C#封装YOLOv4算法进行目标检测
概述
官网：/darknet/
Darknet：【Github】
C#封装代码：【Github】
YOLO: 是实现实时物体检测的系统，Darknet是基于YOLO的框架
采用C#语言对 YOLOv4 目标检测算法封装，将模型在实际应用系统中落地，实现模型在线远程调用。
环境准备
本章只讲解如何对YOLOv4封装进行详解，具体环境安装过程不做介绍
查看你的GPU计算能力是否支持 >= 3.0：【点击查看】
Windows运行要求
CMake >= 3.12: 【点击下载】 CUDA >= 10.0: 【点击下载】 OpenCV >= 2.4: 【点击下载】 cuDNN >= 7.0: 【点击下载】 Visual Studio /: 【点击下载】
我所使用的环境
系统版本：Windows 10 专业版 显卡：GTX 1050 Ti CMake版本：3.18.2 CUDA版本：10.1 OpenCV版本：4.4.0cuDNN版本：10.1 MSVC /: Visual Studio
程序代码准备
源代码下载
下载地址：【Darknet】
使用Git
git clone /AlexeyAB/darknetcd darknet
代码结构
将YOLOv4编译为DLL
详细教程：【点击查看】，这个教程描述的很详细。
进入darknetbuilddarknet目录，打开解决方案 yolo_cpp_dll.sln
设置Windows SDK版本和平台工具集为当前系统安装版本
设置Release和x64
然后执行以下操作：Build-> Build yolo_cpp_dll
已完成生成项目“yolo_cpp_dll.vcxproj”的操作。========== 生成: 成功 1 个，失败 0 个，最新 0 个，跳过 0 个 ==========
在打包DLL的过程中可能遇到如下问题
C1041无法打开程序数据库“D:代码管理Cdarknetbuilddarknetx64DLL_Releasevc142.pdb”；如果要将多个 CL.EXE 写入同一个 .PDB 文件，请使用 /FS yolo_cpp_dll C:UsersadministratorAppDataLocalTemptmpxft_00005db0_00000000-pute_75.cudafe1.cpp 1MSB3721 命令“"C:Program FilesNVIDIA GPU Computing ToolkitCUDAv10.1binnvcc.exe" -gencode=arch=compute_30,code="sm_30,compute_30" -gencode=arch=compute_75,code="sm_75,compute_75" --use-local-env -ccbin "C:Program Files (x86)Microsoft Visual StudioCommunityVCToolsMSVC14.27.29110binHostX86x64" -x cu -IC:opencvbuildinclude -IC:opencv_3.0opencvbuildinclude -I....include -I....3rdpartystbinclude -I....3rdpartypthreadsinclude -I"C:Program FilesNVIDIA GPU Computing ToolkitCUDAv10.1include" -I"C:Program FilesNVIDIA GPU Computing ToolkitCUDAv10.1include" -Iinclude -Iinclude -I"C:Program FilesNVIDIA GPU Computing ToolkitCUDAv10.1include"--keep-dir x64Release -maxrregcount=0 --machine 64 --compile -cudart static-DCUDNN_HALF -DCUDNN -DGPU -DLIB_EXPORTS -D_TIMESPEC_DEFINED -D_SCL_SECURE_NO_WARNINGS -D_CRT_SECURE_NO_WARNINGS -DWIN32 -DNDEBUG -D_CONSOLE -D_LIB -D_WINDLL -D_MBCS -Xcompiler "/EHsc /W3 /nologo /O2 /Fdx64DLL_Releasevc142.pdb /Zi /MD " -o x64DLL_Releasedropout_layer_kernels.cu.obj "D:darknetsrcdropout_layer_kernels.cu"”已退出，返回代码为 2。 yolo_cpp_dll C:Program Files (x86)Microsoft Visual StudioCommunityMSBuildMicrosoftVCv160BuildCustomizationsCUDA 10.1.targets 757
解决方法
在VS 工具》选项》项目和解决方案》生成并运行中最大并行项目生成数设为1
在VS 项目-》属性-》配置属性-》常规将Windows SDK版本设置为系统当前版本即可
封装YOLOv4编译后的DLL
1、进入darknetbuilddarknetx64目录，将pthreadGC2.dll和pthreadVC2.dll拷贝到项目Dll文件夹2、将编译后的YOLOv4 DLL文件拷贝到项目Dll文件夹3、进入darknetbuilddarknetx64cfg目录，将yolov4.cfg拷贝到项目Cfg文件夹4、进入darknetbuilddarknetx64data目录，将coco.names拷贝到项目Data文件夹5、下载 yolov4.weights 权重文件 拷贝到Weights文件夹，文件245 MB 【点击下载】项目文件
代码下载：【Github】
YoloWrapper- YOLOv4封装项目Cfg- 配置文件夹Data- label文件夹Dll- YOLOv4 编译后的DLL文件夹Weights- YOLOv4 权重文件夹BboxContainer.csBoundingBox.csYoloWrapper.cs- 封装主文件，调用 YOLOv4 的动态链接库YoloWrapperConsole- 调用封装DLL控制台程序Program.cs- 控制台主程序，调用 YOLOv4 封装文件
代码
YOLOv4封装项目
YoloWrapper.cs- 封装主文件，调用 YOLOv4 的动态链接库
