光流法的代码,基于python,opencv
时间: 2023-12-26 19:04:52 浏览: 26
好的,以下是基于Python和OpenCV实现光流法的代码示例:
```python
import cv2
# 读取视频
cap = cv2.VideoCapture('video.mp4')
# 创建 ShiTomasi 角点检测器参数
feature_params = dict(maxCorners=100, qualityLevel=0.3, minDistance=7, blockSize=7)
# 创建 Lucas-Kanade 光流法参数
lk_params = dict(winSize=(15, 15), maxLevel=2, criteria=(cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 0.03))
# 随机颜色
color = (0, 255, 0)
# 读取第一帧
ret, old_frame = cap.read()
# 转换为灰度图像
old_gray = cv2.cvtColor(old_frame, cv2.COLOR_BGR2GRAY)
# 获取角点
p0 = cv2.goodFeaturesToTrack(old_gray, mask=None, **feature_params)
# 创建掩膜
mask = np.zeros_like(old_frame)
while True:
# 读取当前帧
ret, frame = cap.read()
# 转换为灰度图像
frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# 计算光流
p1, st, err = cv2.calcOpticalFlowPyrLK(old_gray, frame_gray, p0, None, **lk_params)
# 选择好的点
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, 2)
frame = cv2.circle(frame, (a, b), 5, color, -1)
img = cv2.add(frame, mask)
# 显示图像
cv2.imshow('frame', img)
# 更新上一帧的图像和点
old_gray = frame_gray.copy()
p0 = good_new.reshape(-1, 1, 2)
# 按下 ESC 键退出
k = cv2.waitKey(30) & 0xff
if k == 27:
break
# 释放资源
cap.release()
cv2.destroyAllWindows()
```
这段代码实现了对视频的光流法处理,可以通过读取视频文件,检测角点并计算光流,最后绘制轨迹并显示处理后的图像。