Basler工業(yè)相機(jī)網(wǎng)上資料少渊抽，寫的博客更少，當(dāng)時(shí)為了把這個(gè)Basler相機(jī)用起來零院，不知道耗費(fèi)了我多少心血溉跃。
查閱了Basler的官方文檔，還有各種語焉不詳?shù)牟┛兔欧啵K于能夠在Linux下調(diào)用Basler相機(jī)了喊积。
所以我決定寫一篇非常詳細(xì)的博客，好讓后來者少踩些坑玄妈。
我的第一個(gè)工業(yè)相機(jī)乾吻，據(jù)說這玩意要近萬塊錢
其實(shí)Linux下配置Basler攝像頭時(shí)和配置OpenCV時(shí)相差不大。
先去 官網(wǎng)下載對(duì)應(yīng)的安裝包
https://www.baslerweb.com/cn/sales-support/downloads/software-downloads/#type=pylonsoftware;version=all;os=windows
根據(jù)自己的系統(tǒng)選擇x86或者x86_64(即x64)版本拟蜻。
我的相機(jī)型號(hào)為acA1920-40gc绎签。
下載好后，對(duì)壓縮包進(jìn)行解壓操作酝锅，可以選擇解壓文件到自己選擇的目錄诡必，此處我們選擇默認(rèn)當(dāng)前目錄：
$ tar -xzvf pylon-5.0.***.tar.gz
解壓文件后，打開文件搔扁，里邊還有一個(gè)壓縮包爸舒，此壓縮包即為安裝文件，解壓此文件到/opt目錄下：
$ sudo tar -C /opt -xzvf pylon***armhf.tar.gz
安裝完畢后就開始在qtcreator中進(jìn)行配置稿蹲，以便在Qtcreator中調(diào)用該相機(jī)扭勉。
1、首先打開Qtcreator苛聘，如下圖所示涂炎，創(chuàng)建控制臺(tái)項(xiàng)目或者空項(xiàng)目：
————————————————————————————
2忠聚、然后打開.pro文件，在其中配置Basler相機(jī)：
先找到INCLUDEPATH的路徑：
（1）點(diǎn)開“計(jì)算機(jī)”唱捣，點(diǎn)開文件夾“opt”
（2）接著打開pylon5文件夾
那么INCLUDEPATH 的內(nèi)容為：
INCLUDEPATH += /opt/pylon5/include \
/opt/pylon5/include/pylon
例子：（下圖中我是把OpenCV和Basler一起配置）
——————————————————————————————————
3两蟀、寫好了INCLUDEPATH，再來寫LIBS震缭。
LIBS（我目前知道的）有2種寫法：
第一種是直接寫出路徑來：
例子：
LIBS += /usr/local/lib/libopencv_calib3d.so \
/usr/local/lib/libopencv_calib3d.so.3.2 \
/usr/local/lib/libopencv_calib3d.so.3.2.0 \
/usr/local/lib/libopencv_core.so \
第二種方法是先寫一個(gè)總的赂毯，再寫分的：
例子：
LIBS +=-L/opt/pylon5/lib64 \
-lbxapi-5.0.11 \
-lbxapi \
-lFirmwareUpdate_gcc_v3_0_Basler_pylon_v5_0 \
-lGCBase_gcc_v3_0_Basler_pylon_v5_0 \
-lGenApi_gcc_v3_0_Basler_pylon_v5_0 \
-lgxapi-5.0.11 \
這2種寫法都是一樣的，是通用的蛀序。
先找到LIB所在的路徑為 opt / pylon5 / lib64
可以看到里面有很多后綴為.so的文件欢瞪，把這些文件的路徑寫到.pro文件中就行了。
這里我把我總的.pro文件內(nèi)容貼出來徐裸，可供參考：
（我這里面同時(shí)配置了OpenCV和Basler，注意我的Basler的版本為5.0.11）
TEMPLATE = app
CONFIG += console c++11
CONFIG -= app_bundle
CONFIG -= qt
SOURCES += main.cpp
INCLUDEPATH += /usr/local/include \
/usr/local/include/opencv \
/usr/local/include/opencv2 \
/opt/pylon5/include \
/opt/pylon5/include/pylon
LIBS += /usr/local/lib/libopencv_calib3d.so \
/usr/local/lib/libopencv_calib3d.so.3.2 \
/usr/local/lib/libopencv_calib3d.so.3.2.0 \
/usr/local/lib/libopencv_core.so \
/usr/local/lib/libopencv_core.so.3.2 \
/usr/local/lib/libopencv_core.so.3.2.0 \
/usr/local/lib/libopencv_features2d.so \
/usr/local/lib/libopencv_features2d.so.3.2 \
/usr/local/lib/libopencv_features2d.so.3.2.0 \
/usr/local/lib/libopencv_flann.so \
/usr/local/lib/libopencv_flann.so.3.2 \
/usr/local/lib/libopencv_flann.so.3.2.0 \
/usr/local/lib/libopencv_highgui.so \
