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  # AI Image Detector
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  ## Model Description
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- This model is designed to detect whether an image is real or AI-generated. It uses Vision Transformer (VIT) architecture to provide accurate classification.
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  ## Model Usage
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  ```python
@@ -43,4 +43,41 @@ def detect_image(image_path):
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  # Example usage
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  # result, confidence = detect_image("path/to/image.jpg")
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- # print(f"Result: {result} (Confidence: {confidence:.2f}%)")
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  # AI Image Detector
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  ## Model Description
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+ This model is designed to detect whether an image is real or AI-generated. It uses Vision Transformer (ViT) architecture to provide accurate classification.
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  ## Model Usage
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  ```python
 
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  # Example usage
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  # result, confidence = detect_image("path/to/image.jpg")
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+ # print(f"Result: {result} (Confidence: {confidence:.2f}%)")
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+ Classes
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+ The model classifies images into two categories:
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+
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+ Real Image (0): The image is real and not AI-generated.
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+ AI Generated (1): The image is generated by AI.
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+ Technical Details
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+ Model Architecture: Vision Transformer (ViT)
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+ Input: Images (RGB)
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+ Output: Binary classification with confidence score
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+ Max Image Size: 224x224 (automatically resized)
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+ Requirements
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+ transformers>=4.30.0
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+ torch>=2.0.0
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+ Pillow>=9.0.0
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+ Limitations
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+ Best performance with clear, high-quality images.
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+ May have reduced accuracy with heavily edited photos.
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+ Designed for general image detection.
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+ Web Integration Example
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+ javascript
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+ async function detectImage(imageFile) {
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+ const formData = new FormData();
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+ formData.append('image', imageFile);
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+
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+ const response = await fetch('YOUR_API_ENDPOINT', {
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+ method: 'POST',
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+ body: formData
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+ });
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+
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+ return await response.json();
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+ }
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+ Developer
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+ Created by: yaya36095
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+ License: MIT
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+ Repository: https://huggingface.co/yaya36095/ai-image-detector
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+ markdown
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+