PT-Muxer VS unmixer

Compare PT-Muxer vs unmixer and see what are their differences.

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PT-Muxer unmixer
2 1
46 12
- -
10.0 6.9
about 1 year ago 6 months ago
Python Python
- MIT License
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.

PT-Muxer

Posts with mentions or reviews of PT-Muxer. We have used some of these posts to build our list of alternatives and similar projects.

unmixer

Posts with mentions or reviews of unmixer. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-10-19.

What are some alternatives?

When comparing PT-Muxer and unmixer you can also consider the following projects:

mkvbatchmultiplex - Batch multiplex video files using MKVToolnix generated command line

Demucs-Gui - A GUI for music separation project demucs

mkv-muxing-batch-gui - App to muxing videos with audios/subtitles with so many options!

music-demixing-challenge-starter-kit - Starter kit for getting started in the Music Demixing Challenge.

mdx-net - KUIELAB-MDX-Net got the 2nd place on the Leaderboard A and the 3rd place on the Leaderboard B in the MDX-Challenge ISMIR 2021

KickFlix-cli - A command-line based, minimal torrent streaming client made using Python and Webtorrent-cli. Stream your favorite shows straight from the command line.

AutomaticDemuxer - Automatically Demux tracks from media-files

demucs - Code for the paper Hybrid Spectrogram and Waveform Source Separation, but the goddamm motherfucker doesn't work.

mss-thesis - Pytorch implementation of MDensenet and sparse NMF. Made for my undergraduate thesis "Music Source Separation with Supervised Learning Methods".