vocal-remover | Vocal Remover using Deep Neural Networks | Machine Learning library
kandi X-RAY | vocal-remover Summary
kandi X-RAY | vocal-remover Summary
vocal-remover is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Neural Network applications. vocal-remover has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can download it from GitHub.
Vocal Remover using Deep Neural Networks
Vocal Remover using Deep Neural Networks
Support
Quality
Security
License
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Support
vocal-remover has a medium active ecosystem.
It has 936 star(s) with 148 fork(s). There are 32 watchers for this library.
It had no major release in the last 12 months.
There are 36 open issues and 60 have been closed. On average issues are closed in 84 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of vocal-remover is v5.0.3
Quality
vocal-remover has 0 bugs and 0 code smells.
Security
vocal-remover has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
vocal-remover code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
vocal-remover is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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vocal-remover releases are available to install and integrate.
Build file is available. You can build the component from source.
Installation instructions, examples and code snippets are available.
Top functions reviewed by kandi - BETA
kandi has reviewed vocal-remover and discovered the below as its top functions. This is intended to give you an instant insight into vocal-remover implemented functionality, and help decide if they suit your requirements.
- Separate the features in a set of features
- Split data into masks
- Apply postprocessing
- Performs preprocessing
- Cache the given mix file
- Align wave head and tail
- Convert waveform to spectrogram
- Validate a single epoch
- Return the predicted value
- Split training and validation
- Create a list of files from mixing_dir
- Create validation set
- Make padding
- Convert a spectrogram to an image
- Setup a logger
- Train a single epoch
- Make a list of files from mix_dir and inst_dir
- Parses the input data
- Write image to filename
- Convert a spectrogram to a waveform
Get all kandi verified functions for this library.
vocal-remover Key Features
No Key Features are available at this moment for vocal-remover.
vocal-remover Examples and Code Snippets
No Code Snippets are available at this moment for vocal-remover.
Community Discussions
Trending Discussions on vocal-remover
QUESTION
PermissionError: [Errno 13] Permission denied failure
Asked 2020-Jan-04 at 17:24
I have never used python before and I want to build a project I found on github but I have not solved a problem there for 2 hours. I don't think it's a problem that I've installed all the packages individually. I've applied all the necessary documents that he narrates, but when I run the following command, I get an error How can I solve this error?
https://github.com/tsurumeso/vocal-remover
Run
...ANSWER
Answered 2020-Jan-04 at 17:07I found the solution to the problem.
False
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install vocal-remover
You can download it from GitHub.
You can use vocal-remover like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use vocal-remover like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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