"""Read/write SyncLight differential lightmaps. A lightmap is a float32 array of shape (H, W, 4) with channels [activation, L, a, b], all in [-1, 1]: - activation: -1 = turn the light off, 0 = no change, 1 = set the light to (L, a, b) - L: target intensity mapped to [-1, 1] (intensity = (L + 1) / 2) - a, b: target colour as CIELAB a/b divided by 128 The original training code stored them as .npy. The released dataset stores them as 16-bit RGBA PNGs (R=activation, G=L, B=a, A=b) with the mapping v = round(x * 32767) + 32768 x = (v - 32768) / 32767 so -1, 0 and 1 are exact and every other value is within 1.6e-5 of the original. """ import numpy as np SCALE = 32767.0 OFFSET = 32768.0 def encode_lightmap(lightmap): """float32 (H, W, 4) in [-1, 1] -> uint16 (H, W, 4).""" x = np.asarray(lightmap, dtype=np.float32) if x.ndim != 3 or x.shape[-1] != 4: raise ValueError(f"expected (H, W, 4) lightmap, got {x.shape}") if not np.isfinite(x).all() or x.min() < -1.0 or x.max() > 1.0: raise ValueError(f"lightmap values outside [-1, 1]: [{x.min()}, {x.max()}]") return (np.round(x * SCALE) + OFFSET).astype(np.uint16) def decode_lightmap(encoded): """uint16 (H, W, 4) -> float32 (H, W, 4) in [-1, 1].""" return ((np.asarray(encoded, dtype=np.float32) - OFFSET) / SCALE).astype(np.float32) def save_lightmap_png(path, lightmap): import cv2 ok = cv2.imwrite(str(path), encode_lightmap(lightmap)[..., [2, 1, 0, 3]]) # OpenCV expects BGRA if not ok: raise IOError(f"could not write {path}") def encode_lightmap_png_bytes(lightmap, compression=6): import cv2 ok, buf = cv2.imencode(".png", encode_lightmap(lightmap)[..., [2, 1, 0, 3]], [cv2.IMWRITE_PNG_COMPRESSION, compression]) if not ok: raise IOError("PNG encoding failed") return buf.tobytes() def decode_lightmap_png_bytes(data): import cv2 arr = cv2.imdecode(np.frombuffer(data, np.uint8), cv2.IMREAD_UNCHANGED) return _from_bgra(arr) def load_lightmap(path): """Load a lightmap from .png (release format) or .npy (original format).""" path = str(path) if path.endswith(".npy"): return np.load(path).astype(np.float32) import cv2 arr = cv2.imread(path, cv2.IMREAD_UNCHANGED) if arr is None: raise IOError(f"could not read {path}") return _from_bgra(arr) def _from_bgra(arr): if arr.dtype != np.uint16 or arr.ndim != 3 or arr.shape[-1] != 4: raise ValueError(f"expected 16-bit 4-channel PNG, got {arr.dtype} {arr.shape}") return decode_lightmap(arr[..., [2, 1, 0, 3]])