Nerv-DFVD

AI-powered web app for detecting deepfake videos with high accuracy.

Features

• User authentication system
• Video upload functionality
• Deepfake detection using a pre-trained machine learning model
• User profile to view past detection results

Installation

1. Clone the repository:

   git clone https://github.com/Kenxpx/Nerv-DFVD.git
   cd Nerv-DFVD
   

2. Create a virtual environment and activate it:

   python -m venv venv
   venv\Scripts\activate
   

3. Install the required packages:

   pip install -r requirements.txt
   

4. Apply database migrations:

   python manage.py migrate
   

5. Create a superuser (admin) account:

   python manage.py createsuperuser
   

6. Run the development server:

   python manage.py runserver
   

7. Access the application at

   http://127.0.0.1:8000
   

Usage

1. Register for an account or log in if you already have one.
2. Navigate to the upload page and select a video file to analyze.
3. Submit the video and wait for the detection results.
4. View your detection history in your user profile.

Technology Stack

• Django
• TensorFlow
• OpenCV
• SQLite (default database, can be changed for production)

Contributing

Contributions to Nerv-DFVD are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

Contact

For any queries or suggestions, please open an issue on the GitHub repository.

Project Link: https://github.com/Kenxpx/Nerv-DFVD

File Structure

C:.
│   LICENSE
│   manage.py
│   README.md
│   
├───app
│   │   admin.py
│   │   apps.py
│   │   forms.py
│   │   models.py
│   │   tests.py
│   │   urls.py
│   │   views.py
│   │   __init__.py
│   │
│   └───migrations
│           __init__.py
│
├───detection_unit
│       asgi.py
│       settings.py
│       urls.py
│       wsgi.py
│       __init__.py
│
├───models
│       Ken.h5
│
├───notebooks
│       final.ipynb
│       usinglstmcnn.ipynb
│
└───templates
        base.html
        landing_page.html
        results.html
        upload.html