Yolov8分类检测记录

1.先到github上下载，ultralytics源代码

2.pycharm新建一个项目

3.准备训练数据

数据的结构如下

不需要.yaml文件，代码会自动识别要分的类

4.创建一个训练文件

import torch
import random
import cv2
import numpy as np
import os
from ultralytics import YOLO

def TrainData():
    model = YOLO('D:\\Source\\SourceMe\\PythonProject\\TrainClassificationPill\\TrainClassificationPill\\yolov8x-cls.pt')
    results = model.train(data='D:\\Source\\SourceMe\\PythonProject\\TrainClassificationPill\\TrainClassificationPill\\Dataset', epochs=200,batch=4)
    sucess = model.export(format='onnx')
    print(results)

def TestModelUltralytics():
    model = YOLO("加载训练的.pt文件")
    img=cv2.imread("要检测的图片")
    yolo_classes=list(model.names.values())
    classes_ids=[yolo_classes.index(clas) for clas in yolo_classes]
    conf= 0.2
    results=model.predict(img,conf=conf)
    pass



if __name__ == '__main__':
    TrainData()
    pass