This is the Linux app named Demucs whose latest release can be downloaded as demucsv4.0.1sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named Demucs with OnWorks for free.
Дотримуйтесь цих інструкцій, щоб запустити цю програму:
- 1. Завантажив цю програму на свій ПК.
- 2. Введіть у наш файловий менеджер https://www.onworks.net/myfiles.php?username=XXXXX із потрібним ім'ям користувача.
- 3. Завантажте цю програму в такий файловий менеджер.
- 4. Запустіть онлайн-емулятор OnWorks Linux або Windows або онлайн-емулятор MACOS з цього веб-сайту.
- 5. З ОС OnWorks Linux, яку ви щойно запустили, перейдіть до нашого файлового менеджера https://www.onworks.net/myfiles.php?username=XXXXX з потрібним іменем користувача.
- 6. Завантажте програму, встановіть її та запустіть.
ЕКРАНИ
Ad
Демукс
ОПИС
Demucs (Deep Extractor for Music Sources) is a deep-learning framework for music source separation—extracting individual instrument or vocal tracks from a mixed audio file. The system is based on a U-Net-like convolutional architecture combined with recurrent and transformer elements to capture both short-term and long-term temporal structure. It processes raw waveforms directly rather than spectrograms, allowing for higher-quality reconstruction and fewer artifacts in separated tracks. The repository includes pretrained models for common tasks such as isolating vocals, drums, bass, and accompaniment from stereo music, achieving state-of-the-art results in benchmarks like MUSDB18. Demucs supports GPU-accelerated inference and can process multi-channel audio with chunked streaming for real-time or batch operation. It also provides training scripts and utilities to fine-tune on custom datasets, along with remixing and enhancement tools.
Функції
- Neural music source separation from raw waveforms (vocals, drums, bass, others)
- U-Net-like architecture with recurrent and transformer layers for temporal modeling
- Pretrained models achieving top scores on MUSDB and similar benchmarks
- GPU-accelerated inference and streaming-based processing for real-time use
- Training utilities and scripts for custom datasets or fine-tuning
- Audio remixing, enhancement, and restoration tools integrated with model outputs
Мова програмування
Python
Категорії
This is an application that can also be fetched from https://sourceforge.net/projects/demucs.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
