C# OpenVino Yolov8 Pose 姿态识别

目录

效果

模型信息

项目

代码

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说明

效果

图片源自网络侵删 

模型信息

Model Properties
-------------------------
date：2023-09-07T17:11:43.091306
description：Ultralytics YOLOv8n-pose model trained on /usr/src/app/ultralytics/datasets/coco-pose.yaml
author：Ultralytics
kpt_shape：[17, 3]
task：pose
license：AGPL-3.0 https://ultralytics.com/license
version：8.0.172
stride：32
batch：1
imgsz：[640, 640]
names：{0: 'person'}
---------------------------------------------------------------

Inputs
-------------------------
name：images
tensor：Float[1, 3, 640, 640]
---------------------------------------------------------------

Outputs
-------------------------
name：output0
tensor：Float[1, 56, 8400]
---------------------------------------------------------------

项目

代码

// 图片缩放
Mat image = new Mat(image_path);
int max_image_length = image.Cols > image.Rows ? image.Cols : image.Rows;
Mat max_image = Mat.Zeros(new OpenCvSharp.Size(max_image_length, max_image_length), MatType.CV_8UC3);
Rect roi = new Rect(0, 0, image.Cols, image.Rows);
image.CopyTo(new Mat(max_image, roi));

float[] result_array = new float[8400 * 56];
float[] factors = new float[2];
factors[0] = factors[1] = (float)(max_image_length / 640.0);

byte[] image_data = max_image.ImEncode(".bmp");
//存储byte的长度
ulong image_size = Convert.ToUInt64(image_data.Length);
// 加载推理图片数据
core.load_input_data("images", image_data, image_size, 1);

dt1 = DateTime.Now;
// 模型推理
core.infer();
dt2 = DateTime.Now;

// 读取推理结果
result_array = core.read_infer_result("output0", 8400 * 56);

using System;
using System.Collections.Generic;
using System.ComponentModel;
using System.Data;
using System.Drawing;
using System.Linq;
using System.Text;
using System.Windows.Forms;
using OpenCvSharp;
 
namespace OpenVino_Yolov8_Demo
{
    public partial class Form1 : Form
    {
        public Form1()
        {
            InitializeComponent();
        }
 
        string fileFilter = "*.*|*.bmp;*.jpg;*.jpeg;*.tiff;*.tiff;*.png";
        string image_path = "";
 
        String startupPath;
 
        DateTime dt1 = DateTime.Now;
        DateTime dt2 = DateTime.Now;
        String model_path;
        StringBuilder sb = new StringBuilder();
        Core core;
        Mat image;
        PoseResult result_pro;
 
        private void button1_Click(object sender, EventArgs e)
        {
            OpenFileDialog ofd = new OpenFileDialog();
            ofd.Filter = fileFilter;
            if (ofd.ShowDialog() != DialogResult.OK) return;
            pictureBox1.Image = null;
            image_path = ofd.FileName;
            pictureBox1.Image = new Bitmap(image_path);
            textBox1.Text = "";
            image = new Mat(image_path);
        }
 
        private void button2_Click(object sender, EventArgs e)
        {
            if (image_path == "")
            {
                return;
            }
            // 配置图片数据
            Mat image = new Mat(image_path);
            int max_image_length = image.Cols > image.Rows ? image.Cols : image.Rows;
            Mat max_image = Mat.Zeros(new OpenCvSharp.Size(max_image_length, max_image_length), MatType.CV_8UC3);
            Rect roi = new Rect(0, 0, image.Cols, image.Rows);
            image.CopyTo(new Mat(max_image, roi));
 
            float[] result_array = new float[8400 * 56];
            float[] factors = new float[2];
            factors[0] = factors[1] = (float)(max_image_length / 640.0);
 
            byte[] image_data = max_image.ImEncode(".bmp");
            //存储byte的长度
            ulong image_size = Convert.ToUInt64(image_data.Length);
            // 加载推理图片数据
            core.load_input_data("images", image_data, image_size, 1);
 
            dt1 = DateTime.Now;
            // 模型推理
            core.infer();
            dt2 = DateTime.Now;
 
            // 读取推理结果
            result_array = core.read_infer_result<float>("output0", 8400 * 56);
 
            result_pro = new PoseResult(factors);
            Mat result_image = result_pro.draw_result(result_pro.process_result(result_array), image.Clone());
 
            pictureBox2.Image = new Bitmap(result_image.ToMemoryStream());
            textBox1.Text = "耗时:" + (dt2 - dt1).TotalMilliseconds + "ms";
        }
 
        private void Form1_Load(object sender, EventArgs e)
        {
            startupPath = System.Windows.Forms.Application.StartupPath;
            model_path = startupPath + "\\yolov8n-pose.onnx";
            core = new Core(model_path, "CPU");
        }
 
        private void Form1_FormClosing(object sender, FormClosingEventArgs e)
        {
            core.delet();
        }
    }
}

下载 

源码下载

说明

1、运行路径中不能包含中文，否则模型加载不成功，程序无法运行

2、如果提示“无法加载 DLL“OpenVinoSharpExtern.dll”: 找不到指定的模块。 (异常来自 HRESULT:0x8007007E)。”，请使用depends22_x64等工具查找缺失的依赖库并添加。

也可下载源码自己本地编译，下载地址：https://download.csdn.net/download/lw112190/88806702

实在自己搞不定的，可是使用Sdcb.OpenVINO，地址：https://lw112190.blog.csdn.net/article/details/136051868