces!".format(len(faces))
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# Draw a rectangle around the faces
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for (x, y, w, h) in faces:
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factor = min(1.0*h/papaj.shape[0], 1.0*w/papaj.shape[1]) * 1.3
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scaledpapaj = cv2.resize(papaj, None, None, factor, factor)
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dx = x + (w/2) - scaledpapaj.shape[1]/2
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dy = y + (h/2) - scaledpapaj.shape[0]/2
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print dx, dy, factor
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try:
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blit(image, scaledpapaj, dx, dy)
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except Exception as e:
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print e, dx, dy, factor
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#cv2.rectangle(image, (x, y), (x+w, y+h), (0, 255, 0), 2)
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if __name__ == '__main__':
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imagePath = sys.argv[1]
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cascPath = sys.argv[2]
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# Create the haar cascade
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faceCascade = cv2.CascadeClassifier(cascPath)
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# Read the image
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image = cv2.imread(imagePath)
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papaj = cv2.imread("zoltamorda.png", -1)
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cv2.namedWindow("image")
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def trackbarChanged(value):
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image = cv2.imread(imagePath)
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popeize(faceCascade, image, papaj, 1.1 + value/100.0)
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cv2.imshow("image", downscale(image, 1024, 768))
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print 'showed'
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cv2.createTrackbar("scale", "image", 0, 300, trackbarChanged)
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popeize(faceCascade, image, papaj, 1.1)
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cv2.imwrite("output.jpg", image)
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cv2.imshow("image", downscale(image, 1024, 768))
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while cv2.waitKey(0) & 0xff != ord('q'):
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pass
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