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Open-unmix-pytorch Alternatives
Similar projects and alternatives to open-unmix-pytorch
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spleeter
Deezer source separation library including pretrained models.
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demucs
Code for the paper Hybrid Spectrogram and Waveform Source Separation, but the goddamm motherfucker doesn't work.
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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free-music-demixer
free website for client-side music demixing with Demucs + WebAssembly
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ultimatevocalremovergui
GUI for a Vocal Remover that uses Deep Neural Networks.
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1000sharks.xyz
Discontinued AI "metal artist" with SampleRNN (mirror from GitLab)
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EfficientAT
This repository aims at providing efficient CNNs for Audio Tagging. We provide AudioSet pre-trained models ready for downstream training and extraction of audio embeddings.
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stemroller
Isolate vocals, drums, bass, and other instrumental stems from any song
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umx.cpp
C++17 port of Open-Unmix-PyTorch with streaming inference, ggml, quantization, and Eigen
open-unmix-pytorch reviews and mentions
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Show HN: Improved freemusicdemixer (AI music demixing in the browser)
In my first post, quite a lot of alternatives were discussed: https://news.ycombinator.com/item?id=36707877
The model I'm using is called Open-Unmix (https://github.com/sigsep/open-unmix-pytorch). In 2021, there was an update to Open-Unmix to include new weights, UMX-L, which made it perform better than it used to on the older weights (UMXHQ).
In the grand landscape of music demixing, I don't think UMX-L is near the top anymore.
_However_, the demixing performance of freemusicdemixer.com is very close to the full PyTorch performance of Open-Unmix UMX-L, despite the tricks I needed to get it working in the browser, such as splitting up the inference to operate on segments of the song, or making the LSTM operate on streaming segments rather than holding the entire track in the LSTM memory.
In my first release, I loaded and did inference on the entire track at once (like the PyTorch model), which frequently crashed or exceeded the 4GB WASM memory for medium or large-size tracks.
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Show HN: Free AI-based music demixing in the browser
* Post-processing step (bigger impact)
I tried to tackle the post-processing step in my C++ code (which would win ~1 dB in quality across all targets) but it's too tricky for now [2]. Maybe some other day.
1: https://github.com/sevagh/free-music-demixer/blob/main/examp...
2: https://github.com/sigsep/open-unmix-pytorch/blob/master/ope...
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Splitter.fm: Listen to the individual instrument/vocal tracks (known as "stems") for over 700 songs uploaded by 150+ artists
I've had very good results with open-unmix
Or open-unmix. I've found it performs better than spleeter in some of my tests.
- I've created a website that extracts audio stems from songs using Spleeter, Demucs3, and Open Unmix for free.
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Cassiopeia: New Audio Splitter Superior to Spleeter and UMX
Spleeter and UMX are both FOSS [0] [1], whereas, as far as I can tell, Cassiopeia is not.
There's maybe something useful for you here?
https://github.com/facebookresearch/demucs
https://github.com/sigsep/open-unmix-pytorch
- [N Music Demixing (Audio Source Separation) Competition by Sony | ISMIR 2021
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[Research] Music Source Separation with AI networks: Comparison Tests incl. Spleeter, Lalal.ai, OpenUnmix and Extended Unmix
OpenUnmix ( is a neural network solution from Yuki Mitsufuji and Stefan Uhlich, music industry luminaries that work in Sony's core divisions.
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A note from our sponsor - SaaSHub
www.saashub.com | 29 Mar 2024
Stats
sigsep/open-unmix-pytorch is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of open-unmix-pytorch is Python.
Popular Comparisons
- open-unmix-pytorch VS spleeter
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- open-unmix-pytorch VS music_source_separation
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