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--- |
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language: en |
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tags: |
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- image-classification |
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- ai-detection |
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- vit |
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license: mit |
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--- |
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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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from transformers import ViTImageProcessor, ViTForImageClassification |
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from PIL import Image |
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import torch |
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# تحميل النموذج والمعالج |
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processor = ViTImageProcessor.from_pretrained("C:/Users/SUPREME TECH/Desktop/SAM3/ai-image-detector") |
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model = ViTForImageClassification.from_pretrained("C:/Users/SUPREME TECH/Desktop/SAM3/ai-image-detector") |
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def detect_image(image_path): |
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# فتح وتجهيز الصورة |
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image = Image.open(image_path) |
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if image.mode != 'RGB': |
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image = image.convert('RGB') |
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# معالجة الصورة |
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inputs = processor(images=image, return_tensors="pt") |
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# الحصول على التنبؤات |
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with torch.no_grad(): |
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outputs = model(**inputs) |
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predictions = outputs.logits.softmax(dim=-1) |
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# تحليل النتائج |
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scores = predictions[0].tolist() |
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results = [ |
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{"label": "REAL", "score": scores[0]}, |
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{"label": "FAKE", "score": scores[1]} |
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] |
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# ترتيب النتائج حسب درجة الثقة |
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results.sort(key=lambda x: x["score"], reverse=True) |
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return { |
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"prediction": results[0]["label"], |
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"confidence": f"{results[0]['score']*100:.2f}%", |
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"detailed_scores": [ |
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f"{r['label']}: {r['score']*100:.2f}%" |
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for r in results |
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] |
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} |
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# كود للاختبار |
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if __name__ == "__main__": |
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# يمكنك تغيير مسار الصورة هنا |
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image_path = "path/to/your/image.jpg" |
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try: |
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result = detect_image(image_path) |
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print("\nنتائج تحليل الصورة:") |
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print(f"التصنيف: {result['prediction']}") |
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print(f"درجة الثقة: {result['confidence']}") |
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print("\nالتفاصيل:") |
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for score in result['detailed_scores']: |
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print(f"- {score}") |
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except Exception as e: |
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print(f"حدث خطأ: {str(e)}") |
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``` |
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## Classes |
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The model classifies images into two categories: |
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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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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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return await response.json(); |
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} |
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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](https://huggingface.co/yaya36095/ai-image-detector) |
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