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Deep Learning Tools for Pytorch

Project description

Deep Learning Tools for Pytorch

Python >= 3.8

A package that contains tools for deep learning model. We add the registry class which can make developer use the registry method to manage their models or functions conveniently.

In other side, we will provide our work in classification task for developer, which can use the model directly.

Installation

pip install dlts

Example for using

from typing import Callable

from dlts import Registry

# Example usage
registry = Registry(registry_name="example_registry", base_type=Callable)

@registry.register("example_function")
def example_function(x: int) -> int:
    return x * 2

print(registry.get("example_function")(5))  # Output: 10
print(registry.keys())  # Output: dict_keys(['example_function'])

Papers

BibTex

@article{sheng2024lightweight,
  title={A lightweight hybrid model with location-preserving ViT for efficient food recognition},
  author={Sheng, Guorui and Min, Weiqing and Zhu, Xiangyi and Xu, Liang and Sun, Qingshuo and Yang, Yancun and Wang, Lili and Jiang, Shuqiang},
  journal={Nutrients},
  volume={16},
  number={2},
  pages={200},
  year={2024},
  publisher={MDPI}
}

Update

  • 0.0.2 - We add the EHFR-Net model in the tools.
  • 0.0.1 - It is an official version.
  • 0.0.1alpha2 - It is a test version.

Future Plans

  • Add some models which are used in the food classification.
  • Add more tools for deep learning model management.

License

mDeep Learning Tools for Pytorch is MIT licensed. See the LICENSE for details.

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