ii-pix/convert.py
kris 322123522c Assign scan lines randomly to palettes and cluster independently. This doesn't give good results either, since
neighbouring lines end up getting similar but not identical colours, which still results in horizontal striping.
2021-11-10 00:34:17 +00:00

170 lines
6.5 KiB
Python

"""Image converter to Apple II Double Hi-Res format."""
import argparse
import array
import os.path
import time
import collections
import random
import colour
from PIL import Image
import numpy as np
from sklearn.cluster import KMeans
import dither as dither_pyx
import dither_pattern
import image as image_py
import palette as palette_py
import screen as screen_py
# TODO:
# - support LR/DLR
# - support HGR
def cluster_palette(image: Image):
shuffle_lines = list(range(200))
random.shuffle(shuffle_lines)
line_to_palette = {}
for idx, line in enumerate(shuffle_lines):
line_to_palette[line] = idx % 16
colours_rgb = np.asarray(image).reshape((-1, 3))
with colour.utilities.suppress_warnings(colour_usage_warnings=True):
colours_cam = colour.convert(colours_rgb, "RGB",
"CAM16UCS").astype(np.float32)
palettes_rgb = {}
palette_colours = collections.defaultdict(list)
for line in range(200):
palette = line_to_palette[line]
palette_colours[palette].extend(
colours_cam[line * 320:(line + 1) * 320])
for palette in range(16):
kmeans = KMeans(n_clusters=16, max_iter=10000)
kmeans.fit_predict(palette_colours[palette])
palette_cam = kmeans.cluster_centers_
with colour.utilities.suppress_warnings(colour_usage_warnings=True):
palette_rgb = colour.convert(palette_cam, "CAM16UCS", "RGB")
# SHR colour palette only uses 4-bit values
palette_rgb = np.round(palette_rgb * 15) / 15
# palette_rgb = palette_rgb.astype(np.float32) / 255
palettes_rgb[palette] = palette_rgb.astype(np.float32)
return palettes_rgb, line_to_palette
def main():
parser = argparse.ArgumentParser()
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.")
parser.add_argument(
"--lookahead", type=int, default=8,
help=("How many pixels to look ahead to compensate for NTSC colour "
"artifacts (default: 8)"))
parser.add_argument(
'--dither', type=str, choices=list(dither_pattern.PATTERNS.keys()),
default=dither_pattern.DEFAULT_PATTERN,
help="Error distribution pattern to apply when dithering (default: "
+ dither_pattern.DEFAULT_PATTERN + ")")
parser.add_argument(
'--show-input', action=argparse.BooleanOptionalAction, default=False,
help="Whether to show the input image before conversion.")
parser.add_argument(
'--show-output', action=argparse.BooleanOptionalAction, default=True,
help="Whether to show the output image after conversion.")
parser.add_argument(
'--palette', type=str, choices=list(set(palette_py.PALETTES.keys())),
default=palette_py.DEFAULT_PALETTE,
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()),
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)'
)
args = parser.parse_args()
if args.lookahead < 1:
parser.error('--lookahead must be at least 1')
# 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")
# Open and resize source image
image = image_py.open(args.input)
if args.show_input:
image_py.resize(image, screen.X_RES, screen.Y_RES,
srgb_output=False).show()
rgb = np.array(
image_py.resize(image, screen.X_RES, screen.Y_RES,
gamma=args.gamma_correct, srgb_output=True)).astype(
np.float32) / 255
palettes_rgb, line_to_palette = cluster_palette(rgb)
# print(palette_rgb)
# screen.set_palette(0, (image_py.linear_to_srgb_array(palette_rgb) *
# 15).astype(np.uint8))
for i, p in palettes_rgb.items():
screen.set_palette(i, (np.round(p * 15)).astype(np.uint8))
output_4bit = dither_pyx.dither_shr(rgb, palettes_rgb, rgb_to_cam16,
line_to_palette)
screen.set_pixels(output_4bit)
output_rgb = np.zeros((200, 320, 3), dtype=np.uint8)
for i in range(200):
screen.line_palette[i] = line_to_palette[i]
output_rgb[i, :, :] = (
palettes_rgb[line_to_palette[i]][
output_4bit[i, :]] * 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=False) # XXX true
if args.show_output:
out_image.show()
# Save Double hi-res image
outfile = os.path.join(os.path.splitext(args.output)[0] + "-preview.png")
out_image.save(outfile, "PNG")
screen.pack()
# with open(args.output, "wb") as f:
# f.write(bytes(screen.aux))
# f.write(bytes(screen.main))
with open(args.output, "wb") as f:
f.write(bytes(screen.memory))
if __name__ == "__main__":
main()