2023-12-21 14:13:31 +03:00
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from __future__ import annotations
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2024-01-20 14:23:03 +03:00
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2018-04-12 11:54:54 +03:00
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from array import array
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2024-02-12 13:06:17 +03:00
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from types import ModuleType
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2018-04-12 11:54:54 +03:00
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2020-02-22 16:06:21 +03:00
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import pytest
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2020-08-07 13:28:33 +03:00
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2018-03-29 16:37:35 +03:00
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from PIL import Image, ImageFilter
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2019-07-06 23:40:53 +03:00
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2020-02-23 00:03:01 +03:00
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from .helper import assert_image_equal
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2018-03-26 19:30:00 +03:00
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2024-02-12 13:06:17 +03:00
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numpy: ModuleType | None
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2018-04-14 19:17:15 +03:00
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try:
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import numpy
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except ImportError:
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numpy = None
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2018-03-26 19:30:00 +03:00
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2020-02-23 00:03:01 +03:00
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class TestColorLut3DCoreAPI:
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2024-02-07 11:16:28 +03:00
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def generate_identity_table(
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self, channels: int, size: int | tuple[int, int, int]
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) -> tuple[int, int, int, int, list[float]]:
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2018-03-26 19:30:00 +03:00
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if isinstance(size, tuple):
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2022-04-10 21:23:31 +03:00
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size_1d, size_2d, size_3d = size
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2018-03-26 19:30:00 +03:00
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else:
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2022-04-10 21:23:31 +03:00
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size_1d, size_2d, size_3d = (size, size, size)
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2018-03-26 19:30:00 +03:00
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table = [
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[
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2022-04-10 21:23:31 +03:00
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r / (size_1d - 1) if size_1d != 1 else 0,
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g / (size_2d - 1) if size_2d != 1 else 0,
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b / (size_3d - 1) if size_3d != 1 else 0,
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r / (size_1d - 1) if size_1d != 1 else 0,
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g / (size_2d - 1) if size_2d != 1 else 0,
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2018-03-26 19:30:00 +03:00
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][:channels]
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2022-04-10 21:23:31 +03:00
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for b in range(size_3d)
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for g in range(size_2d)
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for r in range(size_1d)
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2018-03-26 19:30:00 +03:00
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]
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return (
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2019-06-13 18:53:42 +03:00
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channels,
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2022-04-10 21:23:31 +03:00
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size_1d,
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size_2d,
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size_3d,
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2019-06-13 18:53:42 +03:00
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[item for sublist in table for item in sublist],
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)
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2018-03-26 19:30:00 +03:00
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2024-01-31 12:12:58 +03:00
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def test_wrong_args(self) -> None:
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2019-06-13 18:53:42 +03:00
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im = Image.new("RGB", (10, 10), 0)
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2018-03-26 19:30:00 +03:00
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2020-02-22 19:07:04 +03:00
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with pytest.raises(ValueError, match="filter"):
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2022-01-15 01:02:31 +03:00
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im.im.color_lut_3d(
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"RGB", Image.Resampling.BICUBIC, *self.generate_identity_table(3, 3)
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)
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2018-03-26 19:30:00 +03:00
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2020-02-22 19:07:04 +03:00
