title | emoji | colorFrom | colorTo | sdk | app_port | models | tags | pinned | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Moseca |
🎤🎸🥁🎹 |
yellow |
purple |
docker |
7860 |
|
true |
Create a new environment with Python 3.10 and install the requirements:
pip install -r requirements.txt
set the PYTHONPATH
to the root folder:
export PYTHONPATH=path/to/moseca
download the vocal remover model:
wget --progress=bar:force:noscroll https://huggingface.co/fabiogra/baseline_vocal_remover/resolve/main/baseline.pth
then run the app with:
streamlit run app/header.py
You can also run the app with Docker:
docker build -t moseca .
docker run -it --rm -p 7860:7860 $(DOCKER_IMAGE_NAME)
or pull the image from Hugging Face Spaces:
docker run -it -p 7860:7860 --platform=linux/amd64 \
registry.hf.space/fabiogra-moseca:latest
You can set the following environment variables to limit the resources used by the app:
- ENV_LIMITATION=true
- LIMIT_CPU=true
If you want to preprocess the samples used in the demo, you need to set the env variable PREPARE_SAMPLES=true
as a secret (create the file run/secrets/PREPARE_SAMPLES
with true
value inside).
If you run locally you also need to move the files inside scripts
to the root folder and run prepare_samples.sh
.
cp scripts/ .
chmod +x prepare_samples.sh
python prepare_samples.sh
Welcome to Moseca, your personal web application designed to redefine your music experience. Whether you're a musician looking to remix your favorite songs, a karaoke enthusiast, or a music lover wanting to dive deeper into your favorite tracks, Moseca is for you.
Separate up to 6 stems including 🗣voice, 🥁drums, 🔉bass, 🎸guitar, 🎹piano (beta), and 🎶 others.
Moseca utilizes state-of-the-art AI technology to extract voice or music from your original songs accurately.
Engage with your favorite tunes in a whole new way!
Moseca offers an immersive online karaoke experience, allowing you to search for any song on YouTube and remove the vocals online.
Enjoy singing along with high-quality instrumentals at the comfort of your home.
With Moseca, you can deploy your personal Moseca app in the or locally with in just one click.
You can also speed up the music separation process by with GPU support.
Moseca is the free and open-source alternative to lalal.ai, splitter.ai or media.io vocal remover.
You can modify, distribute, and use it free of charge. I believe in the power of community collaboration and encourage users to contribute to our source code, making Moseca better with each update.
- Show your support by giving a star to the GitHub repository .
- If you have found an issue or have a suggestion to improve Moseca, you can open an
- Enjoy Moseca?
Moseca is an open-source web app that utilizes advanced AI technology to separate vocals and instrumentals from music tracks. It also provides an online karaoke experience by allowing you to search for any song on YouTube and remove the vocals.
Yes, in this environment there are some limitations regarding lenght processing and CPU usage to allow a smooth experience for all users.
If you want to remove these limitations you can deploy a Moseca app in your personal environment like in the or locally with
Moseca utilizes the Hybrid Spectrogram and Waveform Source Separation (DEMUCS) model from Facebook. For fast karaoke vocal removal, Moseca uses the AI vocal remover developed by tsurumeso.
-
Upload your file: choose your song and upload it to Moseca. It supports a wide range of music formats for your convenience.
-
Choose separation mode: opt for voice only, 4-stem or 6-stem separation depending on your requirement.
-
Let AI do its magic: Moseca’s advanced AI will work to separate vocals from music in a matter of minutes, giving you high-quality, separated audio tracks.
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Download and enjoy: preview and download your separated audio tracks. Now you can enjoy them anytime, anywhere!
The code for Moseca is readily available on GitHub and Hugging Face.
For any questions or feedback, feel free to contact me on or LinkedIn.
Moseca is designed to separate vocals and instruments from copyrighted music for legally permissible purposes, such as learning, practicing, research, or other non-commercial activities that fall within the scope of fair use or exceptions to copyright. As a user, you are responsible for ensuring that your use of separated audio tracks complies with the legal requirements in your jurisdiction.