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About

ConvNetJS is a Javascript library for training deep learning models (neural networks) entirely in your browser. Open a tab and you're training. No software requirements, no compilers, no installations, no GPUs, no sweat. The library allows you to formulate and solve neural networks in Javascript, and was originally written by @karpathy. However, the library has since been extended by contributions from the community and more are warmly welcome. The fastest way to obtain the library in a plug-and-play way if you don't care about developing is through this link to convnet-min.js, which contains the minified library. Alternatively, you can also choose to download the latest release of the library from Github. The file you are probably most interested in is build/convnet-min.js, which contains the entire library. To use it, create a bare-bones index.html file in some folder and copy build/convnet-min.js to the same folder.

About

Darknet is an open-source neural network framework written in C and CUDA. It is fast, easy to install, and supports CPU and GPU computation. You can find the source on GitHub or you can read more about what Darknet can do. Darknet is easy to install with only two optional dependencies, OpenCV if you want a wider variety of supported image types, and CUDA if you want GPU computation. Darknet on the CPU is fast but it's like 500 times faster on GPU! You'll have to have an Nvidia GPU and you'll have to install CUDA. By default, Darknet uses stb_image.h for image loading. If you want more support for weird formats (like CMYK jpegs, thanks Obama) you can use OpenCV instead! OpenCV also allows you to view images and detections without having to save them to disk. Classify images with popular models like ResNet and ResNeXt. Recurrent neural networks are all the rage for time-series data and NLP.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Supported
Linux Supported
Cloud Not Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Developers, professionals and researchers seeking a solution for training deep learning models

Audience

Anyone requiring an open-source neural network framework for neural network processes and image recognition

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Supported

API

Offers API Not Supported

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

ConvNetJS
cs.stanford.edu/people/karpathy/convnetjs/

Company Information

Darknet
pjreddie.com/darknet/

Alternatives

Alternatives

Threat Landscape

Threat Landscape

Ecliptica Labs AB
Deci

Deci

Deci AI

Categories

Deep Learning Supported
Neural Network Supported

Categories

Neural Network Supported

Integrations

Qwen3-Omni Supported

Integrations

Qwen3-Omni Not Supported
Claim ConvNetJS and update features and information
Claim ConvNetJS and update features and information
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Claim Darknet and update features and information