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2 * r + 2 * t
43 lines
1.0 KiB
Python
43 lines
1.0 KiB
Python
import math
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from PIL import Image
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def mean(values: list[float]) -> float:
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return sum(values) / len(values) if values else 0
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def stddev(values: list[float], mean_val: float) -> float:
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return math.sqrt(sum((x - mean_val) ** 2 for x in values) / len(values)) if values else 0
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def calc_colourfulness(image: Image) -> float:
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width, height = image.size
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pixels = list(image.getdata()) # List of (R, G, B) tuples
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rg_diffs = []
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yb_diffs = []
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for r, g, b in pixels:
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rg = abs(r - g)
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yb = abs(0.5 * (r + g) - b)
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rg_diffs.append(rg)
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yb_diffs.append(yb)
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mean_rg = mean(rg_diffs)
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mean_yb = mean(yb_diffs)
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std_rg = stddev(rg_diffs, mean_rg)
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std_yb = stddev(yb_diffs, mean_yb)
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return math.sqrt(std_rg**2 + std_yb**2) + 0.3 * math.sqrt(mean_rg**2 + mean_yb**2)
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def get_variant(image: Image) -> str:
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colourfulness = calc_colourfulness(image)
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if colourfulness < 10:
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return "neutral"
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if colourfulness < 20:
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return "content"
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return "tonalspot"
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