Deepfake Video and Image Scanner

What It Does

Installation

Usage

python deepfake_scan.py --input <path_to_media_file> [--output <path_to_heatmap_output>]

python deepfake_scan.py --input image.jpg

python deepfake_scan.py --input video.mp4 --output heatmap.png

Source Code

import argparse
import cv2
import numpy as np
import torch
import matplotlib.pyplot as plt

def load_model():
    """Simulates loading a pre-trained deepfake detection model."""
    # Placeholder for model loading
    return lambda x: (np.random.rand(), np.random.rand(*x.shape[:2]))

def analyze_media(file_path, model):
    """Analyzes an image or video for deepfake content.

    Args:
        file_path (str): Path to the image or video file.
        model (callable): A function that takes an image and returns a confidence score and heatmap.

    Returns:
        tuple: (confidence_score, heatmap)
    """
    if file_path.lower().endswith(('.png', '.jpg', '.jpeg')):
        image = cv2.imread(file_path)
        if image is None:
            raise ValueError("Invalid image file.")
        image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
        confidence, heatmap = model(image)
        return confidence, heatmap

    elif file_path.lower().endswith(('.mp4', '.avi', '.mov')):
        cap = cv2.VideoCapture(file_path)
        if not cap.isOpened():
            raise ValueError("Invalid video file.")
        ret, frame = cap.read()
        if not ret:
            raise ValueError("Unable to read video frames.")
        frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
        confidence, heatmap = model(frame)
        cap.release()
        return confidence, heatmap

    else:
        raise ValueError("Unsupported file format.")

def save_heatmap(heatmap, output_path):
    """Saves the heatmap as an image file.

    Args:
        heatmap (numpy.ndarray): The heatmap to save.
        output_path (str): Path to save the heatmap image.
    """
    plt.imshow(heatmap, cmap='jet', alpha=0.5)
    plt.colorbar()
    plt.axis('off')
    plt.savefig(output_path)
    plt.close()

def main():
    parser = argparse.ArgumentParser(description="Deepfake Video and Image Scanner")
    parser.add_argument('--input', required=True, help="Path to the input video or image file.")
    parser.add_argument('--output', help="Path to save the heatmap image.")
    args = parser.parse_args()

    model = load_model()

    try:
        confidence, heatmap = analyze_media(args.input, model)
        print(f"Confidence Score: {confidence:.2f}")

        if args.output:
            save_heatmap(heatmap, args.output)
            print(f"Heatmap saved to {args.output}")

    except Exception as e:
        print(f"Error: {e}")

if __name__ == "__main__":
    main()