Tool Information
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, which is 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 also incorporates CameraBlur Protection, which is a feature that blurs any images that it identifies as being potentially inappropriate. The library is constantly being improved and updated, with new models being released frequently. NSFWJS is free to use, and can be modified and distributed under the MIT license. The library also includes a mobile demo, which allows users to test different images on their mobile devices. Finally, the library is available for download through GitHub, and users are encouraged to report any false positives or contribute to the development of the library.
F.A.Q (20)
NSFW JS is a JavaScript library that specializes in the identification of potentially obscene images on a client's browser.
The purpose of NSFW JS is to detect and filter inappropriate content in images loaded in a client's browser.
NSFW JS recognizes inappropriate images by using machine learning algorithms to detect specific patterns in these images.
NSFW JS uses TensorFlowJS, an open-source machine learning library for JavaScript.
The accuracy rate of NSFW JS in recognizing potentially inappropriate images is noted to be 93%.
The CameraBlur Protection feature in NSFW JS blurs any images it identifies as potentially inappropriate.
Yes, NSFW JS is continually updated and improved with new models being released frequently.
Yes, NSFW JS can be utilized for free.
NSFW JS is distributed under the MIT license which allows for modification and distribution of the software.
Yes, NSFW JS includes a mobile demo which allows users to test different images on their mobile devices.
Anyone can contribute to the development of NSFW JS by reporting false positives or directly contributing via the project's GitHub repository.
NSFW JS can be downloaded from its GitHub repository.
False positives in NSFW JS can be reported through the project's GitHub page.
Yes, NSFW JS is designed to work on the client's browser, detecting inappropriate images without the need to send the images to a server.
Without specifically detailed information, it can be inferred that NSFW JS is trained to recognize patterns in images that are typically associated with inappropriate or explicit content.
The NSFWJS model repository can be accessed via its specific GitHub page.
The NSFWJS model file size is 4.2MB.
JavaScript has to be enabled for NSFW JS to function as it is a JavaScript library.
NSFWJS doesn't have a direct mobile app, but offers a mobile demo that allows you to test images from mobile devices.
More information about NSFW JS can be found on its official page, Github repository, model repository, or through associated blog posts linked on its webpage.
Pros and Cons
Pros
- Client-side Image detection
- Powered by TensorFlowJS
- 93% Accuracy rate
- Includes CameraBlur Protection
- Constant updates and improvement
- Free to use
- Open-source (MIT License)
- Mobile demo included
- Available on GitHub
- Community contribution encouraged
- NSFW Patterns recognition
- Content filtering for images
- Allows reporting false positives
- Lightweight (4.2MB)
- In-browser image evaluation
- Doesn't require server interaction
- Modifiable for user needs
- Reduced privacy risks
- Avoids image data transmission
- Consistently learning and adapting
Cons
- Dependent on TensorFlowJS
- No server-side processing
- 93% Accuracy (false positives)
- Potential privacy issues with CameraBlur
- Regular updates required
- Only Javascript implementation
- Limited cross-platform usage
- No real-time detection
- Reliant on pattern recognition
- Limited user support
Reviews
You must be logged in to submit a review.
No reviews yet. Be the first to review!
Similar Tools
Streamlines your workflow | Writes, edits, and summarizes in seconds ✍️
2025-07-30
$40
