Quantize with a measured Spectra 6 palette and OKLab-space ordered dithering

DEFAULT_PALETTE_RGB was a guessed approximation of the panel's ink
colors (pure sRGB primaries); swap in epdoptimize's measured spectra6
palette instead, which is far more muted/darker, matching how these
inks actually look.

_quantize now matches against the palette in OKLab space (perceptual
distance) instead of PIL's raw-RGB quantize(), with lightness weighted
down relative to hue/chroma when selecting the nearest color -- this
palette's inks are lit so differently from their sRGB namesakes
(muted dark red, bright yellow) that unweighted distance let lightness
dominate and mismatch hue (pure red nearest "yellow").

Dithering switched from Floyd-Steinberg error diffusion to a Bayer
ordered dither: true error diffusion is an inherently serial per-pixel
loop, and doing that in pure Python for a full 800x480 panel took
~1s, blowing past the render-latency budget the "render widgets
concurrently" fix (previous commit) exists to protect. The ordered
dither finds each pixel's true nearest and second-nearest palette
color and mixes between them (via projection onto that segment, not
distance ratio) using a tiled Bayer threshold -- fully vectorized, no
Python-level pixel loop.

server/app/image_pipeline.py

@@ -5,13 +5,14 @@ from __future__ import annotations
 import io
 import math
 
+import numpy as np
 from PIL import Image, ImageDraw, ImageEnhance, ImageFont, ImageOps
 
 EPD_WIDTH = 800
 EPD_HEIGHT = 480
 
 # PIL's TrueType rendering antialiases by default (graduated gray edge
-# pixels). Those survive straight into _quantize's Floyd-Steinberg
+# pixels). Those survive straight into _quantize's error-diffusion
 # dithering, which -- confirmed visually -- turns them into scattered
 # colored speckles along every glyph edge once forced onto the panel's 6
 # colors, since a mid-gray input has no close palette match and the
@@ -148,20 +149,24 @@ def logical_to_native(x: float, y: float, orientation: str) -> tuple[int, int]:
         return int(logical_h - 1 - y), int(x)
     return int(x), int(y)
 
-# Approximate sRGB for each of the panel's 6 ink colors -- reasonable
-# placeholders, not measured values (Waveshare doesn't publish exact
-# color primaries for this panel). This is the fallback for any frame
-# that hasn't tuned its own (Frame.palette_rgb, set from a frame's
-# Configuration tab -- "Advanced configuration" -- once you can compare
-# a rendered test image against the real panel; different panel units
-# can vary enough to be worth calibrating per frame).
+# Measured sRGB appearance of each of the panel's 6 ink colors on an
+# actual Spectra 6 panel -- sourced from epdoptimize's "spectra6" palette
+# (github.com/paperlesspaper/epdoptimize, src/dither/data/default-palettes
+# .json), not our own calibration, but a much better starting point than a
+# guess: e-ink ink never reaches full sRGB saturation/contrast, so this is
+# uniformly darker and more muted than the naive (0,0,0)/(255,255,255)/pure
+# hues this used to be. This is the fallback for any frame that hasn't
+# tuned its own (Frame.palette_rgb, set from a frame's Configuration tab
+# -- "Advanced configuration" -- once you can compare a rendered test
+# image against the real panel; different panel units can vary enough to
+# be worth calibrating per frame).
 DEFAULT_PALETTE_RGB = [
-    (0, 0, 0),  # BLACK
-    (255, 255, 255),  # WHITE
-    (255, 219, 0),  # YELLOW
-    (207, 0, 15),  # RED
-    (0, 39, 133),  # BLUE
-    (0, 133, 55),  # GREEN
+    (31, 34, 38),  # BLACK
+    (185, 199, 201),  # WHITE
+    (193, 187, 30),  # YELLOW
+    (98, 32, 30),  # RED
+    (35, 63, 142),  # BLUE
+    (53, 86, 58),  # GREEN
 ]
 
 PALETTE_LABELS = ["Black", "White", "Yellow", "Red", "Blue", "Green"]
@@ -222,10 +227,137 @@ def hex_to_rgb(hex_str: str) -> tuple[int, int, int] | None:
         return None
 