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with pytest.raises(ValueError, match="image mode"):
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2019-06-13 18:53:42 +03:00
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im.im.color_lut_3d(
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2022-01-15 01:02:31 +03:00
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"wrong", Image.Resampling.BILINEAR, *self.generate_identity_table(3, 3)
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2019-06-13 18:53:42 +03:00
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)
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2018-03-26 19:30:00 +03:00
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2020-02-22 19:07:04 +03:00
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with pytest.raises(ValueError, match="table_channels"):
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2022-01-15 01:02:31 +03:00
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im.im.color_lut_3d(
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"RGB", Image.Resampling.BILINEAR, *self.generate_identity_table(5, 3)
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)
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2018-03-26 19:30:00 +03:00
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2020-02-22 19:07:04 +03:00
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with pytest.raises(ValueError, match="table_channels"):
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2022-01-15 01:02:31 +03:00
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im.im.color_lut_3d(
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"RGB", Image.Resampling.BILINEAR, *self.generate_identity_table(1, 3)
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)
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2018-03-26 19:30:00 +03:00
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2020-02-22 19:07:04 +03:00
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with pytest.raises(ValueError, match="table_channels"):
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2022-01-15 01:02:31 +03:00
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im.im.color_lut_3d(
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"RGB", Image.Resampling.BILINEAR, *self.generate_identity_table(2, 3)
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)
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2018-03-26 19:30:00 +03:00
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2020-02-22 19:07:04 +03:00
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with pytest.raises(ValueError, match="Table size"):
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2019-06-13 18:53:42 +03:00
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im.im.color_lut_3d(
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2022-01-15 01:02:31 +03:00
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"RGB",
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Image.Resampling.BILINEAR,
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*self.generate_identity_table(3, (1, 3, 3)),
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2019-06-13 18:53:42 +03:00
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)
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2018-03-26 19:30:00 +03:00
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2020-02-22 19:07:04 +03:00
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with pytest.raises(ValueError, match="Table size"):
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2019-06-13 18:53:42 +03:00
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im.im.color_lut_3d(
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"RGB",
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Image.Resampling.BILINEAR,
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*self.generate_identity_table(3, (66, 3, 3)),
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2019-06-13 18:53:42 +03:00
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)
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2018-03-26 19:30:00 +03:00
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2020-02-22 19:07:04 +03:00
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with pytest.raises(ValueError, match=r"size1D \* size2D \* size3D"):
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2022-01-15 01:02:31 +03:00
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im.im.color_lut_3d(
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"RGB", Image.Resampling.BILINEAR, 3, 2, 2, 2, [0, 0, 0] * 7
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)
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2018-03-26 22:29:50 +03:00
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2020-02-22 19:07:04 +03:00
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with pytest.raises(ValueError, match=r"size1D \* size2D \* size3D"):
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2022-01-15 01:02:31 +03:00
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im.im.color_lut_3d(
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"RGB", Image.Resampling.BILINEAR, 3, 2, 2, 2, [0, 0, 0] * 9
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)
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2018-03-26 22:29:50 +03:00
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2020-02-22 16:06:21 +03:00
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with pytest.raises(TypeError):
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2022-01-15 01:02:31 +03:00
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im.im.color_lut_3d(
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"RGB", Image.Resampling.BILINEAR, 3, 2, 2, 2, [0, 0, "0"] * 8
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)
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2018-04-14 17:06:54 +03:00
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2020-02-22 16:06:21 +03:00
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with pytest.raises(TypeError):
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2022-01-15 01:02:31 +03:00
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im.im.color_lut_3d("RGB", Image.Resampling.BILINEAR, 3, 2, 2, 2, 16)
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2018-04-14 17:47:53 +03:00
