79 lines
3.5 KiB
Python
79 lines
3.5 KiB
Python
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#!/usr/bin/env python3
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"""
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make_bottom_test1.py — flax-strand skirt texture for bottomTest1.
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python tools/tailor/textures/make_bottom_test1.py
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WHY THIS EXISTS
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The first bottom_test1.png (kept as bottom_test1_prestrand.png) was authored for a
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SOLID skirt panel and has two properties that fight the strand geometry:
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1. It paints its own VERTICAL STRAND LINES. The garment is now 32 discrete
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geometric strands, so those painted lines double up — strands-within-strands.
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2. Its band region VARIES ALONG U (measured horizontal stdev 68-83 per row, vs
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0-13 on the clean rows). Every geometric strand samples a different slice of
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that region, so the horizontal bands do not line up strand-to-strand and the
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skirt reads as broken noise instead of woven rows.
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THE RULE, and it is the whole trick: for a strand garment the texture must be a
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function of V ONLY. Constant along U means every strand samples the same colour at
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the same height, so bands align across all 32 strands automatically — regardless of
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each strand's UV position, its width, or how the drape stretched it. No UV surgery
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needed, and it stays true if the strand count changes.
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METHOD
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Collapse the reference to V-only by taking each row's MEDIAN colour. That keeps the
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original vertical rhythm (waistband, band groups, plain flax field) — the design
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intent — and throws away only the horizontal variation that was causing the noise.
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Then add back a very low-contrast vertical striation for fibre feel, small enough
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(+/- STRIATION levels) that it cannot resurrect the misalignment.
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Re-sampling happens through the EXISTING UVs, so this needs no MD session: rebuild
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the PNG, copy it next to the exported glTF, reimport the texture.
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"""
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import os
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import statistics
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from PIL import Image
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HERE = os.path.dirname(os.path.abspath(__file__))
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REF = os.path.join(HERE, "bottom_test1_prestrand.png") # the pre-strand original
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OUT = os.path.join(HERE, "bottom_test1.png")
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SIZE = 1024
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STRIATION = 6 # +/- levels of vertical fibre variation. Keep SMALL.
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STRIATION_PERIOD = 7 # px between fibre lines
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DPI = 43.3 # matches the original: 1024 px at 43.3 dpi = 600 mm of cloth
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def main():
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ref = Image.open(REF).convert("RGB").resize((SIZE, SIZE), Image.LANCZOS)
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px = ref.load()
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out = Image.new("RGB", (SIZE, SIZE))
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op = out.load()
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row_var_before, row_var_after = [], []
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for y in range(SIZE):
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row = [px[x, y] for x in range(SIZE)]
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med = tuple(int(statistics.median(c[i] for c in row)) for i in range(3))
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row_var_before.append(statistics.pstdev([sum(c) / 3 for c in row]))
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for x in range(SIZE):
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# deterministic, seed-free striation: a fixed comb, not noise, so the
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# result is byte-identical run to run (Date/random are avoided on
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# purpose — this file is a build input).
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d = STRIATION if (x % STRIATION_PERIOD) < STRIATION_PERIOD // 2 else -STRIATION
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op[x, y] = tuple(max(0, min(255, med[i] + d)) for i in range(3))
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row_var_after.append(
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statistics.pstdev([sum(op[x, y]) / 3 for x in range(0, SIZE, 4)]))
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out.save(OUT, dpi=(DPI, DPI))
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print("wrote %s (%dx%d, dpi %.1f)" % (OUT, SIZE, SIZE, DPI))
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print("mean horizontal stdev per row: %.1f -> %.1f (lower = bands align)"
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% (sum(row_var_before) / SIZE, sum(row_var_after) / SIZE))
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print("worst row stdev: %.1f -> %.1f"
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% (max(row_var_before), max(row_var_after)))
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if __name__ == "__main__":
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main()
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