摄像头:1个;
USB数据线:1个;
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。
#include
#include
#include
#include
#include
#include
#include
#include
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 feed
image_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 stream
if (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 faces
std::vector 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("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, "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。
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
cv_bridge_tutorial_pkg
0.0.0
The cv_bridge_tutorial_pkg package
lentin
TODO
catkin
cv_bridge
image_transport
roscpp
sensor_msgs
std_msgs
cv_bridge
image_transport
roscpp
sensor_msgs
std_msgs
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)!