Reverse Image Search Engine(Local)

This is a simple reverse image search tool that uses the Streamlit framework. It allows users to find similar images from a specified directory.

Why is it helpful?

This tool can help identify similar images. This tools uses EfficientNet-B0 for vector embedding and Chromadb(vector database) for vector storage and retrieval. EfficientNet-B0 is a lightweight convolutional neural network architecture that is designed to be efficient and accurate for image recognition tasks.

Installation

To use the reverse image search engine, simply follow these steps:


# clone the repo
git clone https://github.com/tikendraw/reverse-image-search.git

# go inside
cd reverse-image-search

# install with pip
pip install .

Run

bash command

# bash command 
image_search

or just run the launch.py file

python launch.py

Screenshot

How to use

Provide the directory path where the images are located (to embed).
Upload an image (to search).
Number of similar Images to find.

Tech stack use

The reverse image search engine is built using the following technologies:

Python
transformers
pytorch
EfficientNet-B0 for vector embedding
Chromadb(vector database)
Streamlit
Pillow

How to contribute

Future updates:

[ ] Facial Recognition
[ ] Search Images with words

If you would like to contribute to the reverse image search engine, please feel free to open a pull request.

Citation

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

@misc{tan2020efficientnetrethinkingmodelscaling,
      title={EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks}, 
      author={Mingxing Tan and Quoc V. Le},
      year={2020},
      eprint={1905.11946},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/1905.11946}, 
}

License

The reverse image search engine is licensed under the MIT License.

I hope this is helpful!

tikendraw / reverse-image-search

readme