pwkit | Miscellaneous science/astronomy tools | Machine Learning library

by pkgw Python Version: 1.2.0 License: MIT

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

kandi X-RAY | pwkit Summary

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

Miscellaneous science/astronomy tools.

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Quality

Security

License

Reuse

Support

pwkit has a low active ecosystem.

It has 17 star(s) with 7 fork(s). There are 7 watchers for this library.

It had no major release in the last 12 months.

There are 0 open issues and 9 have been closed. On average issues are closed in 38 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of pwkit is 1.2.0

Quality

pwkit has 0 bugs and 0 code smells.

Security

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

pwkit code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

pwkit 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

pwkit releases are available to install and integrate.

Deployable package is available in PyPI.

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

It has 24471 lines of code, 1458 functions and 78 files.

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

Top functions reviewed by kandi - BETA

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

Return a pager
Open an image
Generate slices around a sequence of values
Create a ppplot
Parse command line arguments
Register a Command object
Populates the commands with the given values
Initialize the default environment
Function decorator
Create an image for a model
Compute the probability density function over a time series
Calculate the weighted variance of x
Create a tty plot
Make a multi - spectrum plot
Calculate the lmder1 function for the lmder1 algorithm
Invoke an astropy fits
Integrate quadratic quadrature
Calculate a newton function
Create a xyph plot
Compute the conf conf
Make a spectrum plot
Solve the problem with scipy
Calculate the distance between two points
Invoke epic aliases
Read the contents of a viz file
Handles flagmanager

Get all kandi verified functions for this library.

pwkit Key Features

No Key Features are available at this moment for pwkit.

pwkit Examples and Code Snippets

How to convert from sRGB to linear sRGB for computing the color correction matrix in opencv? (CCM)

Python

Lines of Code : 5

License : Strong Copyleft (CC BY-SA 4.0)

Copy

>>> int(round(colour.models.eotf_inverse_sRGB(0.18) * 255))
118

0.18116424424986022

Community Discussions

Trending Discussions on pwkit

How to convert from sRGB to linear sRGB for computing the color correction matrix in opencv? (CCM)

QUESTION

How to convert from sRGB to linear sRGB for computing the color correction matrix in opencv? (CCM)

Asked 2019-Jul-15 at 07:08

I have referred to the following stackoverflow thread for computing the color correction matrix.

As referred in the thread mentioned above, I want to convert from the sRGB color space to linear sRGB space, I'm trying to use the pwkit colorspace mapper code for the conversion.

However, i'm unsure about the resulting linear sRGB values, since the function requires sRGB in range [0-1], is dividing the sRGB values by 255.0, the correct approach? How to verify that the linear sRGB values returned by the function are correct?

...

ANSWER

Answered 2019-Jul-15 at 06:50

From a terminology standpoint and assuming your image was effectively sRGB encoded, i.e. following IEC 61966-2-1:1999, you are decoding sRGB encoded non-linear light values by applying the sRGB Electro-Optical Transfer Function (EOTF), a type of colour component transfer function (CCTF) thus saying:

I want to convert from the sRGB color space to linear RGB space

is not correct because you are still effectively using sRGB encoded colours, the only difference is that prior to using the decoding CCTF they were non-linearly encoded. An additive RGB colourspace is defined by a set of three components: primaries, whitepoint and CCTFs. By using the CCTF you have not changed at all the primaries or whitepoint, i.e. the gamut is the same, thus what you should say is more along those lines:

I want to convert from the sRGB color space to linear sRGB color space

Now to verify that your approach is correct, you can compare with a reference implementation such as Colour whose code is used in the SO thread you referenced: 18% gray is 118 upon non-linear encoding using sRGB inverse EOTF:

Source https://stackoverflow.com/questions/57033168

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

Vulnerabilities

No vulnerabilities reported

Install pwkit

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