mirror of
https://github.com/KrisKennaway/ii-pix.git
synced 2025-02-20 17:29:03 +00:00
Use .npy format for RGB to CAM16UCS conversion matrix, and get rid of precomputed CIE2000 distances
This commit is contained in:
kris
parent
e979df03bc
commit
feefdb5dc6
26
convert.py
26
convert.py
@ -86,32 +86,22 @@ def main():
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screen = screen_py.DHGR560Screen(palette)
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lookahead = args.lookahead
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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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rgb_to_cam16 = np.load("data/rgb_to_cam16ucs.npy")
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# Open and resize source image
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image = image_py.open(args.input)
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if args.show_input:
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image_py.resize(image, screen.NATIVE_X_RES, screen.NATIVE_Y_RES * 2,
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srgb_output=True).show()
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rgb = np.array(image_py.resize(image, screen.X_RES,
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screen.Y_RES,
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gamma=args.gamma_correct) / 255).astype(
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np.float32)
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rgb = np.array(
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image_py.resize(image, screen.X_RES, screen.Y_RES,
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gamma=args.gamma_correct)).astype(np.float32) / 255
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# bits24 = np.arange(2 ** 24).reshape(-1, 1)
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# all_rgb = (np.concatenate(
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# [bits24 >> 16 & 0xff, bits24 >> 8 & 0xff, bits24 & 0xff],
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# axis=1) / 255).astype(np.float32)
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# all_cam16 = colour.convert(all_rgb, "RGB", "CAM16UCS").astype(np.float32)
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# f = np.memmap("rgb_to_cam16ucs.data", mode="w+", dtype=np.float32,
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# shape=all_cam16.shape)
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# f[:] = all_cam16
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# if True:
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# return
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all_cam16 = np.memmap("rgb_to_cam16ucs.data", mode="r+", dtype=np.float32,
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shape=(2 ** 24, 3))
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dither = dither_pattern.PATTERNS[args.dither]()
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output_nbit, _ = dither_pyx.dither_image(
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screen, rgb, dither, lookahead, args.verbose, all_cam16)
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screen, rgb, dither, lookahead, args.verbose, rgb_to_cam16)
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bitmap = screen.pack(output_nbit)
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# Show output image by rendering in target palette
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173
palette.py
173
palette.py
@ -13,30 +13,19 @@ class Palette:
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XYZ = {}
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DOTS = {}
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DOTS_TO_INDEX = {}
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DISTANCES_PATH = None
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# How many successive screen pixels are used to compute output pixel
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# palette index.
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PALETTE_DEPTH = None
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def __init__(self, load_distances=True):
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# if load_distances:
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# # CIE2000 colour distance matrix from 24-bit RGB tuple to 4-bit
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# # palette colour.
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# self.distances = np.memmap(self.DISTANCES_PATH, mode="r+",
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# dtype=np.uint8, shape=(16777216,
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# len(self.SRGB)))
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def __init__(self):
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self.RGB = {}
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for k, v in self.SRGB.items():
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self.RGB[k] = (np.clip(image.srgb_to_linear_array(v / 255), 0.0,
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1.0) * 255).astype(np.uint8)
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self.CAM16UCS[k] = colour.convert(
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v / 255, "sRGB", "CAM16UCS").astype(np.float32)
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# self.XYZ[k] = colour.convert(v / 255, "sRGB",
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# "CIE XYZ").astype(np.float32)
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# print(self.CAM02UCS)
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with colour.utilities.suppress_warnings(colour_usage_warnings=True):
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self.CAM16UCS[k] = colour.convert(
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v / 255, "sRGB", "CAM16UCS").astype(np.float32)
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# Maps palette values to screen dots. Note that these are the same as
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# the binary index values in reverse order.
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@ -50,86 +39,82 @@ class Palette:
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self.DOTS_TO_INDEX[v] = k
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# class ToHgrPalette(Palette):
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# """4-bit palette used as default by other DHGR image converters."""
