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YOLOv8 adds MobileViTv3 module

By integrating the YOLOv8 algorithm, developed with the PyTorch framework, and incorporating the Vision Transformer (VIT) module, we have successfully enhanced the mean Average Precision (mAP) by 1%.

通过整合YOLOv8算法,使用PyTorch框架进行开发,并引入Vision Transformer(VIT)模块,我们成功提升了模型的平均精度(mAP)1%。

How to use

  • pip install -r requirements.txt
  • Modify the address of the dataset in the data.jaml file(修改data.yaml文件中数据集的地址)
  • python train_det

I have detailed explanation links in CSND: https://blog.csdn.net/W_extend/article/details/140927579

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