opus-java VS javacpp-presets

Compare opus-java vs javacpp-presets and see what are their differences.

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opus-java javacpp-presets
1 9
41 2,576
- 1.4%
3.6 8.0
over 2 years ago 3 days ago
Java Java
Apache License 2.0 GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

opus-java

Posts with mentions or reviews of opus-java. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-01-12.

javacpp-presets

Posts with mentions or reviews of javacpp-presets. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-05-27.

What are some alternatives?

When comparing opus-java and javacpp-presets you can also consider the following projects:

discord-webhooks - Provides easy to use bindings for the Discord Webhook API

Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration

Hibernate - Hibernate's core Object/Relational Mapping functionality

JavaCV - Java interface to OpenCV, FFmpeg, and more

libGDX - Desktop/Android/HTML5/iOS Java game development framework

youtubedl-android - youtube-dl for android

OggJavaPlayer - Play Ogg in Java

Deep Java Library (DJL) - An Engine-Agnostic Deep Learning Framework in Java

rotp-public - Public repository for Remnants of the Precursors

api-swgoh-help - Java client wrapper for the API at https://api.swgoh.help

instancio - A library that creates fully populated objects for your unit tests.

Deeplearning4j - Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learning using automatic differentiation.