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ai-image-detection

capcheck / ai-image-detection

Run on huggingface.co
huggingface.co
Total runs: 2.0K
24-hour runs: 0
7-day runs: 38
30-day runs: 1.0K
Model's Last Updated: December 06 2025
image-classification

Introduction of ai-image-detection

Model Details of ai-image-detection

CapCheck AI Image Detection

Vision Transformer (ViT) fine-tuned for detecting AI-generated images.

Model Lineage & Attribution

This model builds on the work of others:

Layer Model Author License
Base Architecture google/vit-base-patch16-224-in21k Google Apache 2.0
AI Detection Fine-tune dima806/ai_vs_real_image_detection dima806 Apache 2.0
This Model capcheck/ai-image-detection CapCheck Apache 2.0

Special thanks to:

  • Google for the Vision Transformer (ViT) architecture
  • dima806 for fine-tuning on the CIFAKE dataset for AI image detection
Model Description
  • Architecture : ViT-Base (86M parameters)
  • Input Size : 224x224 pixels
  • Training Data : CIFAKE dataset (AI-generated vs real images)
  • Task : Binary classification (Real vs Fake/AI-generated)
Usage 
from transformers import pipeline

detector = pipeline("image-classification", model="capcheck/ai-image-detection")
result = detector("path/to/image.jpg")

# Output:
# [{"label": "Fake", "score": 0.95}, {"label": "Real", "score": 0.05}]
Labels
Label Description
Real Authentic photograph or real-world image
Fake AI-generated or synthetically created image
Performance

This model was trained on the CIFAKE dataset. Performance on modern AI generators (Flux, Midjourney v6, DALL-E 3, Stable Diffusion 3) may vary.

See dima806's model card for detailed training metrics.

Limitations
  • Trained primarily on older AI generators (pre-2024)
  • May have reduced accuracy on:
    • Very new AI generators not in training data
    • Heavily compressed images (low JPEG quality)
    • Images smaller than 224x224 pixels
  • Works best on images with clear subjects
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
Ethical Considerations
  • This tool is not 100% accurate - false positives harm legitimate creators
  • False negatives can allow misinformation to spread
  • Use in conjunction with other verification methods
  • Human review is recommended for high-stakes decisions
Roadmap
Current Version (v1.0.0)

Base model from dima806's CIFAKE-trained ViT. Solid foundation for AI detection.

Planned Improvements

Phase 1: Modern Generator Training

  • Fine-tune on images from Flux, Midjourney v6, DALL-E 3, Stable Diffusion 3
  • Target: Reduce false negatives on 2024+ AI generators

Phase 2: False Positive Reduction

  • Curate dataset of real images commonly flagged as AI
  • Photography edge cases: HDR, heavy editing, digital art
  • Target: <5% false positive rate

Phase 3: Continuous Updates

  • Quarterly re-training as new generators emerge
  • Community feedback integration
  • Benchmark against latest AI generators
Contributing

We welcome:

  • Dataset contributions (properly licensed images)
  • Bug reports and false positive/negative examples
  • Benchmark results on new generators

Join the discussion: https://huggingface.co/capcheck/ai-image-detection/discussions

License

Apache 2.0 (inherited from Google ViT and dima806's fine-tuned model)

Citation

If you use this model, please cite: 

@misc{capcheck-ai-detection,
  author = {CapCheck},
  title = {AI Image Detection Model},
  year = {2024},
  publisher = {HuggingFace},
  url = {https://huggingface.co/capcheck/ai-image-detection},
  note = {Based on dima806/ai_vs_real_image_detection, fine-tuned from google/vit-base-patch16-224-in21k}
}
Changelog
v1.0.0 (Initial Release)
  • Published base model from dima806/ai_vs_real_image_detection
  • Added proper attribution and documentation
  • Established as CapCheck's source of truth for AI image detection

Runs of capcheck ai-image-detection on huggingface.co

2.0K
Total runs
0
24-hour runs
72
3-day runs
38
7-day runs
1.0K
30-day runs

More Information About ai-image-detection huggingface.co Model

More ai-image-detection license Visit here:

https://choosealicense.com/licenses/apache-2.0

ai-image-detection huggingface.co

ai-image-detection huggingface.co is an AI model on huggingface.co that provides ai-image-detection's model effect (), which can be used instantly with this capcheck ai-image-detection model. huggingface.co supports a free trial of the ai-image-detection model, and also provides paid use of the ai-image-detection. Support call ai-image-detection model through api, including Node.js, Python, http.

ai-image-detection huggingface.co Url

https://huggingface.co/capcheck/ai-image-detection

capcheck ai-image-detection online free

ai-image-detection huggingface.co is an online trial and call api platform, which integrates ai-image-detection's modeling effects, including api services, and provides a free online trial of ai-image-detection, you can try ai-image-detection online for free by clicking the link below.

capcheck ai-image-detection online free url in huggingface.co:

https://huggingface.co/capcheck/ai-image-detection

ai-image-detection install

ai-image-detection is an open source model from GitHub that offers a free installation service, and any user can find ai-image-detection on GitHub to install. At the same time, huggingface.co provides the effect of ai-image-detection install, users can directly use ai-image-detection installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

ai-image-detection install url in huggingface.co:

https://huggingface.co/capcheck/ai-image-detection

Url of ai-image-detection

ai-image-detection huggingface.co Url

Provider of ai-image-detection huggingface.co

capcheck
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