 
-def _build_palette_image(palette_rgb: list) -> Image.Image:
-    pal_img = Image.new("P", (1, 1))
-    pal_img.putpalette([channel for rgb in palette_rgb for channel in rgb])
-    return pal_img
+def _rgb_to_oklab(rgb: "np.ndarray") -> "np.ndarray":
+    """(...,3) uint8/float sRGB -> (...,3) float32 OKLab (Bjorn Ottosson's
+    formulation, https://bottosson.github.io/posts/oklab/). Used instead
+    of raw RGB distance for palette matching/error diffusion below --
+    Euclidean distance in OKLab tracks perceived color difference far
+    better than in RGB, which matters a lot once the "colors" being
+    matched against are a 6-entry palette this coarse."""
+    linear = (rgb.astype(np.float32) / 255.0)
+    linear = np.where(linear <= 0.04045, linear / 12.92, ((linear + 0.055) / 1.055) ** 2.4)
+    r, g, b = linear[..., 0], linear[..., 1], linear[..., 2]
+
+    l = 0.4122214708 * r + 0.5363325363 * g + 0.0514459929 * b
+    m = 0.2119034982 * r + 0.6806995451 * g + 0.1073969566 * b
+    s = 0.0883024619 * r + 0.2817188376 * g + 0.6299787005 * b
+    l_, m_, s_ = np.cbrt(l), np.cbrt(m), np.cbrt(s)
+
+    L = 0.2104542553 * l_ + 0.7936177850 * m_ - 0.0040720468 * s_
+    a = 1.9779984951 * l_ - 2.4285922050 * m_ + 0.4505937099 * s_
+    b2 = 0.0259040371 * l_ + 0.7827717662 * m_ - 0.8086757660 * s_
+    return np.stack([L, a, b2], axis=-1)
+
+
+# Lightness is weighted down relative to a/b when *choosing* the nearest
+# palette entry (established color-difference formulas -- CIE94, CMC --
+# do the same, on the general principle that a lightness mismatch reads
+# as less objectionable than a hue mismatch). Not optional polish: this
+# palette's ink colors are far darker/lighter than their sRGB namesakes
+# (e.g. "red" ink is a dark #62201E, "yellow" ink is a bright #C1BB1E),
+# so unweighted OKLab distance lets that lightness gap dominate and pure
+# saturated red (high L) ends up nearer "yellow" (L=0.77) than "red"
+# (L=0.35) even though red is unambiguously closer in hue/chroma (a/b) --
+# confirmed both analytically and by DEFAULT_PALETTE_RGB's own test
+# coverage (test_render_size_invariants.py's pure-red/pure-blue check).
+_LIGHTNESS_MATCH_WEIGHT = 0.5
+
+
+def _nearest_palette_indices(oklab_pixels: "np.ndarray", palette_oklab: "np.ndarray") -> "np.ndarray":
+    """(H,W,3) OKLab pixels, (K,3) OKLab palette -> (H,W) index array, no
+    error diffusion -- the "flat"/undithered quantization, vectorized
+    (K is always 6, so brute-force all-pairs distance is cheap and this
+    stays a single numpy call rather than a per-pixel Python loop)."""
+    diffs2 = (oklab_pixels[:, :, None, :] - palette_oklab[None, None, :, :]) ** 2
+    weights = np.array([_LIGHTNESS_MATCH_WEIGHT, 1.0, 1.0], dtype=np.float32)
+    dist2 = (diffs2 * weights).sum(axis=-1)
+    return np.argmin(dist2, axis=2)
+
+
+def _bayer_matrix(n: int) -> "np.ndarray":
+    """Recursive construction of the standard n x n (n a power of 2)
+    Bayer ordered-dithering threshold matrix, values 0..n*n-1, each used
+    exactly once -- the classic recursive doubling
+    (https://en.wikipedia.org/wiki/Ordered_dithering)."""
+    if n == 1:
+        return np.zeros((1, 1))
+    smaller = _bayer_matrix(n // 2)
+    return np.block([
+        [4 * smaller, 4 * smaller + 2],
+        [4 * smaller + 3, 4 * smaller + 1],
+    ])
+
+
+# Normalized to [0, 1): a deterministic per-pixel threshold tiled across
+# the image, used (like classic ordered/Bayer dithering) to decide, for
+# each pixel, whether it plots as its nearest or second-nearest palette
+# color -- see _ordered_dither_oklab.
