python配合yolov11开发分类训练软件

1. 上一篇文件写了用yolo分类模型开发分类软件，这边文章在上个分类软件的基础上加入训练功能
2. 环境配置:pycharm，PySide6 6.6.1 ，PySide6-Addons 6.6.1，PySide6-Essentials 6.6.1，torch 2.3.1+cu121，torchaudio 2.3.1+cu121，torchvision 0.18.1+cu121，onnx 1.16.1，onnxruntime 1.17.3，opencv-contrib-python 4.10.0.82，opencv-python 4.10.0.82，opencv-python-headless 4.7.0.72
3. 分类使用的数据集，halcon的pill分类demo的数据集
   
   4.软件界面
   
   5.核心代码

    def TrainThrExecut(self):
        _monitor_train.TrainSimple = True
        imagedealwith._image_deal_with.Model = YOLO(imagedealwith._image_deal_with.TrainPreprocessModelPath)
        results = imagedealwith._image_deal_with.Model.train(
            data=imagedealwith._image_deal_with.TrainDataFolderPath,
            project=imagedealwith._image_deal_with.TrainDataSaveFolderPath,
            epochs=200,
            batch=4,
            imgsz=224,
            amp=False)
        print(results)
        sucess = imagedealwith._image_deal_with.Model.export(format='onnx')
        _monitor_train.TrainSimple = False
        imagedealwith._image_deal_with.ImageDealWithStatus = ImageDealWithStatusEnu.Inference
        self.pbtn_training.setText("Train")
        pass

    def MonitorTrainLogCallback(self,message):
        if(len(message)>0):
            self.tedit_training_message.append(message)
        pass

    def MonitorTrainLossCallback(self,message):
        if (len(message) > 0):
            self.tedit_training_loss.setText(message)
            pass
        pass

    def MonitorTrainEpochCallback(self,message):
        if (len(message) > 0):
            self.ledit_training_epoch.setText('epoch:'+message)
        pass

6.训练过程