kapre | kapre : Keras Audio Preprocessors | Machine Learning library

by keunwoochoi Python Version: 0.3.7 License: MIT

X-Ray Key Features Code Snippets(3)Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | kapre Summary

kapre is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow, Keras, Neural Network applications. kapre has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can install using 'pip install kapre' or download it from GitHub, PyPI.

Keras Audio Preprocessors - compute STFT, ISTFT, Melspectrogram, and others on GPU real-time. Tested on Python 3.6 and 3.7.

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Quality

Security

License

Reuse

Support

kapre has a medium active ecosystem.

It has 889 star(s) with 146 fork(s). There are 23 watchers for this library.

It had no major release in the last 12 months.

There are 13 open issues and 82 have been closed. On average issues are closed in 196 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of kapre is 0.3.7

Quality

kapre has 0 bugs and 0 code smells.

Security

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

kapre code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

kapre is licensed under the MIT License. This license is Permissive.

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

Reuse

kapre releases are available to install and integrate.

Deployable package is available in PyPI.

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

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

kapre saves you 682 person hours of effort in developing the same functionality from scratch.

It has 2091 lines of code, 118 functions and 16 files.

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

Top functions reviewed by kandi - BETA

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

Calculate the STFT transform
Construct a fixed frame from a fixed frame
Compute the TFT of the given signal
Calculate the DFT of a signal
Compute the complex Fourier transformation matrix for the Fourier transform
Applies the spectrum segment
Applies masks to the given axis
Calculate the angle of x
Calculate the at least squares at y
Computes the continued fraction of x
Convert magnitude to decimal degrees
Calculates the decimals of magnitude
Compute the mu - law
Calculates the mu - law of a signal
Calculate the tangent function
Calculate the background function
Implements mu - law decoder
Concatenate multiple frequencies
Concatenate frequency map

Get all kandi verified functions for this library.

kapre Key Features

No Key Features are available at this moment for kapre.

kapre Examples and Code Snippets

Checks to see if a number is kapre .

java

Lines of Code : 27

License : Permissive (MIT License)

Copy

public static boolean isKaprekarNumber(long num) {
		String number = Long.toString(num);
		BigInteger originalNumber = new BigInteger(number);
		BigInteger numberSquared = originalNumber.multiply(originalNumber);
		if(number.length() == numberSquared

check the kapre k .

java

Lines of Code : 23

License : Permissive (MIT License)

Copy

static boolean kaprekar(int n)   
    {   
        if (n == 1)//checking   
            return true;   
        int sq_n = n * n;
        int copy=sq_n;
        int d= 0;   
        while (copy != 0)   
        {   
            d++;   
            co

check the kapre of k

java

Lines of Code : 18

License : Permissive (MIT License)

Copy

static boolean kaprekar(int n)   
    {   
        int cpy=n;// copy the number
        int p=1;// initialize
        while(cpy>0)//checking
        {
            p=p*10;
            cpy=cpy/10;
        }
        int s=n*n;// square of the number

Community Discussions

Trending Discussions on kapre

Multipoint(df['geometry']) key error from dataframe but key exist. KeyError: 13 geopandas

How to make predictions on new audio files with pre-trained network?

QUESTION

Multipoint(df['geometry']) key error from dataframe but key exist. KeyError: 13 geopandas

Asked 2021-Oct-11 at 14:51

data source: https://catalog.data.gov/dataset/nyc-transit-subway-entrance-and-exit-data

I tried looking for a similar problem but I can't find an answer and the error does not help much. I'm kinda frustrated at this point. Thanks for the help. I'm calculating the closest distance from a point.

...

ANSWER

Answered 2021-Oct-11 at 14:21

geopandas 0.10.1

have noted that your data is on kaggle, so start by sourcing it
there really is only one issue shapely.geometry.MultiPoint() constructor does not work with a filtered series. Pass it a numpy array instead and it works.
full code below, have randomly selected a point to serve as gpdPoint

Source https://stackoverflow.com/questions/69521034

QUESTION

How to make predictions on new audio files with pre-trained network?

Asked 2020-Nov-23 at 01:20

I needed a deep learning algorithm for sound classification which uses the pre-trained model to make predictions on new audio files. Since I am new to python I was working on this sound classification algorithm that I found but which works great but currently, it outputs the real class of each audio file in the data set and their predicted classes. Instead, I need it to predict the class of new audio files, which are not labeled at all but I was unsuccessful at modifying the code to work as I wanted.

The code I am currently using:

...

ANSWER

Answered 2020-Nov-23 at 01:20

In the section of code

Source https://stackoverflow.com/questions/64954560

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

Vulnerabilities

No vulnerabilities reported

Install kapre

You can install using 'pip install kapre' or download it from GitHub, PyPI.
You can use kapre 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.