https://github.com/53845714nf/dinofind
🦕 Dinofind is a search engine for finding visually similar images.
https://github.com/53845714nf/dinofind
dinov2 flask minio qdrant-vector-database tailwindcss
Last synced: 16 days ago
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🦕 Dinofind is a search engine for finding visually similar images.
- Host: GitHub
- URL: https://github.com/53845714nf/dinofind
- Owner: 53845714nF
- License: apache-2.0
- Created: 2025-07-31T21:27:01.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2025-11-04T14:46:38.000Z (8 months ago)
- Last Synced: 2025-11-04T16:19:57.072Z (8 months ago)
- Topics: dinov2, flask, minio, qdrant-vector-database, tailwindcss
- Language: HTML
- Homepage: https://www.dinofind.com/
- Size: 2.23 MB
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: Readme.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Security: SECURITY.md
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README
> [!WARNING]
> The following repository is no longer maintained. A new, improved version is available at: https://github.com/53845714nF/dinofind2
🦕 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:
```bash
docker compose up
```
Uploade your Images:
Put your Images in the `images` Folder then run:
```bash
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](https://www.kaggle.com/datasets/adityajn105/flickr30k) is a Dataset of 30k Images from Flickr
- [DINOv2](https://github.com/facebookresearch/dinov2) as the image vectorizer to convert images into high-dimensional embeddings.
- [Qdrant](https://github.com/qdrant/qdrant) as the vector database for storing and querying image embeddings.
- [MinIO](https://github.com/minio/minio) as the object storage system to store the original image files.
- [Flask](https://github.com/pallets/flask) as the backend web service framework.