+_BAYER_8 = (_bayer_matrix(8) + 0.5) / 64.0
+
+
+def _ordered_dither_oklab(oklab_pixels: "np.ndarray", palette_oklab: "np.ndarray") -> "np.ndarray":
+    """(H,W,3) OKLab pixels, (K,3) OKLab palette -> (H,W) uint8 index
+    array, ordered (Bayer matrix) dithering -- picked over error
+    diffusion (Floyd-Steinberg/Atkinson/etc.) specifically because it's
+    fully vectorizable: no pixel-to-pixel dependency to chain through a
+    Python loop, just a fixed number of numpy calls over the whole
+    image. A straight per-pixel error-diffusion loop in Python was
+    measured at ~1s for a full 800x480 panel -- see
+    test_widgets_render_concurrently's latency budget (the whole reason
+    widgets render concurrently in the first place, see git history) --
+    which this avoids entirely.
+
+    Finds each pixel's true nearest and second-nearest palette color and
+    mixes between exactly those two, using the Bayer threshold as the
+    per-pixel coin flip -- the standard generalization of ordered
+    dithering to a palette whose entries aren't evenly spaced (unlike,
+    say, dithering 0-255 gray down to a handful of even steps). The
+    mixing fraction is the pixel's projection onto the segment from its
+    nearest color to its second-nearest, NOT distance-to-nearest over
+    total distance (d0/(d0+d1)) -- an earlier version used that ratio
+    and it's wrong whenever the second-nearest color is simply far away
+    in an unrelated direction rather than genuinely "on the other side"
+    of the pixel: d1 being large made the ratio look small-mixing-needed
+    only when d0 was *also* comparably large, so a pixel sitting almost
+    exactly on its nearest color still got a large fraction of an
+    unrelated second color -- confirmed visually as entire regions
+    (e.g. a pale sky, clearly nearest White) rendering as flat blocks of
+    a wrong, unrelated color (Yellow) instead of White. Projection onto
+    the actual nearest-neighbor segment doesn't have that failure mode:
+    a pixel essentially at c0 projects to ~0 regardless of where c1 is."""
+    weights = np.array([_LIGHTNESS_MATCH_WEIGHT, 1.0, 1.0], dtype=np.float32)
+    scale = np.sqrt(weights)
+    pixels_w = oklab_pixels * scale
+    palette_w = palette_oklab * scale
+
+    dist2 = ((pixels_w[:, :, None, :] - palette_w[None, None, :, :]) ** 2).sum(axis=-1)  # (H, W, K)
+    order = np.argsort(dist2, axis=-1)
+    idx0, idx1 = order[..., 0], order[..., 1]
+
+    c0 = palette_w[idx0]  # (H, W, 3)
+    c1 = palette_w[idx1]  # (H, W, 3)
+    segment = c1 - c0
+    to_pixel = pixels_w - c0
+    segment_len2 = (segment * segment).sum(axis=-1)
+    t = np.divide((to_pixel * segment).sum(axis=-1), segment_len2,
+                  out=np.zeros_like(segment_len2), where=segment_len2 > 1e-12)
+    t = np.clip(t, 0.0, 1.0)
+
+    h, w, _ = oklab_pixels.shape
+    threshold = np.tile(_BAYER_8, (h // 8 + 1, w // 8 + 1))[:h, :w]
+    use_second = threshold < t
+    return np.where(use_second, idx1, idx0).astype(np.uint8)
+
+
+def _index_array_to_p_image(idx_array: "np.ndarray", palette_rgb: list) -> Image.Image:
+    """(H,W) palette-index array -> a PIL "P"-mode image carrying
+    `palette_rgb` as its palette, so downstream code (as_png's
+    .convert("RGB"), _transpose_and_pack's pixels[x, y] index lookups)
+    behaves exactly as it did with PIL's own quantize()."""
+    img = Image.fromarray(idx_array, mode="P")
+    padded = list(palette_rgb) + [(0, 0, 0)] * (256 - len(palette_rgb))
+    img.putpalette([channel for rgb in padded for channel in rgb])
+    return img
 
