你给我写个程序opencv给我写一个实时检测铁路钢轨尺寸距离

好的，下面是一个基本的实现，仅供参考：

import cv2
import numpy as np

# 设置相机内参和外参
camera_matrix = np.array([[1000, 0, 320], [0, 1000, 240], [0, 0, 1]])
dist_coeffs = np.array([0, 0, 0, 0])
rot_vec = np.zeros((3, 1))
trans_vec = np.zeros((3, 1))

# 定义铁路钢轨颜色范围
lower_color = np.array([0, 0, 0])
upper_color = np.array([180, 255, 50])

# 创建VideoCapture对象
cap = cv2.VideoCapture(0)

while True:
    # 读取一帧图像
    ret, frame = cap.read()
    
    # 预处理图像
    blur = cv2.GaussianBlur(frame, (5, 5), 0)
    edges = cv2.Canny(blur, 50, 150)
    
    # 检测直线
    lines = cv2.HoughLines(edges, 1, np.pi / 180, 100)
    
    # 绘制直线
    if lines is not None:
        for line in lines:
            rho, theta = line[0]
            a = np.cos(theta)
            b = np.sin(theta)
            x0 = a * rho
            y0 = b * rho
            x1 = int(x0 + 1000 * (-b))
            y1 = int(y0 + 1000 * (a))
            x2 = int(x0 - 1000 * (-b))
            y2 = int(y0 - 1000 * (a))
            cv2.line(frame, (x1, y1), (x2, y2), (0, 0, 255), 2)
            
            # 在钢轨区域绘制矩形
            if (theta < 1.5 or theta > 1.6) and rho > 200:
                mask = cv2.inRange(frame, lower_color, upper_color)
                contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
                for contour in contours:
                    x, y, w, h = cv2.boundingRect(contour)
                    cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
                    
                    # 计算钢轨尺寸和距离
                    object_points = np.array([[x + w / 2, y + h / 2, 0]])
                    image_points, _ = cv2.projectPoints(object_points, rot_vec, trans_vec, camera_matrix, dist_coeffs)
                    distance = abs(trans_vec[2, 0])
                    size = w
                    
                    # 在图像上显示结果
                    cv2.putText(frame, 'Distance: {:.2f} cm'.format(distance), (20, 40), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
                    cv2.putText(frame, 'Size: {:.2f} cm'.format(size), (20, 80), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
    
    # 显示图像
    cv2.imshow('frame', frame)
    
    # 监听键盘事件，按'q'退出
    if cv2.waitKey(1) == ord('q'):
        break

# 释放资源
cap.release()
cv2.destroyAllWindows()

需要注意的是，这个程序只是一个基本的实现，钢轨检测的准确性和稳定性还需要进行优化和调试。同时，相机内参和外参需要进行标定，否则计算结果会有误差。