Each run seems to converge fairly quickly but there is a lot of variation across runs. Run in a loop and keep the running best.
This commit is contained in:
kris
parent
de8a303de2
commit
3b8767782b
184
convert.py
184
convert.py
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@ -61,9 +61,12 @@ class ClusterPalette:
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self._rgb24_to_cam16ucs = rgb24_to_cam16ucs
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self._palette_lines = defaultdict(list)
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# List of line ranges used to train the 16 SHR palettes
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# [(lower_0, upper_0), ...]
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self._palette_splits = self._equal_palette_splits()
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self._init_palette_lines()
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# Whether the previous iteration of proposed palettes was accepted
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self._palettes_accepted = False
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@ -74,7 +77,7 @@ class ClusterPalette:
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# Delta applied to palette split in previous iteration
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self._palette_mutate_delta = (0, 0)
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self._palette_lines = defaultdict(list)
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def _init_palette_lines(self):
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for i, lh in enumerate(self._palette_splits):
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l, h = lh
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self._palette_lines[i].extend(list(range(l, h)))
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@ -132,41 +135,46 @@ class ClusterPalette:
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total_image_error)
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def iterate(self, penalty: float, max_iterations: int):
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iterations_since_improvement = 0
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total_image_error = 1e9
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last_good_splits = self._palette_splits
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self._fit_global_palette()
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while iterations_since_improvement < max_iterations:
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# print("Iterations %d" % iterations_since_improvement)
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new_palettes_cam, new_palettes_rgb12_iigs, new_palette_errors = (
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self._propose_palettes())
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# Recompute image with proposed palettes and check whether it has
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# lower total image error than our previous best.
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(output_4bit, line_to_palette, palettes_linear_rgb,
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new_total_image_error) = self._dither_image(
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new_palettes_cam, penalty)
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self._reassign_unused_palettes(line_to_palette,
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last_good_splits)
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print(total_image_error, new_total_image_error)
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if new_total_image_error >= total_image_error:
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iterations_since_improvement += 1
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continue
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# We found a globally better set of palettes
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while True:
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print("New iteration")
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iterations_since_improvement = 0
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last_good_splits = self._palette_splits
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total_image_error = new_total_image_error
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self._palette_splits = self._equal_palette_splits()
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self._init_palette_lines()
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self._palettes_cam = new_palettes_cam
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self._palettes_rgb = new_palettes_rgb12_iigs
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self._errors = new_palette_errors
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self._palettes_accepted = True
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self._fit_global_palette()
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while iterations_since_improvement < max_iterations:
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# print("Iterations %d" % iterations_since_improvement)
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new_palettes_cam, new_palettes_rgb12_iigs, new_palette_errors = (
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self._propose_palettes())
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yield (new_total_image_error, output_4bit, line_to_palette,
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new_palettes_rgb12_iigs, palettes_linear_rgb)
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# Recompute image with proposed palettes and check whether it has
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# lower total image error than our previous best.
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(output_4bit, line_to_palette, palettes_linear_rgb,
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new_total_image_error) = self._dither_image(
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new_palettes_cam, penalty)
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self._reassign_unused_palettes(line_to_palette,
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last_good_splits)
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# print(total_image_error, new_total_image_error)
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if new_total_image_error >= total_image_error:
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iterations_since_improvement += 1
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continue
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# We found a globally better set of palettes
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iterations_since_improvement = 0
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last_good_splits = self._palette_splits
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total_image_error = new_total_image_error
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self._palettes_cam = new_palettes_cam
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self._palettes_rgb = new_palettes_rgb12_iigs
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self._errors = new_palette_errors
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self._palettes_accepted = True
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yield (new_total_image_error, output_4bit, line_to_palette,
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new_palettes_rgb12_iigs, palettes_linear_rgb)
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def _propose_palettes(self) -> Tuple[np.ndarray, np.ndarray, List[float]]:
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"""Attempt to find new palettes that locally improve image quality.
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@ -192,7 +200,7 @@ class ClusterPalette:
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# Compute a new 16-colour global palette for the entire image,
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# used as the starting center positions for k-means clustering of the
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# individual palettes
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# self._fit_global_palette()
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self._fit_global_palette()
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self._mutate_palette_splits()
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for palette_idx in range(16):
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@ -211,13 +219,13 @@ class ClusterPalette:
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rgb12_iigs_to_cam16ucs=self._rgb12_iigs_to_cam16ucs
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)
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if (palette_error >= self._errors[palette_idx] and not
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self._reserved_colours):
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# Not a local improvement to the existing palette, so ignore it.
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# We can't take this shortcut when we're reserving colours
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# because it would break the invariant that all palettes must
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# share colours.
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continue
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# if (palette_error >= self._errors[palette_idx] and not
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# self._reserved_colours):
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# # Not a local improvement to the existing palette, so ignore it.
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# # We can't take this shortcut when we're reserving colours
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# # because it would break the invariant that all palettes must
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# # share colours.