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2024-01-31 12:12:58 +03:00
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def test_correct_args(self) -> None:
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2019-06-13 18:53:42 +03:00
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im = Image.new("RGB", (10, 10), 0)
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2018-03-26 19:30:00 +03:00
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2022-01-15 01:02:31 +03:00
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im.im.color_lut_3d(
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"RGB", Image.Resampling.BILINEAR, *self.generate_identity_table(3, 3)
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)
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2018-03-26 19:30:00 +03:00
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2022-01-15 01:02:31 +03:00
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im.im.color_lut_3d(
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"CMYK", Image.Resampling.BILINEAR, *self.generate_identity_table(4, 3)
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)
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2018-03-26 19:30:00 +03:00
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2019-06-13 18:53:42 +03:00
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im.im.color_lut_3d(
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2022-01-15 01:02:31 +03:00
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"RGB",
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Image.Resampling.BILINEAR,
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*self.generate_identity_table(3, (2, 3, 3)),
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2019-06-13 18:53:42 +03:00
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)
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2018-03-26 19:30:00 +03:00
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2019-06-13 18:53:42 +03:00
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im.im.color_lut_3d(
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2022-01-15 01:02:31 +03:00
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"RGB",
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Image.Resampling.BILINEAR,
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*self.generate_identity_table(3, (65, 3, 3)),
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2019-06-13 18:53:42 +03:00
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)
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2018-03-26 19:30:00 +03:00
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2019-06-13 18:53:42 +03:00
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im.im.color_lut_3d(
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2022-01-15 01:02:31 +03:00
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"RGB",
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Image.Resampling.BILINEAR,
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*self.generate_identity_table(3, (3, 65, 3)),
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2019-06-13 18:53:42 +03:00
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)
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2018-03-26 19:30:00 +03:00
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2019-06-13 18:53:42 +03:00
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im.im.color_lut_3d(
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2022-01-15 01:02:31 +03:00
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"RGB",
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Image.Resampling.BILINEAR,
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*self.generate_identity_table(3, (3, 3, 65)),
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2019-06-13 18:53:42 +03:00
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)
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2018-03-26 19:30:00 +03:00
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2024-01-31 12:12:58 +03:00
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def test_wrong_mode(self) -> None:
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2020-02-22 19:07:04 +03:00
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with pytest.raises(ValueError, match="wrong mode"):
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2019-06-13 18:53:42 +03:00
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im = Image.new("L", (10, 10), 0)
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2022-01-15 01:02:31 +03:00
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im.im.color_lut_3d(
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"RGB", Image.Resampling.BILINEAR, *self.generate_identity_table(3, 3)
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)
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2018-03-26 19:30:00 +03:00
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2020-02-22 19:07:04 +03:00
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with pytest.raises(ValueError, match="wrong mode"):
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2019-06-13 18:53:42 +03:00
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im = Image.new("RGB", (10, 10), 0)
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2022-01-15 01:02:31 +03:00
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im.im.color_lut_3d(
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"L", Image.Resampling.BILINEAR, *self.generate_identity_table(3, 3)
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)
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2018-03-26 19:30:00 +03:00
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2020-02-22 19:07:04 +03:00
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with pytest.raises(ValueError, match="wrong mode"):
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2019-06-13 18:53:42 +03:00
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im = Image.new("L", (10, 10), 0)
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2022-01-15 01:02:31 +03:00
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im.im.color_lut_3d(
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"L", Image.Resampling.BILINEAR, *self.generate_identity_table(3, 3)
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)
