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162 lines
8.2 KiB
Markdown
162 lines
8.2 KiB
Markdown
# Ultimate Vocal Remover GUI v5.4.0
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<img src="https://raw.githubusercontent.com/Anjok07/ultimatevocalremovergui/master/img/UVR_v54.png?raw=true" />
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[![Release](https://img.shields.io/github/release/anjok07/ultimatevocalremovergui.svg)](https://github.com/anjok07/ultimatevocalremovergui/releases/latest)
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[![Downloads](https://img.shields.io/github/downloads/anjok07/ultimatevocalremovergui/total.svg)](https://github.com/anjok07/ultimatevocalremovergui/releases)
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English | [简体中文](README_CN.md)
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## About
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This application uses state-of-the-art source separation models to remove vocals from audio files. UVR's core developers trained all of the models provided in this package (except for the Demucs v3 4-stem models).
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- **Core Developers**
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- [Anjok07](https://github.com/anjok07)
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- [aufr33](https://github.com/aufr33)
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- **Support the Project**
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- [Donate](https://www.buymeacoffee.com/uvr5)
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## Installation
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### Windows Installation
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This installation bundle contains the UVR interface, Python, PyTorch, and other dependencies needed to run the application effectively. No prerequisites are required.
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- Please Note:
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- This installer is intended for those running Windows 10 or higher.
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- Application functionality for systems running Windows 7 or lower is not guaranteed.
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- Application functionality for Intel Pentium & Celeron CPUs systems is not guaranteed.
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- Download the UVR installer via the link below:
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- [Main Download Link](https://uvr.uvr.workers.dev/UVR_v5.4.0_setup.exe)
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- [Main Download Link mirror](https://www.mediafire.com/file/nrakuh8t8p993y8/UVR_v5.4.0_setup.exe)
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- Update Package instructions for those who have UVR already installed:
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- [Update Package](https://github.com/Anjok07/ultimatevocalremovergui/releases/download/v5.4.0/UVR_v5.4_Update_Package.exe)
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- **Optional**
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- Additional models and application patches can be downloaded via the "Settings" menu within the application.
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- **Please Note:** Please install UVR to the main C:\ drive if you use the Windows installer. Installing UVR to a secondary drive will cause application instability.
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### Other Platforms
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This application does not currently run efficiently on Mac & Linux platforms yet. However, you can experiment with it by performing a manual install (see the **Manual Developer Installation** section below for more information). Some features may not be available on non-Windows platforms. An all-in-one version for MacOS will be coming soon.
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## Application Manual
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**General Options**
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<img src="https://github.com/Anjok07/ultimatevocalremovergui/blob/master/img/gen_opt.png?raw=true" />
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**VR Architecture Options**
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<img src="https://github.com/Anjok07/ultimatevocalremovergui/blob/master/img/vr_opt.png?raw=true" />
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**MDX-Net Options**
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<img src="https://github.com/Anjok07/ultimatevocalremovergui/blob/master/img/mdx_opt.png?raw=true" />
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**Demucs v3 Options**
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<img src="https://github.com/Anjok07/ultimatevocalremovergui/blob/master/img/demucs_opt.png?raw=true" />
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**Ensemble Options**
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<img src="https://github.com/Anjok07/ultimatevocalremovergui/blob/master/img/ense_opt.png?raw=true" />
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**User Ensemble**
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<img src="https://github.com/Anjok07/ultimatevocalremovergui/blob/master/img/user_ens_opt.png?raw=true" />
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### Other Application Notes
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- Nvidia GPUs with at least 8GBs of V-RAM are recommended.
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- This application is only compatible with 64-bit platforms.
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- This application relies on Sox - Sound Exchange for Noise Reduction.
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- This application relies on FFmpeg to process non-wav audio files.
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- The application will automatically remember your settings when closed.
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- Conversion times will significantly depend on your hardware.
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- These models are computationally intensive. Please proceed with caution and pay attention to your PC to ensure it doesn't overheat. ***We are not responsible for any hardware damage.***
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## Change Log
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- **v4 vs. v5**
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- The v5 models significantly outperform the v4 models.
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- The extraction's aggressiveness can be adjusted using the "Aggression Setting." The default value of 10 is optimal for most tracks.
