Religo
January 19, 2024
Introduction:
Are you tired of manually filtering through countless images to ensure they are safe for your users?
Introducing NSFW JS, the powerful JavaScript library that revolutionizes content filtering for images.
With NSFWJS, you can effortlessly identify potentially inappropriate images directly on your client’s browser, eliminating the need to send sensitive data to a server.
Powered by TensorFlowJS, an open-source machine learning library, NSFWJS is trained to recognize specific patterns in images with an impressive accuracy rate of 93%.
But that’s not all – NSFWJS goes the extra mile by incorporating CameraBlur Protection, automatically blurring any images it identifies as potentially inappropriate.
Constantly evolving and improving, NSFWJS releases new models frequently, ensuring you stay ahead in the battle against inappropriate content.
Best of all, NSFWJS is completely free to use, modify, and distribute under the MIT license.
Experience the power of NSFWJS with the mobile demo, allowing you to test different images on your mobile devices.
Download NSFWJS now from GitHub and join our community in reporting false positives and contributing to the library’s development.
Overview:
NSFWJS is a JavaScript library designed to help identify potentially inappropriate images on a client’s browser, without needing to send the image to a server. The library is powered by TensorFlowJS, an open-source machine learning library for JavaScript.
With a current accuracy rate of 93%, NSFWJS is trained to recognize particular patterns in images, enabling it to identify potentially inappropriate content. It incorporates CameraBlur Protection, which automatically blurs any images it identifies as being potentially inappropriate.
Constantly improving and updating, NSFWJS releases new models frequently to enhance its performance. It is freely available for use, modification, and distribution under the MIT license. Additionally, the library offers a mobile demo, allowing users to test different images on their mobile devices.
To facilitate accessibility, NSFWJS can be downloaded through GitHub. Users are encouraged to report any false positives they encounter and contribute to the ongoing development of the library.
Benefits:
- NSFWJS is a JavaScript library designed to help identify potentially inappropriate images on a client’s browser, without needing to send the image to a server.
- The library is powered by TensorFlowJS, an open-source machine learning library for JavaScript.
- The library is trained to recognize particular patterns in the images, with the current accuracy rate at 93%.
- The library incorporates CameraBlur Protection, which blurs any images identified as potentially inappropriate.
- NSFWJS is constantly being improved and updated, with new models being released frequently.
- NSFWJS is free to use, modify, and distribute under the MIT license.
- The library includes a mobile demo for testing images on mobile devices.
- Users are encouraged to report any false positives or contribute to the development of the library.
- The use case for NSFWJS is content filtering for images.
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