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# DISTANCES_PATH = "data/distances_tohgr.data"
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# PALETTE_DEPTH = 4
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#
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# # Default tohgr/bmp2dhr palette
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# SRGB = {
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# 0: np.array((0, 0, 0)), # Black
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# 8: np.array((148, 12, 125)), # Magenta
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# 4: np.array((99, 77, 0)), # Brown
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# 12: np.array((249, 86, 29)), # Orange
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# 2: np.array((51, 111, 0)), # Dark green
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# 10: np.array((126, 126, 126)), # Grey2
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# 6: np.array((67, 200, 0)), # Green
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# 14: np.array((221, 206, 23)), # Yellow
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# 1: np.array((32, 54, 212)), # Dark blue
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# 9: np.array((188, 55, 255)), # Violet
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# 5: np.array((126, 126, 126)), # Grey1
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# 13: np.array((255, 129, 236)), # Pink
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# 3: np.array((7, 168, 225)), # Med blue
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# 11: np.array((158, 172, 255)), # Light blue
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# 7: np.array((93, 248, 133)), # Aqua
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# 15: np.array((255, 255, 255)), # White
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# }
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#
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#
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# class OpenEmulatorPalette(Palette):
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# """4-bit palette chosen to approximately match OpenEmulator output."""
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# DISTANCES_PATH = "data/distances_openemulator.data"
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# PALETTE_DEPTH = 4
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#
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# # OpenEmulator
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# SRGB = {
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# 0: np.array((0, 0, 0)), # Black
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# 8: np.array((203, 0, 121)), # Magenta
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# 4: np.array((99, 103, 0)), # Brown
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# 12: np.array((244, 78, 0)), # Orange
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# 2: np.array((0, 150, 0)), # Dark green
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# 10: np.array((130, 130, 130)), # Grey2
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# 6: np.array((0, 235, 0)), # Green
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# 14: np.array((214, 218, 0)), # Yellow
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# 1: np.array((20, 0, 246)), # Dark blue
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# 9: np.array((230, 0, 244)), # Violet
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# 5: np.array((130, 130, 130)), # Grey1
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# 13: np.array((244, 105, 235)), # Pink
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# 3: np.array((0, 174, 243)), # Med blue
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# 11: np.array((160, 156, 244)), # Light blue
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# 7: np.array((25, 243, 136)), # Aqua
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# 15: np.array((244, 247, 244)), # White
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# }
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#
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#
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# class VirtualIIPalette(Palette):
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# """4-bit palette exactly matching Virtual II emulator output."""
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# DISTANCES_PATH = "data/distances_virtualii.data"
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# PALETTE_DEPTH = 4
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#
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# SRGB = {
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# 0: np.array((0, 0, 0)), # Black
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# 8: np.array((231, 36, 66)), # Magenta
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# 4: np.array((154, 104, 0)), # Brown
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# 12: np.array((255, 124, 0)), # Orange
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# 2: np.array((0, 135, 45)), # Dark green
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# 10: np.array((104, 104, 104)), # Grey2
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# 6: np.array((0, 222, 0)), # Green
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# 14: np.array((255, 252, 0)), # Yellow
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# 1: np.array((1, 30, 169)), # Dark blue
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# 9: np.array((230, 73, 228)), # Violet
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# 5: np.array((185, 185, 185)), # Grey1
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# 13: np.array((255, 171, 153)), # Pink
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# 3: np.array((47, 69, 255)), # Med blue
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# 11: np.array((120, 187, 255)), # Light blue
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# 7: np.array((83, 250, 208)), # Aqua
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# 15: np.array((255, 255, 255)), # White
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# }
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class ToHgrPalette(Palette):
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"""4-bit palette used as default by other DHGR image converters."""
