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Face detection using OpenCV. Refactored from https://realpython.com/blog/python/face-recognition-with-python/.
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import sys, cv2 | |
# Refactored https://realpython.com/blog/python/face-recognition-with-python/ | |
def cascade_detect(cascade, image): | |
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) | |
return cascade.detectMultiScale( | |
gray_image, | |
scaleFactor = 1.15, | |
minNeighbors = 5, | |
minSize = (30, 30), | |
flags = cv2.cv.CV_HAAR_SCALE_IMAGE | |
) | |
def detections_draw(image, detections): | |
for (x, y, w, h) in detections: | |
print "({0}, {1}, {2}, {3})".format(x, y, w, h) | |
cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2) | |
def main(argv = None): | |
if argv is None: | |
argv = sys.argv | |
cascade_path = sys.argv[1] | |
image_path = sys.argv[2] | |
result_path = sys.argv[3] if len(sys.argv) > 3 else None | |
cascade = cv2.CascadeClassifier(cascade_path) | |
image = cv2.imread(image_path) | |
if image is None: | |
print "ERROR: Image did not load." | |
return 2 | |
detections = cascade_detect(cascade, image) | |
detections_draw(image, detections) | |
print "Found {0} objects!".format(len(detections)) | |
if result_path is None: | |
cv2.imshow("Objects found", image) | |
cv2.waitKey(0) | |
else: | |
cv2.imwrite(result_path, image) | |
if __name__ == "__main__": | |
sys.exit(main()) |
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