import numpy as np
import cv2

filepath = 'E:/s15/15_0101disgustingteeth.avi'
filepath1 = 'E:/k.avi'
cap = cv2.VideoCapture(filepath)

#角点检测参数
feature_params = dict(maxCorners=100,
                      qualityLevel=0.3,
                      minDistance=7)
#lucas kanade参数
lk_params = dict(winSize=(15,15),
                 maxLevel=2)
#随机颜色条
color = np.random.randint(0, 255, (100, 3))

#拿到第一帧的图像
ret, old_frame = cap.read()
old_gray = cv2.cvtColor(old_frame, cv2.COLOR_BGR2GRAY)
#返回所有检测特征点，需要输入图像，角点最大数量，品质因子

p0 = cv2.goodFeaturesToTrack(old_gray, mask=None, **feature_params)


#创建一个mask
mask = np.zeros_like(old_frame)

while(True):
    ret, frame = cap.read()
    frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    #需要传入前一帧和当前图片以及前一帧检测到的角点
    p1, st, err = cv2.calcOpticalFlowPyrLK(old_gray, frame_gray, p0, None, **lk_params)
    good_new = p1[st==1]
    good_old = p0[st==1]


    #绘制轨迹
    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(150)&0xff
    if k == 27:
        break

    #更新
    old_gray = frame_gray.copy()
    p0 = good_new.reshape(-1,1,2)