基于ROS使用OpenCV进行人脸识别

ROS使用OpenCV进行人脸识别"/>

基于ROS使用OpenCV进行人脸识别

1 硬件

摄像头：1个;

USB数据线：1个；

1.1 准备

这里需要使用usb-cam软件包：

$ cd ~/catkin_ws/src  
$ git clone .git  
$ cd ~/catkin_ws  
$ catkin_make  

 注意：下面的程序运行前，需要启动usb_cam节点。

roslaunch usb_cam usb_cam-test.launch

运行上面的节点，这时该节点会不断的发布/usb_cam/image_raw话题。如下图所示：

下面的程序将使用这个话题数据。

2 程序

#include <ros/ros.h>
#include <image_transport/image_transport.h>
#include <cv_bridge/cv_bridge.h>
#include <sensor_msgs/image_encodings.h>
#include <opencv2/objdetect.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/core.hpp>using namespace std;
using namespace cv;CascadeClassifier face_cascade;static const std::string OPENCV_WINDOW = "Raw Image window";class Face_Detector
{ros::NodeHandle nh_;image_transport::ImageTransport it_;image_transport::Subscriber image_sub_;image_transport::Publisher image_pub_;public:Face_Detector(): it_(nh_){// Subscribe to input video feed and publish output video feedimage_sub_ = it_.subscribe("/usb_cam/image_raw", 1, &Face_Detector::imageCb, this);image_pub_ = it_.advertise("/face_detector/raw_image", 1);cv::namedWindow(OPENCV_WINDOW);}~Face_Detector(){cv::destroyWindow(OPENCV_WINDOW);}void imageCb(const sensor_msgs::ImageConstPtr& msg){cv_bridge::CvImagePtr cv_ptr;namespace enc = sensor_msgs::image_encodings;try{cv_ptr = cv_bridge::toCvCopy(msg, sensor_msgs::image_encodings::BGR8);}catch (cv_bridge::Exception& e){ROS_ERROR("cv_bridge exception: %s", e.what());return;}// Draw an example circle on the video streamif (cv_ptr->image.rows > 400 && cv_ptr->image.cols > 600){detect_faces(cv_ptr->image);image_pub_.publish(cv_ptr->toImageMsg());}}void detect_faces(cv::Mat img){RNG rng( 0xFFFFFFFF );int lineType = 8;Mat frame_gray;cvtColor( img, frame_gray, COLOR_BGR2GRAY );equalizeHist( frame_gray, frame_gray );//-- Detect facesstd::vector<Rect> faces;face_cascade.detectMultiScale( frame_gray, faces );for ( size_t i = 0; i < faces.size(); i++ ){Point center( faces[i].x + faces[i].width/2, faces[i].y + faces[i].height/2 );ellipse( img, center, Size( faces[i].width/2, faces[i].height/2 ), 0, 0, 360, Scalar( 255, 0, 255 ), 4 );//图像，文本，坐标，文字类型，缩放因子，颜色，线宽，线型//putText( img, "WARNING:Face Recognation!", org, rng.uniform(0,8),//     rng.uniform(0,100)*0.05+0.05, randomColor(rng), rng.uniform(1, 10), lineType);//putText( img, "WARNING : Face Recognation!", org, rng.uniform(0,8),//  1.5, Scalar(0, 255,0 ) , rng.uniform(1, 10), lineType);}Point org = Point(40,40);if (faces.size() >= 1) {putText( img, "WARNING : Face Recognation!", org, rng.uniform(0,8), 1.5, Scalar(0, 255,0 ) , rng.uniform(1, 10), lineType);}imshow(OPENCV_WINDOW,img);waitKey(3);}	static Scalar randomColor( RNG& rng ){int icolor = (unsigned) rng;return Scalar( icolor&255, (icolor>>8)&255, (icolor>>16)&255 ); //移位操作，进而生成不同的颜色}};int main(int argc, char** argv)
{//从命令行读取必要的信息,注意路径CommandLineParser parser(argc, argv,"{help h||}""{face_cascade|/home/junjun/projects/main2/haarcascade_frontalface_alt.xml|Path to face cascade.}");parser.about( "\nThis program demonstrates using the cv::CascadeClassifier class to detect objects (Face + eyes) in a video stream.\n""You can use Haar or LBP features.\n\n" );parser.printMessage();String face_cascade_name = parser.get<String>("face_cascade");//-- 1. Load the cascadesif( !face_cascade.load( face_cascade_name ) ){cout << "--(!)Error loading face cascade\n";return -1;};ros::init(argc, argv, "Face_Detector");Face_Detector ic;ros::spin();return 0;
}

程序不再解释，基本都很简单，基于ROS平台调用OpenCV程序如果多写几次，似乎可以找到一个固定的模板。

2.1 CMakeLists.txt文件

这个很重要，以后再写程序可以直接参考这个文件：

如果有不懂的可以参考ROS学习笔记15（ROS/CMakeLists.txt文件）：

cmake_minimum_required(VERSION 2.8.3)
project(cv_bridge_tutorial_pkg)find_package(catkin REQUIRED COMPONENTScv_bridgeimage_transportroscppsensor_msgsstd_msgs)find_package( OpenCV REQUIRED )catkin_package()include_directories(${catkin_INCLUDE_DIRS}${OpenCV_INCLUDE_DIRS}
)add_executable(sample_cv_bridge_node src/sample_cv_bridge_node.cpp)target_link_libraries(sample_cv_bridge_node${catkin_LIBRARIES}${OpenCV_LIBRARIES})include_directories(${catkin_INCLUDE_DIRS} ${OpenCV_INCLUDE_DIRS})

2.3 package.xml文件

不懂得也可以参考《ROS学习笔记6（package.xml》

<?xml version="1.0"?>
<package><name>cv_bridge_tutorial_pkg</name><version>0.0.0</version><description>The cv_bridge_tutorial_pkg package</description><maintainer email="lentin@todo.todo">lentin</maintainer><license>TODO</license><buildtool_depend>catkin</buildtool_depend><build_depend>cv_bridge</build_depend><build_depend>image_transport</build_depend><build_depend>roscpp</build_depend><build_depend>sensor_msgs</build_depend><build_depend>std_msgs</build_depend><run_depend>cv_bridge</run_depend><run_depend>image_transport</run_depend><run_depend>roscpp</run_depend><run_depend>sensor_msgs</run_depend><run_depend>std_msgs</run_depend><export></export>
</package>

3 运行

首先运行：roscore

然后：roslaunch usb_cam usb_cam-test.launch

最后：rosrun cv_bridge_tutorial_pkg sample_cv_bridge_node

结果如图所示：下图帅哥为我舍友（没办法，他的照片较帅，单身可撩）！