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