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A Python library for detecting deepfake images and videos.

Project description

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:

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 live_video_prediction, image_prediction

# Set a custom threshold
live_video_prediction(source='name.mp4',threshold=0.5)

For Image Detection

Detect deepfake content in a single image.

from deepfake_detector import live_video_prediction, image_prediction

# Image prediction example
image_prediction('name.png', threshold=0.6)

Customizing Detection Threshold

You can set the threshold to control the sensitivity of the detection.

# Example with a higher sensitivity threshold
live_video_prediction(source='name.mp4',threshold=0.5)
image_prediction('name.png', threshold=0.6)

Paper Reference

For more detailed information about the techniques used in this library, please refer to the following research paper:

Contributing

If you would like to contribute to the development of this library, please contact me.

Contact

For any questions or feedback, please contact:


Thank you for using Deepfake Detector. We hope you find it useful for your deepfake detection needs!

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