Deep Learning Tools for Pytorch
Project description
Deep Learning Tools for Pytorch
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
-
Nutrients 2024, "A Lightweight Hybrid Model with Location-Preserving ViT for Efficient Food Recognition"
-
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.
Project details
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