How to Install and Uninstall python3-colorspacious Package on openSUSE Leap
Last updated: January 11,2025
1. Install "python3-colorspacious" package
This guide covers the steps necessary to install python3-colorspacious on openSUSE Leap
$
sudo zypper refresh
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$
sudo zypper install
python3-colorspacious
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2. Uninstall "python3-colorspacious" package
This guide covers the steps necessary to uninstall python3-colorspacious on openSUSE Leap:
$
sudo zypper remove
python3-colorspacious
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3. Information about the python3-colorspacious package on openSUSE Leap
Information for package python3-colorspacious:
----------------------------------------------
Repository : Main Repository
Name : python3-colorspacious
Version : 1.1.2-bp155.2.11
Arch : noarch
Vendor : openSUSE
Installed Size : 245.4 KiB
Installed : No
Status : not installed
Source package : python-colorspacious-1.1.2-bp155.2.11.src
Upstream URL : https://github.com/njsmith/colorspacious
Summary : Python library for doing colorspace conversions
Description :
Colorspacious is a library for performing colorspace conversions.
In addition to the most common standard colorspaces (sRGB, XYZ, xyY,
CIELab, CIELCh), it also includes color vision deficiency ("color
blindness") simulations using the approach of Machado et al (2009), a
complete implementation of CIECAM02
, and the perceptually
uniform CAM02-UCS / CAM02-LCD / CAM02-SCD spaces proposed by Luo et al
(2006).
----------------------------------------------
Repository : Main Repository
Name : python3-colorspacious
Version : 1.1.2-bp155.2.11
Arch : noarch
Vendor : openSUSE
Installed Size : 245.4 KiB
Installed : No
Status : not installed
Source package : python-colorspacious-1.1.2-bp155.2.11.src
Upstream URL : https://github.com/njsmith/colorspacious
Summary : Python library for doing colorspace conversions
Description :
Colorspacious is a library for performing colorspace conversions.
In addition to the most common standard colorspaces (sRGB, XYZ, xyY,
CIELab, CIELCh), it also includes color vision deficiency ("color
blindness") simulations using the approach of Machado et al (2009), a
complete implementation of CIECAM02
uniform CAM02-UCS / CAM02-LCD / CAM02-SCD spaces proposed by Luo et al
(2006).