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