Mature-Content-Detection
| Property | Value |
|---|---|
| Base Model | google/siglip2-base-patch16-224 |
| Architecture | SiglipForImageClassification |
| Task | Single-label Image Classification |
| Accuracy | 82.96% |
| Model URL | huggingface.co/prithivMLmods/Mature-Content-Detection |
What is Mature-Content-Detection?
Mature-Content-Detection is a specialized vision-language model fine-tuned for classifying images into five distinct categories: Anime Picture, Hentai, Neutral, Pornography, and Enticing or Sensual content. Built on the robust google/siglip2-base-patch16-224 architecture, this model achieves impressive classification metrics with an overall accuracy of 82.96%.
Implementation Details
The model utilizes the SiglipForImageClassification architecture and can be easily implemented using the Transformers library. It processes images through a pre-trained image processor and returns probability scores for each category. The model demonstrates strong performance across all classes, with particularly high precision (91.61%) for pornographic content detection.
- Built on Transformers framework with PyTorch backend
- Includes custom image processor for optimal input handling
- Outputs probability distributions across 5 distinct categories
- Implements efficient batch processing for scalable deployment
Core Capabilities
- High-accuracy classification of anime and mature content
- Reliable neutral content detection (80.55% F1-score)
- Effective distinction between various content categories
- Real-time processing capability through Gradio interface
- Support for content moderation systems
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its specialized focus on anime and mature content detection, achieving high accuracy while maintaining ethical guidelines for content moderation. Its balanced performance across multiple categories makes it particularly suitable for digital content filtering systems.
Q: What are the recommended use cases?
The model is ideal for content moderation platforms, parental control systems, dataset curation, and search engine filtering. It's specifically designed to support safe and respectful digital spaces while ensuring proper content categorization for various applications.
