C#基于yolov3的行人检测

using System;
using System.Collections.Generic;
using System.Drawing;
using System.IO;
using System.Runtime.ExceptionServices;
using System.Runtime.InteropServices;
using System.Security;
using System.Threading.Tasks;
using System.Windows.Forms;
using Emgu.CV;
using Emgu.CV.CvEnum;
using Emgu.CV.Structure;


namespace WindowsFormsApp1
{
    public partial class Form1 : Form
    {
        private const string YoloLibraryName = @"D:\darknet-master (1)\darknet-master\build\darknet\x64\yolo_cpp_dll.dll";
        private const int MaxObjects = 1000;
        object ThreadLock = new object();


        [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(uint width, uint height, byte[] pArray, int nSize, ref BboxContainer container);


        //[DllImport(YoloLibraryName, EntryPoint = "adddd")]
        //private static extern int adddd(int a, int b, ref int result, byte[] pArray);


        [DllImport(YoloLibraryName, EntryPoint = "dispose")]
        private static extern int DisposeYolo();






        [StructLayout(LayoutKind.Sequential)]
        public struct BboxContainer
        {
            [MarshalAs(UnmanagedType.ByValArray, SizeConst = MaxObjects)]
            public bbox_t[] candidates;
        }
        [StructLayout(LayoutKind.Sequential)]
        public struct bbox_t
        {
            public UInt32 x, y, w, h;    // (x,y) - top-left corner, (w, h) - width & height of bounded box
            public float prob;                 // confidence - probability that the object was found correctly
            public UInt32 obj_id;        // class of object - from range [0, classes-1]
            public UInt32 track_id;      // tracking id for video (0 - untracked, 1 - inf - tracked object)
            public UInt32 frames_counter;
        };
        public Form1()
        {
            InitializeComponent();
        }


        private void Form1_Load(object sender, EventArgs e)
        {
            //Task.Run(() => InitYolo());
            InitYolo();
        }
        public static void InitYolo()
        {
           InitializeYolo(
                      Path.Combine(AppDomain.CurrentDomain.BaseDirectory, "yolo-obj.cfg"),
                      Path.Combine(AppDomain.CurrentDomain.BaseDirectory, "yolo-obj_best.weights"),
                      0);


        }


        [HandleProcessCorruptedStateExceptions]
        [SecurityCritical]
        public List Detect(int Height, int Width, 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((uint)Width, (uint)Height, imageData, imageData.Length, ref container);
                if (count == -1)
                {
                    throw new NotSupportedException(" has no OpenCV support");
                }


                List result = new List();
                for (int i = 0; i < count; i++)
                {
                    result.Add(container.candidates[i]);
                }
                return result;
            }


            catch (Exception exception)
            {
                Console.WriteLine("Error : ");
                Console.WriteLine(exception.Message);
                return new List();
            }
            finally
            {
                // Free the unmanaged memory.
                Marshal.FreeHGlobal(pnt); //不释放内存会报错
            }


        }


        private void button1_Click(object sender, EventArgs e)
        {
            //Image img = new Image(@"C:\Users\admin\source\repos\WindowsFormsApp1\WindowsFormsApp1\bin\x64\Debug\Camera20200421194241118.jpg");
            Image img1 = new Image(@"Camera20200421194241118.jpg");
 
            int Width, Height;
            Width = img1.Width;
            Height = img1.Height;
            while (Width % 4 != 0)
            {
                Width++;
            }
            CvInvoke.Resize(img1, img1, new Size(Width, Height), 0, 0, Inter.Lanczos4);
            Matrix showImage = new Matrix(img1.Height, img1.Width, 3);
            CvInvoke.CvtColor(img1, showImage, ColorConversion.Gray2Bgr);
            List bboxes = new List();
           
            lock (ThreadLock)                       //锁线程  
            {
                int byte_size = showImage.Rows * showImage.Cols * 3;
                byte[] img_data_in = new byte[byte_size];
                Array.Copy(showImage.Mat.GetData(), img_data_in, byte_size);
                //bboxes = Detect(showImage.Height, showImage.Width, img_data_in);//方法一
                bboxes = Detect(showImage.Height, showImage.Width, showImage.Bytes);//方法二
            }
            if (bboxes.ToArray().Length != 0)
            {
                //MessageBox.Show("1111");
            }


            foreach (var bbox in bboxes)
            {
                var color_red = new MCvScalar(0, 0, 255); // BGR
                var color_green = new MCvScalar(0, 255, 0);
                var color_yellow = new MCvScalar(0, 255, 255);
                Rectangle rect = new Rectangle((int)bbox.x, (int)bbox.y, (int)bbox.w, (int)bbox.h);
                if (bbox.obj_id == 0)
                {
                    CvInvoke.Rectangle(showImage, rect, color_yellow);
                }
                else if (bbox.obj_id == 2)
                {
                    CvInvoke.Rectangle(showImage, rect, color_green);
                }
                else
                {
                    CvInvoke.Rectangle(showImage, rect, color_red);
                }
            }
            pictureBox1.Image = showImage.Mat.Bitmap;


        }
    }
}

运行结果：

yolo_cpp_dll中的yolo_v2_class.cpp需要修改下构造函数detect_image

int detect_image(unsigned int width, unsigned int height, unsigned char* data, const size_t data_length, bbox_t_container &container)
{
    cv::Mat image = cv::Mat(height, width, CV_8UC3, data, 3 * width);
    //cv::imshow("test_img", image);
    //cv::waitKey(1);
    std::vector detection = detector->detect(image);
    for (size_t i = 0; i < detection.size() && i < C_SHARP_MAX_OBJECTS; ++i)
        container.candidates[i] = detection[i];
    return detection.size();;
}

.weights是yolo权重文件，.cfg是yolo的配置文件，此外还有yolo_cpp_dll.dll为yolo的库文件，都需要放置到程序运行目录下！