Created
January 26, 2015 12:52
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CCV Object Tracking
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import numpy as np | |
import cv2 | |
def run_main(): | |
cap = cv2.VideoCapture('upabove.mp4') | |
# Read the first frame of the video | |
ret, frame = cap.read() | |
# Set the ROI (Region of Interest). Actually, this is a | |
# rectangle of the building that we're tracking | |
c,r,w,h = 900,650,70,70 | |
track_window = (c,r,w,h) | |
# Create mask and normalized histogram | |
roi = frame[r:r+h, c:c+w] | |
hsv_roi = cv2.cvtColor(roi, cv2.COLOR_BGR2HSV) | |
mask = cv2.inRange(hsv_roi, np.array((0., 30.,32.)), np.array((180.,255.,255.))) | |
roi_hist = cv2.calcHist([hsv_roi], [0], mask, [180], [0, 180]) | |
cv2.normalize(roi_hist, roi_hist, 0, 255, cv2.NORM_MINMAX) | |
term_crit = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 80, 1) | |
while True: | |
ret, frame = cap.read() | |
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) | |
dst = cv2.calcBackProject([hsv], [0], roi_hist, [0,180], 1) | |
ret, track_window = cv2.meanShift(dst, track_window, term_crit) | |
x,y,w,h = track_window | |
img2 = cv2.rectangle(frame, (x,y), (x+w,y+h), 255, 2) | |
cv2.putText(frame, 'Tracked', (x-25,y-10), cv2.FONT_HERSHEY_SIMPLEX, | |
1, (255,255,255), 2, cv2.CV_AA) | |
cv2.imshow('Tracking', frame) | |
if cv2.waitKey(1) & 0xFF == ord('q'): | |
break | |
cap.release() | |
cv2.destroyAllWindows() | |
if __name__ == "__main__": | |
run_main() |
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