A Python-based web application developed to detect deepfake content in images and videos using machine learning.
In an era where digital media can be easily manipulated, distinguishing authentic content from fabricated content has become a critical challenge. DeepFake Detector offers a user-friendly tool to analyze images and videos and determine the likelihood of them being a deepfake.
This project leverages advanced computer vision and deep learning models, packaged into a simple web interface built with Django.
- Image & Video Analysis: Detect deepfakes in both static images and video files.
- Deep Learning Powered: Utilizes a robust deep learning model to identify subtle artifacts common in fake media.
- Web-Based Interface: Easy-to-use interface for uploading files and viewing results directly in your browser.
- Open Source: A community-driven project that is open for contributions and improvements.
This project is built with the following technologies:
- Backend:
- Frontend:
- Machine Learning Libraries:
Follow these instructions to get a local copy of the project up and running for development and testing.
Make sure you have the following installed on your system:
-
Clone the repository:
git clone https://github.com/ArYaNsAiNi-here/DeepFake_Detector.git cd DeepFake_Detector -
Create and activate a virtual environment:
- On macOS/Linux:
python3 -m venv venv source venv/bin/activate - On Windows:
python -m venv venv venv\Scripts\activate
- On macOS/Linux:
-
Install the required dependencies:
pip install -r requirements.txt -
Set up the Django database and start the server:
cd DeepfakeDetector python manage.py makemigrations python manage.py migrate python manage.py runserver
Once the server is running, you can access the application:
- Open your web browser and navigate to
http://127.0.0.1:8000/. - Use the form on the page to upload an image or video file you want to analyze.
- The application will process the file and display the detection result.
Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
Don't forget to give the project a star! Thanks again!
Distributed under the GPL-3.0 License. See LICENSE file for more information.
- Developed with ❤️ by Me
ArYaNsAiNi-here - GitHub Profile
Project Link: https://github.com/ArYaNsAiNi-here/DeepFake_Detector