https://github.com/hitthecodelabs/deepfaceregistry
Real-time face recognition using IP cameras
https://github.com/hitthecodelabs/deepfaceregistry
deepface django flask javascript mediapipe mysql opencv vue vue3 vuejs
Last synced: 2 months ago
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Real-time face recognition using IP cameras
- Host: GitHub
- URL: https://github.com/hitthecodelabs/deepfaceregistry
- Owner: hitthecodelabs
- License: mit
- Created: 2023-11-01T04:17:46.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-11-09T17:05:48.000Z (over 2 years ago)
- Last Synced: 2025-02-04T11:44:04.942Z (over 1 year ago)
- Topics: deepface, django, flask, javascript, mediapipe, mysql, opencv, vue, vue3, vuejs
- Language: Vue
- Homepage:
- Size: 21.7 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# DeepFaceRegistry
This project offers a robust solution for real-time face recognition using IP cameras, integrating technologies like Django, Vue.js, DeepFace, OpenCV, and MediaPipe. The core feature allows for real-time logging of recognized faces against a pre-registered database of users.
## Features
- **User Registration**: Register users and store their facial information for later recognition.
- **IP Camera Integration**: Link IP cameras to the system for real-time face tracking.
- **Real-time Face Recognition**: Every face captured by the IP cameras is compared against the user database in real-time.
- **Automatic Logging**: If a recognized face matches a registered user, the information gets logged in real-time. Faces that aren't in the database are ignored.
## Technologies Used
- **Backend**: Django, Flask
- **Frontend**: Vue.js
- **Face Recognition**: DeepFace, OpenCV, MediaPipe
## Directory Structure
- `camera_track_backend`: Contains all backend code, built with Django.
- `camera_track_frontend`: Contains frontend code, developed using Vue.js.
## Local Setup
To run this project locally, you need to set up both frontend and backend.
### Frontend
Navigate to the `camera_track_frontend` directory:
```bash
cd camera_track_frontend
npm run serve -- --port 4000
```
### Backend
Ensure you have poetry installed. Navigate to the `camera_track_backend` directory:
```bash
cd camera_track_backend
poetry run python manage.py runserver localhost:8000
```
This will start the backend server on http://localhost:8000/
## Contributing
Contributions to DeepFaceRegistry are welcome! Here's how you can contribute:
Fork the repository on GitHub.
Create a new branch for your proposed feature or fix.
Commit your changes with an informative description.
Push your branch and submit a pull request.
We appreciate your input!
## License
DeepFaceRegistry is open source software licensed under the MIT License. See the LICENSE file for more details.