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_CheckedChanged
        private 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OK
                return;
            }
        }

        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;
        }



        #endregion

        private void btn_time_Click(object sender, EventArgs e)
        {
            log.print();
        }

        
    }
}

效果演示