yolov5实例分割跑通以及C#读取yolov5_Seg实例分割转换onnx进行检测部署

一、首先需要训练yolov5_seg的模型，可以去网上学习，或者你直接用我的，

训练环境和yolov5—7.0的环境一样，你可以直接拷过来用。

yolov5_seg算法

链接：https://pan.baidu.com/s/1m-3lFWRHwg5t8MmIOKm4FA
提取码：6qiz

或者你直接下载我的环境，都喂你嘴里，就看你吃不吃了，

标注就用pip安装labelme就行

yolov5_seg算法的环境

链接：https://pan.baidu.com/s/1mwl2poblQUuFEwSpE2dvqA
提取码：age7

然后训练完成后

转化onnx 用export.py 转化就行

二、部署

下载源码这是一个大佬的代码里面什么都有

https://github.com/guojin-yan/YoloDeployCsharp.git

打开vs2022

安装 OpenCvSharp4 相关的包

openvino 相关的包

剩下的少什么就下载什么就行了

你可能会报错这个错是因为你的框架是net4.6.1左右的但是框架换到net6.0就不会错

修改的方法就是

将这里的

\bin\Debug\dll\win-x64

所有dll库复制到带有.exe的文件夹中

也就是 \bin\Debug 中就可以了

更改参数：

打开

Score_Threshold 置信度也就是小于此值的都被滤掉

NMS_Threshold 非极大值抑制的值，确定框的数量

classes_count_1 类别的个数你有多少类别你就设置几个

W_H_size_1宽高设定

class_names 是你的类别名

然后我们右键dll程序，生成dll库

将YoloSegDll_all\src\YoloV5_Seg_dll\obj\Debug\YoloV5_Seg_dll.dll路径下的dll文件

引用到控件程序中

主程序代码如下

using Microsoft.ML.OnnxRuntime;
using OpenCvSharp;
using OpenVinoSharp.Extensions.result;
using OpenVinoSharp.Extensions.process;
using SharpCompress.Common;
using System;
using System.Collections.Generic;
using System.ComponentModel;
using System.Data;
using System.Diagnostics;
using System.Drawing;
using System.IO;
using System.Linq;
using System.Text;
using System.Threading;
using System.Threading.Tasks;
using System.Timers;
using System.Windows.Forms;
using YoloDeployPlatform;
using YoloDeployPlatform.predictor;
using Timer = System.Windows.Forms.Timer;
using OpenVinoSharp;
using System.Security.Cryptography;
using YoloDeployPlatform.Properties;namespace YoloDeployPlatform
{public partial class YoloDeployPlatform : Form{private YOLO yolo = new YOLO();private Log log = Log.Instance;private Stopwatch sw = new Stopwatch();private List<string> class_names= new List<string>();private VideoCapture video;private Timer video_timer = new Timer();private bool timerRunning = false;private string infer_type = "det"; public YoloDeployPlatform(){InitializeComponent();}//===============================标签===============已封装为库中===========================//private void btn_class_select_Click(object sender, EventArgs e)//{//    //OpenFileDialog dlg = new OpenFileDialog();//    classesLabel label = new classesLabel();//    List<string> classes_name = label.class_names;//}//########################## 输入图片 ##########################//private void btn_input_select_Click(object sender, EventArgs e)//{//    OpenFileDialog dlg = new OpenFileDialog();//    if (dlg.ShowDialog() == DialogResult.OK)//    {//        string filePath = "";//        filePath=dlg.FileName;//    }//}#region RadioButton_CheckedChangedprivate void rb_openvino_CheckedChanged(object sender, EventArgs e){if (rb_openvino.Checked) {cb_device.Items.Clear();cb_device.Items.AddRange(new object[] { "AUTO", "CPU", "GPU.0", "GPU.1" });cb_device.SelectedIndex = 1;}}private void rb_opencv_CheckedChanged(object sender, EventArgs e){if (rb_opencv.Checked){cb_device.Items.Clear();cb_device.Items.AddRange(new object[] { "CPU"});cb_device.SelectedIndex = 0;}}#endregion//##############################  模型读取 &  模型推理 #########################################private void btn_load_model_Click(object sender, EventArgs e){//读取图片OpenFileDialog