mirror of
https://github.com/KrisKennaway/ii-pix.git
synced 2024-06-01 06:41:29 +00:00
ad9515dcf2
Use this to precompute a new ntsc palette with 256 entries (though only 84 unique colours) that are available by appropriate pixel sequences. Unfortunately the precomputed distance matrix for this palette is 4GB! Optimize the precomputation to be less memory hungry, while also making efficient use of the mmapped output file. Add support for dithering images using this 8-bit palette depth, i.e. to optimize for NTSC rendering. This often gives better image quality since more colours are available, especially when modulating areas of similar colour. Fix 140 pixel dithering and render the output including NTSC fringing instead of the unrealistic 140px output that doesn't include it. Add support for rendering output image using any target palette, which is useful e.g. for comparing how an 8-pixel NTSC rendered image will be displayed on an emulator using 4-pixel ntsc emulation (there is usually some colour bias, because the 8 pixel chroma blending tends to average away colours). Switch the output binary format to write AUX memory first, which matches the image format of other utilities.
87 lines
3.0 KiB
Python
87 lines
3.0 KiB
Python
"""Precompute CIE2000 perceptual colour distance matrices.
|
|
|
|
The matrix of delta-E values is computed for all pairs of 24-bit RGB values,
|
|
and Apple II target palette values. This is written out as a file that is
|
|
mmapped at runtime for efficient access. For a 16-colour target palette this
|
|
file is 256MB; for a 256-colour (NTSC) target palette it is 4GB.
|
|
"""
|
|
|
|
import argparse
|
|
import os
|
|
|
|
import image
|
|
import palette as palette_py
|
|
import colour.difference
|
|
import numpy as np
|
|
|
|
RGB_LEVELS = 256
|
|
# Largest possible value of delta_E_CIE2000 between two RGB values
|
|
DELTA_E_MAX = 120 # TODO: fine-tune
|
|
|
|
|
|
def rgb_to_lab(rgb: np.ndarray):
|
|
srgb = np.clip(
|
|
image.linear_to_srgb_array(rgb.astype(np.float32) / 255), 0.0,
|
|
1.0)
|
|
xyz = colour.sRGB_to_XYZ(srgb)
|
|
return colour.XYZ_to_Lab(xyz)
|
|
|
|
|
|
def all_lab_colours():
|
|
all_rgb = np.array(tuple(np.ndindex(RGB_LEVELS, RGB_LEVELS, RGB_LEVELS)),
|
|
dtype=np.uint8)
|
|
return rgb_to_lab(all_rgb)
|
|
|
|
|
|
def nearest_colours(palette, all_lab, diffs):
|
|
palette_size = len(palette)
|
|
palette_labs = np.empty((palette_size, 3), dtype=np.float)
|
|
for i, palette_rgb in palette.RGB.items():
|
|
palette_labs[i, :] = rgb_to_lab(palette_rgb)
|
|
|
|
print("Computing all 24-bit palette diffs:")
|
|
for i in range(palette_size):
|
|
print(" %d/%d" % (i, palette_size))
|
|
# Compute all palette diffs for a block of 65536 successive RGB
|
|
# source values at once, which bounds the memory use while also writing
|
|
# contiguously to the mmapped array.
|
|
diffs[i * (1 << 16):(i + 1) * (1 << 16), :] = (
|
|
colour.difference.delta_E_CIE2000(
|
|
all_lab[i * (1 << 16):(i + 1) * (
|
|
1 << 16)].reshape((1 << 16, 1, 3)),
|
|
palette_labs.reshape((1, palette_size, 3))) / DELTA_E_MAX *
|
|
255).astype(np.uint8)
|
|
|
|
|
|
def main():
|
|
parser = argparse.ArgumentParser()
|
|
parser.add_argument('--palette', type=str, choices=list(
|
|
palette_py.PALETTES.keys()),
|
|
default=palette_py.DEFAULT_PALETTE,
|
|
help="Palette for which to compute distance matrix.")
|
|
parser.add_argument('--all', type=bool, default=False,
|
|
help="Whether to compute distances for all palettes")
|
|
args = parser.parse_args()
|
|
|
|
if args.all:
|
|
palette_names = list(palette_py.PALETTES.keys())
|
|
else:
|
|
palette_names = [args.palette]
|
|
|
|
print("Precomputing matrix of all 24-bit LAB colours")
|
|
all_lab = all_lab_colours()
|
|
for palette_name in palette_names:
|
|
print("Creating distance file for palette %s" % palette_name)
|
|
palette = palette_py.PALETTES[palette_name](load_distances=False)
|
|
try:
|
|
os.mkdir(os.path.dirname(palette.DISTANCES_PATH))
|
|
except FileExistsError:
|
|
pass
|
|
out = np.memmap(filename=palette.DISTANCES_PATH, mode="w+",
|
|
dtype=np.uint8, shape=(RGB_LEVELS ** 3, len(palette)))
|
|
nearest_colours(palette, all_lab, out)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|