PaddleHub
spleeter
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PaddleHub | spleeter | |
---|---|---|
9 | 230 | |
12,488 | 24,839 | |
0.6% | 1.2% | |
1.9 | 1.5 | |
6 months ago | about 1 month ago | |
Python | Python | |
Apache License 2.0 | MIT License |
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.
PaddleHub
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Where are all the multi-modal models?
China: All of the ERNIE 260B cross-modal stuff.
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[R] ERNIE-ViLG 2.0: Improving Text-to-Image Diffusion Model with Knowledge-Enhanced Mixture-of-Denoising-Experts + Gradio Demo
Hmm, is the code published? The thing on github just makes requests to a remote server.
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PaddleHub ERNIE-ViLG
PaddleHub has many interesting model, I have starred it. https://github.com/PaddlePaddle/PaddleHub
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[R] ERNIE-ViLG, a state-of-the-art text-to-image model that generates images from Chinese text
Was someone able to find out how big the model is and what hardware you need to run it? That info seems to be missing here.
- Baidu ERNIE-ViLG, output comparable to Stable Diffusion, better in anime
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ERNIE-ViLG, a state-of-the-art text-to-image model that generates images from Chinese text
note this is an updated version, more info here (in chinese): https://github.com/PaddlePaddle/PaddleHub/tree/develop/modules/image/text_to_image/ernie_vilg
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A text-to-image web app for ERNIE-ViLG is available, with output at 1024x1024 pixels. Example: "a beautiful chipmunk iceskating" (translated to Simplified Chinese by Google Translate). Links are in a comment.
GitHub repo.
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[P] PaddleHub: An awesome and easy-to-use pre-trained models toolkit
code:https://github.com/PaddlePaddle/PaddleHub
spleeter
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Are stems a good way of making mashups
virtual dj and others stem separator is shrinked model of this https://github.com/deezer/spleeter you will get better results downloading original + their large model.
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Big News!
I have used multiple tools at this point. It depends on the scene. I use https://ultimatevocalremover.com/, https://github.com/deezer/spleeter/, iZotope RX. There are also multiple options online, I would personally recommend https://vocalremover.org/.
- Anybody here know what AI model does Steinberg's Spectralayers use to do stem separation?
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Show HN: Free AI-based music demixing in the browser
I tried to use it but I had some issues as others in the thread.
I have tried many sources and method over the years and settled on spleeter [0]. Works well even for 10+ minute songs, varying styles from flamenco to heavy metal.
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AI tools list sorted by category in one place
Spleeter is pretty good https://github.com/deezer/spleeter. Apparently it is used in some dj applications
- Software to lower tracks?
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Where does one legally get stems for remixes?
Haha GitHub and command lines and all can be confusing, but it’s certainly worth the effort because it lets you do everything for free.. here’s the online tutorial: https://github.com/deezer/spleeter/wiki/1.-Installation
- Audio and python help
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Are there any websites or programs that can separate vocals and drums from samples?
Chopped from their website Simple Stems is a quick and easy way to decompose any audio into it’s constituent parts. The plugin uses the well established Spleeter algorithm by Deezer to deconstruct songs into 2, 4 or 5 stems. The results are stunning, though more complicated mixes and live recordings are not always perfectly decomposed.
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Ask HN: Is there an ML model that can go from an audio song to sheet music?
I was going to post basic pitch from Spotify but it looks like billconan beat me to it. That said I can give you a bit more advice. The Spotify basic pitch model isn't too good at multi-track input. It's capable of it, but you may actually get better results if you separate out the tracks first and then run them individually through the basic pitch model.
In order to do this you can use a source/stem separation model like spleeter (https://github.com/deezer/spleeter) and then run the basic pitch model (or any other midi transcription model). There's other you can try which may yield better results, for example: (https://github.com/Music-and-Culture-Technology-Lab/omnizart)
Either way the key words you want to be looking for are "midi transcription" and "stem separation", should help you find more models to try for both steps. Good luck! :)
What are some alternatives?
HDR-Multi-Tool - A graphical user interface for parsing HDR10+ and Dolby Vision
ultimatevocalremovergui - GUI for a Vocal Remover that uses Deep Neural Networks.
allennlp - An open-source NLP research library, built on PyTorch.
open-unmix-pytorch - Open-Unmix - Music Source Separation for PyTorch
stanford-tensorflow-tutorials - This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
demucs - Code for the paper Hybrid Spectrogram and Waveform Source Separation, but the goddamm motherfucker doesn't work.
deepdrive - Deepdrive is a simulator that allows anyone with a PC to push the state-of-the-art in self-driving
SpleeterGui - Windows desktop front end for Spleeter - AI source separation
best-of-ml-python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
SpleetGUI - Spleeter GUI version
tsdf-fusion-python - Python code to fuse multiple RGB-D images into a TSDF voxel volume.
spleeter-web - Self-hostable web app for isolating the vocal, accompaniment, bass, and drums of any song. Supports Spleeter, D3Net, Demucs, Tasnet, X-UMX. Built with React and Django.