ii-pix/convert.py

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Python
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"""Image converter to Apple II Double Hi-Res format."""
import argparse
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import os.path
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import time
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import colour
from PIL import Image
import numpy as np
from sklearn.cluster import KMeans
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import dither as dither_pyx
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import dither_pattern
import image as image_py
import palette as palette_py
import screen as screen_py
# TODO:
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# - support LR/DLR
# - support HGR
def _to_pixel(float_array):
return tuple(np.clip(float_array.astype(np.uint8), 0, 255))
def cluster_palette(image: Image):
# TODO: cluster in CAM16-UCS space
colours = np.asarray(image).reshape((-1, 3))
kmeans = KMeans(n_clusters=16)
kmeans.fit_predict(colours)
palette = kmeans.cluster_centers_
pal_image = Image.new('P', (1, 1), 0)
pal_image.putpalette(palette.reshape(-1).astype(np.uint8))
working_image = np.asarray(image).astype(np.float32)
for y in range(200):
print(y)
for x in range(320):
pixel = working_image[y, x]
best_distance = 1e9
best_colour = None
for colour in palette:
distance = np.sum(np.power(colour - pixel, 2))
if distance < best_distance:
best_distance = distance
best_colour = colour
quant_error = pixel - best_colour
# Floyd-Steinberg dither
# 0 * 7
# 3 5 1
working_image[y, x] = best_colour
if x < 319:
working_image[y, x + 1] = np.clip(
working_image[y, x + 1] + quant_error * (7 / 16), 0, 255)
if y < 199:
working_image[y + 1, x] = np.clip(
working_image[y + 1, x] + quant_error * (5 / 16), 0, 255)
if x < 319:
working_image[y + 1, x + 1] = np.clip(
working_image[y + 1, x + 1] + quant_error * (1 / 16),
0, 255)
if x > 0:
working_image[y + 1, x - 1] = np.clip(
working_image[y + 1, x - 1] + quant_error * (3 / 16), 0,
255)
return working_image
def main():
parser = argparse.ArgumentParser()
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parser.add_argument("input", type=str, help="Input image file to process.")
parser.add_argument("output", type=str, help="Output file for converted "
"Apple II image.")
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parser.add_argument(
"--lookahead", type=int, default=8,
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help=("How many pixels to look ahead to compensate for NTSC colour "
"artifacts (default: 8)"))
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parser.add_argument(
'--dither', type=str, choices=list(dither_pattern.PATTERNS.keys()),
default=dither_pattern.DEFAULT_PATTERN,
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help="Error distribution pattern to apply when dithering (default: "
+ dither_pattern.DEFAULT_PATTERN + ")")
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parser.add_argument(
'--show-input', action=argparse.BooleanOptionalAction, default=False,
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help="Whether to show the input image before conversion.")
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parser.add_argument(
'--show-output', action=argparse.BooleanOptionalAction, default=True,
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help="Whether to show the output image after conversion.")
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parser.add_argument(
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'--palette', type=str, choices=list(set(palette_py.PALETTES.keys())),
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default=palette_py.DEFAULT_PALETTE,
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help='RGB colour palette to dither to. "ntsc" blends colours over 8 '
'pixels and gives better image quality on targets that '
'use/emulate NTSC, but can be substantially slower. Other '
'palettes determine colours based on 4 pixel sequences '
'(default: ' + palette_py.DEFAULT_PALETTE + ")")
parser.add_argument(
'--show-palette', type=str, choices=list(palette_py.PALETTES.keys()),
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help="RGB colour palette to use when --show_output (default: "
"value of --palette)")
parser.add_argument(
'--verbose', action=argparse.BooleanOptionalAction,
default=False, help="Show progress during conversion")
parser.add_argument(
'--gamma_correct', type=float, default=2.4,
help='Gamma-correct image by this value (default: 2.4)'
)
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args = parser.parse_args()
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if args.lookahead < 1:
parser.error('--lookahead must be at least 1')
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# palette = palette_py.PALETTES[args.palette]()
screen = screen_py.SHR320Screen()
# Conversion matrix from RGB to CAM16UCS colour values. Indexed by
# 24-bit RGB value
rgb_to_cam16 = np.load("data/rgb_to_cam16ucs.npy")
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# Open and resize source image
image = image_py.open(args.input)
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if args.show_input:
image_py.resize(image, screen.X_RES, screen.Y_RES,
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srgb_output=True).show()
rgb = np.array(
image_py.resize(image, screen.X_RES, screen.Y_RES,
gamma=args.gamma_correct)).astype(np.float32) / 255
output_rgb = cluster_palette(Image.fromarray((rgb * 255).astype(np.uint8)))
output_srgb = image_py.linear_to_srgb(output_rgb).astype(np.uint8)
# dither = dither_pattern.PATTERNS[args.dither]()
# bitmap = dither_pyx.dither_image(
# screen, rgb, dither, args.lookahead, args.verbose, rgb_to_cam16)
# Show output image by rendering in target palette
# output_palette_name = args.show_palette or args.palette
# output_palette = palette_py.PALETTES[output_palette_name]()
# output_screen = screen_py.DHGRScreen(output_palette)
# if output_palette_name == "ntsc":
# output_srgb = output_screen.bitmap_to_image_ntsc(bitmap)
# else:
# output_srgb = image_py.linear_to_srgb(
# output_screen.bitmap_to_image_rgb(bitmap)).astype(np.uint8)
out_image = image_py.resize(
Image.fromarray(output_srgb), screen.X_RES, screen.Y_RES,
srgb_output=True)
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if args.show_output:
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out_image.show()
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# Save Double hi-res image
# outfile = os.path.join(os.path.splitext(args.output)[0] + "-preview.png")
# out_image.save(outfile, "PNG")
# screen.pack(bitmap)
# with open(args.output, "wb") as f:
# f.write(bytes(screen.aux))
# f.write(bytes(screen.main))
if __name__ == "__main__":
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main()