ros小车红绿灯识别功能代码

红绿灯识别是一个比较复杂的任务，需要用到图像处理和深度学习等技术。以下是一个简单的红绿灯识别功能的代码示例：

import rospy
import cv2
import numpy as np
from sensor_msgs.msg import Image
from cv_bridge import CvBridge

class TrafficLightDetector:
    def __init__(self):
        self.image_sub = rospy.Subscriber('/camera/image_raw', Image, self.image_callback)
        self.bridge = CvBridge()

    def image_callback(self, msg):
        cv_image = self.bridge.imgmsg_to_cv2(msg, "bgr8")

        # 图像处理，提取红色区域
        hsv = cv2.cvtColor(cv_image, cv2.COLOR_BGR2HSV)
        lower_red = np.array([0, 100, 100])
        upper_red = np.array([10, 255, 255])
        mask1 = cv2.inRange(hsv, lower_red, upper_red)

        lower_red = np.array([160, 100, 100])
        upper_red = np.array([179, 255, 255])
        mask2 = cv2.inRange(hsv, lower_red, upper_red)

        mask = mask1 + mask2

        # 查找轮廓
        contours, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

        # 判断是否有红色圆形
        for cnt in contours:
            area = cv2.contourArea(cnt)
            if area > 500:
                approx = cv2.approxPolyDP(cnt, 0.01 * cv2.arcLength(cnt, True), True)
                if len(approx) > 6:
                    (x, y), radius = cv2.minEnclosingCircle(cnt)
                    if radius > 20 and radius < 100:
                        cv2.circle(cv_image, (int(x), int(y)), int(radius), (0, 255, 0), 2)
                        rospy.loginfo('Traffic light detected')
                        # 通过 ROS 发布消息
                        # ...

        # 显示图像
        cv2.imshow('image', cv_image)
        cv2.waitKey(1)

if __name__ == '__main__':
    rospy.init_node('traffic_light_detector')
    detector = TrafficLightDetector()
    rospy.spin()

以上代码基于 ROS 框架实现，订阅相机图像，使用 OpenCV 库来提取红色区域，并查找轮廓来识别红色圆形。如果检测到红色圆形，则发布一个 ROS 消息。注意，以上代码仅供参考，具体实现需要根据实际情况进行调整和优化。