palettecleanse

palettecleanse

palettecleanse is a python library for quick conversions of images to custom color palettes

Installation

pip import palettecleanse

For manually installing requirements: pip install -r requirements.txt

To verify the installation worked, run the following code:

from palettecleanse.presets import TwilightSunset

TwilightSunset.display_plotly_examples()

Quickstart

To convert an image to a custom color palette, simply select an image and load it into palettecleanse as a Palette object, where desired attributes such as the number of colors (n_colors) can be specified as part of the class initialization. All available palettes for the image can be displayed via. the display_all_palettes method.

from palettecleanse.palettes import Palette

# load image
vangogh = Palette('images/vangogh.jpg')
vangogh.display_all_palettes()

Specific palette types (sequential, qualitative, etc) are stored as attributes for this object and are compatible with matplotlib, seaborn, and plotly.

# sequential palette in matplotlib
plt.scatter(x, y, c=colors, palette=vangogh.sequential)

# qualitative palette in matplotlib
plt.bar(categories, values, color=vangogh.qualitative)

# qualitative palette in seaborn
sns.swarmplot(df, x="x", y="y", hue="z", palette=vangogh.qualitative)

# generic palette in plotly
px.scatter(df, x="x", y="y", color="z", color_continuous_scale=vangogh.plotly)

To get a sense for how well your palette works, use the display_example_plots method

# this creates some misc plots using your generated palettes
vangogh.display_example_plots()

# plotly equivalent
vangogh.display_plotly_examples()

palettecleanse also comes prepackaged with some preset palettes:

from palettecleanse.presets import TwilightSunset

TwilightSunset.display_all_palettes()

See usage.ipynb for more examples.

Examples

All available preset palettes can be accessed via. the display_all_preset_palettes method

display_all_preset_palettes('sequential')

Below are example plots made using via. the display_example_plots method that can be used to get a bird's eye view on how well a palette behaves across generic plot types

Hokusai - The Great Wave off Kanagawa

Red Rose

Sunset

Bladerunner Olive

More examples available in usage.ipynb.

Contributing

Contributions at all levels are welcome! I'm happy to discuss with anyone the potential for contributions. Please see CONTRIBUTING.md for some general guidelines and message me with any questions!

Meta

Jiaming Chen – [e-mail]

Distributed under the MIT license. See LICENSE.txt for more information.

https://github.com/sansona/palettecleanse