/usr/local/lib/libopencv_highgui.so.3.2 \
/usr/local/lib/libopencv_highgui.so.3.2.0 \
/usr/local/lib/libopencv_imgcodecs.so \
/usr/local/lib/libopencv_imgcodecs.so.3.2 \
/usr/local/lib/libopencv_imgcodecs.so.3.2.0 \
/usr/local/lib/libopencv_imgproc.so \
/usr/local/lib/libopencv_imgproc.so.3.2 \
/usr/local/lib/libopencv_imgproc.so.3.2.0 \
/usr/local/lib/libopencv_ml.so \
/usr/local/lib/libopencv_ml.so.3.2 \
/usr/local/lib/libopencv_ml.so.3.2.0 \
/usr/local/lib/libopencv_objdetect.so \
/usr/local/lib/libopencv_objdetect.so.3.2 \
/usr/local/lib/libopencv_objdetect.so.3.2.0 \
/usr/local/lib/libopencv_photo.so \
/usr/local/lib/libopencv_photo.so.3.2 \
/usr/local/lib/libopencv_photo.so.3.2.0 \
/usr/local/lib/libopencv_shape.so \
/usr/local/lib/libopencv_shape.so.3.2 \
/usr/local/lib/libopencv_shape.so.3.2.0 \
/usr/local/lib/libopencv_stitching.so \
/usr/local/lib/libopencv_stitching.so.3.2 \
/usr/local/lib/libopencv_stitching.so.3.2.0 \
/usr/local/lib/libopencv_superres.so \
/usr/local/lib/libopencv_superres.so.3.2 \
/usr/local/lib/libopencv_superres.so.3.2.0 \
/usr/local/lib/libopencv_video.so \
/usr/local/lib/libopencv_video.so.3.2 \
/usr/local/lib/libopencv_video.so.3.2.0 \
/usr/local/lib/libopencv_videoio.so \
/usr/local/lib/libopencv_videoio.so.3.2 \
/usr/local/lib/libopencv_videoio.so.3.2.0 \
/usr/local/lib/libopencv_videostab.so \
/usr/local/lib/libopencv_videostab.so.3.2 \
/usr/local/lib/libopencv_videostab.so.3.2.0 \
/usr/local/lib/libopencv_viz.so \
/usr/local/lib/libopencv_viz.so.3.2 \
/usr/local/lib/libopencv_viz.so.3.2.0 \
-L/opt/pylon5/lib64 \
-lbxapi-5.0.11 \
-lbxapi \
-lFirmwareUpdate_gcc_v3_0_Basler_pylon_v5_0 \
-lGCBase_gcc_v3_0_Basler_pylon_v5_0 \
-lGenApi_gcc_v3_0_Basler_pylon_v5_0 \
-lgxapi-5.0.11 \
-lgxapi \
-llog4cpp_gcc_v3_0_Basler_pylon_v5_0 \
-lLog_gcc_v3_0_Basler_pylon_v5_0 \
-lMathParser_gcc_v3_0_Basler_pylon_v5_0 \
-lNodeMapData_gcc_v3_0_Basler_pylon_v5_0 \
-lpylonbase-5.0.11 \
-lpylonbase \
-lpylonc-5.0.11 \
-lpylonc \
-lpylon_TL_bcon-5.0.11 \
-lpylon_TL_bcon \
-lpylon_TL_camemu-5.0.11 \
-lpylon_TL_camemu \
-lpylon_TL_gige-5.0.11 \
-lpylon_TL_gige \
-lpylon_TL_usb-5.0.11 \
-lpylon_TL_usb \
-lpylonutility-5.0.11 \
-lpylonutility \
-luxapi-5.0.11 \
-luxapi \
-lXmlParser_gcc_v3_0_Basler_pylon_v5_0 \
4啸盏、這樣配置好了.pro文件重贺，就能開始寫程序了。
在Linux中調(diào)用Basler攝像頭回懦，需要一段比較長(zhǎng)的代碼气笙，代碼如下：
//定義是否保存圖片
#define saveImages 0
//定義是否記錄視頻
#define recordVideo 0
// 加載OpenCV API
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/video/video.hpp>
#include<opencv2/opencv.hpp>
//加載PYLON API.
