visualized_2.py

import cv2 as cv
import numpy as np

cap = cv.VideoCapture('image/fangdou.mp4')
orb = cv.ORB_create()
color = np.random.randint(0, 255, (1000, 3))
fps = cap.get(cv.CAP_PROP_FPS)
ret, old_frame = cap.read()
if not ret:
    print("Cannot read video file or stream.")
    exit()

old_gray = cv.cvtColor(old_frame, cv.COLOR_BGR2GRAY)
key1 = orb.detect(old_gray)
key1, des1 = orb.compute(old_gray, key1)
p0 = np.float32([keypoint.pt for keypoint in key1]).reshape(-1, 1, 2)

mask = np.zeros_like(old_frame)

lk_params = dict(winSize=(15, 15), maxLevel=2, criteria=(cv.TERM_CRITERIA_EPS | cv.TERM_CRITERIA_COUNT, 10, 0.03))

cv.namedWindow('Warped Frame', cv.WINDOW_NORMAL)
cv.resizeWindow('Warped Frame', 1920, 1000)

while True:
    ret, frame = cap.read()
    if not ret:
        break

    frame_gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
    key=orb.detect(frame_gray,None)
    key, des=orb.compute(frame_gray,key)
    p1, st, err = cv.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()
        a, b, c, d = int(a), int(b), int(c), int(d)

        mask = cv.line(mask, (a, b), (c, d), color[i].tolist(), 2)

        cv.imshow('mask', mask)

    img = cv.add(frame, mask)

    cv.imshow('frame', img)

    k = cv.waitKey(1) & 0xff
    if k == 27:
        break


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


cv.destroyAllWindows()
cap.release()