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2018-03-26 19:30:00 +03:00
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2020-02-22 19:07:04 +03:00
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with pytest.raises(ValueError, match="wrong mode"):
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2019-06-13 18:53:42 +03:00
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im = Image.new("RGB", (10, 10), 0)
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im.im.color_lut_3d(
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2022-01-15 01:02:31 +03:00
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"RGBA", Image.Resampling.BILINEAR, *self.generate_identity_table(3, 3)
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2019-06-13 18:53:42 +03:00
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)
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2018-03-26 19:30:00 +03:00
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2020-02-22 19:07:04 +03:00
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with pytest.raises(ValueError, match="wrong mode"):
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2019-06-13 18:53:42 +03:00
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im = Image.new("RGB", (10, 10), 0)
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2022-01-15 01:02:31 +03:00
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im.im.color_lut_3d(
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"RGB", Image.Resampling.BILINEAR, *self.generate_identity_table(4, 3)
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)
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2018-03-26 19:30:00 +03:00
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2024-01-31 12:12:58 +03:00
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def test_correct_mode(self) -> None:
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2019-06-13 18:53:42 +03:00
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im = Image.new("RGBA", (10, 10), 0)
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2022-01-15 01:02:31 +03:00
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im.im.color_lut_3d(
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"RGBA", Image.Resampling.BILINEAR, *self.generate_identity_table(3, 3)
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)
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2018-03-26 19:30:00 +03:00
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2019-06-13 18:53:42 +03:00
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im = Image.new("RGBA", (10, 10), 0)
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2022-01-15 01:02:31 +03:00
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im.im.color_lut_3d(
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"RGBA", Image.Resampling.BILINEAR, *self.generate_identity_table(4, 3)
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)
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2018-03-26 19:30:00 +03:00
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2019-06-13 18:53:42 +03:00
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im = Image.new("RGB", (10, 10), 0)
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2022-01-15 01:02:31 +03:00
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im.im.color_lut_3d(
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"HSV", Image.Resampling.BILINEAR, *self.generate_identity_table(3, 3)
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)
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2018-03-26 19:30:00 +03:00
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2019-06-13 18:53:42 +03:00
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im = Image.new("RGB", (10, 10), 0)
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2022-01-15 01:02:31 +03:00
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im.im.color_lut_3d(
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"RGBA", Image.Resampling.BILINEAR, *self.generate_identity_table(4, 3)
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)
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2018-03-26 19:30:00 +03:00
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2024-01-31 12:12:58 +03:00
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def test_identities(self) -> None:
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2019-06-13 18:53:42 +03:00
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g = Image.linear_gradient("L")
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im = Image.merge(
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2022-01-15 01:02:31 +03:00
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"RGB",
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[
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g,
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g.transpose(Image.Transpose.ROTATE_90),
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g.transpose(Image.Transpose.ROTATE_180),
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],
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2019-06-13 18:53:42 +03:00
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)
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2018-03-26 22:29:50 +03:00
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# Fast test with small cubes
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for size in [2, 3, 5, 7, 11, 16, 17]:
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2020-01-30 17:56:07 +03:00
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assert_image_equal(
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2019-06-13 18:53:42 +03:00
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im,
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im._new(
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im.im.color_lut_3d(
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2022-01-15 01:02:31 +03:00
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"RGB",
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Image.Resampling.BILINEAR,
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*self.generate_identity_table(3, size),
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2019-06-13 18:53:42 +03:00
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)
