9e8c8f6b8d
REC-117: both functions had definitions but no imports, calls, tests, or doc references anywhere in the repo. Kill attempts that failed: none. - `rg -n -w 'bilinear_resize|lattice_source_rgba' src tests tools scripts README.md docs` -> only the two now-removed definitions (repeated the census command against current HEAD). - Cross-repo `rg -n -w 'bilinear_resize|lattice_source_rgba'` over all of F:/Projects -> only this repo's own source and the census docs. - Confirmed `build_source_lattice_reference`, which `lattice_source_rgba` called, is still used by two other live callers in metrics.py (lines 280, 311) and was left untouched. Checks run: `python -m py_compile src/repixelizer/io.py src/repixelizer/metrics.py` -> compiles cleanly. Did not run the pytest suite: this repo's runtime dependencies include torch>=2.6.0, which is not installed in this worktree and installing it would be a multi-GB download outside this pass's focused-check budget; no test file references either function by name (`rg -n -w 'bilinear_resize|lattice_source_rgba' tests` -> no matches), so this is a compile-level check only, stated plainly rather than reported as a full green test run. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
47 lines
1.7 KiB
Python
47 lines
1.7 KiB
Python
from __future__ import annotations
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from pathlib import Path
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import numpy as np
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from PIL import Image
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def load_rgba(path: str | Path) -> np.ndarray:
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image = Image.open(path).convert("RGBA")
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return np.asarray(image, dtype=np.float32) / 255.0
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def save_rgba(path: str | Path, rgba: np.ndarray) -> None:
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clipped = np.clip(np.rint(rgba * 255.0), 0, 255).astype(np.uint8)
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Image.fromarray(clipped, mode="RGBA").save(path)
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def premultiply(rgba: np.ndarray) -> np.ndarray:
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premult = rgba.copy()
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premult[..., :3] *= premult[..., 3:4]
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return premult
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def unpremultiply(rgba: np.ndarray, eps: float = 1e-6) -> np.ndarray:
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out = rgba.copy()
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alpha = np.maximum(out[..., 3:4], eps)
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out[..., :3] = np.where(out[..., 3:4] > eps, out[..., :3] / alpha, 0.0)
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return np.clip(out, 0.0, 1.0)
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def nearest_resize(rgba: np.ndarray, width: int, height: int) -> np.ndarray:
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image = Image.fromarray(np.clip(np.rint(rgba * 255.0), 0, 255).astype(np.uint8), mode="RGBA")
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resized = image.resize((width, height), resample=Image.Resampling.NEAREST)
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return np.asarray(resized, dtype=np.float32) / 255.0
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def box_resize(rgba: np.ndarray, width: int, height: int) -> np.ndarray:
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image = Image.fromarray(np.clip(np.rint(rgba * 255.0), 0, 255).astype(np.uint8), mode="RGBA")
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resized = image.resize((width, height), resample=Image.Resampling.BOX)
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return np.asarray(resized, dtype=np.float32) / 255.0
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def lanczos_resize(rgba: np.ndarray, width: int, height: int) -> np.ndarray:
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image = Image.fromarray(np.clip(np.rint(rgba * 255.0), 0, 255).astype(np.uint8), mode="RGBA")
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resized = image.resize((width, height), resample=Image.Resampling.LANCZOS)
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return np.asarray(resized, dtype=np.float32) / 255.0
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