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import cv2
import time
person_cascade = cv2.CascadeClassifier(
os.path.join('/path/to/haarcascade_fullbody.xml'))
cap = cv2.VideoCapture("/path/to/test/video")
while True:
r, frame = cap.read()
if r:
start_time = time.time()
frame = cv2.resize(frame,(640,360)) # Downscale to improve frame rate
gray_frame = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY) # Haar-cascade classifier needs a grayscale image
rects = person_cascade.detectMultiScale(gray_frame)
end_time = time.time()
print("Elapsed Time:",end_time-start_time)
for (x, y, w, h) in rects:
cv2.rectangle(frame, (x,y), (x+w,y+h),(0,255,0),2)
cv2.imshow("preview", frame)
k = cv2.waitKey(1)
if k & 0xFF == ord("q"): # Exit condition
break
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