using System;using System.Runtime.InteropServices;namespace YoloWrapper{public class YoloWrapper : IDisposable{private const string YoloLibraryName = @"Dllsyolo_cpp_dll.dll";[DllImport(YoloLibraryName, EntryPoint = "init")]private static extern int InitializeYolo(string configurationFilename, string weightsFilename, int gpu);[DllImport(YoloLibraryName, EntryPoint = "detect_image")]private static extern int DetectImage(string filename, ref BboxContainer container);[DllImport(YoloLibraryName, EntryPoint = "detect_mat")]private static extern int DetectImage(IntPtr pArray, int nSize, ref BboxContainer container);[DllImport(YoloLibraryName, EntryPoint = "dispose")]private static extern int DisposeYolo();public YoloWrapper(string configurationFilename, string weightsFilename, int gpu){InitializeYolo(configurationFilename, weightsFilename, gpu);}public void Dispose(){DisposeYolo();}public BoundingBox[] Detect(string filename){var container = new BboxContainer();var count = DetectImage(filename, ref container);return container.candidates;}public BoundingBox[] Detect(byte[] imageData){var container = new BboxContainer();var size = Marshal.SizeOf(imageData[0]) * imageData.Length;var pnt = Marshal.AllocHGlobal(size);try{Marshal.Copy(imageData, 0, pnt, imageData.Length);var count = DetectImage(pnt, imageData.Length, ref container);if (count == -1){throw new NotSupportedException($"{YoloLibraryName} has no OpenCV support");}}catch (Exception exception){return null;}finally{Marshal.FreeHGlobal(pnt);}return container.candidates;}}}
BboxContainer.cs
using System.Runtime.InteropServices;namespace YoloWrapper{[StructLayout(LayoutKind.Sequential)]public struct BboxContainer{[MarshalAs(UnmanagedType.ByValArray, SizeConst = 1000)]public BoundingBox[] candidates;}}
BoundingBox.cs
using System;using System.Runtime.InteropServices;namespace YoloWrapper{[StructLayout(LayoutKind.Sequential)]public struct BoundingBox{public UInt32 x, y, w, h;public float prob;public UInt32 obj_id;public UInt32 track_id;public UInt32 frames_counter;public float x_3d, y_3d, z_3d;}}
调用封装DLL控制台程序
BoundingBox.cs
using ConsoleTables;using System;using System.Collections.Generic;using System.IO;using System.Linq;using YoloWrapper;namespace YoloWrapperConsole{class Program{private const string configurationFilename = @".Cfgyolov4.cfg";private const string weightsFilename = @".Weightsyolov4.weights";private const string namesFile = @".Datacoco.names";private static Dictionary<int, string> _namesDic = new Dictionary<int, string>();private static YoloWrapper.YoloWrapper _wrapper;static void Main(string[] args){Initilize();Console.Write("ImagePath：");string imagePath = Console.ReadLine();var bbox = _wrapper.Detect(imagePath);Convert(bbox);Console.ReadKey();}private static void Initilize(){_wrapper = new YoloWrapper.YoloWrapper(configurationFilename, weightsFilename, 0);var lines = File.ReadAllLines(namesFile);for (var i = 0; i < lines.Length; i++)_namesDic.Add(i, lines[i]);}private static void Convert(BoundingBox[] bbox){Console.WriteLine("Result：");var table = new ConsoleTable("Type", "Confidence", "X", "Y", "Width", "Height");foreach (var item in bbox.Where(o => o.h > 0 || o.w > 0)){var type = _namesDic[(int)item.obj_id];table.AddRow(type, item.prob, item.x, item.y, item.w, item.h);}table.Write(Format.MarkDown);}}}
