【必备技能】机器视觉C#开发者低代码开发OpenCV算法
更多参考资料猛戳这里 《OpenCV4 C# 系统化开发》
OpenCV C# 概述
OpenCV4已经支持多种开发语言包含C++、Java、Python、C#、JS等开发语言。其中工业界最常用的两种OpenCV SDK分别是C++与C#。在机器视觉行业中80%的项目开发以C#语言为主,所以掌握OpenCV C#开发对每个上位机开发者与机器视觉算法开发者尤为重要。
环境配置与测试
VS2022 + OpenCVCSharp4.10配置安装与测试
OpenCV支持C#语言SDK是通过开源OpenCV Wapper库支持opencvsharp框架实现,github地址如下:
https://github.com/shimat/opencvsharp
用 opencvsharp 就可以跟Python、C++一样轻松在C#语言中使用OpenCV SDK完成各种图像处理与深度学习模型推理部署。

从VS2022中直接安装,截图如下:


代码测试
安装好OpenCVCSharp开发包支持以后,直接创建一个C#语言的控制台空项目,然后创建一个cs文件,把下面的代码直接贴进去
using OpenCvSharp;
class Program
{
static void Main()
{
using var src = new Mat("D:/lena.png", ImreadModes.Grayscale);
using var dst = new Mat();
Cv2.Canny(src, dst, 50, 200);
using (new Window("src image", src))
using (new Window("dst image", dst))
{
Cv2.WaitKey();
}
}
}

OpenCV C#工作流引擎 - 高效OpenCV C#开发
OpenCV C# 工作流引擎,轻松帮助机器视觉与C#上位机开发者提升OpenCV开发能力,低代码轻松实现OpenCV模板匹配、卡尺测量、深度学习模型部署、轮廓分析等多种OpenCV操作。工作流引擎SDK下载地址:
https://gitee.com/opencv_ai/opencv_workflow
首先从这里下载OpenCV工作流SDK开发包,解压缩之后把DLL文件拷贝到对应的C#项目的bin目录里面。
首先实现一个多目标多角度多尺度的模板匹配,OpenCV实验大师中导出对应的OpenCV算法工作流文件以后,直接在C#中调用代码如下:
public void run_workflow_ncc_match()
{
//1.create instance
IntPtr myInstance = OEMTSWorkflowHelper.workflowClassInit2();
// 2.load workflow file
bool succ = OEMTSWorkflowHelper.loadVMConfigFile(myInstance, "D:/match_template_test.vm".ToCharArray(), "ba8e9ea82fb37f1722ad2d9f4962e7e4".ToCharArray());
// 3.run workflow with input image
Mat src = Cv2.ImRead("D:/test001.bmp");
Mat dst = new Mat(src.Size(), src.Type());
int w = src.Cols;
int h = src.Rows;
OEMTSWorkflowHelper.runWorkflow(myInstance, src.CvPtr, dst.CvPtr, w, h);
int num = OEMTSWorkflowHelper.getNumOfMatchedBoxes(myInstance);
OEMTSWorkflowHelper.TplBoxInfoWrapper[] tplBoxInfo;
tplBoxInfo = new OEMTSWorkflowHelper.TplBoxInfoWrapper[num];
OEMTSWorkflowHelper.getWrapperMatchedBoxInfos(myInstance, tplBoxInfo);
Console.WriteLine("get num of matched boxes " + num);
for (int i = 0; i < num; i++)
{
Console.WriteLine("box.x: " + tplBoxInfo[i].x);
Console.WriteLine("box.y: " + tplBoxInfo[i].y);
Console.WriteLine("box score: " + tplBoxInfo[i].score);
Console.WriteLine("box angle: " + tplBoxInfo[i].angle);
}
// 4.display result image
Cv2.ImShow("OpenCV学堂-工作流引擎SDK之边缘模板匹配演示", dst);
Cv2.ImShow("input", src);
Cv2.WaitKey(0);
Cv2.DestroyAllWindows();
// 5.release resource
src.Release();
dst.Release();
OEMTSWorkflowHelper.deleWorkflowInstance(myInstance);
}

再实现一个OpenCV的二值图像分析,OpenCV实验大师中导出对应的OpenCV算法工作流文件以后,直接在C#中调用代码如下:
public void run_ca_workflow()
{
//1.create instance
IntPtr myInstance = OEMTSWorkflowHelper.workflowClassInit2();
// 2.load workflow file
bool succ = OEMTSWorkflowHelper.loadVMConfigFile(myInstance, "D:/contours_analysis_demo.vm".ToCharArray(), "ba8e9ea82fb37f1722ad2d9f4962e7e4".ToCharArray());
// 3.run workflow with input image
Mat src = Cv2.ImRead("D:/2.jpg");
Mat dst = new Mat(src.Size(), src.Type());
int w = src.Cols;
int h = src.Rows;
OEMTSWorkflowHelper.runWorkflow(myInstance, src.CvPtr, dst.CvPtr, w, h);
int num = OEMTSWorkflowHelper.getNumOfContours(myInstance);
Console.WriteLine("get num of contours: " + num);
// retrieve the contour information
OEMTSWorkflowHelper.ContourInfoWrapper[] contoursInfo =
new OEMTSWorkflowHelper.ContourInfoWrapper[num];
OEMTSWorkflowHelper.getWrapperContoursInfo(myInstance, contoursInfo);
for(int i=0; i< contoursInfo.Length; i++)
{
Console.WriteLine(i + "th contour info as below");
Console.WriteLine("roundness: " + contoursInfo[i].roundness);
Console.WriteLine("contour area: " + contoursInfo[i].area);
}
// 4.display result image
Cv2.ImShow("OpenCV学堂-工作流引擎SDK之轮廓分析", dst);
Cv2.ImShow("input", src);
Cv2.WaitKey(0);
Cv2.DestroyAllWindows();
// 5.release resource
src.Release();
dst.Release();
OEMTSWorkflowHelper.deleWorkflowInstance(myInstance);
}

总结:
只需要调用几行OpenCV工作流SDK接口代码,就可以实现在C#上位机中完成各种OpenCV算法的集成调用,非常容易上手。通过调用几行相同的OpenCV工作流SDK接口代码即可实现C#上位机跟OpenCV算法的集成。更多参考资料猛戳这里 《OpenCV4 C# 系统化开发》
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