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 """Image transformation functions.""" import numpy as np from PIL import Image def srgb_to_linear_array(a: np.ndarray, gamma=2.4) -> np.ndarray: return np.where(a <= 0.04045, a / 12.92, ((a + 0.055) / 1.055) ** gamma) def linear_to_srgb_array(a: np.ndarray, gamma=2.4) -> np.ndarray: return np.where(a <= 0.0031308, a * 12.92, 1.055 * a ** (1.0 / gamma) - 0.055) def srgb_to_linear(im: np.ndarray, gamma=2.4) -> np.ndarray: rgb_linear = srgb_to_linear_array(im / 255.0, gamma=gamma) return (np.clip(rgb_linear, 0.0, 1.0) * 255).astype(np.float32) def linear_to_srgb(im: np.ndarray, gamma=2.4) -> np.ndarray: srgb = linear_to_srgb_array(im / 255.0, gamma=gamma) return (np.clip(srgb, 0.0, 1.0) * 255).astype(np.float32) def open(filename: str) -> np.ndarray: im = Image.open(filename) # TODO: convert to sRGB colour profile explicitly, in case it has some other # profile already. if im.mode != "RGB": im = im.convert("RGB") return im def resize( image: Image, x_res, y_res, gamma: float = 2.4, srgb_output: bool = False) -> Image: # Convert to linear RGB before rescaling so that colour interpolation is # in linear space linear = srgb_to_linear(np.asarray(image), gamma=gamma).astype(np.uint8) res = Image.fromarray(linear).resize((x_res, y_res), Image.LANCZOS) if srgb_output: return Image.fromarray( linear_to_srgb(np.array(res, dtype=np.float32), gamma=gamma).astype( np.uint8)) else: return res def resize_mono(image: Image, x_res, y_res) -> Image: return image.resize((x_res, y_res), Image.LANCZOS)