C#基于yolov3的行人检测

Posted 2021-04-14 CSharp编程大全

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<bbox_t> 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<bbox_t> result = new List<bbox_t>(); 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<bbox_t>(); } 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<Bgr, byte> img = new Image<Bgr, byte>(@"C:\Users\admin\source\repos\WindowsFormsApp1\WindowsFormsApp1\bin\x64\Debug\Camera20200421194241118.jpg"); Image<Gray, byte> img1 = new Image<Gray, byte>(@"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<byte> showImage = new Matrix<byte>(img1.Height, img1.Width, 3); CvInvoke.CvtColor(img1, showImage, ColorConversion.Gray2Bgr); List<bbox_t> bboxes = new List<bbox_t>();  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<bbox_t> 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();;}