What is NSFW Detector
NSFW Detector (Not Safe For Work, abbreviated NSFW) is an open-source tool for detecting inappropriate content. NSFW Detector can identify inappropriate content in images, PDFs, and video files. The tool is based on Google'svit-base-patch16-224-in21kmodel, supports CPU-only inference, requires no GPU, and can run on most servers. NSFW Detector provides services via API, is easy to integrate into other applications, supports Docker deployment, and is suitable for distributed deployment. NSFW Detector automatically uses multiple CPUs to accelerate inference, runs entirely locally to protect data security, and supports detection of multiple file types.
Main Features of NSFW Detector
- Content Detection: Detects whether files in images, PDF files, videos, and compressed archives contain Not Safe For Work (NSFW) content.
- CPU Inference: Supports inference using CPU, requires no GPU support, and lowers hardware requirements.
- Multi-CPU Acceleration: Automatically uses multiple CPU cores to accelerate the inference process and improve processing speed.
- Simple Classification: Classifies content into two categories, "nsfw" and "normal", simplifying the classification process.
- API Service: Provides API interfaces for easy integration with other applications to achieve automated content detection.
Technical Principles of NSFW Detector
- Deep Learning Model: Uses Google's
vit-base-patch16-224-in21kmodel, a deep learning model based on Vision Transformer (ViT), specifically for image recognition and classification tasks. - Feature Extraction: The model learns through training to extract features from input images, videos, or documents.
- Classifier: The extracted features are fed into a classifier, which determines whether the content belongs to the NSFW category based on the training data.
Project Address of NSFW Detector
- GitHub Repository：https://github.com/tmplink/nsfw_detector
Application Scenarios of NSFW Detector
- Social Media Platforms: Automatically detect and filter inappropriate content uploaded by users, protect the community environment, and comply with laws and regulations.
- Content Sharing Websites: Automatically detect when users upload images, videos, or documents to prevent the spread of inappropriate content.
- Enterprise Internal Networks: Deploy within enterprise internal networks to prevent employees from accessing or sharing inappropriate content and maintain a professional work environment.
- Online Advertising and Marketing: Ensure the compliance of advertising content and avoid damaging brand image due to inappropriate content.
- Online Education Platforms: Protect the learning environment and prevent students from being exposed to inappropriate learning materials.