使用chatGPT编写一段树莓派视觉识别小车程序（待验证）

问：

设计一段python程序，用于安装有opencv库的树莓派小车，小车安装有四个麦克纳姆轮电机， 实现 “摄像头采集实时画面,分析画面中黑线走向,给出四个电机转速(如果反转则给出负数值), 小车能沿着黑线行驶，遇到T字路口或十字路口则停止"

答：

import cv2
import numpy as np
import RPi.GPIO as GPIO

# 设置GPIO引脚
GPIO.setmode(GPIO.BCM)
GPIO.setup(17, GPIO.OUT)
GPIO.setup(18, GPIO.OUT)
GPIO.setup(19, GPIO.OUT)
GPIO.setup(20, GPIO.OUT)

# 初始化电机速度为0
motor_speeds = [0, 0, 0, 0]

# 摄像头设置
camera = cv2.VideoCapture(0)
camera.set(cv2.CAP_PROP_FRAME_WIDTH, 320)
camera.set(cv2.CAP_PROP_FRAME_HEIGHT, 240)

while True:
    # 读取一帧画面
    ret, frame = camera.read()
    
    # 将画面转为灰度图像
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    
    # 二值化处理，将灰度图像变为黑白二值图像
    ret, binary = cv2.threshold(gray, 100, 255, cv2.THRESH_BINARY_INV)
    
    # 进行形态学处理，去除噪声和填充空洞
    kernel = np.ones((3,3), np.uint8)
    binary = cv2.morphologyEx(binary, cv2.MORPH_OPEN, kernel)
    binary = cv2.morphologyEx(binary, cv2.MORPH_CLOSE, kernel)
    
    # 寻找轮廓
    contours, hierarchy = cv2.findContours(binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    
    # 判断是否有黑线
    if len(contours) > 0:
        # 找到最大的轮廓
        max_contour = max(contours, key=cv2.contourArea)
        
        # 拟合直线
        x, y, w, h = cv2.boundingRect(max_contour)
        if w > h:
            # 横向黑线
            cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
            direction = (x + w / 2) / (frame.shape[1] / 2) - 1
            motor_speeds[0] = -direction
            motor_speeds[1] = direction
            motor_speeds[2] = -direction
            motor_speeds[3] = direction
        else:
            # 纵向黑线
            cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 0, 255), 2)
            direction = (y + h / 2) / (frame.shape[0] / 2) - 1
            motor_speeds[0] = -direction
            motor_speeds[1] = -direction
            motor_speeds[2] = direction
            motor_speeds[3] = direction
            
    # 控制电机转速
    for i in range(4):
        if motor_speeds[i] >= 0:
            GPIO.output(17 + i, GPIO.HIGH)
        else:
            GPIO.output(17 + i, GPIO.LOW)
            motor_speeds[i] = -motor_speeds[i]

        #根据电机速度设置PWM占空比
        motor_pwm = abs(motor_speeds[i]) * 100
        GPIO.PWM(17 + i, 100).start(motor_pwm)

    # 显示画面
    cv2.imshow("frame", frame)

    # 等待按键或者延时50毫秒
    key = cv2.waitKey(50)
    if key == ord('q'):
        break
    
# 停止电机
for i in range(4):
    GPIO.output(17 + i, GPIO.LOW)
    GPIO.PWM(17 + i, 100).stop()

# 释放摄像头
camera.release()
cv2.destroyAllWindows()

# 注意：上述代码仅供参考，具体实现还需要根据具体硬件和环境进行调整。例如需要调整电机控制引脚的编号，以及PWM频率等参数。