Jetson Nano使用CSI摄像头教程（c++）

一、 人脸检测

C++下开发Opencv需要进行一些额外的配置，先看一下opencv的文件位置。Jetson Nano预装的Opencv4.1.1的头文件位置如下图所示：

库文件位置如下图所示：

只需要在Qt的pro文件中将上述两个目录包含进来。另外注意头文件和lib文件的添加方法。
QT的pro文件如下：

QT -= gui
 
CONFIG += c++11 console
CONFIG -= app_bundle
CONFIG += C++11  # 添加对C++11的支持
 
# The following define makes your compiler emit warnings if you use
# any feature of Qt which as been marked deprecated (the exact warnings
# depend on your compiler). Please consult the documentation of the
# deprecated API in order to know how to port your code away from it.
DEFINES += QT_DEPRECATED_WARNINGS
 
# You can also make your code fail to compile if you use deprecated APIs.
# In order to do so, uncomment the following line.
# You can also select to disable deprecated APIs only up to a certain version of Qt.
#DEFINES += QT_DISABLE_DEPRECATED_BEFORE=0x060000    # disables all the APIs deprecated before Qt 6.0.0
 
INCLUDEPATH += /usr/include/opencv4 #添加头文件路径
 
LIBS += -L/usr/lib/aarch64-linux-gnu -lopencv_core -lopencv_imgcodecs -lopencv_imgproc -lopencv_highgui -lopencv_objdetect  #添加需要链接的库
 
 
SOURCES += main.cpp

重新生成整个项目，然后将test.jpeg和haarcascade_frontalface_default.xml文件放置在编译生成的build-QTtest-unknown-Debug文件夹中，运行项目效果图如下所示：

二、读取CSI摄像头

使用C++编程读取CSI摄像头，可以看到已经可以正常的显示视频流图像了，但是由于树莓派摄像头本身的原因，其图像中还有很多的噪点，颜色也有些失真（真实工业场景中建议购买更好的摄像头）。C++版本的main.cpp文件如下：

#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 

using namespace std;
using namespace cv;

string gstreamer_pipeline (int capture_width, int capture_height, int display_width, int display_height, int framerate, int flip_method)
{
    return "nvarguscamerasrc ! video/x-raw(memory:NVMM), width=(int)" + to_string(capture_width) + ", height=(int)" +
           to_string(capture_height) + ", format=(string)NV12, framerate=(fraction)" + to_string(framerate) +
           "/1 ! nvvidconv flip-method=" + to_string(flip_method) + " ! video/x-raw, width=(int)" + to_string(display_width) + ", height=(int)" +
           to_string(display_height) + ", format=(string)BGRx ! videoconvert ! video/x-raw, format=(string)BGR ! appsink";
}

int main( int argc, char** argv )
{
    int capture_width = 1280 ;
    int capture_height = 720 ;
    int display_width = 1280 ;
    int display_height = 720 ;
    int framerate = 60 ;
    int flip_method = 0 ;

    //创建管道
    string pipeline = gstreamer_pipeline(capture_width,
    capture_height,
    display_width,
    display_height,
    framerate,
    flip_method);
    std::cout << "使用gstreamer管道: \n\t" << pipeline << "\n";

    //管道与视频流绑定
    VideoCapture cap(pipeline, CAP_GSTREAMER);
    if(!cap.isOpened())
    {
        std::cout<<"打开摄像头失败."<<std::endl;
        return (-1);
    }

    //创建显示窗口
    namedWindow("CSI Camera", WINDOW_AUTOSIZE);
    Mat img;

    //逐帧显示
    while(true)
    {
        if (!cap.read(img))
        {
            std::cout<<"捕获失败"<<std::endl;
            break;
        }
        int new_width,new_height,width,height,channel;
            width=img.cols;
            height=img.rows;
            channel=img.channels();


        //调整图像大小
        new_width=640;
        if(width>800)
          {
             new_height=int(new_width*1.0/width*height);
           }
         resize(img, img, cv::Size(new_width, new_height));

        imshow("CSI Camera",img);

        int keycode = cv::waitKey(30) & 0xff ; //ESC键退出
            if (keycode == 27) break ;
    }

    cap.release();
    destroyAllWindows() ;
}

其中需要额外的添加opencv用于视频处理的头文件#include 。另外，还需要修改对pro文件，将视频处理对应的opencv_videoio库包含进来，完整的pro文件如下：

