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365 lines
11 KiB
Python
365 lines
11 KiB
Python
import pytest
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from PIL import Image, ImageDraw, ImageOps, ImageStat, 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"), cutoff=(2, 10))
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ImageOps.autocontrast(hopper("L"), ignore=[0, 255])
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ImageOps.autocontrast(hopper("L"), mask=hopper("L"))
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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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def test_autocontrast_cutoff():
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# Test the cutoff argument of autocontrast
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with Image.open("Tests/images/bw_gradient.png") as img:
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def autocontrast(cutoff):
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return ImageOps.autocontrast(img, cutoff).histogram()
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assert autocontrast(10) == autocontrast((10, 10))
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assert autocontrast(10) != autocontrast((1, 10))
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def test_autocontrast_mask_toy_input():
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# Test the mask argument of autocontrast
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with Image.open("Tests/images/bw_gradient.png") as img:
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rect_mask = Image.new("L", img.size, 0)
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draw = ImageDraw.Draw(rect_mask)
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x0 = img.size[0] // 4
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y0 = img.size[1] // 4
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x1 = 3 * img.size[0] // 4
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y1 = 3 * img.size[1] // 4
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draw.rectangle((x0, y0, x1, y1), fill=255)
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result = ImageOps.autocontrast(img, mask=rect_mask)
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result_nomask = ImageOps.autocontrast(img)
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assert result != result_nomask
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assert ImageStat.Stat(result, mask=rect_mask).median == [127]
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assert ImageStat.Stat(result_nomask).median == [128]
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def test_auto_contrast_mask_real_input():
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# Test the autocontrast with a rectangular mask
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with Image.open("Tests/images/iptc.jpg") as img:
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rect_mask = Image.new("L", img.size, 0)
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draw = ImageDraw.Draw(rect_mask)
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x0, y0 = img.size[0] // 2, img.size[1] // 2
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x1, y1 = img.size[0] - 40, img.size[1]
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draw.rectangle((x0, y0, x1, y1), fill=255)
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result = ImageOps.autocontrast(img, mask=rect_mask)
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result_nomask = ImageOps.autocontrast(img)
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assert result_nomask != result
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assert_tuple_approx_equal(
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ImageStat.Stat(result, mask=rect_mask).median,
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[195, 202, 184],
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threshold=2,
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msg="autocontrast with mask pixel incorrect",
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)
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assert_tuple_approx_equal(
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ImageStat.Stat(result_nomask).median,
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[119, 106, 79],
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threshold=2,
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msg="autocontrast without mask pixel incorrect",
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)
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