🦕 Dinofind

⚡ A website that allows users to search for images based on images. 🔍

This project is a minimal search for finding visually similar images. It is an experimental project designed to explore the use of vector databases for image similarity search.

✨ Features

• Upload and vectorize in advance.
• Search for visually similar images.
• Store image metadata and embeddings efficiently.
• Scalable and modular architecture.

🚀 Getting started

Start with:

docker compose up

Uploade your Images: Put your Images in the images Folder then run:

python3 -m venv .venv
source .venv/bin/activate
pip3 install -r requirements.txt
python -m upload.main

⚙ Components

The core components of the system include:

• Kaggle is a Dataset of 30k Images from Flickr
• DINOv2 as the image vectorizer to convert images into high-dimensional embeddings.
• Qdrant as the vector database for storing and querying image embeddings.
• MinIO as the object storage system to store the original image files.
• Flask as the backend web service framework.