Python OpenCV学习笔记之：图像Lucas-Kanad流光算法-优快云博客

为什么80%的码农都做不了架构师？>>>

# -*- coding: utf-8 -*-
"""
图像Lucas-Kanad流光算法
Lucas-Kanad算法请参考:http://www.cnblogs.com/hrlnw/p/3600291.html
"""

import numpy as np
import cv2
cap = cv2.VideoCapture(0)

# ShiTomasi角点检测参数
feature_params = dict( maxCorners = 100,
                       qualityLevel = 0.3,
                       minDistance = 7,
                       blockSize = 7 )
# lucas kanade算法参数
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 = np.random.randint(0,255,(100,3))

# 读取第一张帧并进行角点检测
ret, old_frame = cap.read()
while True:
    ret, old_frame = cap.read()
    if ret == True:
        break

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 True:
    ret, frame = cap.read()
    frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    # 计算流光
    p1, st, err = cv2.calcOpticalFlowPyrLK(old_gray, frame_gray, p0, None, **lk_params)
    if p1 is None or p0 is None:
        cv2.imshow("frame",frame)
        continue
    # 选择条件好的点
    good_new = p1[st == 1]
    good_old = p0[st == 1]

    # 绘制跟踪
    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',mask)

    k = cv2.waitKey(10) & 0xFF
    if k == 27:
        break
    # 更新点和帧
    old_gray = frame_gray.copy()
    p0 = good_new.reshape(-1, 1, 2)
cap.release()
cv2.destroyAllWindows()

转载于:https://my.oschina.net/wujux/blog/801952