pyAudioProcessing | Audio feature extraction and classification | Audio Utils library

by jsingh811 Python Version: 1.1.13 License: GPL-3.0

X-Ray Key Features Code Snippets(4)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | pyAudioProcessing Summary

pyAudioProcessing is a Python library typically used in Audio, Audio Utils, Neural Network applications. pyAudioProcessing has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. You can install using 'pip install pyAudioProcessing' or download it from GitHub, PyPI.

A Python based library for processing audio data into features and building Machine Learning models. This was written using Python 3.7.6, and has been tested to work with Python >= 3.6, <4.

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Quality

Security

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Support

pyAudioProcessing has a low active ecosystem.

It has 71 star(s) with 23 fork(s). There are 4 watchers for this library.

It had no major release in the last 12 months.

There are 5 open issues and 8 have been closed. On average issues are closed in 35 days. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of pyAudioProcessing is 1.1.13

Quality

pyAudioProcessing has 0 bugs and 0 code smells.

Security

pyAudioProcessing has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

pyAudioProcessing code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

pyAudioProcessing is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

pyAudioProcessing releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

pyAudioProcessing saves you 291 person hours of effort in developing the same functionality from scratch.

It has 1191 lines of code, 43 functions and 16 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed pyAudioProcessing and discovered the below as its top functions. This is intended to give you an instant insight into pyAudioProcessing implemented functionality, and help decide if they suit your requirements.

Classify audio files
Train and classify and classify the given data folder
Write data to a JSON file
Classify data using features
Extract features from audio files
Extract features from a signal
Calculate the gfcc for a given signal
Compute the DCT matrix of the mesh
Convert audio files to wav
Convert from ana file to a WAV file
Plot time series
Compute the MFCC feature
Read requirements file
Calculate the singal flux
Center frequency space
Calculate the entropy of a signal
Wrapper for SpeechVSmusicVS
Roll off off of a signal
Compute the centroids of the centroids
Remove silence
Plot a spectrogram
Classify SpeechVSmusic model
Classify a music genre
Train and classify the model
Extract features
Compute the energy of a signal

Get all kandi verified functions for this library.

pyAudioProcessing Key Features

No Key Features are available at this moment for pyAudioProcessing.

pyAudioProcessing Examples and Code Snippets

pyAudioProcessing,Training and Testing Data structuring

Python

Lines of Code : 25

License : Strong Copyleft (GPL-3.0)

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.
├── training_data
├── music
│   ├── music_sample1.wav
│   ├── music_sample2.wav
│   ├── music_sample3.wav
│   ├── music_sample4.wav
├── speech
│   ├── speech_sample1.wav
│   ├── speech_sam

pyAudioProcessing,Extracting features from audios,Examples

Python

Lines of Code : 14

License : Strong Copyleft (GPL-3.0)

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from pyAudioProcessing.extract_features import get_features
# Feature extraction
features = get_features("data_samples/testing", ["gfcc", "mfcc"])
# features is a dictionary that will hold data of the following format
"""
{
  subdir1_name: {file1_pat

pyAudioProcessing,Getting Started

Python

Lines of Code : 7

License : Strong Copyleft (GPL-3.0)

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pip install pyAudioProcessing

pip install -U pyAudioProcessing

git clone git@github.com:jsingh811/pyAudioProcessing.git
cd pyAudioProcessing
pip install -e .

pip install -r requirements/requirements.txt

pip install -U numpy

Meeting a pip requirement using an alternative module

Python

Lines of Code : 4

License : Strong Copyleft (CC BY-SA 4.0)

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pip install git+https://github.com/julian-r/python-magic.git

pip install --no-deps git+https://github.com/jsingh811/pyAudioProcessing.git

Community Discussions

Trending Discussions on pyAudioProcessing

Meeting a pip requirement using an alternative module

QUESTION

Meeting a pip requirement using an alternative module

Asked 2021-Jun-10 at 11:17

I'm trying to install a python module, 'pyAudioProcessing' (https://github.com/jsingh811/pyAudioProcessing) on my Linux Mint distribution, and one of the items in requirements.txt is causing issues: python-magic-bin==0.4.14. When I run pip3 install -e pyAudioInstaller, I get an error:

...

ANSWER

Answered 2021-Mar-21 at 14:06

python-magic-bin 0.4.14 provides wheels for OSX, w32 and w64, but not for Linux. And there is no source code at PyPI.

You need to install it from github:

Source https://stackoverflow.com/questions/66732553

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install pyAudioProcessing

To upgrade to the latest version of pyAudioProcessing, the following pip command can be used. You can also get the requirements by running. If you are on Python 3.9 and experience any issues with the code samples regarding numpy, please run.
One way to install pyAudioProcessing and it's dependencies is from PyPI using pip
Or, you could also clone the project and get it setup

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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