mirror of
https://github.com/caelestia-dots/cli.git
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2 * r + 2 * t
f9a83990a9
Fix some wallpapers not having enough colours by disabling filter (also gives better colours) Use GNU parallel to run scheme generation in parallel Also ensure all schemes exist when generating Cache wallpaper thumbnails
105 lines
3.4 KiB
Python
Executable File
105 lines
3.4 KiB
Python
Executable File
#!/bin/python
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import sys
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from materialyoucolor.quantize import ImageQuantizeCelebi
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from materialyoucolor.hct import Hct
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from materialyoucolor.utils.math_utils import sanitize_degrees_int, difference_degrees
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from materialyoucolor.dislike.dislike_analyzer import DislikeAnalyzer
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class Score:
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TARGET_CHROMA = 48.0
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WEIGHT_PROPORTION = 0.7
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WEIGHT_CHROMA_ABOVE = 0.3
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WEIGHT_CHROMA_BELOW = 0.1
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CUTOFF_CHROMA = 5.0
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CUTOFF_EXCITED_PROPORTION = 0.01
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def __init__(self):
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pass
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@staticmethod
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def score(colors_to_population: dict) -> list[int]:
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desired = 14
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filter_enabled = False
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dislike_filter = True
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colors_hct = []
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hue_population = [0] * 360
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population_sum = 0
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for rgb, population in colors_to_population.items():
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hct = Hct.from_int(rgb)
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colors_hct.append(hct)
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hue = int(hct.hue)
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hue_population[hue] += population
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population_sum += population
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hue_excited_proportions = [0.0] * 360
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for hue in range(360):
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proportion = hue_population[hue] / population_sum
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for i in range(hue - 14, hue + 16):
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neighbor_hue = int(sanitize_degrees_int(i))
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hue_excited_proportions[neighbor_hue] += proportion
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scored_hct = []
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for hct in colors_hct:
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hue = int(sanitize_degrees_int(round(hct.hue)))
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proportion = hue_excited_proportions[hue]
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if filter_enabled and (
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hct.chroma < Score.CUTOFF_CHROMA
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or proportion <= Score.CUTOFF_EXCITED_PROPORTION
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):
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continue
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proportion_score = proportion * 100.0 * Score.WEIGHT_PROPORTION
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chroma_weight = (
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Score.WEIGHT_CHROMA_BELOW
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if hct.chroma < Score.TARGET_CHROMA
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else Score.WEIGHT_CHROMA_ABOVE
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)
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chroma_score = (hct.chroma - Score.TARGET_CHROMA) * chroma_weight
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score = proportion_score + chroma_score
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scored_hct.append({"hct": hct, "score": score})
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scored_hct.sort(key=lambda x: x["score"], reverse=True)
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chosen_colors = []
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for difference_degrees_ in range(90, 0, -1):
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chosen_colors.clear()
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for hct in [item["hct"] for item in scored_hct]:
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duplicate_hue = any(
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difference_degrees(hct.hue, chosen_hct.hue) < difference_degrees_
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for chosen_hct in chosen_colors
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)
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if not duplicate_hue:
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chosen_colors.append(hct)
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if len(chosen_colors) >= desired:
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break
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if len(chosen_colors) >= desired:
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break
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colors = []
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if dislike_filter:
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for chosen_hct in chosen_colors:
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chosen_colors[chosen_colors.index(chosen_hct)] = (
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DislikeAnalyzer.fix_if_disliked(chosen_hct)
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)
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for chosen_hct in chosen_colors:
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colors.append(chosen_hct.to_int())
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return colors
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if __name__ == "__main__":
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img = sys.argv[1]
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colours = ImageQuantizeCelebi(img, 1, 128)
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colours = [Hct.from_int(c).to_rgba()[:3] for c in Score.score(colours)]
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# print("".join(["\x1b[48;2;{};{};{}m \x1b[0m".format(*colour) for colour in colours]))
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print(" ".join(["{:02X}{:02X}{:02X}".format(*colour) for colour in colours]))
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