Created
December 17, 2019 21:52
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Mean Shift Object Tracking in opencv python
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import numpy as np | |
import cv2 as cv | |
cap = cv.VideoCapture('slow_traffic_small.mp4') | |
# take first frame of the video | |
ret, frame = cap.read() | |
# setup initial location of window | |
x, y, width, height = 300, 200, 100, 50 | |
track_window = (x, y ,width, height) | |
# set up the ROI for tracking | |
roi = frame[y:y+height, x : x+width] | |
hsv_roi = cv.cvtColor(roi, cv.COLOR_BGR2HSV) | |
mask = cv.inRange(hsv_roi, np.array((0., 60., 32.)), np.array((180., 255., 255))) | |
roi_hist = cv.calcHist([hsv_roi], [0], mask, [180], [0, 180]) | |
cv.normalize(roi_hist, roi_hist, 0, 255,cv.NORM_MINMAX) | |
# Setup the termination criteria, either 10 iteration or move by atleast 1 pt | |
term_crit = ( cv.TERM_CRITERIA_EPS | cv.TERM_CRITERIA_COUNT, 10, 1) | |
cv.imshow('roi',roi) | |
while(1): | |
ret, frame = cap.read() | |
if ret == True: | |
hsv = cv.cvtColor(frame, cv.COLOR_BGR2HSV) | |
dst = cv.calcBackProject([hsv], [0], roi_hist, [0, 180], 1) | |
# apply meanshift to get the new location | |
ret, track_window = cv.meanShift(dst, track_window, term_crit) | |
# Draw it on image | |
x,y,w,h = track_window | |
final_image = cv.rectangle(frame, (x,y), (x+w, y+h), 255, 3) | |
cv.imshow('dst', dst) | |
cv.imshow('final_image',final_image) | |
k = cv.waitKey(30) & 0xff | |
if k == 27: | |
break | |
else: | |
break |
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