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https://github.com/KrisKennaway/ii-pix.git
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3aa29f2d2c
Hi-Res is essentially a more constrained version of Double Hi-Res, in which only about half of the 560 horizontal screen pixels can be independently addressed. In particular an 8 bit byte in screen memory controls 14 or 15 screen pixels. Bits 0-7 are doubled, and bit 8 shifts these 14 dots to the right if enabled. In this case bit 7 of the previous byte is repeated a third time. This means that we have to optimize all 8 bits at once and move forward in increments of 14 screen pixels. There's also a timing difference that results in a phase shift of the NTSC colour signal, which means the mappings from dot patterns to effective colours are rotated. Error diffusion seems to give best results if we only distribute about 2/3 of the quantization error according to the dither pattern.
60 lines
1.9 KiB
Python
60 lines
1.9 KiB
Python
import os.path
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from PIL import Image
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import numpy as np
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import dither_dhr as dither_dhr_pyx
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import dither_pattern
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import palette as palette_py
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import screen as screen_py
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import image as image_py
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def _output(out_image: Image, args):
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if args.show_output:
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out_image.show()
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if args.save_preview:
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# Save Hi-res image
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outfile = os.path.join(
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os.path.splitext(args.output)[0] + "-preview.png")
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out_image.save(outfile, "PNG")
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def _write(screen: screen_py.HGRNTSCScreen, linear_bytemap: np.ndarray, args):
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screen.pack_bytes(linear_bytemap)
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with open(args.output, "wb") as f:
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f.write(bytes(screen.main))
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# TODO: unify with convert_dhr.convert()
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def convert(screen: screen_py.HGRNTSCScreen, image: Image, args):
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rgb = np.array(image).astype(np.float32) / 255
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# Conversion matrix from RGB to CAM16UCS colour values. Indexed by
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# 24-bit RGB value
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base_dir = os.path.dirname(__file__)
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rgb24_to_cam16ucs = np.load(
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os.path.join(base_dir, "data/rgb24_to_cam16ucs.npy"))
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dither = dither_pattern.PATTERNS[args.dither](
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error_fraction = args.error_fraction)
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bitmap, linear_bytemap = dither_dhr_pyx.dither_image(
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screen, rgb, dither, 8, args.verbose, rgb24_to_cam16ucs)
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# Show output image by rendering in target palette
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output_palette_name = args.show_palette or args.palette
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output_palette = palette_py.PALETTES[output_palette_name]()
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output_screen = screen_py.HGRNTSCScreen(output_palette)
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if output_palette_name == "ntsc":
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output_srgb = output_screen.bitmap_to_image_ntsc(bitmap)
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else:
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output_srgb = image_py.linear_to_srgb(
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output_screen.bitmap_to_image_rgb(bitmap)).astype(np.uint8)
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out_image = image_py.resize(
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Image.fromarray(output_srgb), screen.X_RES, screen.Y_RES * 2,
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srgb_output=True)
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_output(out_image, args)
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_write(screen, linear_bytemap, args)
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