#!/usr/bin/env python# -*- coding: utf-8 -*-import rospyimport cv2import numpy as npfrom sensor_msgs.msg import Imageimport cv_bridgeclass 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()