QT -= gui

CONFIG += c++11 console
CONFIG -= app_bundle
CONFIG += C++11  # 添加对C++11的支持

# The following define makes your compiler emit warnings if you use
# any feature of Qt which as been marked deprecated (the exact warnings
# depend on your compiler). Please consult the documentation of the
# deprecated API in order to know how to port your code away from it.
DEFINES += QT_DEPRECATED_WARNINGS

# You can also make your code fail to compile if you use deprecated APIs.
# In order to do so, uncomment the following line.
# You can also select to disable deprecated APIs only up to a certain version of Qt.
#DEFINES += QT_DISABLE_DEPRECATED_BEFORE=0x060000    # disables all the APIs deprecated before Qt 6.0.0

INCLUDEPATH += /usr/include/opencv4 #添加头文件路径

LIBS += -L/usr/lib/aarch64-linux-gnu -lopencv_core -lopencv_imgcodecs -lopencv_imgproc -lopencv_highgui -lopencv_objdetect -lopencv_videoio  #添加需要链接的库


SOURCES += main.cpp

三、二维码检测和识读

本小节将使用Opencv实现二维码检测和识读功能。在opencv4.0以后，已经集成了二维码识读模块，因此，我们可以采用最新的opencv来实现二维码检测和识读。二维码检测和识别主要分为3步：使用QRCodeDetector()函数创建二维码检测器；使用detectAndDecode函数对图像进行二维码检测和识别；将检测结果输出。main.cpp文件如下

#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 

using namespace std;
using namespace cv;

string gstreamer_pipeline (int capture_width, int capture_height, int display_width, int display_height, int framerate, int flip_method)
{
    return "nvarguscamerasrc ! video/x-raw(memory:NVMM), width=(int)" + to_string(capture_width) + ", height=(int)" +
           to_string(capture_height) + ", format=(string)NV12, framerate=(fraction)" + to_string(framerate) +
           "/1 ! nvvidconv flip-method=" + to_string(flip_method) + " ! video/x-raw, width=(int)" + to_string(display_width) + ", height=(int)" +
           to_string(display_height) + ", format=(string)BGRx ! videoconvert ! video/x-raw, format=(string)BGR ! appsink";
}

int main( int argc, char** argv )
{
    int capture_width = 1280 ;
    int capture_height = 720 ;
    int display_width = 1280 ;
    int display_height = 720 ;
    int framerate = 60 ;
    int flip_method = 0 ;

    //创建管道
    string pipeline = gstreamer_pipeline(capture_width,
    capture_height,
    display_width,
    display_height,
    framerate,
    flip_method);
    std::cout << "使用gstreamer管道: \n\t" << pipeline << "\n";

    //管道与视频流绑定
    VideoCapture cap(pipeline, CAP_GSTREAMER);
    if(!cap.isOpened())
    {
        std::cout<<"打开摄像头失败."<<std::endl;
        return (-1);
    }

    //创建显示窗口
    namedWindow("CSI Camera", WINDOW_AUTOSIZE);
    Mat img;
    //创建二维码检测器
    QRCodeDetector qrDecoder = QRCodeDetector();

    //逐帧显示
    while(true)
    {
        if (!cap.read(img))
        {
            std::cout<<"捕获失败"<<std::endl;
            break;
        }
        int new_width,new_height,width,height,channel;
            width=img.cols;
            height=img.rows;
            channel=img.channels();


        //调整图像大小
        new_width=640;
        if(width>800)
          {
             new_height=int(new_width*1.0/width*height);
           }
         resize(img, img, cv::Size(new_width, new_height));
         
         //二维码检测和识读
         Mat bbox, rectifiedImage;
         std::string data = qrDecoder.detectAndDecode(img, bbox, rectifiedImage);
         if(data.length()>0)
         {
            cout << "解码数据: " << data << endl;

                  int n = bbox.rows;
                  for(int i = 0 ; i < n ; i++)
                  {
                      line(img, Point2i(bbox.at<float>(i,0),bbox.at<float>(i,1)), Point2i(bbox.at<float>((i+1) % n,0), bbox.at<float>((i+1) % n,1)), Scalar(255,0,0), 3);
                  }
                 }
          else
              cout << "没有检测到二维码" << endl;


        imshow("CSI Camera",img);

        int keycode = cv::waitKey(30) & 0xff ; //ESC键退出
            if (keycode == 27) break ;
    }

    cap.release();
    destroyAllWindows() ;
}