https://github.com/techthrives/facelinker
Effortlessly Organize and Analyze Event Photos with Advanced Facial Recognition
https://github.com/techthrives/facelinker
deepface flask mongodb supabase
Last synced: 4 months ago
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Effortlessly Organize and Analyze Event Photos with Advanced Facial Recognition
- Host: GitHub
- URL: https://github.com/techthrives/facelinker
- Owner: TechThrives
- Created: 2024-02-05T08:18:44.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-06-02T08:19:38.000Z (4 months ago)
- Last Synced: 2025-06-02T18:48:59.623Z (4 months ago)
- Topics: deepface, flask, mongodb, supabase
- Language: HTML
- Homepage: https://facelinker.onrender.com
- Size: 1.01 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# FaceLinker
Effortlessly Organize and Analyze Event Photos with Advanced Facial Recognition
## Overview
FaceLinker is an advanced image processing and facial recognition application designed to streamline the organization and analysis of event photos. With FaceLinker, users can:
- Upload multiple images from various events.
- Extract faces from these images.
- Group similar faces together for easy organization and analysis.
## Features
- **Bulk Image Upload:** Upload multiple images from different events for batch processing.
- **Facial Extraction:** Automatically detect and extract faces from uploaded images.
- **Face Grouping:** Organize photos by grouping similar faces together.
- **Event Management:** Keep your event photos organized by categorizing them into different events.
## Tech Stack
**Frontend:** HTML, Tailwind, JavaScript
**Backend:** Python Flask
**Database:** MongoDB
**Facial Recognition:** DeepFace
**Image Storage:** Supabase
## Installation
To get started with FaceLinker, follow these steps:
Prerequisites
- Python installed on your machine.
- MongoDB installed and running.
- Supabase account and project set up.
### Clone the project
```bash
git clone https://github.com/yourusername/FaceLinker.git
```
Go to the project directory
```bash
cd FaceLinker
```
### Install Dependencies
Create and activate a virtual environment:
```bash
python3 -m venv venv
source venv/bin/activate # On Windows use `venv\Scripts\activate`
```
Install the required Python packages:
```bash
pip install -r requirements.txt
```
## Environment Variables
To run this project, you will need to add the following environment variables to your .env file
`SECRET_KEY`
`MONGO_URI`
`SUPABASE_URL`
`SUPABASE_KEY`
`SUPABASE_BUCKET`
## Start the Application
```bash
flask run
```
The application will be available at http://localhost:5000.
## Demo
https://github.com/user-attachments/assets/25b751b4-d94e-4911-b037-f293759363a0
## Contributing
Contributions are welcome! Please follow these steps:
- Fork the repository.
- Create a new branch (`git checkout -b feature/your-feature-name`).
- Commit your changes (`git commit -m 'Add some feature'`).
- Push to the branch (`git push origin feature/your-feature-name`).
- Open a Pull Request.
## Contact
For any questions or suggestions, please feel free to contact us.