AI-image-detector
| Property | Value |
|---|---|
| License | CC-BY-4.0 |
| Downloads | 5,503 |
| Validation Accuracy | 94.2% |
| CO2 Emissions | 7.94g |
What is AI-image-detector?
The AI-image-detector is a specialized Vision Transformer (ViT) model designed to identify AI-generated artistic images. Created in October 2022, this proof-of-concept model demonstrates remarkable accuracy in distinguishing between human-created and AI-generated artwork, achieving a 94.2% accuracy rate on validation data.
Implementation Details
Built using PyTorch and trained with AutoTrain, this model implements a binary classification approach with impressive metrics including 93.8% precision and 97.8% recall. The model was developed with environmental consciousness, generating only 7.94g of CO2 emissions during training.
- Architecture: Vision Transformer (ViT)
- Training Framework: AutoTrain
- Implementation: PyTorch
- Classification Type: Binary (AI vs. Non-AI art)
Core Capabilities
- Detects AI-generated artistic images with high accuracy
- Specialized for artistic content rather than general photography
- Provides confidence scores for AI generation probability
- Optimized for pre-2023 AI art models
Frequently Asked Questions
Q: What makes this model unique?
This model specializes specifically in artistic image detection, focusing on AI-generated artwork rather than deepfakes or general computer imagery. Its high validation metrics (94.2% accuracy, 98% AUC) make it a reliable tool for initial AI art screening.
Q: What are the recommended use cases?
The model is best suited for preliminary screening of artistic images where AI generation is suspected. It's particularly effective for images with confidence scores above 90%, which can then be referred to human experts for detailed analysis. However, it's not recommended for newer AI art models like Midjourney 5, SDXL, or DALLE-3.
