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 https://github.com/bosch-ros-pkg/usb_cam.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 Edge_Detector
{
  ros::NodeHandle nh_;
  image_transport::ImageTransport it_;
  image_transport::Subscriber image_sub_;
  image_transport::Publisher image_pub_;
  
public:
  Edge_Detector()
    : it_(nh_)
  {
    // Subscribe to input video feed and publish output video feed
    image_sub_ = it_.subscribe("/usb_cam/image_raw", 1, 
      &Edge_Detector::imageCb, this);
    image_pub_ = it_.advertise("/edge_detector/raw_image", 1);
    cv::namedWindow(OPENCV_WINDOW);

  }

  ~Edge_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 stream
    if (cv_ptr->image.rows > 400 && cv_ptr->image.cols > 600){

	    detect_edges(cv_ptr->image);
    	image_pub_.publish(cv_ptr->toImageMsg());
	  }
  }
  
  void detect_edges(cv::Mat img)
  {
    RNG rng( 0xFFFFFFFF );
    int lineType = 8;
    Mat frame_gray;
    cvtColor( img, frame_gray, COLOR_BGR2GRAY );
    equalizeHist( frame_gray, frame_gray );
    //-- Detect faces
    std::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 cascades
    if( !face_cascade.load( face_cascade_name ) )
    {
        cout << "--(!)Error loading face cascade\n";
        return -1;
    };

  ros::init(argc, argv, "Edge_Detector");
  Edge_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）：

https://blog.csdn.net/qq_27806947/article/details/82709620

cmake_minimum_required(VERSION 2.8.3)
project(cv_bridge_tutorial_pkg)

find_package(catkin REQUIRED COMPONENTS
  cv_bridge
  image_transport
  roscpp
  sensor_msgs
  std_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》

https://blog.csdn.net/qq_27806947/article/details/82084707

<?xml version="1.0"?>
<package>
  <name>cv_bridge_tutorial_pkg</name>
  <version>0.0.0</version>
  <description>The cv_bridge_tutorial_pkg package</description>

  <!-- One maintainer tag required, multiple allowed, one person per tag --> 
  <!-- Example:  -->
  <!-- <maintainer email="[email protected]">Jane Doe</maintainer> -->
  <maintainer email="[email protected]">lentin</maintainer>


  <!-- One license tag required, multiple allowed, one license per tag -->
  <!-- Commonly used license strings: -->
  <!--   BSD, MIT, Boost Software License, GPLv2, GPLv3, LGPLv2.1, LGPLv3 -->
  <license>TODO</license>


  <!-- Url tags are optional, but mutiple are allowed, one per tag -->
  <!-- Optional attribute type can be: website, bugtracker, or repository -->
  <!-- Example: -->
  <!-- <url type="website">http://wiki.ros.org/cv_bridge_tutorial_pkg</url> -->


  <!-- Author tags are optional, mutiple are allowed, one per tag -->
  <!-- Authors do not have to be maintianers, but could be -->
  <!-- Example: -->
  <!-- <author email="[email protected]">Jane Doe</author> -->


  <!-- The *_depend tags are used to specify dependencies -->
  <!-- Dependencies can be catkin packages or system dependencies -->
  <!-- Examples: -->
  <!-- Use build_depend for packages you need at compile time: -->
  <!--   <build_depend>message_generation</build_depend> -->
  <!-- Use buildtool_depend for build tool packages: -->
  <!--   <buildtool_depend>catkin</buildtool_depend> -->
  <!-- Use run_depend for packages you need at runtime: -->
  <!--   <run_depend>message_runtime</run_depend> -->
  <!-- Use test_depend for packages you need only for testing: -->
  <!--   <test_depend>gtest</test_depend> -->
  <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>


  <!-- The export tag contains other, unspecified, tags -->
  <export>
    <!-- Other tools can request additional information be placed here -->

  </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）！