https://blog.csdn.net/weixin_42284380/article/details/151273480
可以直接跑:
import cv2
import numpy as np
cap = cv2.VideoCapture('../test-1920X1080.mp4')
# 获取第一帧并检测特征点
ret, old_frame = cap.read()
old_gray = cv2.cvtColor(old_frame, cv2.COLOR_BGR2GRAY)
p0 = cv2.goodFeaturesToTrack(old_gray, maxCorners=100, qualityLevel=0.3, minDistance=7)
# 创建随机颜色用于轨迹绘制
color = np.random.randint(0, 255, (100, 3))
# 用于保存特征点轨迹
trajectory = [[] for _ in range(len(p0))]
while True:
ret, frame = cap.read()
if not ret:
break
frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# 计算光流
p1, st, err = cv2.calcOpticalFlowPyrLK(old_gray, frame_gray, p0, None)
# 选择良好匹配点
good_new = p1[st == 1]
good_old = p0[st == 1]
# 更新轨迹
for i, (new, old) in enumerate(zip(good_new, good_old)):
a, b = new.ravel()
trajectory[i].append((int(a), int(b)))
# 绘制轨迹
for j in range(1, len(trajectory[i])):
cv2.line(frame, trajectory[i][j-1], trajectory[i][j], color[i].tolist(), 2)
# 显示结果
cv2.imshow('Frame', frame)
# 更新前一帧和特征点
old_gray = frame_gray.copy()
p0 = good_new.reshape(-1, 1, 2)
if cv2.waitKey(30) & 0xff == 27:
break
cap.release()
cv2.destroyAllWindows()