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),
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)
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2018-03-26 22:29:50 +03:00
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# Not so fast
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2020-01-30 17:56:07 +03:00
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assert_image_equal(
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2019-06-13 18:53:42 +03:00
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im,
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im._new(
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im.im.color_lut_3d(
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2022-01-15 01:02:31 +03:00
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"RGB",
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Image.Resampling.BILINEAR,
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*self.generate_identity_table(3, (2, 2, 65)),
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2019-06-13 18:53:42 +03:00
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)
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),
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)
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2018-03-26 22:29:50 +03:00
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2024-01-31 12:12:58 +03:00
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def test_identities_4_channels(self) -> None:
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2019-06-13 18:53:42 +03:00
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g = Image.linear_gradient("L")
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im = Image.merge(
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2022-01-15 01:02:31 +03:00
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"RGB",
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[
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g,
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g.transpose(Image.Transpose.ROTATE_90),
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g.transpose(Image.Transpose.ROTATE_180),
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],
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2019-06-13 18:53:42 +03:00
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)
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2018-03-26 23:17:17 +03:00
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# Red channel copied to alpha
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2020-01-30 17:56:07 +03:00
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assert_image_equal(
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2019-06-13 18:53:42 +03:00
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Image.merge("RGBA", (im.split() * 2)[:4]),
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im._new(
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im.im.color_lut_3d(
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2022-01-15 01:02:31 +03:00
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"RGBA",
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Image.Resampling.BILINEAR,
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*self.generate_identity_table(4, 17),
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2019-06-13 18:53:42 +03:00
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)
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),
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)
|
2018-03-26 23:17:17 +03:00
|
|
|
|
2024-01-31 12:12:58 +03:00
|
|
|
def test_copy_alpha_channel(self) -> None:
|
2019-06-13 18:53:42 +03:00
|
|
|
g = Image.linear_gradient("L")
|
|
|
|
im = Image.merge(
|
|
|
|
"RGBA",
|
|
|
|
[
|
|
|
|
g,
|
2022-01-15 01:02:31 +03:00
|
|
|
g.transpose(Image.Transpose.ROTATE_90),
|
|
|
|
g.transpose(Image.Transpose.ROTATE_180),
|
|
|
|
g.transpose(Image.Transpose.ROTATE_270),
|
2019-06-13 18:53:42 +03:00
|
|
|
],
|
|
|
|
)
|
2018-03-26 23:17:17 +03:00
|
|
|
|
2020-01-30 17:56:07 +03:00
|
|
|
assert_image_equal(
|
2019-06-13 18:53:42 +03:00
|
|
|
im,
|
|
|
|
im._new(
|
|
|
|
im.im.color_lut_3d(
|
2022-01-15 01:02:31 +03:00
|
|
|
"RGBA",
|
|
|
|
Image.Resampling.BILINEAR,
|
|
|
|
*self.generate_identity_table(3, 17),
|
2019-06-13 18:53:42 +03:00
|
|
|
)
|
|
|
|
),
|
|
|
|
)
|
2018-03-26 23:17:17 +03:00
|
|
|
|
2024-01-31 12:12:58 +03:00
|
|
|
def test_channels_order(self) -> None:
|
2019-06-13 18:53:42 +03:00
|
|
|
g = Image.linear_gradient("L")
|
|
|
|
im = Image.merge(
|
2022-01-15 01:02:31 +03:00
|
|
|
"RGB",
|
|
|
|
[
|
|
|
|
g,
|
|
|
|
g.transpose(Image.Transpose.ROTATE_90),
|
|
|
|
g.transpose(Image.Transpose.ROTATE_180),
|
|
|
|
],
|
2019-06-13 18:53:42 +03:00
|
|
|
)
|
2018-03-26 22:29:50 +03:00
|
|
|
|
|
|
|
# Reverse channels by splitting and using table
|
2019-06-13 18:53:42 +03:00
|
|
|
# fmt: off
|
2020-01-30 17:56:07 +03:00
|
|
|
assert_image_equal(
|
2018-03-26 22:29:50 +03:00
|
|
|
Image.merge('RGB', im.split()[::-1]),
|
2022-01-15 01:02:31 +03:00
|
|
|
im._new(im.im.color_lut_3d('RGB', Image.Resampling.BILINEAR,
|
2018-06-16 03:06:45 +03:00
|
|
|
3, 2, 2, 2, [
|
|
|
|
0, 0, 0, 0, 0, 1,
|
|
|
|
0, 1, 0, 0, 1, 1,
|
2018-03-26 22:29:50 +03:00
|
|
|
|
2018-06-16 03:06:45 +03:00
|
|
|
1, 0, 0, 1, 0, 1,
|
|
|
|
1, 1, 0, 1, 1, 1,
|
|
|
|
])))
|
2019-06-13 18:53:42 +03:00
|
|
|
# fmt: on
|
2018-03-26 22:29:50 +03:00
|
|
|
|
2024-01-31 12:12:58 +03:00
|
|
|
def test_overflow(self) -> None:
|
2019-06-13 18:53:42 +03:00
|
|
|
g = Image.linear_gradient("L")
|
|
|
|
im = Image.merge(
|
2022-01-15 01:02:31 +03:00
|
|
|
"RGB",
|
|
|
|
[
|
|
|
|
g,
|
|
|
|
g.transpose(Image.Transpose.ROTATE_90),
|
|
|
|
g.transpose(Image.Transpose.ROTATE_180),
|
|
|
|
],
|
2019-06-13 18:53:42 +03:00
|
|
|
)
|
2018-03-26 22:29:50 +03:00
|
|
|
|
2019-06-13 18:53:42 +03:00
|
|
|
# fmt: off
|
2022-01-15 01:02:31 +03:00
|
|
|
transformed = im._new(im.im.color_lut_3d('RGB', Image.Resampling.BILINEAR,
|
2018-06-16 03:06:45 +03:00
|
|
|
3, 2, 2, 2,
|
|
|
|
[
|
|
|
|
-1, -1, -1, 2, -1, -1,
|
|
|
|
-1, 2, -1, 2, 2, -1,
|
|
|
|
|
|
|
|
-1, -1, 2, 2, -1, 2,
|
|
|
|
-1, 2, 2, 2, 2, 2,
|
|
|
|
])).load()
|
2019-06-13 18:53:42 +03:00
|
|
|
# fmt: on
|
2020-02-22 16:06:21 +03:00
|
|
|
assert transformed[0, 0] == (0, 0, 255)
|
|
|
|
