基于OpenCV的camshift跟踪算法

  代码实现如下：

import numpy as np
import cv2

cap = cv2.VideoCapture('output_2.avi')
fourcc = cv2.VideoWriter_fourcc(*'XVID')
out = cv2.VideoWriter('result.avi', fourcc, 20.0, (640, 480))
ret, frame = cap.read()  # take first frame of the video
# setup initial location of window
r, h, c, w = 200, 170, 260, 100  # simply hardcoded the values
track_window = (c, r, w, h)
# set up the ROI for tracking
roi = frame[r:r + h, c:c + w]
hsv_roi = cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hsv_roi, np.array((0., 60., 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)
# Setup the termination criteria, either 10 iteration or move by at least 1 pt
term_crit = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1)

while (1):
    ret, frame = cap.read()

    if ret == True:
        hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
        dst = cv2.calcBackProject([hsv], [0], roi_hist, [0, 180], 1)
        # apply meanshift to get the new location
        ret, track_window = cv2.CamShift(dst, track_window, term_crit)
        # Draw it on image
        pts = cv2.boxPoints(ret)
        pts = np.int0(pts)
        img2 = cv2.polylines(frame, [pts], True, 255, 2)
        cv2.imshow('img2', img2)
        out.write(img2)
        k = cv2.waitKey(60) & 0xff

        if k == 27:
            break
        else:
            cv2.imwrite(chr(k) + ".jpg", img2)
    else:
        break

cv2.destroyAllWindows()
cap.release()
out.release()