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- All v2 and v4 models have been removed.
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- Ensemble Mode added - This allows the user to get the most robust result from each model.
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- Stacked models have been entirely removed.
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The new aggression setting and model ensembling have replaced the stacked model feature.
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- The NFFT, HOP_SIZE, and SR values are now set internally.
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- The MDX-NET AI engine and models have been added.
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- This is a brand new feature added to the UVR GUI.
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- 4 MDX-Net models are included in this package.
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- The MDX-Net models provided were trained by the core UVR developers
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- This network is less resource-intensive but incredibly powerful.
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- MDX-Net is a Hybrid Waveform/Spectrogram network.
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- The Demucs v3 AI engine and models have been added.
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- The ability to separate all 4 stems through Demucs v3.
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## Troubleshooting
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### Common Issues
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- If FFmpeg is not installed, the application will throw an error if the user attempts to convert a non-WAV file.
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- Memory allocation errors can usually be resolved by lowering the "Chunk Size".
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### Issue Reporting
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Please be as detailed as possible when posting a new issue.
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If possible, click the "Settings Button" to the left of the "Start Processing" button and click the "Error Log" button for detailed error information that can be provided to us.
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## Manual Installation (For Developers)
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These instructions are for those installing UVR v5.2.0 **manually** only.
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1. Download & install Python 3.9 or lower (but no lower than 3.6) [here](https://www.python.org/downloads/)
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- **Note:** Ensure the *"Add Python to PATH"* box is checked
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2. Download the Source code [here](https://github.com/Anjok07/ultimatevocalremovergui/archive/refs/heads/master.zip)
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3. Download the models via the "Settings" menu within the application.
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4. Extract the *ultimatevocalremovergui-master* folder within ultimatevocalremovergui-master.zip where ever you wish.
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5. Download the SoX archive [here](https://sourceforge.net/projects/sox/files/sox/14.4.2/sox-14.4.2-win32.zip/download) and extract the contents into the *ultimatevocalremovergui-master/lib_v5/sox* directory.
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6. Open the command prompt from the ultimatevocalremovergui-master directory and run the following commands, separately -
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```
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pip install --no-cache-dir -r requirements.txt
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```
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```
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pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio==0.9.0 -f https://download.pytorch.org/whl/torch_stable.html
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```
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From here you should be able to open and run the UVR.py file
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- FFmpeg
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- FFmpeg must be installed and configured for the application to process any track that isn't a *.wav* file. You will need to look up instruction on how to configure it on your operating system.
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## License
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The **Ultimate Vocal Remover GUI** code is [MIT-licensed](LICENSE).
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- **Please Note:** For all third-party application developers who wish to use our models, please honor the MIT license by providing credit to UVR and its developers.
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## Credits
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- [DilanBoskan](https://github.com/DilanBoskan) - Your contributions at the start of this project were essential to the success of UVR. Thank you!
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- [Bas Curtiz](https://www.youtube.com/user/bascurtiz) - Designed the official UVR logo, icon, banner, and splash screen.
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- [tsurumeso](https://github.com/tsurumeso) - Developed the original VR Architecture code.
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- [Kuielab & Woosung Choi](https://github.com/kuielab) - Developed the original MDX-Net AI code.
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- [Adefossez & Demucs](https://github.com/facebookresearch/demucs) - Developed the original Demucs AI code.
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- [KimberleyJSN](https://github.com/KimberleyJensen) - Advised and aided the implementation of the training scripts for MDX-Net and Demucs. Thank you!
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- [Hv](https://github.com/NaJeongMo/Colab-for-MDX_B) - Helped implement chunks into the MDX-Net AI code. Thank you!
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## Contributing
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- For anyone interested in the ongoing development of **Ultimate Vocal Remover GUI**, please send us a pull request, and we will review it.
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- This project is 100% open-source and free for anyone to use and modify as they wish.
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- We only maintain the development and support for the **Ultimate Vocal Remover GUI** and the models provided.
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## References
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- [1] Takahashi et al., "Multi-scale Multi-band DenseNets for Audio Source Separation", https://arxiv.org/pdf/1706.09588.pdf
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