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https://github.com/python-pillow/Pillow.git
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4f185329f4
This adds a new test decorator: skip_unless_feature(). The argument is the same as passed to features.check(). If the feature is not supported, the test will be skipped. This removes several kinds of boilerplate copied and pasted around tests so test feature checking is handled and displayed more consistently. Refs #4193
303 lines
8.5 KiB
Python
303 lines
8.5 KiB
Python
import pytest
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from PIL import Image, ImageOps, features
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from .helper import (
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assert_image_equal,
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assert_image_similar,
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assert_tuple_approx_equal,
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hopper,
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)
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class Deformer:
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def getmesh(self, im):
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x, y = im.size
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return [((0, 0, x, y), (0, 0, x, 0, x, y, y, 0))]
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deformer = Deformer()
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def test_sanity():
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ImageOps.autocontrast(hopper("L"))
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ImageOps.autocontrast(hopper("RGB"))
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ImageOps.autocontrast(hopper("L"), cutoff=10)
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ImageOps.autocontrast(hopper("L"), ignore=[0, 255])
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ImageOps.colorize(hopper("L"), (0, 0, 0), (255, 255, 255))
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ImageOps.colorize(hopper("L"), "black", "white")
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ImageOps.pad(hopper("L"), (128, 128))
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ImageOps.pad(hopper("RGB"), (128, 128))
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ImageOps.crop(hopper("L"), 1)
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ImageOps.crop(hopper("RGB"), 1)
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ImageOps.deform(hopper("L"), deformer)
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ImageOps.deform(hopper("RGB"), deformer)
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ImageOps.equalize(hopper("L"))
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ImageOps.equalize(hopper("RGB"))
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ImageOps.expand(hopper("L"), 1)
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ImageOps.expand(hopper("RGB"), 1)
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ImageOps.expand(hopper("L"), 2, "blue")
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ImageOps.expand(hopper("RGB"), 2, "blue")
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ImageOps.fit(hopper("L"), (128, 128))
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ImageOps.fit(hopper("RGB"), (128, 128))
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ImageOps.flip(hopper("L"))
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ImageOps.flip(hopper("RGB"))
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ImageOps.grayscale(hopper("L"))
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ImageOps.grayscale(hopper("RGB"))
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ImageOps.invert(hopper("L"))
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ImageOps.invert(hopper("RGB"))
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ImageOps.mirror(hopper("L"))
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ImageOps.mirror(hopper("RGB"))
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ImageOps.posterize(hopper("L"), 4)
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ImageOps.posterize(hopper("RGB"), 4)
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ImageOps.solarize(hopper("L"))
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ImageOps.solarize(hopper("RGB"))
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ImageOps.exif_transpose(hopper("L"))
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ImageOps.exif_transpose(hopper("RGB"))
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def test_1pxfit():
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# Division by zero in equalize if image is 1 pixel high
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newimg = ImageOps.fit(hopper("RGB").resize((1, 1)), (35, 35))
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assert newimg.size == (35, 35)
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newimg = ImageOps.fit(hopper("RGB").resize((1, 100)), (35, 35))
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assert newimg.size == (35, 35)
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newimg = ImageOps.fit(hopper("RGB").resize((100, 1)), (35, 35))
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assert newimg.size == (35, 35)
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def test_fit_same_ratio():
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# The ratio for this image is 1000.0 / 755 = 1.3245033112582782
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# If the ratios are not acknowledged to be the same,
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# and Pillow attempts to adjust the width to
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# 1.3245033112582782 * 755 = 1000.0000000000001
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# then centering this greater width causes a negative x offset when cropping
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with Image.new("RGB", (1000, 755)) as im:
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new_im = ImageOps.fit(im, (1000, 755))
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assert new_im.size == (1000, 755)
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def test_pad():
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# Same ratio
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im = hopper()
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new_size = (im.width * 2, im.height * 2)
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new_im = ImageOps.pad(im, new_size)
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assert new_im.size == new_size
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for label, color, new_size in [
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("h", None, (im.width * 4, im.height * 2)),
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("v", "#f00", (im.width * 2, im.height * 4)),
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]:
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for i, centering in enumerate([(0, 0), (0.5, 0.5), (1, 1)]):
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new_im = ImageOps.pad(im, new_size, color=color, centering=centering)
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assert new_im.size == new_size
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with Image.open(
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"Tests/images/imageops_pad_" + label + "_" + str(i) + ".jpg"
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) as target:
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assert_image_similar(new_im, target, 6)
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def test_pil163():
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# Division by zero in equalize if < 255 pixels in image (@PIL163)
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i = hopper("RGB").resize((15, 16))
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ImageOps.equalize(i.convert("L"))
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ImageOps.equalize(i.convert("P"))
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ImageOps.equalize(i.convert("RGB"))
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def test_scale():
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# Test the scaling function
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i = hopper("L").resize((50, 50))
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with pytest.raises(ValueError):
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ImageOps.scale(i, -1)
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newimg = ImageOps.scale(i, 1)
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assert newimg.size == (50, 50)
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newimg = ImageOps.scale(i, 2)
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assert newimg.size == (100, 100)
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newimg = ImageOps.scale(i, 0.5)
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assert newimg.size == (25, 25)
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def test_colorize_2color():
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# Test the colorizing function with 2-color functionality
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# Open test image (256px by 10px, black to white)
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with Image.open("Tests/images/bw_gradient.png") as im:
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im = im.convert("L")
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# Create image with original 2-color functionality
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im_test = ImageOps.colorize(im, "red", "green")
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# Test output image (2-color)
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left = (0, 1)
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middle = (127, 1)
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right = (255, 1)
