diff --git a/Tests/test_image_resample.py b/Tests/test_image_resample.py index 883bb9b19..5ce98a235 100644 --- a/Tests/test_image_resample.py +++ b/Tests/test_image_resample.py @@ -514,13 +514,15 @@ class TestCoreResampleBox: assert_image_similar(reference, without_box, 5) @pytest.mark.parametrize("mode", ("RGB", "L", "RGBA", "LA", "I", "")) - def test_formats(self, mode): - for resample in [Image.Resampling.NEAREST, Image.Resampling.BILINEAR]: - im = hopper(mode) - box = (20, 20, im.size[0] - 20, im.size[1] - 20) - with_box = im.resize((32, 32), resample, box) - cropped = im.crop(box).resize((32, 32), resample) - assert_image_similar(cropped, with_box, 0.4) + @pytest.mark.parametrize( + "resample", (Image.Resampling.NEAREST, Image.Resampling.BILINEAR) + ) + def test_formats(self, mode, resample): + im = hopper(mode) + box = (20, 20, im.size[0] - 20, im.size[1] - 20) + with_box = im.resize((32, 32), resample, box) + cropped = im.crop(box).resize((32, 32), resample) + assert_image_similar(cropped, with_box, 0.4) def test_passthrough(self): # When no resize is required diff --git a/Tests/test_image_resize.py b/Tests/test_image_resize.py index ae12202e4..83c54cf62 100644 --- a/Tests/test_image_resize.py +++ b/Tests/test_image_resize.py @@ -46,33 +46,58 @@ class TestImagingCoreResize: assert r.size == (15, 12) assert r.im.bands == im.im.bands - def test_reduce_filters(self): - for f in [ + @pytest.mark.parametrize( + "resample", + ( Image.Resampling.NEAREST, Image.Resampling.BOX, Image.Resampling.BILINEAR, Image.Resampling.HAMMING, Image.Resampling.BICUBIC, Image.Resampling.LANCZOS, - ]: - r = self.resize(hopper("RGB"), (15, 12), f) - assert r.mode == "RGB" - assert r.size == (15, 12) + ), + ) + def test_reduce_filters(self, resample): + r = self.resize(hopper("RGB"), (15, 12), resample) + assert r.mode == "RGB" + assert r.size == (15, 12) - def test_enlarge_filters(self): - for f in [ + @pytest.mark.parametrize( + "resample", + ( Image.Resampling.NEAREST, Image.Resampling.BOX, Image.Resampling.BILINEAR, Image.Resampling.HAMMING, Image.Resampling.BICUBIC, Image.Resampling.LANCZOS, - ]: - r = self.resize(hopper("RGB"), (212, 195), f) - assert r.mode == "RGB" - assert r.size == (212, 195) + ), + ) + def test_enlarge_filters(self, resample): + r = self.resize(hopper("RGB"), (212, 195), resample) + assert r.mode == "RGB" + assert r.size == (212, 195) - def test_endianness(self): + @pytest.mark.parametrize( + "resample", + ( + Image.Resampling.NEAREST, + Image.Resampling.BOX, + Image.Resampling.BILINEAR, + Image.Resampling.HAMMING, + Image.Resampling.BICUBIC, + Image.Resampling.LANCZOS, + ), + ) + @pytest.mark.parametrize( + "mode, channels_set", + ( + ("RGB", ("blank", "filled", "dirty")), + ("RGBA", ("blank", "blank", "filled", "dirty")), + ("LA", ("filled", "dirty")), + ), + ) + def test_endianness(self, resample, mode, channels_set): # Make an image with one colored pixel, in one channel. # When resized, that channel should be the same as a GS image. # Other channels should be unaffected. @@ -86,47 +111,37 @@ class TestImagingCoreResize: } samples["dirty"].putpixel((1, 1), 128) - for f in [ + # samples resized with current filter + references = { + name: self.resize(ch, (4, 4), resample) for name, ch in samples.items() + } + + for channels in set(permutations(channels_set)): + # compile image from different channels permutations + im = Image.merge(mode, [samples[ch] for ch in channels]) + resized = self.resize(im, (4, 4), resample) + + for i, ch in enumerate(resized.split()): + # check what resized channel in image is the same + # as separately resized channel + assert_image_equal(ch, references[channels[i]]) + + @pytest.mark.parametrize( + "resample", + ( Image.Resampling.NEAREST, Image.Resampling.BOX, Image.Resampling.BILINEAR, Image.Resampling.HAMMING, Image.Resampling.BICUBIC, Image.Resampling.LANCZOS, - ]: - # samples resized with current filter - references = { - name: self.resize(ch, (4, 4), f) for name, ch in samples.items() - } - - for mode, channels_set in [ - ("RGB", ("blank", "filled", "dirty")), - ("RGBA", ("blank", "blank", "filled", "dirty")), - ("LA", ("filled", "dirty")), - ]: - for channels in set(permutations(channels_set)): - # compile image from different channels permutations - im = Image.merge(mode, [samples[ch] for ch in channels]) - resized = self.resize(im, (4, 4), f) - - for i, ch in enumerate(resized.split()): - # check what resized channel in image