capcheck
/

ai-human-generated-image-detection

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-tags: []
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 ---
+license: apache-2.0
+base_model: dima806/ai_vs_human_generated_image_detection
+tags:
+- image-classification
+- vision
+- ai-detection
+- deepfake-detection
+- vit
+metrics:
+- accuracy
+- f1
+pipeline_tag: image-classification
 ---
+# CapCheck AI vs Human-Generated Image Detection
+Vision Transformer (ViT) fine-tuned for detecting AI-generated images.
+Uses newer training data than the original CIFAKE-based model.
+## Model Lineage & Attribution
+This model builds on the work of others:
+| Layer | Model | Author | License |
+|-------|-------|--------|---------|
+| Base Architecture | [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) | Google | Apache 2.0 |
+| AI Detection Fine-tune | [dima806/ai_vs_human_generated_image_detection](https://huggingface.co/dima806/ai_vs_human_generated_image_detection) | dima806 | Apache 2.0 |
+| This Model | capcheck/ai-human-generated-image-detection | CapCheck | Apache 2.0 |
+**Special thanks to:**
+- **Google** for the Vision Transformer (ViT) architecture
+- **dima806** for fine-tuning on AI vs human-generated image datasets
+## Model Description
+- **Architecture**: ViT-Base (86M parameters)
+- **Input Size**: 224x224 pixels
+- **Training Data**: AI-generated vs human-created images (newer dataset than CIFAKE)
+- **Task**: Binary classification (human vs AI-generated)
+## Usage
+```python
+from transformers import pipeline
+detector = pipeline("image-classification", model="capcheck/ai-human-generated-image-detection")
+result = detector("path/to/image.jpg")
+# Output:
+# [{"label": "AI-generated", "score": 0.95}, {"label": "human", "score": 0.05}]
+```
+## Labels
+| Label | Description |
+|-------|-------------|
+| `human` | Authentic photograph or human-created image |
+| `AI-generated` | AI-generated or synthetically created image |
+## Comparison with capcheck/ai-image-detection
+| Feature | ai-image-detection | ai-human-generated-image-detection |
+|---------|-------------------|-------------------------------------|
+| Source | dima806/ai_vs_real_image_detection | dima806/ai_vs_human_generated_image_detection |
+| Training Data | CIFAKE dataset | Newer AI vs human dataset |
+| Labels | `REAL` / `FAKE` | `human` / `AI-generated` |
+| Handle | `ai-image-detection` | `ai-human-generated-image-detection` |
+## Limitations
+- May have reduced accuracy on very new AI generators not in training data
+- Heavily compressed images (low JPEG quality) can affect results
+- Works best on images with clear subjects (224x224+ pixels)
+## Intended Use
+- Content moderation and authenticity verification
+- Research into AI-generated content detection
+- Educational purposes
+**Not intended for**:
+- Making consequential decisions without human review
+- Law enforcement evidence without corroborating sources
+## License
+Apache 2.0 (inherited from Google ViT and dima806's fine-tuned model)
+## Citation
+```bibtex
+@misc{capcheck-ai-human-generated-detection,
+  author = {CapCheck},
+  title = {AI vs Human-Generated Image Detection Model},
+  year = {2025},
+  publisher = {HuggingFace},
+  url = {https://huggingface.co/capcheck/ai-human-generated-image-detection},
+  note = {Based on dima806/ai_vs_human_generated_image_detection, fine-tuned from google/vit-base-patch16-224-in21k}
+}
+```