35 lines
1.3 KiB
Python
35 lines
1.3 KiB
Python
"""C16 TED monochrome: 320x200, restricted to the TED's neutral grey ramp (8
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luminance levels of hue 1, plus black) for smooth greyscale. ``--mono-base``
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tints it toward one hue (black -> hue -> white). Two greys per 8x8 cell, packed
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into the same TED hires layout as the colour mode."""
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from __future__ import annotations
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import numpy as np
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from ...convert import base
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from .. import palette as tedpal
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from . import hires
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WIDTH, HEIGHT = hires.WIDTH, hires.HEIGHT
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CELL_W, CELL_H = hires.CELL_W, hires.CELL_H
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PIXEL_ASPECT = hires.PIXEL_ASPECT
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def convert(img_rgb, palette_name="ted", dither_mode="floyd",
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intensive=False, base_color=None):
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plab = tedpal.palette_lab()
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prgb = tedpal.get_palette().astype(np.uint8)
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ramp = base.luminance_ramp(plab, tedpal.GREYS, base_color)
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idx, sets, rows, cols, err = base.mono_render(
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img_rgb, plab, ramp, WIDTH, HEIGHT, CELL_W, CELL_H, dither_mode, n_free=2)
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bitmap, attr, ch = hires._encode(idx, sets, rows, cols)
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payload = bytes(bitmap) + bytes(attr) + bytes(ch)
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return base.Conversion(
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mode="mono", width=WIDTH, height=HEIGHT, pixel_aspect=PIXEL_ASPECT,
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index_image=idx.astype(np.uint16), data=payload, viewer="c16",
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preview_rgb=prgb[idx], error=err,
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meta={"palette": "ted", "dither": dither_mode, "border": 0},
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)
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