First public commit.

lenser/intv/convert/mono.py

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+"""Mattel Intellivision monochrome / tinted-mono mode.
+
+160x96 matched by luminance to two greys (black + white, or black + a tinted base
+colour).  With the colours fixed, the whole image budget goes into the 64-tile
+GRAM shapes, which are optimised by the same vector-quantisation reshape/reassign
+used by the colour encoder -- a clean two-tone Intellivision picture.
+"""
+
+from __future__ import annotations
+
+import numpy as np
+
+from ... import dither, palette as c64pal
+from ...convert import base
+from .. import palette as ipal
+from . import stic
+
+BLACK = 0
+WHITE = 7                  # white is a foreground-legal colour (0-7)
+
+
+def convert(img_rgb, palette_name="stic", dither_mode="none",
+            intensive=False, base_color=None):
+    # mono is carried entirely by dithering, so it needs error diffusion -- the
+    # colour mode's "none" default would give a stark, high-contrast result.
+    if dither_mode not in base.DIFFUSION_DITHERS:
+        dither_mode = "floyd"
+    plab = ipal.palette_lab()
+    prgb = ipal.get_palette().astype(np.uint8)
+    fg = base_color if base_color in range(1, 8) else WHITE
+    bg = BLACK
+
+    # luminance image + luminance-only palette
+    L = c64pal.srgb_to_lab(img_rgb)[..., 0]
+    img_mono = np.zeros((stic.HEIGHT, stic.WIDTH, 3))
+    img_mono[..., 0] = L
+    plab_mono = np.zeros_like(plab)
+    plab_mono[:, 0] = plab[:, 0]
+
+    cells, rows, cols = base.cells_lab(img_mono, stic.CELL_W, stic.CELL_H)
+
+    sets = np.tile(np.array([bg, fg], np.int64), (stic.N_ROWS * stic.N_COLS, 1))
+    allowed = base.per_pixel_allowed(sets, rows, cols, stic.CELL_W, stic.CELL_H,
+                                     stic.HEIGHT, stic.WIDTH)
+    idx = dither.quantize(img_mono, allowed, plab_mono, dither_mode).astype(np.uint8)
+
+    bitmaps = np.zeros((stic.N_ROWS * stic.N_COLS, 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)
+
+    tiles, labels = base.mono_codebook(bitmaps, stic.N_TILES)
+
+    prev_idx = np.empty((stic.HEIGHT, stic.WIDTH), np.uint8)
+    cards = np.zeros(stic.N_ROWS * stic.N_COLS, np.uint16)
+    for ci in range(stic.N_ROWS * stic.N_COLS):
+        cr, cc = divmod(ci, cols)
+        tile = tiles[labels[ci]].reshape(8, 8)
+        prev_idx[cr * 8:cr * 8 + 8, cc * 8:cc * 8 + 8] = np.where(tile == 1, fg, bg)
+        cards[ci] = (fg & 0x07) | stic.GRAM_BIT | ((labels[ci] & 0x3F) << 3) \
+            | stic._bg_bits(bg)
+
+    gram = np.zeros(stic.N_TILES * 8, np.uint16)
+    for t in range(stic.N_TILES):
+        rb = tiles[t].reshape(8, 8)
+        for r in range(8):
+            byte = 0
+            for x in range(8):
+                byte = (byte << 1) | int(rb[r, x])
+            gram[t * 8 + r] = byte
+
+    data = {"gram": gram, "cards": cards}
+    preview = prgb[prev_idx]
+    disp_w = int(round(stic.WIDTH * stic.PIXEL_ASPECT))
+    xs = (np.arange(disp_w) * stic.WIDTH) // disp_w
+    preview = preview[:, xs]
+
+    return base.Conversion(
+        mode="mono", width=stic.WIDTH, height=stic.HEIGHT,
+        pixel_aspect=stic.PIXEL_ASPECT, index_image=prev_idx.astype(np.uint16),
+        data=data, data_addr=0, viewer="stic", preview_rgb=preview,
+        error=base.perceptual_error(prev_idx, img_mono, plab_mono),
+        meta={"palette": "stic", "dither": dither_mode, "base_color": base_color,
+              "mode": "fgbg"},
+    )