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PALETTE_DEPTH = 4
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# Default tohgr/bmp2dhr palette
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SRGB = {
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0: np.array((0, 0, 0)), # Black
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8: np.array((148, 12, 125)), # Magenta
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4: np.array((99, 77, 0)), # Brown
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12: np.array((249, 86, 29)), # Orange
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2: np.array((51, 111, 0)), # Dark green
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10: np.array((126, 126, 126)), # Grey2
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6: np.array((67, 200, 0)), # Green
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14: np.array((221, 206, 23)), # Yellow
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1: np.array((32, 54, 212)), # Dark blue
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9: np.array((188, 55, 255)), # Violet
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5: np.array((126, 126, 126)), # Grey1
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13: np.array((255, 129, 236)), # Pink
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3: np.array((7, 168, 225)), # Med blue
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11: np.array((158, 172, 255)), # Light blue
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7: np.array((93, 248, 133)), # Aqua
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15: np.array((255, 255, 255)), # White
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}
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class OpenEmulatorPalette(Palette):
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"""4-bit palette chosen to approximately match OpenEmulator output."""
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PALETTE_DEPTH = 4
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# OpenEmulator
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SRGB = {
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0: np.array((0, 0, 0)), # Black
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8: np.array((203, 0, 121)), # Magenta
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4: np.array((99, 103, 0)), # Brown
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12: np.array((244, 78, 0)), # Orange
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2: np.array((0, 150, 0)), # Dark green
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10: np.array((130, 130, 130)), # Grey2
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6: np.array((0, 235, 0)), # Green
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14: np.array((214, 218, 0)), # Yellow
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1: np.array((20, 0, 246)), # Dark blue
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9: np.array((230, 0, 244)), # Violet
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5: np.array((130, 130, 130)), # Grey1
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13: np.array((244, 105, 235)), # Pink
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3: np.array((0, 174, 243)), # Med blue
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11: np.array((160, 156, 244)), # Light blue
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7: np.array((25, 243, 136)), # Aqua
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15: np.array((244, 247, 244)), # White
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}
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class VirtualIIPalette(Palette):
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"""4-bit palette exactly matching Virtual II emulator output."""
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PALETTE_DEPTH = 4
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SRGB = {
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0: np.array((0, 0, 0)), # Black
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8: np.array((231, 36, 66)), # Magenta
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4: np.array((154, 104, 0)), # Brown
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12: np.array((255, 124, 0)), # Orange
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2: np.array((0, 135, 45)), # Dark green
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10: np.array((104, 104, 104)), # Grey2
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6: np.array((0, 222, 0)), # Green
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14: np.array((255, 252, 0)), # Yellow
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1: np.array((1, 30, 169)), # Dark blue
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9: np.array((230, 73, 228)), # Violet
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5: np.array((185, 185, 185)), # Grey1
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13: np.array((255, 171, 153)), # Pink
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3: np.array((47, 69, 255)), # Med blue
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11: np.array((120, 187, 255)), # Light blue
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7: np.array((83, 250, 208)), # Aqua
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15: np.array((255, 255, 255)), # White
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}
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class NTSCPalette(Palette):
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"""8-bit NTSC palette computed by averaging chroma signal over 8 pixels."""
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DISTANCES_PATH = 'data/distances_ntsc.data'
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PALETTE_DEPTH = 8
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# Computed using ntsc_colours.py
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@ -137,9 +122,9 @@ class NTSCPalette(Palette):
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PALETTES = {
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# 'openemulator': OpenEmulatorPalette,
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# 'virtualii': VirtualIIPalette,
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# 'tohgr': ToHgrPalette,
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'openemulator': OpenEmulatorPalette,
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'virtualii': VirtualIIPalette,
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'tohgr': ToHgrPalette,
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'ntsc': NTSCPalette
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}
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31
precompute_conversion.py
Normal file
31
precompute_conversion.py
Normal file
@ -0,0 +1,31 @@
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"""Precompute CIE2000 perceptual colour distance matrices.
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The matrix of delta-E values is computed for all pairs of 24-bit RGB values,
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and Apple II target palette values. This is written out as a file that is
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mmapped at runtime for efficient access. For a 16-colour target palette this
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file is 256MB; for a 256-colour (NTSC) target palette it is 4GB.
