基于ROS的运动识别

#!/usr/bin/env python
# -*- coding: utf-8 -*-
import rospy
import cv2
import numpy as np
from sensor_msgs.msg import Image
import cv_bridge


class MotionDetector:
    def __init__(self):
        rospy.on_shutdown(self.cleanup)

        # 创建cv_bridge
        self.bridge = cv_bridge.CvBridge()
        self.image_pub = rospy.Publisher("cv_bridge_image", Image, queue_size=1)
        self.image_sub = rospy.Subscriber("/usb_cam/image_raw", Image, self.image_callback, queue_size=1)

        # 设置参数：最小区域、阈值
        self.minArea = rospy.get_param("~minArea", 500)
        self.threshold = rospy.get_param("~threshold", 25)

        self.firstFrame = None
        self.text = "Unoccupied"

    def image_callback(self, data):
        # 使用cv_bridge将ROS的图像数据转换成OpenCV的图像格式
        cv_image = self.bridge.imgmsg_to_cv2(data, "bgr8")
        frame = np.array(cv_image, dtype=np.uint8)

        # 创建灰度图像
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        gray = cv2.GaussianBlur(gray, (21, 21), 0)

        # 使用两帧图像做比较，检测移动物体的区域
        if self.firstFrame is None:
            self.firstFrame = gray
            return
        frameDelta = cv2.absdiff(self.firstFrame, gray)
        thresh = cv2.threshold(frameDelta, self.threshold, 255, cv2.THRESH_BINARY)[1]

        thresh = cv2.dilate(thresh, None, iterations=2)
        # binary, cnts, hierarchy = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
        cnts, hierarchy = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

        for c in cnts:
            # 如果检测到的区域小于设置值，则忽略
            if cv2.contourArea(c) < self.minArea:
                continue

            # 在输出画面上框出识别到的物体
            (x, y, w, h) = cv2.boundingRect(c)
            cv2.rectangle(frame, (x, y), (x + w, y + h), (50, 255, 50), 2)
            self.text = "Occupied"

        # 在输出画面上打当前状态和时间戳信息
        cv2.putText(frame, "Status: {}".format(self.text), (10, 20),
                    cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)

        # 将识别后的图像转换成ROS消息并发布
        self.image_pub.publish(self.bridge.cv2_to_imgmsg(frame, "bgr8"))

    def cleanup(self):
        print("强制结束程序。。。")
        cv2.destroyAllWindows()


if __name__ == '__main__':
    try:
        # 初始化ros节点
        rospy.init_node("motion_detector")
        rospy.loginfo("运动检测程序启动。。。")
        rospy.loginfo("请打开opencv节点订阅消息。。。")
        MotionDetector()
        rospy.spin()
    except KeyboardInterrupt:
        print("强制结束程序。。。")
        cv2.destroyAllWindows()