FLAD | Fake Lossless Audio Detector | Audio Utils library

by Sg4Dylan Python Version: v0.1 License: Apache-2.0

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

kandi X-RAY | FLAD Summary

FLAD is a Python library typically used in Audio, Audio Utils applications. FLAD has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However FLAD build file is not available. You can download it from GitHub.

Fake Lossless Audio Detector.

Support

Quality

Security

License

Reuse

Support

FLAD has a low active ecosystem.

It has 28 star(s) with 1 fork(s). There are 2 watchers for this library.

It had no major release in the last 12 months.

There are 1 open issues and 1 have been closed. On average issues are closed in 128 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of FLAD is v0.1

Quality

FLAD has 0 bugs and 0 code smells.

Security

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

FLAD code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

FLAD is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

FLAD releases are available to install and integrate.

FLAD has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

It has 281 lines of code, 17 functions and 7 files.

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

Top functions reviewed by kandi - BETA

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

Compute the result of the model
Generate a spectrogram
Preprocess image
Resample the side of a file
Add noise to y_s
Compute the STFT
Generate noise files
Get list of files in target_root
Export a model
Load all files
Get the spectrum

Get all kandi verified functions for this library.

FLAD Key Features

No Key Features are available at this moment for FLAD.

FLAD Examples and Code Snippets

Usage

Python

Lines of Code : 4

License : Permissive (Apache-2.0)

Copy

# set input & output path  
audio_root = '/home/audio'  
ds_root = '/home/FLAD_Dataset/noise'  
ds_test = '/home/FLAD_Dataset/origin'

Community Discussions

Trending Discussions on FLAD

OutOfMemory when parsing a CSV file of 7M lines into Java Object

QUESTION

OutOfMemory when parsing a CSV file of 7M lines into Java Object

Asked 2018-Jul-05 at 23:29

I am extracting line by line a CSV file containing more than 7M lines occupuying more than 1Gig on disk space.

The reading operation into a List is fine and happens in less than 2 minutes. But the problem is when I try to loop on this list to and map each line to an object Balance then I created I get an OuyOfMemoryException:

...

ANSWER

Answered 2018-Jul-05 at 23:22

You are creating tons of instances (including the strings, which you are parsing later) in a short time, in which the garbage collector can't keep up. I recommend you to build the whole system in a stream design and to only parse the ones that you actually will need.

Source https://stackoverflow.com/questions/51201004

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

Vulnerabilities

No vulnerabilities reported

Install FLAD

You can download it from GitHub.
You can use FLAD 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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