mirror of
https://github.com/python-pillow/Pillow.git
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268 lines
7.9 KiB
Python
268 lines
7.9 KiB
Python
from __future__ import annotations
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import warnings
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from typing import TYPE_CHECKING
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import pytest
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from PIL import Image, _typing
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from .helper import assert_deep_equal, assert_image, hopper, skip_unless_feature
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if TYPE_CHECKING:
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import numpy
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import numpy.typing as npt
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else:
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numpy = pytest.importorskip("numpy", reason="NumPy not installed")
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TEST_IMAGE_SIZE = (10, 10)
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def test_numpy_to_image() -> None:
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def to_image(dtype: npt.DTypeLike, bands: int = 1, boolean: int = 0) -> Image.Image:
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if bands == 1:
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if boolean:
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data = [0, 255] * 50
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else:
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data = list(range(100))
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a = numpy.array(data, dtype=dtype)
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a.shape = TEST_IMAGE_SIZE
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i = Image.fromarray(a)
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if list(i.getdata()) != data:
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print("data mismatch for", dtype)
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else:
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data = list(range(100))
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a = numpy.array([[x] * bands for x in data], dtype=dtype)
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a.shape = TEST_IMAGE_SIZE[0], TEST_IMAGE_SIZE[1], bands
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i = Image.fromarray(a)
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if list(i.getchannel(0).getdata()) != list(range(100)):
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print("data mismatch for", dtype)
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return i
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# Check supported 1-bit integer formats
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assert_image(to_image(bool, 1, 1), "1", TEST_IMAGE_SIZE)
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assert_image(to_image(numpy.bool_, 1, 1), "1", TEST_IMAGE_SIZE)
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# Check supported 8-bit integer formats
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assert_image(to_image(numpy.uint8), "L", TEST_IMAGE_SIZE)
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assert_image(to_image(numpy.uint8, 3), "RGB", TEST_IMAGE_SIZE)
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assert_image(to_image(numpy.uint8, 4), "RGBA", TEST_IMAGE_SIZE)
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assert_image(to_image(numpy.int8), "I", TEST_IMAGE_SIZE)
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# Check non-fixed-size integer types
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# These may fail, depending on the platform, since we have no native
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# 64-bit int image types.
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# assert_image(to_image(numpy.uint), "I", TEST_IMAGE_SIZE)
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# assert_image(to_image(numpy.int), "I", TEST_IMAGE_SIZE)
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# Check 16-bit integer formats
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if Image._ENDIAN == "<":
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assert_image(to_image(numpy.uint16), "I;16", TEST_IMAGE_SIZE)
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else:
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assert_image(to_image(numpy.uint16), "I;16B", TEST_IMAGE_SIZE)
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assert_image(to_image(numpy.int16), "I", TEST_IMAGE_SIZE)
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# Check 32-bit integer formats
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assert_image(to_image(numpy.uint32), "I", TEST_IMAGE_SIZE)
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assert_image(to_image(numpy.int32), "I", TEST_IMAGE_SIZE)
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# Check 64-bit integer formats
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with pytest.raises(TypeError):
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to_image(numpy.uint64)
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with pytest.raises(TypeError):
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to_image(numpy.int64)
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# Check floating-point formats
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assert_image(to_image(float), "F", TEST_IMAGE_SIZE)
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with pytest.raises(TypeError):
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to_image(numpy.float16)
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assert_image(to_image(numpy.float32), "F", TEST_IMAGE_SIZE)
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assert_image(to_image(numpy.float64), "F", TEST_IMAGE_SIZE)
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assert_image(to_image(numpy.uint8, 2), "LA", (10, 10))
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assert_image(to_image(numpy.uint8, 3), "RGB", (10, 10))
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assert_image(to_image(numpy.uint8, 4), "RGBA", (10, 10))
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# Based on an erring example at
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# https://stackoverflow.com/questions/10854903/what-is-causing-dimension-dependent-attributeerror-in-pil-fromarray-function
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def test_3d_array() -> None:
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size = (5, TEST_IMAGE_SIZE[0], TEST_IMAGE_SIZE[1])
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a = numpy.ones(size, dtype=numpy.uint8)
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assert_image(Image.fromarray(a[1, :, :]), "L", TEST_IMAGE_SIZE)
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size = (TEST_IMAGE_SIZE[0], 5, TEST_IMAGE_SIZE[1])
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a = numpy.ones(size, dtype=numpy.uint8)
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assert_image(Image.fromarray(a[:, 1, :]), "L", TEST_IMAGE_SIZE)
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size = (TEST_IMAGE_SIZE[0], TEST_IMAGE_SIZE[1], 5)
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a = numpy.ones(size, dtype=numpy.uint8)
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assert_image(Image.fromarray(a[:, :, 1]), "L", TEST_IMAGE_SIZE)
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def test_1d_array() -> None:
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a = numpy.ones(5, dtype=numpy.uint8)
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assert_image(Image.fromarray(a), "L", (1, 5))
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def _test_img_equals_nparray(img: Image.Image, np_img: _typing.NumpyArray) -> None:
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assert len(np_img.shape) >= 2
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np_size = np_img.shape[1], np_img.shape[0]
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assert img.size == np_size
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px = img.load()
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assert px is not None
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for x in range(0, img.size[0], int(img.size[0] / 10)):
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for y in range(0, img.size[1], int(img.size[1] / 10)):
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assert_deep_equal(px[x, y], np_img[y, x])
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def test_16bit() -> None:
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with Image.open("Tests/images/16bit.cropped.tif") as img:
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np_img = numpy.array(img)
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_test_img_equals_nparray(img, np_img)
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assert np_img.dtype == numpy.dtype("<u2")
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def test_1bit() -> None:
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# Test that 1-bit arrays convert to numpy and back
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# See: https://github.com/python-pillow/Pillow/issues/350
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arr = numpy.array([[1, 0, 0, 1, 0], [0, 1, 0, 0, 0]], "u1")
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img = Image.fromarray(arr * 255).convert("1")
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assert img.mode == "1"
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arr_back = numpy.array(img)
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numpy.testing.assert_array_equal(arr, arr_back)
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def test_save_tiff_uint16() -> None:
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# Tests that we're getting the pixel value in the right byte order.
