OpenCV 实时识别赛道线并标记黑色赛道中点

要实时识别赛道两边的线并标记灰度处理下黑色赛道中点，你可以按照以下步骤进行操作：

导入必要的库和模块：

import cv2
import numpy as np

定义函数来处理图像：

def process_image(image):
    ' 转换为灰度图像 '
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    
    ' 进行灰度阈值处理，将颜色转换为二进制图像 '
    ret, binary = cv2.threshold(gray, 120, 255, cv2.THRESH_BINARY)
    
    ' 执行边缘检测 '
    edges = cv2.Canny(binary, 50, 150)
    
    ' 对边缘图像进行霍夫直线检测 '
    lines = cv2.HoughLinesP(edges, 1, np.pi/180, threshold=100, minLineLength=100, maxLineGap=50)
    
    ' 遍历检测到的线条，并画出标记 '
    if lines is not None:
        for line in lines:
            x1, y1, x2, y2 = line[0]
            cv2.line(image, (x1, y1), (x2, y2), (0, 255, 0), 3)
    
    ' 标记黑色赛道中点 '
    hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
    lower_black = np.array([0, 0, 0])
    upper_black = np.array([180, 255, 50])
    mask = cv2.inRange(hsv, lower_black, upper_black)
    contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    if contours:
        c = max(contours, key=cv2.contourArea)
        M = cv2.moments(c)
        cx = int(M['m10'] / M['m00'])
        cy = int(M['m01'] / M['m00'])
        cv2.circle(image, (cx, cy), 5, (0, 0, 255), -1)
    
    return image

读取视频流并实时处理：

cap = cv2.VideoCapture(0)  ' 或者读取视频文件cap = cv2.VideoCapture('video.mp4') '

while True:
    ret, frame = cap.read()
    if not ret:
        break
    
    processed_frame = process_image(frame)
    
    cv2.imshow('Processed Frame', processed_frame)
    
    if cv2.waitKey(1) == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()

请注意，这只是一个简单的示例，具体的参数和阈值需要根据实际情况进行调整。