【官方框架地址】
https://github.com/ultralytics/ultralytics.git
【算法介绍】
YOLOv8 抛弃了前几代模型的 Anchor-Base。
YOLO 是一种基于图像全局信息进行预测的目标检测系统。自 2015 年 Joseph Redmon、Ali Farhadi 等人提出初代模型以来，领域内的研究者们已经对 YOLO 进行了多次更新迭代，模型性能越来越强大。现在，YOLOv8 已正式发布。
YOLOv8 是由小型初创公司 Ultralytics 创建并维护的，值得注意的是 YOLOv5 也是由该公司创建的。
【效果展示】
【实现部分代码】
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();Yolov8Manager ym = new Yolov8Manager();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(src,result);pictureBox2.Image= OpenCvSharp.Extensions.BitmapConverter.ToBitmap(resultMat); //Mat转Bitmap}private void Form1_Load(object sender, EventArgs e){ym.LoadWeights(Application.StartupPath+ "\\weights\\yolov8n.onnx", Application.StartupPath + "\\weights\\labels.txt");}}
}
【视频演示】
bilibili.com/video/BV1Pi4y1z7H3/
【源码下载】
【测试环境】
vs2019
netframework4.8
opencvsharp4.8.0
openvinosharp
注意无需额外安装openvino运行库直接可以运行