assert transformed[50, 50] == (0, 0, 255)
|
|
|
|
assert transformed[255, 0] == (0, 255, 255)
|
|
|
|
assert transformed[205, 50] == (0, 255, 255)
|
|
|
|
assert transformed[0, 255] == (255, 0, 0)
|
|
|
|
assert transformed[50, 205] == (255, 0, 0)
|
|
|
|
assert transformed[255, 255] == (255, 255, 0)
|
|
|
|
assert transformed[205, 205] == (255, 255, 0)
|
2018-03-26 22:29:50 +03:00
|
|
|
|
2019-06-13 18:53:42 +03:00
|
|
|
# fmt: off
|
2022-01-15 01:02:31 +03:00
|
|
|
transformed = im._new(im.im.color_lut_3d('RGB', Image.Resampling.BILINEAR,
|
2018-06-16 03:06:45 +03:00
|
|
|
3, 2, 2, 2,
|
|
|
|
[
|
|
|
|
-3, -3, -3, 5, -3, -3,
|
|
|
|
-3, 5, -3, 5, 5, -3,
|
|
|
|
|
|
|
|
-3, -3, 5, 5, -3, 5,
|
|
|
|
-3, 5, 5, 5, 5, 5,
|
|
|
|
])).load()
|
2019-06-13 18:53:42 +03:00
|
|
|
# fmt: on
|
2020-02-22 16:06:21 +03:00
|
|
|
assert transformed[0, 0] == (0, 0, 255)
|
|
|
|
assert transformed[50, 50] == (0, 0, 255)
|
|
|
|
assert transformed[255, 0] == (0, 255, 255)
|
|
|
|
assert transformed[205, 50] == (0, 255, 255)
|
|
|
|
assert transformed[0, 255] == (255, 0, 0)
|
|
|
|
assert transformed[50, 205] == (255, 0, 0)
|
|
|
|
assert transformed[255, 255] == (255, 255, 0)
|
|
|
|
assert transformed[205, 205] == (255, 255, 0)
|
2018-03-26 22:29:50 +03:00
|
|
|
|
2018-03-26 19:30:00 +03:00
|
|
|
|
2020-02-23 00:03:01 +03:00
|
|
|
class TestColorLut3DFilter:
|
2024-01-31 12:12:58 +03:00
|
|
|
def test_wrong_args(self) -> None:
|
2020-02-22 19:07:04 +03:00
|
|
|
with pytest.raises(ValueError, match="should be either an integer"):
|
2018-03-29 16:37:35 +03:00
|
|
|
ImageFilter.Color3DLUT("small", [1])
|
|
|
|
|
2020-02-22 19:07:04 +03:00
|
|
|
with pytest.raises(ValueError, match="should be either an integer"):
|
2018-03-29 16:37:35 +03:00
|
|
|
ImageFilter.Color3DLUT((11, 11), [1])
|
|
|
|
|
2020-02-22 19:07:04 +03:00
|
|
|
with pytest.raises(ValueError, match=r"in \[2, 65\] range"):
|
2018-03-29 16:37:35 +03:00
|
|
|
ImageFilter.Color3DLUT((11, 11, 1), [1])
|
|
|
|
|
2020-02-22 19:07:04 +03:00
|
|
|
with pytest.raises(ValueError, match=r"in \[2, 65\] range"):
|
2018-03-29 16:37:35 +03:00
|
|
|
ImageFilter.Color3DLUT((11, 11, 66), [1])
|
|
|
|
|
2020-02-22 19:07:04 +03:00
|
|
|
with pytest.raises(ValueError, match="table should have .+ items"):
|
2018-03-29 16:37:35 +03:00
|
|
|
ImageFilter.Color3DLUT((3, 3, 3), [1, 1, 1])
|
|
|
|
|
2020-02-22 19:07:04 +03:00
|
|
|
with pytest.raises(ValueError, match="table should have .+ items"):
|
2018-03-29 16:37:35 +03:00
|
|
|
ImageFilter.Color3DLUT((3, 3, 3), [[1, 1, 1]] * 2)
|
|
|
|
|
2020-02-22 19:07:04 +03:00
|
|
|
with pytest.raises(ValueError, match="should have a length of 4"):
|
2018-03-29 16:37:35 +03:00
|
|
|
ImageFilter.Color3DLUT((3, 3, 3), [[1, 1, 1]] * 27, channels=4)
|
|
|
|
|
2020-02-22 19:07:04 +03:00
|
|
|
with pytest.raises(ValueError, match="should have a length of 3"):
|
2018-03-29 16:37:35 +03:00
|
|
|
ImageFilter.Color3DLUT((2, 2, 2), [[1, 1]] * 8)
|
|
|
|
|
2020-02-22 19:07:04 +03:00
|
|
|
with pytest.raises(ValueError, match="Only 3 or 4 output"):
|
2018-04-12 12:40:40 +03:00
|
|
|
ImageFilter.Color3DLUT((2, 2, 2), [[1, 1]] * 8, channels=2)
|
|
|
|
|
2024-01-31 12:12:58 +03:00
|
|
|
def test_convert_table(self) -> None:
|
2018-03-30 02:02:37 +03:00
|
|
|
lut = ImageFilter.Color3DLUT(2, [0, 1, 2] * 8)
|
2020-02-22 16:06:21 +03:00
|
|
|
assert tuple(lut.size) == (2, 2, 2)
|
|
|
|
assert lut.name == "Color 3D LUT"
|
2018-03-29 16:37:35 +03:00
|
|
|
|
2019-06-13 18:53:42 +03:00
|
|
|
# fmt: off
|
2018-03-30 02:02:37 +03:00
|
|
|
lut = ImageFilter.Color3DLUT((2, 2, 2), [
|
2018-03-29 16:37:35 +03:00
|
|
|
(0, 1, 2), (3, 4, 5), (6, 7, 8), (9, 10, 11),
|
|
|
|
(12, 13, 14), (15, 16, 17), (18, 19, 20), (21, 22, 23)])
|
2019-06-13 18:53:42 +03:00
|
|
|
# fmt: on
|
2020-02-22 16:06:21 +03:00
|
|
|
assert tuple(lut.size) == (2, 2, 2)
|
|
|
|
assert lut.table == list(range(24))
|
2018-03-29 16:37:35 +03:00
|
|
|
|
2019-06-13 18:53:42 +03:00
|
|
|
lut = ImageFilter.Color3DLUT((2, 2, 2), [(0, 1, 2, 3)] * 8, channels=4)
|
2020-02-22 16:06:21 +03:00
|
|
|
assert tuple(lut.size) == (2, 2, 2)
|
|
|
|
assert lut.table == list(range(4)) * 8
|
2018-03-29 16:37:35 +03:00
|
|
|
|
2020-02-23 00:03:01 +03:00
|
|
|
@pytest.mark.skipif(numpy is None, reason="NumPy not installed")
|
2024-01-31 12:12:58 +03:00
|
|
|
def test_numpy_sources(self) -> None:
|
2024-02-12 13:06:17 +03:00
|
|
|
assert numpy is not None
|
2018-04-14 19:17:15 +03:00
|
|
|
table = numpy.ones((5, 6, 7, 3), dtype=numpy.float16)
|
2020-02-22 19:07:04 +03:00
|
|
|
with pytest.raises(ValueError, match="should have either channels"):
|
2018-04-14 19:17:15 +03:00
|
|
|
lut = ImageFilter.Color3DLUT((5, 6, 7), table)
|
|
|
|
|
|
|
|
table = numpy.ones((7, 6, 5, 3), dtype=numpy.float16)
|
|
|
|
lut = ImageFilter.Color3DLUT((5, 6, 7), table)
|
2020-02-22 16:06:21 +03:00
|
|
|
assert isinstance(lut.table, numpy.ndarray)
|
|
|
|
assert lut.table.dtype == table.dtype
|
|
|
|
assert lut.table.shape == (table.size,)
|
2018-04-14 19:17:15 +03:00
|
|
|
|
|
|
|
table = numpy.ones((7 * 6 * 5, 3), dtype=numpy.float16)
|
|
|
|
lut = ImageFilter.Color3DLUT((5, 6, 7), table)
|
2020-02-22 16:06:21 +03:00
|
|
|
assert lut.table.shape == (table.size,)
|
2018-04-14 19:17:15 +03:00
|
|
|
|
|
|
|
table = numpy.ones((7 * 6 * 5 * 3), dtype=numpy.float16)
|
|
|
|
lut = ImageFilter.Color3DLUT((5, 6, 7), table)
|
2020-02-22 16:06:21 +03:00
|
|
|
assert lut.table.shape == (table.size,)
|
2018-04-14 19:17:15 +03:00
|
|
|
|
|
|
|
# Check application
|
2019-06-13 18:53:42 +03:00
|
|
|
Image.new("RGB", (10, 10), 0).filter(lut)
|
2018-04-14 19:17:15 +03:00
|
|
|
|
|
|
|
# Check copy
|
|
|
|
table[0] = 33
|
2020-02-22 16:06:21 +03:00
|
|
|
assert lut.table[0] == 1
|
2018-04-14 19:17:15 +03:00
|
|
|
|
|
|
|
# Check not copy
|
|
|
|
table = numpy.ones((7 * 6 * 5 * 3), dtype=numpy.float16)
|
|
|
|
lut = ImageFilter.Color3DLUT((5, 6, 7), table, _copy_table=False)
|
|
|
|
table[0] = 33
|
2020-02-22 16:06:21 +03:00
|
|
|
assert lut.table[0] == 33
|
2018-04-14 19:17:15 +03:00
|
|
|
|
2020-02-23 00:03:01 +03:00
|
|
|
@pytest.mark.skipif(numpy is None, reason="NumPy not installed")
|
2024-01-31 12:12:58 +03:00
|
|
|
def test_numpy_formats(self) -> None:
|
2024-02-12 13:06:17 +03:00
|
|
|
assert numpy is not None
|
2019-06-13 18:53:42 +03:00
|
|
|
g = Image.linear_gradient("L")
|
|
|
|
im = Image.merge(
