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:

1. Noise and Artifact Patterns:

   • Specific noise patterns introduced by AI generation methods
   • Artifacts and inconsistencies in image details

2. Texture Inconsistencies:

   • Unnatural texture patterns
   • Texture smoothness and regularity

3. Color and Lighting Anomalies:

   • Unusual color distributions
   • Lighting inconsistencies

4. Structural Patterns:

   • Geometric inconsistencies
   • Unnatural object boundaries
   • Perspective and proportion issues

Usage

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}
}