Img2Loc: Revisiting Image Geolocalization using Multi-modality Foundation Models and Image-based Retrieval-Augmented Generation

Code for Img2Loc paper presented on SIGIR 2024.

Table of Contents

• Installation
• Usage
• License
• Contact
• Citation

Installation

Instructions on how to install and set up the project. If you needs help to access the generated embeddings, please contact us directly.

# Clone the repository
git clone [email protected]:Douglas2Code/Img2Loc.git

# Change to the project directory
cd Img2Loc

# Create a conda environment
conda create -n img2loc python=3.10 -y

# Activate the conda environment
conda activate img2loc

# Install faiss databse following this guide
https://github.com/facebookresearch/faiss/blob/main/INSTALL.md

# Install the project dependencies
pip install -r requirements.txt

# Download MP16 dataset
http://www.multimediaeval.org/mediaeval2016/placing/

# Generate embeddings using CLIP model
https://github.com/openai/CLIP

# Generate a vector database using FAISS
https://github.com/facebookresearch/faiss/wiki/Getting-started#in-python-1

Usage

Run the streamlip application

streamlit run app.py --browser.gatherUsageStats false

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

Zhongliang Zhou: [email protected] Jielu Zhang: [email protected]

Citation

If you find this project helpful, please consider cite our work.

@inproceedings{zhou2024img2loc,
  title={Img2Loc: Revisiting Image Geolocalization using Multi-modality Foundation Models and Image-based Retrieval-Augmented Generation},
  author={Zhou, Zhongliang and Zhang, Jielu and Guan, Zihan and Hu, Mengxuan and Lao, Ni and Mu, Lan and Li, Sheng and Mai, Gengchen},
  booktitle={Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval},
  pages={2749--2754},
  year={2024}
}