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# continue
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for i in range(16):
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new_palettes_cam[palette_idx, i, :] = (
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np.array(dither_pyx.convert_rgb12_iigs_to_cam(
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@ -299,43 +307,56 @@ class ClusterPalette:
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palettes_used = [False] * 16
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for palette in new_line_to_palette:
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palettes_used[palette] = True
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best_palette_lines = [v for k, v in sorted(list(zip(
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self._palette_line_errors, range(200))))]
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# print(self._palette_lines)
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for palette_idx, palette_used in enumerate(palettes_used):
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if palette_used:
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continue
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print("Reassigning palette %d" % palette_idx)
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# print("Reassigning palette %d" % palette_idx)
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worst_average_palette_error = 0
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split_palette_idx = -1
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idx = 0
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for idx, lines in self._palette_lines.items():
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if len(lines) < 10:
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continue
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average_palette_error = np.sum(self._palette_line_errors[
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lines]) / len(lines)
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print(idx, average_palette_error)
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if average_palette_error > worst_average_palette_error:
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worst_average_palette_error = average_palette_error
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split_palette_idx = idx
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# TODO: also remove from old entry
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worst_line = best_palette_lines.pop()
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self._palette_lines[palette_idx] = [worst_line]
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print("Picked %d with avg error %f" % (split_palette_idx, worst_average_palette_error))
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# TODO: split off lines with largest error
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# print("Picked line %d with error %f" % (worst_line,
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# self._palette_line_errors[worst_line]))
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palette_line_errors = self._palette_line_errors[
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self._palette_lines[split_palette_idx]]
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print(sorted(
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list(zip(palette_line_errors, self._palette_lines[
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split_palette_idx])), reverse=True))
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best_palette_lines = [v for k, v in sorted(
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list(zip(palette_line_errors, self._palette_lines[
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split_palette_idx])))]
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num_max_lines = len(self._palette_lines[split_palette_idx])
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self._palette_lines[split_palette_idx] = best_palette_lines[
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:num_max_lines // 2]
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# Move worst half to new palette
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self._palette_lines[palette_idx] = best_palette_lines[
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num_max_lines // 2:]
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#
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# worst_average_palette_error = 0
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# split_palette_idx = -1
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# idx = 0
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# for idx, lines in self._palette_lines.items():
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# if len(lines) < 10:
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# continue
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# average_palette_error = np.sum(self._palette_line_errors[
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# lines]) / len(lines)
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# print(idx, average_palette_error)
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# if average_palette_error > worst_average_palette_error:
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# worst_average_palette_error = average_palette_error
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# split_palette_idx = idx
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#
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# print("Picked %d with avg error %f" % (split_palette_idx, worst_average_palette_error))
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# # TODO: split off lines with largest error
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#
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# palette_line_errors = self._palette_line_errors[
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# self._palette_lines[split_palette_idx]]
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#
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# print(sorted(
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# list(zip(palette_line_errors, self._palette_lines[
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# split_palette_idx])), reverse=True))
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# best_palette_lines = [v for k, v in sorted(
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# list(zip(palette_line_errors, self._palette_lines[
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# split_palette_idx])))]
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# num_max_lines = len(self._palette_lines[split_palette_idx])
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#
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# self._palette_lines[split_palette_idx] = best_palette_lines[
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# :num_max_lines // 2]
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# # Move worst half to new palette
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# self._palette_lines[palette_idx] = best_palette_lines[
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# num_max_lines // 2:]
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def main():
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@ -400,7 +421,7 @@ def main():
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# TODO: flags
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penalty = 1 # 1e18 # TODO: is this needed any more?
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iterations = 200
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iterations = 10 # 20
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pygame.init()
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# TODO: for some reason I need to execute this twice - the first time
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@ -417,6 +438,7 @@ def main():
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rgb12_iigs_to_cam16ucs=rgb12_iigs_to_cam16ucs,
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rgb24_to_cam16ucs=rgb24_to_cam16ucs)
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seq = 0
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for (new_total_image_error, output_4bit, line_to_palette,
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palettes_rgb12_iigs, palettes_linear_rgb) in cluster_palette.iterate(
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penalty, iterations):
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@ -463,20 +485,24 @@ def main():
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np.asarray(out_image).transpose((1, 0, 2))) # flip y/x axes
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canvas.blit(surface, (0, 0))
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pygame.display.flip()
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seq += 1
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# Save Double hi-res image
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outfile = os.path.join(
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os.path.splitext(args.output)[0] + "-%d-preview.png" % seq)
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out_image.save(outfile, "PNG")
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screen.pack()
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# with open(args.output, "wb") as f:
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# f.write(bytes(screen.aux))
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# f.write(bytes(screen.main))
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with open(args.output, "wb") as f:
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f.write(bytes(screen.memory))
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# print((palettes_rgb * 255).astype(np.uint8))
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unique_colours = np.unique(
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palettes_rgb12_iigs.reshape(-1, 3), axis=0).shape[0]
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print("%d unique colours" % unique_colours)
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# Save Double hi-res image
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outfile = os.path.join(os.path.splitext(args.output)[0] + "-preview.png")
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out_image.save(outfile, "PNG")
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screen.pack()
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# with open(args.output, "wb") as f:
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# f.write(bytes(screen.aux))
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# f.write(bytes(screen.main))
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with open(args.output, "wb") as f:
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f.write(bytes(screen.memory))
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if __name__ == "__main__":
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