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"""
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import colour
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import numpy as np
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def main():
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print("Precomputing conversion matrix from RGB to CAM16UCS colour space")
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# Compute matrix of all 24-bit RGB values, normalized to 0..1 range
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bits24 = np.arange(2 ** 24).reshape(-1, 1)
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all_rgb = (np.concatenate(
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[bits24 >> 16 & 0xff, bits24 >> 8 & 0xff, bits24 & 0xff],
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axis=1) / 255).astype(np.float32)
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with colour.utilities.suppress_warnings(colour_usage_warnings=True):
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# Compute matrix of corresponding CAM16UCS colour values, indexed
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# by 24-bit RGB value
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all_cam16 = colour.convert(all_rgb, "RGB", "CAM16UCS").astype(
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np.float32)
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np.save("data/rgb_to_cam16ucs.npy", all_cam16)
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if __name__ == "__main__":
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main()
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@ -1,88 +0,0 @@
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"""Precompute CIE2000 perceptual colour distance matrices.
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The matrix of delta-E values is computed for all pairs of 24-bit RGB values,
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and Apple II target palette values. This is written out as a file that is
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mmapped at runtime for efficient access. For a 16-colour target palette this
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file is 256MB; for a 256-colour (NTSC) target palette it is 4GB.
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"""
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import argparse
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import os
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import image
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import palette as palette_py
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import colour.difference
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import numpy as np
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RGB_LEVELS = 256
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# Largest possible value of delta_E_CIE2000 between two RGB values
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DELTA_E_MAX = 120 # TODO: fine-tune
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def rgb_to_lab(rgb: np.ndarray):
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srgb = np.clip(
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image.linear_to_srgb_array(rgb.astype(np.float32) / 255), 0.0,
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1.0)
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xyz = colour.sRGB_to_XYZ(srgb)
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return colour.XYZ_to_Lab(xyz)
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def all_lab_colours():
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all_rgb = np.array(tuple(np.ndindex(RGB_LEVELS, RGB_LEVELS, RGB_LEVELS)),
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dtype=np.uint8)
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return rgb_to_lab(all_rgb)
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def nearest_colours(palette, all_lab, diffs):
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palette_size = len(palette.RGB)
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palette_labs = np.empty((palette_size, 3), dtype=np.float32)
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for i, palette_rgb in palette.RGB.items():
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palette_labs[i, :] = rgb_to_lab(palette_rgb)
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print("Computing all 24-bit palette diffs:")
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for i in range(palette_size):
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print(" %d/%d" % (i, palette_size))
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# Compute all palette diffs for a block of 65536 successive RGB
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# source values at once, which bounds the memory use while also writing
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# contiguously to the mmapped array.
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diffs[i * (1 << 16):(i + 1) * (1 << 16), :] = (
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colour.difference.delta_E_CIE2000(
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all_lab[i * (1 << 16):(i + 1) * (
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1 << 16)].reshape((1 << 16, 1, 3)),
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palette_labs.reshape((1, palette_size, 3))) / DELTA_E_MAX *
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255).astype(np.uint8)
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument('--palette', type=str, choices=list(
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palette_py.PALETTES.keys()),
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default=palette_py.DEFAULT_PALETTE,
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help="Palette for which to compute distance matrix.")
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parser.add_argument('--all', action=argparse.BooleanOptionalAction,
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default=False,
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help="Whether to compute distances for all palettes")
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args = parser.parse_args()
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if args.all:
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palette_names = list(palette_py.PALETTES.keys())
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else:
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palette_names = [args.palette]
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print("Precomputing matrix of all 24-bit LAB colours")
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all_lab = all_lab_colours()
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for palette_name in palette_names:
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print("Creating distance file for palette %s" % palette_name)
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palette = palette_py.PALETTES[palette_name](load_distances=False)
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try:
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os.mkdir(os.path.dirname(palette.DISTANCES_PATH))
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except FileExistsError:
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pass
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out = np.memmap(filename=palette.DISTANCES_PATH, mode="w+",
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dtype=np.uint8, shape=(RGB_LEVELS ** 3,
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len(palette.RGB)))
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nearest_colours(palette, all_lab, out)
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if __name__ == "__main__":
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main()
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