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import cv2import numpy as npcapture = cv2.VideoCapture('car.mp4')feature_params = dict( maxCorners = 100,     qualityLevel = 0.3,     minDistance = 7,    blockSize = 7 )# lucas kanade光流参数lk_params = dict( winSize = (15,15),    maxLevel = 2,    criteria = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10,    0.03))# 创建一些随机的颜色color = np.random.randint(0,255,(100,3))ret, old_frame = capture.read()old_gray = cv2.cvtColor(old_frame,cv2.COLOR_BGR2GRAY)p0 = cv2.goodFeaturesToTrack(old_gray,mask= None, **feature_params)mask = np.zeros_like(old_frame)while 1:    ret,frame = capture.read()    frame_gray = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)    p1, st, err = cv2.calcOpticalFlowPyrLK(old_gray, frame_gray, p0, None,**lk_params)    good_new = p1[st==1]    good_old = p0[st==1]    for i, (new, old) in enumerate(zip(good_new, good_old)):        a, b = new.ravel()        c, d = old.ravel()        mask = cv2.line(mask, (a, b), (c, d), color[i].tolist(), 2)        frame = cv2.circle(frame, (a, b), 5, color[i].tolist(), -1)    img = cv2.add(frame, mask)    cv2.imshow('frame', img)    k = cv2.waitKey(30) & 0xff    if k == 27:        break    old_gray = frame_gray.copy()    p0 = good_new.reshape(-1, 1, 2)

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