First public commit.

2026-07-03 19:35:35 -07:00 · 2026-07-03 19:35:35 -07:00 · 4bac9d83ed
commit 4bac9d83ed
parent 2a48f52979
288 changed files with 18417 additions and 1076 deletions
--- a/lenser/vic20/convert/mono.py
+++ b/lenser/vic20/convert/mono.py
@ -0,0 +1,83 @@
+"""Commodore VIC-20 monochrome / tinted-mono mode.
+
+176x184 hi-res matched by luminance: a single global background (black) and one
+foreground colour (white, or a tinted base) used by every cell, so the picture is
+carried entirely by the custom character shapes + dithering -- a clean two-tone
+image with no per-cell colour budget to spend.  Reuses the hires char clustering,
+data layout and viewer.
+"""
+
+from __future__ import annotations
+
+import numpy as np
+
+from ... import palette as c64pal
+from ...convert import base
+from .. import palette as vpal
+from . import hires
+
+WIDTH, HEIGHT, PIXEL_ASPECT = hires.WIDTH, hires.HEIGHT, hires.PIXEL_ASPECT
+
+
+def convert(img_rgb, palette_name="vic", dither_mode="floyd",
+            intensive=False, base_color=None):
+    plab = vpal.palette_lab()
+    prgb = vpal.get_palette().astype(np.uint8)
+
+    bg = 0                                      # black background
+    fg = base_color if base_color in range(1, 8) else 1    # white (or tinted)
+    ramp = sorted([bg, fg], key=lambda i: plab[i, 0])
+
+    idx, sets, rows, cols, err = base.mono_render(
+        img_rgb, plab, ramp, hires.WIDTH, hires.HEIGHT,
+        hires.CELL_W, hires.CELL_H, dither_mode, n_free=2)
+
+    # cell bitmaps (1 = foreground) reduced to the 256-char dictionary by a
+    # frequency codebook -- keeps the dithered detail (k-means centroids would
+    # invent near-solid 'average' chars -> block artefacts).
+    bitmaps = np.zeros((hires.N_CELLS, 64), np.uint8)
+    for cr in range(rows):
+        for cc in range(cols):
+            ci = cr * cols + cc
+            block = idx[cr * 8:cr * 8 + 8, cc * 8:cc * 8 + 8]
+            bitmaps[ci] = (block == fg).astype(np.uint8).reshape(-1)
+    chars, labels = base.mono_codebook(bitmaps, hires.N_CHARS)
+
+    img_mono = np.zeros((hires.HEIGHT, hires.WIDTH, 3))
+    img_mono[..., 0] = c64pal.srgb_to_lab(img_rgb)[..., 0]
+    plab_mono = np.zeros_like(plab)
+    plab_mono[:, 0] = plab[:, 0]
+
+    prev_idx = np.empty((hires.HEIGHT, hires.WIDTH), np.uint8)
+    screen = np.zeros(hires.N_CELLS, np.uint8)
+    color = np.zeros(hires.N_CELLS, np.uint8)
+    for ci in range(hires.N_CELLS):
+        cr, cc = divmod(ci, cols)
+        ch = chars[labels[ci]].reshape(8, 8)
+        prev_idx[cr * 8:cr * 8 + 8, cc * 8:cc * 8 + 8] = np.where(ch == 1, fg, bg)
+        screen[ci] = labels[ci] & 0xFF
+        color[ci] = fg & 0x07
+    chardata = np.zeros(hires.N_CHARS * 8, np.uint8)
+    for t in range(hires.N_CHARS):
+        rb = chars[t].reshape(8, 8)
+        for r in range(8):
+            byte = 0
+            for x in range(8):
+                byte = (byte << 1) | int(rb[r, x])
+            chardata[t * 8 + r] = byte
+
+    data = {"chardata": chardata, "screen": screen, "color": color,
+            "bg": int(bg), "border": 0, "aux": 0}
+
+    preview = prgb[prev_idx]
+    disp_w = int(round(hires.WIDTH * hires.PIXEL_ASPECT))
+    xs = (np.arange(disp_w) * hires.WIDTH) // disp_w
+    preview = preview[:, xs]
+
+    return base.Conversion(
+        mode="mono", width=hires.WIDTH, height=hires.HEIGHT,
+        pixel_aspect=hires.PIXEL_ASPECT, index_image=prev_idx.astype(np.uint16),
+        data=data, data_addr=0, viewer="hires", preview_rgb=preview,
+        error=base.perceptual_error(prev_idx, img_mono, plab_mono),
+        meta={"palette": "vic", "dither": dither_mode, "base_color": base_color},
+    )