🔥🔥🔥色情图片离线识别，基于TensorFlow实现。识别只需20ms,可断网测试，成功率99%，调用只要一行代码，从雅虎的开源项目open_nsfw移植，该模型文件可用于iOS、java、C++等平台

A free, open source, and privacy-focused browser extension to block “not safe for work” content built using TypeScript and TensorFlow.js.

Rest API Written In Python To Classify NSFW Images.

Containerized self-hosted REST API for vision classification, utilizing Hugging Face transformers.

Telegram media filter bot that can detect nsfw content using Keras model predictions

NSFW C# Proxy Server using Yahoo Open NSFW as Backend

NSFW.js implementation for image, gif and video. NSFW detection on the client-side via TensorFlow.js

siglip2-mini-explicit-content is an image classification vision-language encoder model fine-tuned from siglip2-base-patch16-512 for a single-label classification task. It is designed to classify images into categories related to explicit, sensual, or safe-for-work content using the SiglipForImageClassification architecture.

vit-mini-explicit-content is an image classification vision-language model fine-tuned from vit-base-patch16-224-in21k for a single-label classification task. It categorizes images based on their explicitness using the ViTForImageClassification architecture.

vit-mini-explicit-content is an image classification vision-language model fine-tuned from vit-base-patch16-224-in21k for a single-label classification task. It categorizes images based on their explicitness using the ViTForImageClassification architecture.