SafeScan

모델 소개

**SafeScan** is a multi-class image classifier designed to detect and categorize NSFW (Not Safe For Work) content in images. Built on top of the `google/vit-base-patch16-224` vision transformer backbone, SafeScan classifies visual media across five distinct categories to aid in automated content moderation and platform safety. The model maps visual inputs to the following labels: * **0: safe** – General, non-explicit content * **1: drawing** – Non-explicit artistic illustrations and drawings * **2: sexy** – Suggestive, provocative, or borderline content * **3: hentai** – Explicit anime/manga or illustrated adult content * **4: porn** – Explicit adult photographic media 1. **Multi-Class Granularity:** Differentiates between both real/photographic media and illustrated content across safe, suggestive, and explicit tiers. 2. **Social Media Compression Robustness:** Trained with almost all common social media compression artifacts, ensuring performance stays consistent when analyzing images uploaded across different platforms and formats. 3. **Vision Transformer Backbone:** Leverages `google/vit-base-patch16-224` for high-capacity visual representation learning. 4. **Fast and Scalable:** Standard patch-based transformer architecture suitable for batch processing and automated moderation pipelines.

주요 특징

特点摘要待依据来源补齐，不凭模型名称推断能力。

한계 및 유의 사항

구체적 한계를 판단할 출처가 부족합니다. 실제 성능, 지연, 데이터 정책, 라이선스와 버전 수명을 확인하세요.

출처별 요금 및 비용 분석

요금은 채널, 지역, 설정에 따라 다릅니다. 각 채널 요금은 개별 표시되며 제공사의 통일 공식 요금이 아닙니다.

공개 평가 및 실행 설정

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

자주 묻는 질문

출처 및 추적 기록

许可证：mit。模型介绍与第三方评测均以原来源的具体版本和方法为准。