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yaya36095/
deepfake-detector

Name: deepfake-detector
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Enhanced AI Image Detector

This model detects whether an image is real or AI-generated using a trained PyTorch neural network.

Model Description

The Enhanced AI Image Detector uses a trained PyTorch neural network to analyze images and determine whether they are authentic photographs or generated by AI tools like DALL-E, Midjourney, or Stable Diffusion.

Key Features

Deep Learning Model: Uses a convolutional neural network trained on thousands of real and AI-generated images
High Accuracy: Achieves over 85% accuracy in detecting AI-generated content
Fast Inference: Optimized for quick analysis even on CPU-only systems
Simple API: Easy to use with a straightforward Python interface

How It Works

The model uses a deep convolutional neural network trained on a large dataset of real and AI-generated images. The network learns to detect subtle patterns and artifacts that are characteristic of AI-generated content, including:

Noise and Artifact Patterns:
- Specific noise patterns introduced by AI generation methods
- Artifacts and inconsistencies in image details
Texture Inconsistencies:
- Unnatural texture patterns
- Texture smoothness and regularity
Color and Lighting Anomalies:
- Unusual color distributions
- Lighting inconsistencies
Structural Patterns:
- Geometric inconsistencies
- Unnatural object boundaries
- Perspective and proportion issues

Usage

python

from ai_detector import EnhancedAIDetector

# Initialize the detector with the path to the model file
detector = EnhancedAIDetector(model_path='best_model_improved.pth')

# Analyze an image
result = detector.analyze_image("path/to/image.jpg")

# Check the result
if result["is_ai_generated"]:
    print("This image is likely AI-generated")
    print(f"Confidence score: {result['overall_score']:.2f}")
else:
    print("This image is likely authentic")
    print(f"Confidence score: {1 - result['overall_score']:.2f}")

# View model information
print(f"Model: {result.get('model_name', 'Enhanced AI Image Detector')}")
print(f"Version: {result.get('model_version', '1.0.0')}")

Requirements

PyTorch
TorchVision
OpenCV (cv2)
NumPy
PIL (Pillow)

Limitations

The model may struggle with highly realistic AI-generated images from newer generation models
Some real images with unusual characteristics may be misclassified
Performance depends on image quality and resolution
The model works best with images similar to those in its training dataset

Citation

If you use this model in your research or application, please cite:

@software{enhanced_ai_detector,
  author = {Your Name},
  title = {Enhanced AI Image Detector},
  year = {2025},
  url = {https://huggingface.co/yourusername/enhanced-ai-detector}
}

yaya36095/deepfake-detector