dlg = new OpenFileDialog();string filePath = "";if (dlg.ShowDialog() == DialogResult.OK){//tb_input_path.Text = dlg.FileName;filePath = dlg.FileName;}//YOLOv5Seg gb_model = new YOLOv5Seg;string model_type_str = check_rb(gb_model.Controls);if (model_type_str == ""){show_worn_msg_box("Please select a model category.");return;}string engine_type_str = check_rb(gb_engine.Controls);if (engine_type_str == ""){show_worn_msg_box("Please select an inference engine.");return;}ModelType model_type = MyEnum.GetModelType<ModelType>(model_type_str);EngineType engine_type = MyEnum.GetEngineType<EngineType>(engine_type_str);if ((model_type == ModelType.YOLOv5Seg)){infer_type = "seg";}//================================ model read =======================================//string model_path = tb_model_path.Text;string model_path = "F:\\Desk\\models\\bestsegMd.onnx";string device = cb_device.SelectedItem.ToString();string extension = Path.GetExtension(model_path);yolo.Dispose();//####################################### 阈 值 #################################//classesLabel my = new classesLabel();float score = my.Score_Threshold;float nms = my.NMS_Threshold;//int categ_num = my.classes_count_1;int categ_num = 1;int input_size = my.W_H_size_1;yolo = YOLO.GetYolo(model_type, model_path, engine_type, device, categ_num, score, nms, input_size);//############################# 图片处理阶段 ################################################DateTime start = DateTime.Now;//string input_path = filePath;Mat img = Cv2.ImRead(filePath);sw.Restart();pictureBox1.BackgroundImage = OpenCvSharp.Extensions.BitmapConverter.ToBitmap(img);Mat re_img = image_predict(img);sw.Stop();pictureBox2.BackgroundImage = OpenCvSharp.Extensions.BitmapConverter.ToBitmap(re_img);//DateTime end = DateTime.Now;//label1.Text = "耗时：" + (end - start).TotalMilliseconds.ToString();label2.Text = sw.ElapsedMilliseconds.ToString();}#region private string check_rb(Control.ControlCollection controls){string key = "";foreach (Control ctr in controls){if (ctr is RadioButton && (ctr as RadioButton).Checked){key = ctr.Text;}}return key;}private void show_worn_msg_box(string message){string caption = "Warning";MessageBoxButtons buttons = MessageBoxButtons.OK; // 设置按钮MessageBoxIcon icon = MessageBoxIcon.Warning; // 设置图标DialogResult result = MessageBox.Show(this, message, caption, buttons, icon);// 根据用户的点击按钮处理逻辑if (result == DialogResult.OK){// 用户点击了OKreturn;}}Mat image_predict(Mat img, bool is_video = false){Mat re_img = new Mat();BaseResult result;if (log.flag_time && !is_video){log.flag_time = false;yolo.predict(img);log.flag_time = true;result = yolo.predict(img);}else{result = yolo.predict(img);}if (class_names.Count > 0){result.update_lable(class_names);}re_img = Visualize.draw_seg_result(result, img);//}if (log.flag_time && log.flag_fps){Cv2.Rectangle(re_img, new OpenCvSharp.Point(30, 20), new OpenCvSharp.Point(250, 60),new Scalar(0.0, 255.0, 255.0), -1);Cv2.PutText(re_img, "FPS: " + (1000.0 / log.infer_time).ToString("0.00"), new OpenCvSharp.Point(50, 50),HersheyFonts.HersheySimplex, 0.8, new Scalar(0, 0, 0), 2);}return re_img;}#endregionprivate void btn_time_Click(object sender, EventArgs e){log.print();}}
}

效果演示