[C#]C# winform部署yolov12目标检测的onnx模型
yolov12官方框架:github.com/sunsmarterjie/yolov12
【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();
Yolov12Manager ym = new Yolov12Manager();
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 Yolov12Manager();
detector.LoadWeights(Application.StartupPath + "\\weights\\yolov12n.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yolov12环境
(2)下载模型:yolov12n.pt或者直接下载yolov12n.onnx
(3)导出onnx模型:yolo export model=yolov12n.pt format=onnx dynamic=False opset=12
(4)然后将yolov12.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】
www.bilibili.com/video/BV1RVAbeqEXa/