#include <pylon/PylonIncludes.h>
#include <pylon/gige/BaslerGigEInstantCamera.h> //自動(dòng)調(diào)節(jié)
//加載C++ 頭文件
#include<iostream>
//命名空間.
using namespace Pylon;
using namespace cv;
using namespace std;
using namespace Basler_GigECameraParams; //自動(dòng)調(diào)節(jié)
typedef Pylon::CBaslerGigEInstantCamera Camera_t; //自動(dòng)調(diào)節(jié)
typedef Camera_t::GrabResultPtr_t GrabResultPtr_t; //自動(dòng)調(diào)節(jié)
static const uint32_t c_countOfImagesToGrab = 2000;
int saveImage_flag=0; //保存一張圖片
int main()
{
cout<<"000"<<endl;
//Pylon自動(dòng)初始化和終止
Pylon::PylonAutoInitTerm autoInitTerm;
try
{
cout<<"0"<<endl;
// 原程序?qū)amera的定義
//CInstantCamera camera(CTlFactory::GetInstance().CreateFirstDevice());
CDeviceInfo info;
info.SetDeviceClass( Camera_t::DeviceClass());
// Create an instant camera object with the first found camera device that matches the specified device class.
Camera_t camera( CTlFactory::GetInstance().CreateFirstDevice( info));
cout<<"1"<<endl;
// 打印相機(jī)的名稱
std::cout << "Using device " << camera.GetDeviceInfo().GetModelName() << endl;
cout<<"2"<<endl;
//獲取相機(jī)節(jié)點(diǎn)映射以獲得相機(jī)參數(shù)
GenApi::INodeMap& nodemap = camera.GetNodeMap();
cout<<"3"<<endl;
//打開相機(jī)
camera.Open();
cout<<"4"<<endl;
//獲取相機(jī)成像寬度和高度
GenApi::CIntegerPtr width = nodemap.GetNode("Width");
GenApi::CIntegerPtr height = nodemap.GetNode("Height");
cout<<"5"<<endl;
//設(shè)置相機(jī)最大緩沖區(qū),默認(rèn)為10
camera.MaxNumBuffer = 5;
// 新建pylon ImageFormatConverter對(duì)象.
CImageFormatConverter formatConverter;
cout<<"6"<<endl;
//確定輸出像素格式
formatConverter.OutputPixelFormat = PixelType_BGR8packed;
// 創(chuàng)建一個(gè)Pylonlmage后續(xù)將用來創(chuàng)建OpenCV images
CPylonImage pylonImage;
cout<<"7"<<endl;
//聲明一個(gè)整形變量用來計(jì)數(shù)抓取的圖像，以及創(chuàng)建文件名索引
int grabbedlmages = 0;
// 新建一個(gè)OpenCV video creator對(duì)象.
VideoWriter cvVideoCreator;
//新建一個(gè)OpenCV image對(duì)象.