|
2022-01-15 01:02:31 +03:00
|
|
|
"RGB",
|
|
|
|
[
|
|
|
|
g,
|
|
|
|
g.transpose(Image.Transpose.ROTATE_90),
|
|
|
|
g.transpose(Image.Transpose.ROTATE_180),
|
|
|
|
],
|
2019-06-13 18:53:42 +03:00
|
|
|
)
|
2018-04-15 00:33:15 +03:00
|
|
|
|
2019-06-13 18:53:42 +03:00
|
|
|
lut = ImageFilter.Color3DLUT.generate((7, 9, 11), lambda r, g, b: (r, g, b))
|
2018-04-15 00:33:15 +03:00
|
|
|
lut.table = numpy.array(lut.table, dtype=numpy.float32)[:-1]
|
2020-02-22 19:07:04 +03:00
|
|
|
with pytest.raises(ValueError, match="should have table_channels"):
|
2018-04-15 00:33:15 +03:00
|
|
|
im.filter(lut)
|
|
|
|
|
2019-06-13 18:53:42 +03:00
|
|
|
lut = ImageFilter.Color3DLUT.generate((7, 9, 11), lambda r, g, b: (r, g, b))
|
|
|
|
lut.table = numpy.array(lut.table, dtype=numpy.float32).reshape((7 * 9 * 11), 3)
|
2020-02-22 19:07:04 +03:00
|
|
|
with pytest.raises(ValueError, match="should have table_channels"):
|
2018-04-15 00:33:15 +03:00
|
|
|
im.filter(lut)
|
|
|
|
|
2019-06-13 18:53:42 +03:00
|
|
|
lut = ImageFilter.Color3DLUT.generate((7, 9, 11), lambda r, g, b: (r, g, b))
|
2018-04-15 00:33:15 +03:00
|
|
|
lut.table = numpy.array(lut.table, dtype=numpy.float16)
|
2020-01-30 17:56:07 +03:00
|
|
|
assert_image_equal(im, im.filter(lut))
|
2018-04-15 00:33:15 +03:00
|
|
|
|
2019-06-13 18:53:42 +03:00
|
|
|
lut = ImageFilter.Color3DLUT.generate((7, 9, 11), lambda r, g, b: (r, g, b))
|
2018-04-15 00:33:15 +03:00
|
|
|
lut.table = numpy.array(lut.table, dtype=numpy.float32)
|
2020-01-30 17:56:07 +03:00
|
|
|
assert_image_equal(im, im.filter(lut))
|
2018-04-15 00:33:15 +03:00
|
|
|
|
2019-06-13 18:53:42 +03:00
|
|
|
lut = ImageFilter.Color3DLUT.generate((7, 9, 11), lambda r, g, b: (r, g, b))
|
2018-04-15 00:33:15 +03:00
|
|
|
lut.table = numpy.array(lut.table, dtype=numpy.float64)
|
2020-01-30 17:56:07 +03:00
|
|
|
assert_image_equal(im, im.filter(lut))
|
2018-04-15 00:33:15 +03:00
|
|
|
|
2019-06-13 18:53:42 +03:00
|
|
|
lut = ImageFilter.Color3DLUT.generate((7, 9, 11), lambda r, g, b: (r, g, b))
|
2018-04-15 00:33:15 +03:00
|
|
|
lut.table = numpy.array(lut.table, dtype=numpy.int32)
|
|
|
|
im.filter(lut)
|
|
|
|
lut.table = numpy.array(lut.table, dtype=numpy.int8)
|
|
|
|
im.filter(lut)
|
|
|
|
|
2024-01-31 12:12:58 +03:00
|
|
|
def test_repr(self) -> None:
|
2018-04-12 11:54:54 +03:00
|
|
|
lut = ImageFilter.Color3DLUT(2, [0, 1, 2] * 8)
|
2020-02-22 16:06:21 +03:00
|
|
|
assert repr(lut) == "<Color3DLUT from list size=2x2x2 channels=3>"
|
2018-04-12 11:54:54 +03:00
|
|
|
|
|
|
|
lut = ImageFilter.Color3DLUT(
|
2019-06-13 18:53:42 +03:00
|
|
|
(3, 4, 5),
|
|
|
|
array("f", [0, 0, 0, 0] * (3 * 4 * 5)),
|
|
|
|
channels=4,
|
|
|
|
target_mode="YCbCr",
|
|
|
|
_copy_table=False,
|
|
|
|
)
|
2020-02-22 16:06:21 +03:00
|
|
|
assert (
|
|
|
|
repr(lut)
|
|
|
|
== "<Color3DLUT from array size=3x4x5 channels=4 target_mode=YCbCr>"
|
2019-06-13 18:53:42 +03:00
|
|
|
)
|
2018-04-11 17:05:48 +03:00
|
|
|
|
2018-04-10 13:40:44 +03:00
|
|
|
|
2020-02-23 00:03:01 +03:00
|
|
|
class TestGenerateColorLut3D:
|
2024-01-31 12:12:58 +03:00
|
|
|
def test_wrong_channels_count(self) -> None:
|
2020-02-22 19:07:04 +03:00
|
|
|
with pytest.raises(ValueError, match="3 or 4 output channels"):
|
2018-06-16 03:06:45 +03:00
|
|
|
ImageFilter.Color3DLUT.generate(
|
2019-06-13 18:53:42 +03:00
|
|
|
5, channels=2, callback=lambda r, g, b: (r, g, b)
|
|
|
|
)
|
2018-03-29 16:37:35 +03:00
|
|
|
|
2020-02-22 19:07:04 +03:00
|
|
|
with pytest.raises(ValueError, match="should have either channels"):
|
2018-04-11 17:05:48 +03:00
|
|
|
ImageFilter.Color3DLUT.generate(5, lambda r, g, b: (r, g, b, r))
|
|
|
|
|
2020-02-22 19:07:04 +03:00
|
|
|
with pytest.raises(ValueError, match="should have either channels"):
|
2018-06-16 03:06:45 +03:00
|
|
|
ImageFilter.Color3DLUT.generate(
|
2019-06-13 18:53:42 +03:00
|
|
|
5, channels=4, callback=lambda r, g, b: (r, g, b)
|
|
|
|
)
|
2018-04-11 17:05:48 +03:00
|
|
|
|
2024-01-31 12:12:58 +03:00
|
|
|
def test_3_channels(self) -> None:
|
2018-03-30 02:02:37 +03:00
|
|
|
lut = ImageFilter.Color3DLUT.generate(5, lambda r, g, b: (r, g, b))
|
2020-02-22 16:06:21 +03:00
|
|
|
assert tuple(lut.size) == (5, 5, 5)
|
|
|
|
assert lut.name == "Color 3D LUT"
|
2019-06-13 18:53:42 +03:00
|
|
|
# fmt: off
|
2020-02-22 16:06:21 +03:00
|
|
|
assert lut.table[:24] == [
|
2018-03-29 17:26:21 +03:00
|
|
|
0.0, 0.0, 0.0, 0.25, 0.0, 0.0, 0.5, 0.0, 0.0, 0.75, 0.0, 0.0,
|
2020-02-22 16:06:21 +03:00
|
|
|
1.0, 0.0, 0.0, 0.0, 0.25, 0.0, 0.25, 0.25, 0.0, 0.5, 0.25, 0.0]
|
2019-06-13 18:53:42 +03:00
|
|
|
# fmt: on
|
2018-03-29 17:26:21 +03:00
|
|
|
|
2024-01-31 12:12:58 +03:00
|
|
|
def test_4_channels(self) -> None:
|
2018-06-16 03:06:45 +03:00
|
|
|
lut = ImageFilter.Color3DLUT.generate(
|
2019-06-13 18:53:42 +03:00
|
|
|
5, channels=4, callback=lambda r, g, b: (b, r, g, (r + g + b) / 2)
|
|
|
|
)
|
2020-02-22 16:06:21 +03:00
|
|
|
assert tuple(lut.size) == (5, 5, 5)
|
|
|
|
assert lut.name == "Color 3D LUT"
|
2019-06-13 18:53:42 +03:00
|
|
|
# fmt: off
|
2020-02-22 16:06:21 +03:00
|
|
|
assert lut.table[:24] == [
|
2018-03-29 17:26:21 +03:00
|
|
|
0.0, 0.0, 0.0, 0.0, 0.0, 0.25, 0.0, 0.125, 0.0, 0.5, 0.0, 0.25,
|
2018-06-24 15:32:25 +03:00
|
|
|
0.0, 0.75, 0.0, 0.375, 0.0, 1.0, 0.0, 0.5, 0.0, 0.0, 0.25, 0.125
|
2020-02-22 16:06:21 +03:00
|
|
|
]
|
2019-06-13 18:53:42 +03:00
|
|
|
# fmt: on
|
2018-03-29 17:26:21 +03:00
|
|
|
|
2024-01-31 12:12:58 +03:00
|
|
|
def test_apply(self) -> None:
|
2018-04-11 17:05:48 +03:00
|
|
|
lut = ImageFilter.Color3DLUT.generate(5, lambda r, g, b: (r, g, b))
|
2018-03-29 17:26:21 +03:00
|
|
|
|
2019-06-13 18:53:42 +03:00
|
|
|
g = Image.linear_gradient("L")
|
|
|
|
im = Image.merge(
|
2022-01-15 01:02:31 +03:00
|
|
|
"RGB",
|
|
|
|
[
|
|
|
|
g,
|
|
|
|
g.transpose(Image.Transpose.ROTATE_90),
|
|
|
|
g.transpose(Image.Transpose.ROTATE_180),
|
|
|
|
],
|
2019-06-13 18:53:42 +03:00
|
|
|
)
|
2020-02-22 16:06:21 +03:00
|
|
|
assert im == im.filter(lut)
|
2018-04-11 17:05:48 +03:00
|
|
|
|
|
|
|
|
2020-02-23 00:03:01 +03:00
|
|
|
class TestTransformColorLut3D:
|
2024-01-31 12:12:58 +03:00
|
|
|
def test_wrong_args(self) -> None:
|
2018-04-11 17:05:48 +03:00
|
|
|
source = ImageFilter.Color3DLUT.generate(5, lambda r, g, b: (r, g, b))
|
|
|
|
|
2020-02-22 19:07:04 +03:00
|
|
|
with pytest.raises(ValueError, match="Only 3 or 4 output"):
