A Python library for detecting deepfake images and videos.
Project description
Deepfake Detector
# Deepfake Detector
Deepfake Detector is a Python library designed for detecting deepfake content in images and videos. Leveraging advanced machine learning techniques, it provides an easy-to-use interface for real-time and batch processing of media files.
## Features
- **Real-time Deepfake Detection**: Analyze live video feeds to detect deepfake content.
- **Batch Processing**: Process multiple images and videos to classify them as real or fake.
- **Customizable Thresholds**: Adjust detection sensitivity to suit your specific needs.
## Installation
You can install the `deepfake_detector` package using pip:
```bash
pip install deepfake_detector
Usage
For Video Detection
Detect deepfake content in a video file. You can provide a video file path or use a webcam.
from deepfake_detector import DeepfakeDetector
# Create a detector object with a custom threshold
detector = DeepfakeDetector(threshold=0.5)
# Detect deepfakes in a video file
detector.detect_from_video('path_to_video.mp4')
# Use webcam (source=0) for live detection
detector.detect_from_video(source=0)
For Image Detection
Detect deepfake content in a single image.
from deepfake_detector import DeepfakeDetector
# Create a detector object with a custom threshold
detector = DeepfakeDetector(threshold=0.5)
# Detect deepfakes in an image
result = detector.detect_from_image('path_to_image.jpg')
print(f'The image is classified as: {"FAKE" if result > 0.5 else "REAL"}')
Customizing Detection Threshold
You can set the threshold to control the sensitivity of the detection.
# Example with a higher sensitivity threshold
detector = DeepfakeDetector(threshold=0.7)
Paper Reference
For more detailed information about the techniques used in this library, please refer to the following research paper:
- Title: Deepfake Detection Using Convolutional Neural Networks
- Authors: [Author Name], [Co-Author Name]
- Journal: MDPI Sensors
- Abstract: This paper explores advanced methods for detecting deepfake media using convolutional neural networks (CNNs). The study provides a comprehensive analysis of various techniques and their effectiveness in identifying manipulated content.
Contributing
If you would like to contribute to the development of this library, please follow these steps:
- Fork the repository on GitHub.
- Create a new branch for your changes.
- Commit your changes with descriptive messages.
- Push your changes to your fork.
- Submit a pull request to the main repository.
License
This project is licensed under the MIT License. See the LICENSE file for details.
Contact
For any questions or feedback, please contact:
- Author: Adupa Nithin Sai
- Email: adupanithinsai@gmail.com
- GitHub: https://github.com/saiadupa/Deepfake-detector
Thank you for using Deepfake Detector. We hope you find it useful for your deepfake detection needs!
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