NSFW JS

Overview of NSFW JS

NSFW JS utilizes a pre-trained model to evaluate images on the webpage and categorize them based on their appropriateness. The library leverages TensorFlow.js for machine learning directly in the browser, ensuring a seamless and efficient content checking process. Upon loading, the model quickly assesses images and applies the necessary actions based on its findings, such as blurring images or flagging them for review.

Key Features of NSFW JS

• Client-Side Processing : NSFW JS operates entirely within the user's browser, ensuring privacy and reducing server load.

• Accuracy : The current model boasts a 93% accuracy rate in identifying indecent content, making it a reliable tool for content moderation.

• Lightweight Model : With a model size of just 4.2MB, NSFW JS is designed to be efficient and fast, minimizing the impact on page load times.

• Blur Protection : An additional feature that provides an immediate visual safeguard by blurring potentially inappropriate images until they can be verified.

• Camera Integration : Offers the capability to directly analyze images captured from the user's camera, enhancing real-time content moderation.

How it works

NSFW JS utilizes a pre-trained model to evaluate images on the webpage and categorize them based on their appropriateness. The library leverages TensorFlow.js for machine learning directly in the browser, ensuring a seamless and efficient content checking process. Upon loading, the model quickly assesses images and applies the necessary actions based on its findings, such as blurring images or flagging them for review.