import cv2
def inside(r, q): rx, ry, rw, rh = r qx, qy, qw, qh = q return rx > qx and ry > qy and rx + rw < qx + qw and ry + rh < qy + qh
def draw_detections(img, rects, thickness = 1): for x, y, w, h in rects: # the HOG detector returns slightly larger rectangles than the real objects. # so we slightly shrink the rectangles to get a nicer output. pad_w, pad_h = int(0.15w), int(0.05h) cv2.rectangle(img, (x+pad_w, y+pad_h), (x+w-pad_w, y+h-pad_h), (0, 255, 0), thickness)
if __name__ == '__main__':
optical flow algorithm
hog = cv2.HOGDescriptor()
hog.setSVMDetector( cv2.HOGDescriptor_getDefaultPeopleDetector() )
cap=cv2.VideoCapture(0)
while True:
_,frame=cap.read()
found,w=hog.detectMultiScale(frame, winStride=(8,8), padding=(32,32), scale=(1.05))
draw_detections(frame,found)
cv2.imshow('feed',frame)
ch = 0xFF & cv2.waitKey(1)
if ch == 27:
break
cv2.destroyAllWindows()
