paleta 1.0.1

Palette Extraction and Management Tool for Game Assets Experimentation

Paleta

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Paleta is a Color Pallet Extraction and Management Tool that is focused on enhancing Visual Game Assets. It supports pallet conversion, mixing, minimizing, and matching in any way possible.

Quick Guide

from paleta.color import Color
from paleta.palette import Palette
from paleta.image import export_palette, extract_convert_palette

# Initializing Colors
red = Color.from_hex("#F00")
green = Color.from_hex("#0F0")
blue = Color.from_hex("#00F")

# Operations on Color
magenta = red + blue
yellow = red + green
cyan = green + blue

print(magenta.rgba)  # Get RGBA value
print(yellow.to_lightness())  # To 0...255 Value
print(cyan.to_hsl())  # Get HSL Value

magenta += 10  # Add 10 across values of RGB
cyan -= (10, 0, 10)  # Subtract 10 across R and B value

twilight_5 = Palette(
    Color.from_hex("fbbbad"),
    Color.from_hex("ee8695"),
    Color.from_hex("4a7a96"),
    Color.from_hex("333f58"),
    Color.from_hex("292831")
)  # Create a Palette Class

tw = Palette.from_lospec("twilight-5")  # Or use the Lospec API

assert (twilight_5.colors == tw.colors)  # They're the same

twilight_5.add(yellow)  # Add yellow to the palette
twilight_5.remove(yellow)  # And Remove it

warm_ochre = Palette.from_lospec("warm-ochre")
the_after = Palette.from_lospec("the-after")

twilight_5.union(warm_ochre)  # Combine Palette Sets
twilight_5.intersection(the_after)  # Or find where they intersect

extract_convert_palette("ref.png", "palette.png", f_out="new_ref.png")  # Map a Palette to an Image
export_palette(warm_ochre, f="warm-ochre.png")  # Export a Created or Imported Palette

The script above shows the basics for simple use of this package. Simply, it treats Colors as a Vector(R, G, B, Alpha[Optional=255]) and a Palette as a Set of Colors with all basic set operations.

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Going Deeper

Mapping Palettes

from paleta.palette import Palette
from paleta.palette import ConversionPalette
from paleta.metric import euclidean_distance, cosine_distance, cosine_similarity

warm_ochre = Palette.from_lospec("warm-ochre")
the_after = Palette.from_lospec("the-after")

# Will create a Dictionary of how Palette (Warm Ochre) be mapped with Palette (The After)
# Using a Euclidean Distance Function and the Metric of Minimum Distance
cmap = ConversionPalette.map(warm_ochre, the_after, algo=euclidean_distance, metric=min)
print(cmap.to_dict())


# Making your own function works
def some_distance_function() -> float:
    # Map by distance
    return float()


def some_metric_function() -> object:
    # Find Max Value
    return max()


cmap2 = ConversionPalette.map(warm_ochre, the_after, algo=some_metric_function, metric=some_metric_function)
print(cmap2.to_dict())

# Randomize the Mapping
cmap3 = ConversionPalette.random(warm_ochre, the_after)
print(cmap3.to_dict())

Minimize or Maximize Palette

from paleta.palette import Palette
from paleta.palette import minimize_by_average, maximize_by_average

warm_ochre = Palette.from_lospec("warm-ochre")
the_after = Palette.from_lospec("the-after")

# Reduce the Palette by Averaging Neighboring Colors
min_warm_ochre = minimize_by_average(warm_ochre)
print(warm_ochre.color_set)
print(minimize_by_average(warm_ochre).color_set)
print(len(min_warm_ochre))

# Increase the Palette by Adding the Averaging of Neighboring Colors
max_the_after = minimize_by_average(the_after)
print(the_after.color_set)
print(minimize_by_average(the_after).color_set)
print(len(max_the_after))