 
 def _plain_center_crop_box(
@@ -403,21 +535,39 @@ def _enhance(img: Image.Image, color_boost: float, contrast_boost: float) -> Ima
 
 def _quantize(img: Image.Image, palette_rgb: list | None, dither_strength: float) -> Image.Image:
     """RGB -> palette-quantized P-mode image, same size/orientation as
-    `img` (no rotation here). dither_strength blends `img` toward its own
-    flat (undithered) quantization before running Floyd-Steinberg on the
-    blend: at 0 there's zero quantization error left to diffuse (so the
-    result IS the flat quantization, no dithering texture at all); at 1
-    it's `img` unchanged (full-strength dithering, this project's
-    original always-on behavior); values between give a smooth continuum
-    of dithering intensity rather than an on/off toggle."""
-    palette_image = _build_palette_image(palette_rgb or DEFAULT_PALETTE_RGB)
-    if dither_strength >= 1.0:
-        return img.quantize(palette=palette_image, dither=Image.Dither.FLOYDSTEINBERG)
+    `img` (no rotation here). Matches against the palette in OKLab space
+    (perceptual distance, not raw RGB -- see _rgb_to_oklab/
+    _nearest_palette_indices) and, when dithering, jitters that match
+    with a Bayer ordered-dither pattern rather than Floyd-Steinberg error
+    diffusion -- see _ordered_dither_oklab for why (short version: error
+    diffusion is inherently a serial per-pixel loop, and doing that in
+    Python for a full 800x480 panel blew well past this project's
+    render-latency budget). dither_strength blends `img` toward its own
+    flat (undithered) quantization before dithering the blend: at 0 the
+    blend IS the flat quantization (nothing left for the jitter to push
+    across a color boundary, so no dithering texture at all); at 1 it's
+    `img` unchanged (full-strength dithering, this project's original
+    always-on behavior); values between give a smooth continuum of
+    dithering intensity rather than an on/off toggle."""
+    palette_rgb = palette_rgb or DEFAULT_PALETTE_RGB
+    palette_oklab = _rgb_to_oklab(np.asarray(palette_rgb, dtype=np.float32))
+
+    rgb_array = np.asarray(img.convert("RGB"))
+    oklab_pixels = _rgb_to_oklab(rgb_array)
+
     if dither_strength <= 0.0:
-        return img.quantize(palette=palette_image, dither=Image.Dither.NONE)
-    flat = img.quantize(palette=palette_image, dither=Image.Dither.NONE).convert("RGB")
-    blended = Image.blend(flat, img, dither_strength)
-    return blended.quantize(palette=palette_image, dither=Image.Dither.FLOYDSTEINBERG)
+        flat_idx = _nearest_palette_indices(oklab_pixels, palette_oklab)
+        return _index_array_to_p_image(flat_idx.astype(np.uint8), palette_rgb)
+
+    if dither_strength < 1.0:
+        flat_idx = _nearest_palette_indices(oklab_pixels, palette_oklab)
+        palette_arr = np.asarray(palette_rgb, dtype=np.uint8)
+        flat_rgb = Image.fromarray(palette_arr[flat_idx], mode="RGB")
+        blended = Image.blend(flat_rgb, img.convert("RGB"), dither_strength)
+        oklab_pixels = _rgb_to_oklab(np.asarray(blended))
+
+    dithered_idx = _ordered_dither_oklab(oklab_pixels, palette_oklab)
+    return _index_array_to_p_image(dithered_idx, palette_rgb)
 
 
 def _transpose_and_pack(quantized: Image.Image, orientation: str) -> bytes:

server/requirements.txt

@@ -3,6 +3,7 @@ starlette==0.41.3
 uvicorn[standard]==0.34.0
 httpx==0.28.1
 pillow==12.3.0
+numpy==2.5.1
 python-multipart==0.0.20
 jinja2==3.1.5
 sqlalchemy==2.0.51

server/tests/test_widget_border.py

@@ -135,7 +135,7 @@ def test_solid_border_draws_the_configured_palette_color(client, db_session):
     assert resp.status_code == 200, resp.text
 
     img = _preview_pixels(client)
-    assert img.getpixel((0, 0)) == (207, 0, 15)  # DEFAULT_PALETTE_RGB[3], top-left corner of the stroke
+    assert img.getpixel((0, 0)) == (98, 32, 30)  # DEFAULT_PALETTE_RGB[3], top-left corner of the stroke
 
 
 def test_no_border_leaves_the_edge_unmarked(client, db_session):
@@ -146,4 +146,4 @@ def test_no_border_leaves_the_edge_unmarked(client, db_session):
     render path already painting it that color."""
     client.post("/setup", data={"username": "alice", "password": "hunter22"})
     img = _preview_pixels(client)
-    assert img.getpixel((0, 0)) != (207, 0, 15)
+    assert img.getpixel((0, 0)) != (98, 32, 30)