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