|
2018-04-11 17:05:48 +03:00
|
|
|
source.transform(lambda r, g, b: (r, g, b), channels=8)
|
|
|
|
|
2020-02-22 19:07:04 +03:00
|
|
|
with pytest.raises(ValueError, match="should have either channels"):
|
2018-04-11 17:05:48 +03:00
|
|
|
source.transform(lambda r, g, b: (r, g, b), channels=4)
|
2018-03-29 17:26:21 +03:00
|
|
|
|
2020-02-22 19:07:04 +03:00
|
|
|
with pytest.raises(ValueError, match="should have either channels"):
|
2018-04-11 17:05:48 +03:00
|
|
|
source.transform(lambda r, g, b: (r, g, b, 1))
|
|
|
|
|
2020-02-22 16:06:21 +03:00
|
|
|
with pytest.raises(TypeError):
|
2018-04-11 17:05:48 +03:00
|
|
|
source.transform(lambda r, g, b, a: (r, g, b))
|
|
|
|
|
2024-01-31 12:12:58 +03:00
|
|
|
def test_target_mode(self) -> None:
|
2018-04-11 17:05:48 +03:00
|
|
|
source = ImageFilter.Color3DLUT.generate(
|
2019-06-13 18:53:42 +03:00
|
|
|
2, lambda r, g, b: (r, g, b), target_mode="HSV"
|
|
|
|
)
|
2018-04-11 17:05:48 +03:00
|
|
|
|
|
|
|
lut = source.transform(lambda r, g, b: (r, g, b))
|
2020-02-22 16:06:21 +03:00
|
|
|
assert lut.mode == "HSV"
|
2018-04-11 17:05:48 +03:00
|
|
|
|
2019-06-13 18:53:42 +03:00
|
|
|
lut = source.transform(lambda r, g, b: (r, g, b), target_mode="RGB")
|
2020-02-22 16:06:21 +03:00
|
|
|
assert lut.mode == "RGB"
|
2018-04-11 17:05:48 +03:00
|
|
|
|
2024-01-31 12:12:58 +03:00
|
|
|
def test_3_to_3_channels(self) -> None:
|
2019-06-13 18:53:42 +03:00
|
|
|
source = ImageFilter.Color3DLUT.generate((3, 4, 5), lambda r, g, b: (r, g, b))
|
|
|
|
lut = source.transform(lambda r, g, b: (r * r, g * g, b * b))
|
2020-02-22 16:06:21 +03:00
|
|
|
assert tuple(lut.size) == tuple(source.size)
|
|
|
|
assert len(lut.table) == len(source.table)
|
|
|
|
assert lut.table != source.table
|
2022-04-25 15:50:08 +03:00
|
|
|
assert lut.table[:10] == [0.0, 0.0, 0.0, 0.25, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0]
|
2018-04-11 17:05:48 +03:00
|
|
|
|
2024-01-31 12:12:58 +03:00
|
|
|
def test_3_to_4_channels(self) -> None:
|
2019-06-13 18:53:42 +03:00
|
|
|
source = ImageFilter.Color3DLUT.generate((6, 5, 4), lambda r, g, b: (r, g, b))
|
|
|
|
lut = source.transform(lambda r, g, b: (r * r, g * g, b * b, 1), channels=4)
|
2020-02-22 16:06:21 +03:00
|
|
|
assert tuple(lut.size) == tuple(source.size)
|
|
|
|
assert len(lut.table) != len(source.table)
|
|
|
|
assert lut.table != source.table
|
2019-06-13 18:53:42 +03:00
|
|
|
# fmt: off
|
2022-04-25 15:50:08 +03:00
|
|
|
assert lut.table[:16] == [
|
2018-04-11 17:05:48 +03:00
|
|
|
0.0, 0.0, 0.0, 1, 0.2**2, 0.0, 0.0, 1,
|
2020-02-22 16:06:21 +03:00
|
|
|
0.4**2, 0.0, 0.0, 1, 0.6**2, 0.0, 0.0, 1]
|
2019-06-13 18:53:42 +03:00
|
|
|
# fmt: on
|
2018-04-11 17:05:48 +03:00
|
|
|
|
2024-01-31 12:12:58 +03:00
|
|
|
def test_4_to_3_channels(self) -> None:
|
2018-04-11 17:05:48 +03:00
|
|
|
source = ImageFilter.Color3DLUT.generate(
|
2019-06-13 18:53:42 +03:00
|
|
|
(3, 6, 5), lambda r, g, b: (r, g, b, 1), channels=4
|
|
|
|
)
|
|
|
|
lut = source.transform(
|
|
|
|
lambda r, g, b, a: (a - r * r, a - g * g, a - b * b), channels=3
|
|
|
|
)
|
2020-02-22 16:06:21 +03:00
|
|
|
assert tuple(lut.size) == tuple(source.size)
|
|
|
|
assert len(lut.table) != len(source.table)
|
|
|
|
assert lut.table != source.table
|
2019-06-13 18:53:42 +03:00
|
|
|
# fmt: off
|
2022-04-25 15:50:08 +03:00
|
|
|
assert lut.table[:18] == [
|
2018-04-11 17:05:48 +03:00
|
|
|
1.0, 1.0, 1.0, 0.75, 1.0, 1.0, 0.0, 1.0, 1.0,
|
2020-02-22 16:06:21 +03:00
|
|
|
1.0, 0.96, 1.0, 0.75, 0.96, 1.0, 0.0, 0.96, 1.0]
|
2019-06-13 18:53:42 +03:00
|
|
|
# fmt: on
|
2018-04-11 17:05:48 +03:00
|
|
|
|
2024-01-31 12:12:58 +03:00
|
|
|
def test_4_to_4_channels(self) -> None:
|
2018-04-11 17:05:48 +03:00
|
|
|
source = ImageFilter.Color3DLUT.generate(
|
2019-06-13 18:53:42 +03:00
|
|
|
(6, 5, 4), lambda r, g, b: (r, g, b, 1), channels=4
|
|
|
|
)
|
|
|
|
lut = source.transform(lambda r, g, b, a: (r * r, g * g, b * b, a - 0.5))
|
2020-02-22 16:06:21 +03:00
|
|
|
assert tuple(lut.size) == tuple(source.size)
|
|
|
|
assert len(lut.table) == len(source.table)
|
|
|
|
assert lut.table != source.table
|
2019-06-13 18:53:42 +03:00
|
|
|
# fmt: off
|
2022-04-25 15:50:08 +03:00
|
|
|
assert lut.table[:16] == [
|
2018-04-11 17:05:48 +03:00
|
|
|
0.0, 0.0, 0.0, 0.5, 0.2**2, 0.0, 0.0, 0.5,
|
2020-02-22 16:06:21 +03:00
|
|
|
0.4**2, 0.0, 0.0, 0.5, 0.6**2, 0.0, 0.0, 0.5]
|
2019-06-13 18:53:42 +03:00
|
|
|
# fmt: on
|
2018-04-11 17:05:48 +03:00
|
|
|
|
2024-01-31 12:12:58 +03:00
|
|
|
def test_with_normals_3_channels(self) -> None:
|
2018-04-11 17:05:48 +03:00
|
|
|
source = ImageFilter.Color3DLUT.generate(
|
2019-06-13 18:53:42 +03:00
|
|
|
(6, 5, 4), lambda r, g, b: (r * r, g * g, b * b)
|
|
|
|
)
|
2018-04-11 17:05:48 +03:00
|
|
|
lut = source.transform(
|
2019-06-13 18:53:42 +03:00
|
|
|
lambda nr, ng, nb, r, g, b: (nr - r, ng - g, nb - b), with_normals=True
|
|
|
|
)
|
2020-02-22 16:06:21 +03:00
|
|
|
assert tuple(lut.size) == tuple(source.size)
|
|
|
|
assert len(lut.table) == len(source.table)
|
|
|
|
assert lut.table != source.table
|
2019-06-13 18:53:42 +03:00
|
|
|
# fmt: off
|
2022-04-25 15:50:08 +03:00
|
|
|
assert lut.table[:18] == [
|
2018-04-11 17:05:48 +03:00
|
|
|
0.0, 0.0, 0.0, 0.16, 0.0, 0.0, 0.24, 0.0, 0.0,
|
2020-02-22 16:06:21 +03:00
|
|
|
0.24, 0.0, 0.0, 0.8 - (0.8**2), 0, 0, 0, 0, 0]
|
2019-06-13 18:53:42 +03:00
|
|
|
# fmt: on
|
2018-04-11 17:05:48 +03:00
|
|
|
|
2024-01-31 12:12:58 +03:00
|
|
|
def test_with_normals_4_channels(self) -> None:
|
2018-04-11 17:05:48 +03:00
|
|
|
source = ImageFilter.Color3DLUT.generate(
|
2019-06-13 18:53:42 +03:00
|
|
|
(3, 6, 5), lambda r, g, b: (r * r, g * g, b * b, 1), channels=4
|
|
|
|
)
|
2018-04-11 17:05:48 +03:00
|
|
|
lut = source.transform(
|
2019-06-13 18:53:42 +03:00
|
|
|
lambda nr, ng, nb, r, g, b, a: (nr - r, ng - g, nb - b, a - 0.5),
|
|
|
|
with_normals=True,
|
|
|
|
)
|
2020-02-22 16:06:21 +03:00
|
|
|
assert tuple(lut.size) == tuple(source.size)
|
|
|
|
assert len(lut.table) == len(source.table)
|
|
|
|
assert lut.table != source.table
|
2019-06-13 18:53:42 +03:00
|
|
|
# fmt: off
|
2022-04-25 15:50:08 +03:00
|
|
|
assert lut.table[:16] == [
|
2018-04-11 17:05:48 +03:00
|
|
|
0.0, 0.0, 0.0, 0.5, 0.25, 0.0, 0.0, 0.5,
|
2020-02-22 16:06:21 +03:00
|
|
|
0.0, 0.0, 0.0, 0.5, 0.0, 0.16, 0.0, 0.5]
|
2019-06-13 18:53:42 +03:00
|
|
|
# fmt: on
|