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pixel_value = 0x1234
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a = numpy.array(
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[pixel_value] * TEST_IMAGE_SIZE[0] * TEST_IMAGE_SIZE[1], dtype=numpy.uint16
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)
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a.shape = TEST_IMAGE_SIZE
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img = Image.fromarray(a)
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assert img.getpixel((0, 0)) == pixel_value
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@pytest.mark.parametrize(
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"mode, dtype",
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(
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("L", numpy.uint8),
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("I", numpy.int32),
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("F", numpy.float32),
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("LA", numpy.uint8),
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("RGB", numpy.uint8),
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("RGBA", numpy.uint8),
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("RGBX", numpy.uint8),
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("CMYK", numpy.uint8),
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("YCbCr", numpy.uint8),
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("I;16", "<u2"),
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("I;16B", ">u2"),
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("I;16L", "<u2"),
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("HSV", numpy.uint8),
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),
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)
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def test_to_array(mode: str, dtype: npt.DTypeLike) -> None:
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img = hopper(mode)
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# Resize to non-square
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img = img.crop((3, 0, 124, 127))
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assert img.size == (121, 127)
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np_img = numpy.array(img)
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_test_img_equals_nparray(img, np_img)
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assert np_img.dtype == dtype
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def test_point_lut() -> None:
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# See https://github.com/python-pillow/Pillow/issues/439
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data = list(range(256)) * 3
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lut = numpy.array(data, dtype=numpy.uint8)
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im = hopper()
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im.point(lut)
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def test_putdata() -> None:
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# Shouldn't segfault
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# See https://github.com/python-pillow/Pillow/issues/1008
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im = Image.new("F", (150, 100))
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arr = numpy.zeros((15000,), numpy.float32)
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im.putdata(arr)
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assert len(im.getdata()) == len(arr)
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def test_resize() -> None:
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im = hopper()
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size = (64, 64)
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im_resized = im.resize(numpy.array(size))
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assert im_resized.size == size
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@pytest.mark.parametrize(
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"dtype",
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(
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bool,
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numpy.bool_,
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numpy.int8,
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numpy.int16,
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numpy.int32,
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numpy.uint8,
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numpy.uint16,
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numpy.uint32,
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float,
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numpy.float32,
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numpy.float64,
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),
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)
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def test_roundtrip_eye(dtype: npt.DTypeLike) -> None:
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arr = numpy.eye(10, dtype=dtype)
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numpy.testing.assert_array_equal(arr, numpy.array(Image.fromarray(arr)))
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def test_zero_size() -> None:
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# Shouldn't cause floating point exception
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# See https://github.com/python-pillow/Pillow/issues/2259
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im = Image.fromarray(numpy.empty((0, 0), dtype=numpy.uint8))
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assert im.size == (0, 0)
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@skip_unless_feature("libtiff")
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def test_transposed() -> None:
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with Image.open("Tests/images/g4_orientation_5.tif") as im:
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assert im.size == (590, 88)
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a = numpy.array(im)
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assert a.shape == (88, 590)
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def test_bool() -> None:
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# https://github.com/python-pillow/Pillow/issues/2044
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a = numpy.zeros((10, 2), dtype=bool)
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a[0][0] = True
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im2 = Image.fromarray(a)
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assert im2.getdata()[0] == 255
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def test_no_resource_warning_for_numpy_array() -> None:
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# https://github.com/python-pillow/Pillow/issues/835
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# Arrange
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from numpy import array
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test_file = "Tests/images/hopper.png"
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with Image.open(test_file) as im:
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# Act/Assert
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with warnings.catch_warnings():
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warnings.simplefilter("error")
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array(im)
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