#!/usr/bin/env python # -*- coding: utf-8 -*- import rospy import cv2 import numpy as np from sensor_msgs.msg import Image import cv_bridgeclass FaceDetector:def __init__(self):rospy.on_shutdown(self.cleanup)# 創建cv_bridgeself.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)# self.image_sub = rospy.Subscriber("/camera/rgb/image_raw", Image, self.image_callback, queue_size=1)# 獲取haar特征的級聯表的XML文件，文件路徑在launch文件中傳入cascade_1 = rospy.get_param("~cascade_1", "～/catkin_ws/src/opencv/data/haar_detectors/haarcascade_frontalface_alt.xml")cascade_2 = rospy.get_param("~cascade_2", "～/catkin_ws/src/opencv/data/haar_detectors/haarcascade_profileface.xml")# 使用級聯表初始化haar特征檢測器self.cascade_1 = cv2.CascadeClassifier(cascade_1)self.cascade_2 = cv2.CascadeClassifier(cascade_2)# 設置級聯表的參數，優化人臉識別，可以在launch文件中重新配置self.haar_scaleFactor = rospy.get_param("~haar_scaleFactor", 1.2)self.haar_minNeighbors = rospy.get_param("~haar_minNeighbors", 2)self.haar_minSize = rospy.get_param("~haar_minSize", 40)self.haar_maxSize = rospy.get_param("~haar_maxSize", 60)self.color = (50, 255, 50)def image_callback(self, data):# 使用cv_bridge將ROS的圖像數據轉換成OpenCV的圖像格式cv_image = self.bridge.imgmsg_to_cv2(data, "bgr8")frame = np.array(cv_image, dtype=np.uint8)# 創建灰度圖像grey_image = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)# 創建平衡直方圖，減少光線影響grey_image = cv2.equalizeHist(grey_image)# 嘗試檢測人臉faces_result = self.detect_face(grey_image)# 在opencv的窗口中框出所有人臉區域if len(faces_result) > 0:for face in faces_result:x, y, w, h = facecv2.rectangle(cv_image, (x, y), (x + w, y + h), self.color, 2)# 將識別后的圖像轉換成ROS消息并發布self.image_pub.publish(self.bridge.cv2_to_imgmsg(cv_image, "bgr8"))def detect_face(self, input_image):# 首先匹配正面人臉的模型if self.cascade_1:faces = self.cascade_1.detectMultiScale(input_image,self.haar_scaleFactor,self.haar_minNeighbors,cv2.CASCADE_SCALE_IMAGE,(self.haar_minSize, self.haar_maxSize))# 如果正面人臉匹配失敗，那么就嘗試匹配側面人臉的模型if len(faces) == 0 and self.cascade_2:faces = self.cascade_2.detectMultiScale(input_image,self.haar_scaleFactor,self.haar_minNeighbors,cv2.CASCADE_SCALE_IMAGE,(self.haar_minSize, self.haar_maxSize))return facesdef cleanup(self):print("強制結束程序。。")cv2.destroyAllWindows()if __name__ == '__main__':try:# 初始化ros節點rospy.init_node("face_detector")follower = FaceDetector()rospy.loginfo("人臉識別已經啟動。。。")rospy.loginfo("請打開opencv節點訂閱消息。。。")rospy.spin()except KeyboardInterrupt:print("強制結束程序。。")cv2.destroyAllWindows()

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轉載于:https://www.cnblogs.com/dingyc/p/10677171.html

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