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Reorder

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kris 2021-11-23 14:58:46 +00:00
parent 0b985a66b9
commit e488955c23
1 changed files with 30 additions and 30 deletions
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60
convert.py
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@ -72,6 +72,36 @@ class ClusterPalette:
# Delta applied to palette split in previous iteration
self._palette_mutate_delta = (0, 0)
def _image_colours_cam(self, image: Image):
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)
return colours_cam
def _equal_palette_splits(self, palette_height=35):
# The 16 palettes are striped across consecutive (overlapping) line
# ranges. Since nearby lines tend to have similar colours, this has
# the effect of smoothing out the colour transitions across palettes.
# If we want to overlap 16 palettes in 200 lines, where each palette
# has height H and overlaps the previous one by L lines, then the
# boundaries are at lines:
# (0, H), (H-L, 2H-L), (2H-2L, 3H-2L), ..., (15H-15L, 16H - 15L)
# i.e. 16H - 15L = 200, so for a given palette height H we need to
# overlap by:
# L = (16H - 200)/15
palette_overlap = (16 * palette_height - 200) / 15
palette_ranges = []
for palette_idx in range(16):
palette_lower = palette_idx * (palette_height - palette_overlap)
palette_upper = palette_lower + palette_height
palette_ranges.append((int(np.round(palette_lower)),
int(np.round(palette_upper))))
return palette_ranges
def iterate(self, penalty: float, max_iterations: int):
iterations_since_improvement = 0
total_image_error = 1e9
@ -116,36 +146,6 @@ class ClusterPalette:
yield (new_total_image_error, new_output_4bit, new_line_to_palette,
new_palettes_rgb12_iigs, new_palettes_linear_rgb)
def _image_colours_cam(self, image: Image):
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)
return colours_cam
def _equal_palette_splits(self, palette_height=35):
# The 16 palettes are striped across consecutive (overlapping) line
# ranges. Since nearby lines tend to have similar colours, this has
# the effect of smoothing out the colour transitions across palettes.
# If we want to overlap 16 palettes in 200 lines, where each palette
# has height H and overlaps the previous one by L lines, then the
# boundaries are at lines:
# (0, H), (H-L, 2H-L), (2H-2L, 3H-2L), ..., (15H-15L, 16H - 15L)
# i.e. 16H - 15L = 200, so for a given palette height H we need to
# overlap by:
# L = (16H - 200)/15
palette_overlap = (16 * palette_height - 200) / 15
palette_ranges = []
for palette_idx in range(16):
palette_lower = palette_idx * (palette_height - palette_overlap)
palette_upper = palette_lower + palette_height
palette_ranges.append((int(np.round(palette_lower)),
int(np.round(palette_upper))))
return palette_ranges
def _propose_palettes(self) -> Tuple[np.ndarray, np.ndarray, List[float]]:
"""Attempt to find new palettes that locally improve image quality.