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assert_tuple_approx_equal(
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im_test.getpixel(left),
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(255, 0, 0),
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threshold=1,
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msg="black test pixel incorrect",
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)
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assert_tuple_approx_equal(
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im_test.getpixel(middle),
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(127, 63, 0),
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threshold=1,
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msg="mid test pixel incorrect",
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)
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assert_tuple_approx_equal(
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im_test.getpixel(right),
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(0, 127, 0),
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threshold=1,
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msg="white test pixel incorrect",
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)
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def test_colorize_2color_offset():
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# Test the colorizing function with 2-color functionality and offset
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# Open test image (256px by 10px, black to white)
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with Image.open("Tests/images/bw_gradient.png") as im:
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im = im.convert("L")
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# Create image with original 2-color functionality with offsets
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im_test = ImageOps.colorize(
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im, black="red", white="green", blackpoint=50, whitepoint=100
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)
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# Test output image (2-color) with offsets
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left = (25, 1)
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middle = (75, 1)
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right = (125, 1)
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assert_tuple_approx_equal(
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im_test.getpixel(left),
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(255, 0, 0),
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threshold=1,
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msg="black test pixel incorrect",
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)
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assert_tuple_approx_equal(
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im_test.getpixel(middle),
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(127, 63, 0),
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threshold=1,
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msg="mid test pixel incorrect",
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)
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assert_tuple_approx_equal(
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im_test.getpixel(right),
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(0, 127, 0),
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threshold=1,
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msg="white test pixel incorrect",
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)
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def test_colorize_3color_offset():
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# Test the colorizing function with 3-color functionality and offset
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# Open test image (256px by 10px, black to white)
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with Image.open("Tests/images/bw_gradient.png") as im:
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im = im.convert("L")
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# Create image with new three color functionality with offsets
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im_test = ImageOps.colorize(
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im,
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black="red",
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white="green",
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mid="blue",
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blackpoint=50,
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whitepoint=200,
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midpoint=100,
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)
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# Test output image (3-color) with offsets
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left = (25, 1)
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left_middle = (75, 1)
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middle = (100, 1)
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right_middle = (150, 1)
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right = (225, 1)
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assert_tuple_approx_equal(
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im_test.getpixel(left),
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(255, 0, 0),
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threshold=1,
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msg="black test pixel incorrect",
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)
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assert_tuple_approx_equal(
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im_test.getpixel(left_middle),
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(127, 0, 127),
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threshold=1,
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msg="low-mid test pixel incorrect",
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)
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assert_tuple_approx_equal(
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im_test.getpixel(middle), (0, 0, 255), threshold=1, msg="mid incorrect"
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)
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assert_tuple_approx_equal(
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im_test.getpixel(right_middle),
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(0, 63, 127),
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threshold=1,
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msg="high-mid test pixel incorrect",
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)
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assert_tuple_approx_equal(
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im_test.getpixel(right),
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(0, 127, 0),
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threshold=1,
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msg="white test pixel incorrect",
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)
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def test_exif_transpose():
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exts = [".jpg"]
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if features.check("webp") and features.check("webp_anim"):
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exts.append(".webp")
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for ext in exts:
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with Image.open("Tests/images/hopper" + ext) as base_im:
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def check(orientation_im):
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for im in [
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orientation_im,
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orientation_im.copy(),
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]: # ImageFile # Image
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if orientation_im is base_im:
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assert "exif" not in im.info
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else:
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original_exif = im.info["exif"]
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transposed_im = ImageOps.exif_transpose(im)
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assert_image_similar(base_im, transposed_im, 17)
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if orientation_im is base_im:
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assert "exif" not in im.info
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else:
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assert transposed_im.info["exif"] != original_exif
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assert 0x0112 not in transposed_im.getexif()
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# Repeat the operation to test that it does not keep transposing
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transposed_im2 = ImageOps.exif_transpose(transposed_im)
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assert_image_equal(transposed_im2, transposed_im)
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check(base_im)
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for i in range(2, 9):
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with Image.open(
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"Tests/images/hopper_orientation_" + str(i) + ext
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) as orientation_im:
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check(orientation_im)
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