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 YOLOdef 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= 0.2results=model.predict(img,conf=conf)passif __name__ == '__main__':TrainData()pass