Mat openCvImage;
// 視頻文件名
cout<<"8"<<endl;
std::string videoFileName = "openCvVideo.avi";
// 定義視頻幀大小
cv::Size frameSize = Size((int)width->GetValue(), (int)height->GetValue());
cout<<"9"<<endl;
cout<<"Width: "<<frameSize.width<<endl;
cout<<"Height: "<<frameSize.height<<endl;
//設(shè)置視頻編碼類型和幀率怯晕，有三種選擇
// 幀率必須小于等于相機(jī)成像幀率!!!!
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);
cout<<"10"<<endl;
// 開始抓取c_countOfImagesToGrab images.
//相機(jī)默認(rèn)設(shè)置連續(xù)抓取模式
camera.StartGrabbing(-1, GrabStrategy_LatestImageOnly); //c_countOfImagesToGrab
//抓取結(jié)果數(shù)據(jù)指針
CGrabResultPtr ptrGrabResult;
// 當(dāng)c_countOfImagesToGrab images獲取恢復(fù)成功時(shí)潜圃，Camera.StopGrabbing()
//被RetrieveResult()方法自動(dòng)調(diào)用停止抓取
cout << "Initial Gain = " << camera.GainRaw.GetValue() << endl;
cout << "Initial exposure time = ";
cout << camera.ExposureTimeAbs.GetValue() << " us" << endl;
cout << "Initial balance ratio: ";
camera.BalanceRatioSelector.SetValue(BalanceRatioSelector_Red);
cout << "R = " << camera.BalanceRatioAbs.GetValue() << " ";
camera.BalanceRatioSelector.SetValue(BalanceRatioSelector_Green);
cout << "G = " << camera.BalanceRatioAbs.GetValue() << " ";
camera.BalanceRatioSelector.SetValue(BalanceRatioSelector_Blue);
cout << "B = " << camera.BalanceRatioAbs.GetValue() << endl;
while (camera.IsGrabbing())
{
// 等待接收和恢復(fù)圖像，超時(shí)時(shí)間設(shè)置為5000 ms.
camera.RetrieveResult(5000, ptrGrabResult, TimeoutHandling_ThrowException);
//如果圖像抓取成功
if (ptrGrabResult->GrabSucceeded())
{
// 獲取圖像數(shù)據(jù)
// cout <<"SizeX: "<<ptrGrabResult->GetWidth()<<endl;
// cout <<"SizeY: "<<ptrGrabResult->GetHeight()<<endl;
//將抓取的緩沖數(shù)據(jù)轉(zhuǎn)化成pylon image.
formatConverter.Convert(pylonImage, ptrGrabResult);
// 將 pylon image轉(zhuǎn)成OpenCV image.
openCvImage = cv::Mat(ptrGrabResult->GetHeight(), ptrGrabResult->GetWidth(), CV_8UC3, (uint8_t *) pylonImage.GetBuffer());
//如果需要保存圖片
if (saveImages)
{
std::ostringstream s;
// 按索引定義文件名存儲(chǔ)圖片
s << "image_" << grabbedlmages << ".jpg";
std::string imageName(s.str());
//保存OpenCV image.
imwrite(imageName, openCvImage);
grabbedlmages++;
}
//如果需要記錄視頻
if (recordVideo)
{
cvVideoCreator.write(openCvImage);
}
//新建OpenCV display window.
namedWindow("OpenCV Display Window", CV_WINDOW_NORMAL); // other options: CV_AUTOSIZE, CV_FREERATIO
//顯示及時(shí)影像.
if(!openCvImage.data)
{
cout<<"opencvImage fail"<<endl;
continue;
}
imshow("OpenCV Display Window", openCvImage);
if(saveImage_flag==0) //只保存一張圖片
{
imwrite("/home/fsac/2.jpg",openCvImage);
saveImage_flag=1;
}
// 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(10);
}
else
{
cout<<"圖像讀取失敗,即ptrGrabResult->GrabSucceeded()未成功"<<endl;
continue;
}
}
if(!camera.IsGrabbing())
cout<<"camera.IsGrabbing() is failed"<<endl;
}
catch (GenICam::GenericException &e)
{
// Error handling.
cerr << "An exception occurred." << endl
<< e.GetDescription() << endl;
}
return 0;
}
