RRS First version

2026-09-12 03:08:23 -04:00
commit c050d25a84
41 changed files with 5575 additions and 0 deletions
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+"""Create original illustrative knit textures, not photographs of RRS products.
+Requires Pillow and NumPy. Generated assets are committed; runtime needs neither.
+"""
+from pathlib import Path
+import math
+import random
+import numpy as np
+from PIL import Image, ImageDraw, ImageFilter
+
+OUTPUT = Path(__file__).resolve().parents[1] / 'public' / 'images'
+OUTPUT.mkdir(parents=True, exist_ok=True)
+
+
+def texture(name, spacing, base, seed):
+    rng = random.Random(seed)
+    width, height = 1600, 1200
+    image = Image.new('RGB', (width, height), tuple(round(c * .7) for c in base))
+    draw = ImageDraw.Draw(image)
+    for row in range(-2, round(height / (spacing * .72)) + 3):
+        for column in range(-2, width // spacing + 3):
+            x = column * spacing + math.sin(row * .16) * spacing * .16
+            y = row * spacing * .72
+            tone = rng.uniform(.91, 1.05)
+            for side in (-1, 1):
+                points = []
+                for step in range(35):
+                    t = step / 34
+                    px = x + side * spacing * (.04 + .43 * (1 - t) + .07 * math.sin(t * math.pi))
+                    py = y + spacing * (t * .95 - .15)
+                    points.append((px, py))
+                draw.line([(px + 3, py + 4) for px, py in points], fill=tuple(round(c * .55) for c in base), width=round(spacing * .36))
+                draw.line(points, fill=tuple(min(255, round(c * tone * .84)) for c in base), width=round(spacing * .32))
+                for strand in range(11):
+                    offset = (strand - 5) * spacing * .027
+                    fibre = [(px + offset + math.sin(i * .9 + strand) * .7, py) for i, (px, py) in enumerate(points)]
+                    light = tone * (.78 + .24 * math.sin(strand * .28))
+                    draw.line(fibre, fill=tuple(min(255, round(c * light)) for c in base), width=max(1, spacing // 32))
+    pixels = np.asarray(image).astype(float)
+    yy, xx = np.mgrid[0:height, 0:width]
+    folds = .91 + .14 * np.sin(xx / 210 + yy / 380) + .05 * np.sin(xx / 82 - yy / 230)
+    noise = np.random.default_rng(seed).normal(0, 2.1, (height, width))
+    pixels = np.clip(pixels * folds[:, :, None] + noise[:, :, None], 0, 255).astype('uint8')
+    Image.fromarray(pixels).filter(ImageFilter.GaussianBlur(.3)).save(OUTPUT / name, quality=90, optimize=True)
+
+
+texture('knit-natural.jpg', 70, (218, 205, 181), 21)
+texture('knit-fine.jpg', 27, (221, 214, 197), 42)
+texture('knit-structured.jpg', 108, (180, 170, 147), 63)