Pylon5 SDK搭配OpenCV使用入门

本文假设已经安装了Basler官网提供的Pylon

目前最新的版本是5.0.5,如果上述链接打不开，请直接所有Basler官网下载，需要注意的是在安装Pylon5时要选择Developer模式，这样才会安装关于pylon5 SDK开发包，安装完可以到安装路径下找到，软件也会自动将一些路径自动添加到系统环境变量。

使用Pylon5 SDK开发与使用OpenCV开发一些功能流程一样，无非是引入包目录（include）和库包含目录(lib),本文使用的OpenCV版本为2.4.9.。。关于工程如何配置，我不想说话，只扔出两张属性表。
Pylon.props

<?xml version="1.0" encoding="utf-8"?>
<Project ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
  <ImportGroup Label="PropertySheets" />
  <PropertyGroup Label="UserMacros" />
  <PropertyGroup />
  <ItemDefinitionGroup>
    <ClCompile>
      <AdditionalIncludeDirectories>$(PYLON_DEV_DIR)include;%(AdditionalIncludeDirectories)</AdditionalIncludeDirectories>
    </ClCompile>
    <Link>
      <AdditionalLibraryDirectories>$(PYLON_DEV_DIR)libwin32;%(AdditionalLibraryDirectories)</AdditionalLibraryDirectories>
    </Link>
  </ItemDefinitionGroup>
  <ItemGroup />
</Project>

OpenCVConsole.props

<?xml version="1.0" encoding="utf-8"?>
<Project ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
  <ImportGroup Label="PropertySheets" />
  <PropertyGroup Label="UserMacros" />
  <PropertyGroup>
    <IncludePath>$(OPENCV_ROOT)include;$(IncludePath)</IncludePath>
    <LibraryPath Condition="'$(Platform)'=='Win32'">$(OPENCV_ROOT)x86vc12lib;$(LibraryPath)</LibraryPath>
    <LibraryPath Condition="'$(Platform)'=='X64'">$(OPENCV_ROOT)x64vc12lib;$(LibraryPath)</LibraryPath>
  </PropertyGroup>
  <ItemDefinitionGroup>
    <Link Condition="'$(Configuration)'=='Debug'">
      <AdditionalDependencies>opencv_calib3d249d.lib;opencv_contrib249d.lib;opencv_core249d.lib;opencv_features2d249d.lib;opencv_flann249d.lib;opencv_gpu249d.lib;opencv_highgui249d.lib;opencv_imgproc249d.lib;opencv_legacy249d.lib;opencv_ml249d.lib;opencv_nonfree249d.lib;opencv_objdetect249d.lib;opencv_ocl249d.lib;opencv_photo249d.lib;opencv_stitching249d.lib;opencv_superres249d.lib;opencv_ts249d.lib;opencv_video249d.lib;opencv_videostab249d.lib;%(AdditionalDependencies)</AdditionalDependencies>
    </Link>
    <Link Condition="'$(Configuration)'=='Release'">
      <AdditionalDependencies>opencv_calib3d249.lib;opencv_contrib249.lib;opencv_core249.lib;opencv_features2d249.lib;opencv_flann249.lib;opencv_gpu249.lib;opencv_highgui249.lib;opencv_imgproc249.lib;opencv_legacy249.lib;opencv_ml249.lib;opencv_nonfree249.lib;opencv_objdetect249.lib;opencv_ocl249.lib;opencv_photo249.lib;opencv_stitching249.lib;opencv_superres249.lib;opencv_ts249.lib;opencv_video249.lib;opencv_videostab249.lib;%(AdditionalDependencies)</AdditionalDependencies>
    </Link>
    <ClCompile>
      <PreprocessorDefinitions>_CRT_SECURE_NO_WARNINGS;%(PreprocessorDefinitions)</PreprocessorDefinitions>
    </ClCompile>
  </ItemDefinitionGroup>
  <ItemGroup />
</Project>

注意根据本机的库安装地址可能要修改上面的属性表文件，只需要到属性管理器窗口添加现有属性表就好了。如果没有属性窗口，请到VS视图菜单中打开。

使用Pylon5 SDK搭配OpenCV采集图像程序流程如下：

下面是完整的源代码，该工程使用Basler piA2400-17gc GigE 相机测试成功。

//定义是否保存图片
#define saveImages 1
//定义是否记录视频
#define recordVideo 1

// 加载OpenCV API
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/video/video.hpp>

