[C#]C# winform部署yolov13目标检测的onnx模型

发布于:2025-07-02 ⋅ 阅读:(17) ⋅ 点赞:(0)

yolov13官方框架:github.com/iMoonLab/yolov13/releases/tag/yolov13

【测试环境】

vs2019

netframework4.7.2

opencvsharp4.8.0

onnxruntime==1.16.3

【效果展示】

【调用代码】

using System;
using System.Collections.Generic;
using System.ComponentModel;
using System.Data;
using System.Diagnostics;
using System.Drawing;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using System.Windows.Forms;
using OpenCvSharp;

namespace FIRC
{
    public partial class Form1 : Form
    {
        Mat src = new Mat();
        Yolov13Manager ym = new Yolov13Manager();
        public Form1()
        {
            InitializeComponent();
        }

        private void button1_Click(object sender, EventArgs e)
        {
            OpenFileDialog openFileDialog = new OpenFileDialog();
            openFileDialog.Filter = "图文件(*.*)|*.jpg;*.png;*.jpeg;*.bmp";
            openFileDialog.RestoreDirectory = true;
            openFileDialog.Multiselect = false;
            if (openFileDialog.ShowDialog() == DialogResult.OK)
            {
              
                src = Cv2.ImRead(openFileDialog.FileName);
                pictureBox1.Image = OpenCvSharp.Extensions.BitmapConverter.ToBitmap(src);


            }


        }

        private void button2_Click(object sender, EventArgs e)
        {
            if(pictureBox1.Image==null)
            {
                return;
            }
            Stopwatch sw = new Stopwatch();
            sw.Start();
            var result = ym.Inference(src);
            sw.Stop();
            this.Text = "耗时" + sw.Elapsed.TotalSeconds + "秒";
            var resultMat = ym.DrawImage(result,src);
            pictureBox2.Image= OpenCvSharp.Extensions.BitmapConverter.ToBitmap(resultMat); //Mat转Bitmap
        }

        private void Form1_Load(object sender, EventArgs e)
        {
            ym.LoadWeights(Application.StartupPath+ "\\weights\\yolov12n.onnx", Application.StartupPath + "\\weights\\labels.txt");

        }

        private void btn_video_Click(object sender, EventArgs e)
        {
            var detector = new Yolov13Manager();
            detector.LoadWeights(Application.StartupPath + "\\weights\\yolov13n.onnx", Application.StartupPath + "\\weights\\labels.txt");
            VideoCapture capture = new VideoCapture(0);
            if (!capture.IsOpened())
            {
                Console.WriteLine("video not open!");
                return;
            }
            Mat frame = new Mat();
            var sw = new Stopwatch();
            int fps = 0;
            while (true)
            {

                capture.Read(frame);
                if (frame.Empty())
                {
                    Console.WriteLine("data is empty!");
                    break;
                }
                sw.Start();
                var result = detector.Inference(frame);
                var resultImg = detector.DrawImage(result,frame);
                sw.Stop();
                fps = Convert.ToInt32(1 / sw.Elapsed.TotalSeconds);
                sw.Reset();
                Cv2.PutText(resultImg, "FPS=" + fps, new OpenCvSharp.Point(30, 30), HersheyFonts.HersheyComplex, 1.0, new Scalar(255, 0, 0), 3);
                //显示结果
                Cv2.ImShow("Result", resultImg);
                int key = Cv2.WaitKey(10);
                if (key == 27)
                    break;
            }

            capture.Release();
  
        }
    }
}

【运行步骤】

(1)首先依据官方安装教程或者其他网站给的安装教程,安装好yolov13环境

(2)下载模型:yolov13n.pt
(3)导出onnx模型:yolo export model=yolov13n.pt format=onnx dynamic=False opset=12
(4)然后将yolov13.onnx模型放进FIRC\bin\x64\Debug\weights
最后运行项目选择x64 Debug即可,由于初次运行可能报错,如果报错请查看blog.csdn.net/FL1623863129/article/details/135424751
解决方法

【视频演示】

bilibili.com/video/BV1GaKRzrEC4/