NSFWJS is an ingenious JavaScript library designed to identify potentially inappropriate images directly on a client’s browser, eliminating the need to send the images to a server.
The library’s robust functionality is powered by TensorFlowJS, an open-source machine learning library for JavaScript. Through extensive training, the library has achieved an impressive accuracy rate of 93% in recognizing specific patterns in images.
To further enhance user safety, NSFWJS incorporates CameraBlur Protection, which automatically blurs any images deemed potentially inappropriate. Regular updates and continuous improvement ensure that new models are frequently released to enhance performance.
The best part is that NSFWJS is entirely free to use, and it can be modified and distributed under the MIT license, promoting collaboration and flexibility.
For users’ convenience, the library offers a mobile demo, allowing them to test different images on their mobile devices effortlessly.
Downloading NSFWJS is a breeze through GitHub, and users are encouraged to contribute to the library’s development or report any false positives they encounter.
Take control of your online safety with NSFWJS, a reliable JavaScript library that ensures a secure browsing experience by locally identifying potentially inappropriate images.