//加载PYLON API.
#include <pylon/PylonIncludes.h>

#include<iostream>

#ifdef PYLON_WIN_BUILD
#include <pylon/PylonGUI.h>    
#endif

//命名空间.
using namespace Pylon;
using namespace cv;
using namespace std;
//定义抓取的图像数
static const uint32_t c_countOfImagesToGrab = 10;

void main()
{

    //Pylon自动初始化和终止
    Pylon::PylonAutoInitTerm autoInitTerm;
    try
    {
        //创建相机对象（以最先识别的相机）
        CInstantCamera camera(CTlFactory::GetInstance().CreateFirstDevice());
        // 打印相机的名称
        std::cout << "Using device " << camera.GetDeviceInfo().GetModelName() << endl;
        //获取相机节点映射以获得相机参数
        GenApi::INodeMap& nodemap = camera.GetNodeMap();
        //打开相机
        camera.Open();
        //获取相机成像宽度和高度
        GenApi::CIntegerPtr width = nodemap.GetNode("Width");
        GenApi::CIntegerPtr height = nodemap.GetNode("Height");

        //设置相机最大缓冲区,默认为10
        camera.MaxNumBuffer = 5;
        // 新建pylon ImageFormatConverter对象.
        CImageFormatConverter formatConverter;
        //确定输出像素格式
        formatConverter.OutputPixelFormat = PixelType_BGR8packed;
        // 创建一个Pylonlmage后续将用来创建OpenCV images
        CPylonImage pylonImage;

        //声明一个整形变量用来计数抓取的图像，以及创建文件名索引
        int grabbedlmages = 0;

        // 新建一个OpenCV video creator对象.
        VideoWriter cvVideoCreator;
        //新建一个OpenCV image对象.

        Mat openCvImage;
        // 视频文件名

        std::string videoFileName = "openCvVideo.avi";
        // 定义视频帧大小
        cv::Size frameSize = Size((int)width->GetValue(), (int)height->GetValue());

        //设置视频编码类型和帧率，有三种选择
        // 帧率必须小于等于相机成像帧率
        cvVideoCreator.open(videoFileName, CV_FOURCC('D', 'I', 'V','X'), 10, frameSize, true);
        //cvVideoCreator.open(videoFileName, CV_F0URCC('M','P',,4','2’), 20, frameSize, true);
        //cvVideoCreator.open(videoFileName, CV_FOURCC('M', '3', 'P', 'G'), 20, frameSize, true);


        // 开始抓取c_countOfImagesToGrab images.
        //相机默认设置连续抓取模式
        camera.StartGrabbing(c_countOfImagesToGrab, GrabStrategy_LatestImageOnly);

        //抓取结果数据指针
        CGrabResultPtr ptrGrabResult;

        // 当c_countOfImagesToGrab images获取恢复成功时，Camera.StopGrabbing() 
        //被RetrieveResult()方法自动调用停止抓取
    
        while (camera.IsGrabbing())

        {
            // 等待接收和恢复图像，超时时间设置为5000 ms.
            camera.RetrieveResult(5000, ptrGrabResult, TimeoutHandling_ThrowException);

            //如果图像抓取成功
            if (ptrGrabResult->GrabSucceeded())
            {
                // 获取图像数据
                cout <<"SizeX: "<<ptrGrabResult->GetWidth()<<endl;
                cout <<"SizeY: "<<ptrGrabResult->GetHeight()<<endl;

                //将抓取的缓冲数据转化成pylon image.
                formatConverter.Convert(pylonImage, ptrGrabResult);

                // 将 pylon image转成OpenCV image.
                openCvImage = cv::Mat(ptrGrabResult->GetHeight(), ptrGrabResult->GetWidth(), CV_8UC3, (uint8_t *) pylonImage.GetBuffer());

                //如果需要保存图片
                if (saveImages)
                {
                   std::ostringstream s;
                    // 按索引定义文件名存储图片
                   s << "image_" << grabbedlmages << ".jpg";
                   std::string imageName(s.str());
                    //保存OpenCV image.
                   imwrite(imageName, openCvImage);
                   grabbedlmages++;
                }

                //如果需要记录视频
                if (recordVideo)
                {
            
                    cvVideoCreator.write(openCvImage);
                }

                //新建OpenCV display window.
                namedWindow("OpenCV Display Window", CV_WINDOW_NORMAL); // other options: CV_AUTOSIZE, CV_FREERATIO
                //显示及时影像.
                imshow("OpenCV Display Window", openCvImage);

                // Define a timeout for customer's input in
                // '0' means indefinite, i.e. the next image will be displayed after closing the window.
                // '1' means live stream
                waitKey(0);

            }

        }            

    }
    catch (GenICam::GenericException &e)
    {
        // Error handling.
        cerr << "An exception occurred." << endl
            << e.GetDescription() << endl;
    }
    return;
}

参考文档：
Application_Note_Build_pylon_C++_Apps_with_Free_Visual_Studio_IDE
Getting_Started_with_pylon5_and_OpenCV