is the same - # as separately resized channel - assert_image_equal(ch, references[channels[i]]) - - def test_enlarge_zero(self): - for f in [ - Image.Resampling.NEAREST, - Image.Resampling.BOX, - Image.Resampling.BILINEAR, - Image.Resampling.HAMMING, - Image.Resampling.BICUBIC, - Image.Resampling.LANCZOS, - ]: - r = self.resize(Image.new("RGB", (0, 0), "white"), (212, 195), f) - assert r.mode == "RGB" - assert r.size == (212, 195) - assert r.getdata()[0] == (0, 0, 0) + ), + ) + def test_enlarge_zero(self, resample): + r = self.resize(Image.new("RGB", (0, 0), "white"), (212, 195), resample) + assert r.mode == "RGB" + assert r.size == (212, 195) + assert r.getdata()[0] == (0, 0, 0) def test_unknown_filter(self): with pytest.raises(ValueError): @@ -170,74 +185,71 @@ class TestReducingGapResize: (52, 34), Image.Resampling.BICUBIC, reducing_gap=0.99 ) - def test_reducing_gap_1(self, gradients_image): - for box, epsilon in [ - (None, 4), - ((1.1, 2.2, 510.8, 510.9), 4), - ((3, 10, 410, 256), 10), - ]: - ref = gradients_image.resize((52, 34), Image.Resampling.BICUBIC, box=box) - im = gradients_image.resize( - (52, 34), Image.Resampling.BICUBIC, box=box, reducing_gap=1.0 - ) - - with pytest.raises(AssertionError): - assert_image_equal(ref, im) - - assert_image_similar(ref, im, epsilon) - - def test_reducing_gap_2(self, gradients_image): - for box, epsilon in [ - (None, 1.5), - ((1.1, 2.2, 510.8, 510.9), 1.5), - ((3, 10, 410, 256), 1), - ]: - ref = gradients_image.resize((52, 34), Image.Resampling.BICUBIC, box=box) - im = gradients_image.resize( - (52, 34), Image.Resampling.BICUBIC, box=box, reducing_gap=2.0 - ) - - with pytest.raises(AssertionError): - assert_image_equal(ref, im) - - assert_image_similar(ref, im, epsilon) - - def test_reducing_gap_3(self, gradients_image): - for box, epsilon in [ - (None, 1), - ((1.1, 2.2, 510.8, 510.9), 1), - ((3, 10, 410, 256), 0.5), - ]: - ref = gradients_image.resize((52, 34), Image.Resampling.BICUBIC, box=box) - im = gradients_image.resize( - (52, 34), Image.Resampling.BICUBIC, box=box, reducing_gap=3.0 - ) - - with pytest.raises(AssertionError): - assert_image_equal(ref, im) - - assert_image_similar(ref, im, epsilon) - - def test_reducing_gap_8(self, gradients_image): - for box in [None, (1.1, 2.2, 510.8, 510.9), (3, 10, 410, 256)]: - ref = gradients_image.resize((52, 34), Image.Resampling.BICUBIC, box=box) - im = gradients_image.resize( - (52, 34), Image.Resampling.BICUBIC, box=box, reducing_gap=8.0 - ) + @pytest.mark.parametrize( + "box, epsilon", + ((None, 4), ((1.1, 2.2, 510.8, 510.9), 4), ((3, 10, 410, 256), 10)), + ) + def test_reducing_gap_1(self, gradients_image, box, epsilon): + ref = gradients_image.resize((52, 34), Image.Resampling.BICUBIC, box=box) + im = gradients_image.resize( + (52, 34), Image.Resampling.BICUBIC, box=box, reducing_gap=1.0 + ) + with pytest.raises(AssertionError): assert_image_equal(ref, im) - def test_box_filter(self, gradients_image): - for box, epsilon in [ - ((0, 0, 512, 512), 5.5), - ((0.9, 1.7, 128, 128), 9.5), - ]: - ref = gradients_image.resize((52, 34), Image.Resampling.BOX, box=box) - im = gradients_image.resize( - (52, 34), Image.Resampling.BOX, box=box, reducing_gap=1.0 - ) + assert_image_similar(ref, im, epsilon) - assert_image_similar(ref, im, epsilon) + @pytest.mark.parametrize( + "box, epsilon", + ((None, 1.5), ((1.1, 2.2, 510.8, 510.9), 1.5), ((3, 10, 410, 256), 1)), + ) + def test_reducing_gap_2(self, gradients_image, box, epsilon): + ref = gradients_image.resize((52, 34), Image.Resampling.BICUBIC, box=box) + im = gradients_image.resize( + (52, 34), Image.Resampling.BICUBIC, box=box, reducing_gap=2.0 + ) + + with pytest.raises(AssertionError): + assert_image_equal(ref, im) + + assert_image_similar(ref, im, epsilon) + + @pytest.mark.parametrize( + "box, epsilon", + ((None, 1), ((1.1, 2.2, 510.8, 510.9), 1), ((3, 10, 410, 256), 0.5)), + ) + def test_reducing_gap_3(self, gradients_image, box, epsilon): + ref = gradients_image.resize((52, 34), Image.Resampling.BICUBIC, box=box) + im = gradients_image.resize( + (52, 34), Image.Resampling.BICUBIC, box=box, reducing_gap=3.0 + ) + + with pytest.raises(AssertionError): + assert_image_equal(ref, im) + + assert_image_similar(ref, im, epsilon) + + @pytest.mark.parametrize("box", (None, (1.1, 2.2, 510.8, 510.9), (3, 10, 410, 256))) + def test_reducing_gap_8(self, gradients_image, box): + ref = gradients_image.resize((52, 34), Image.Resampling.BICUBIC, box=box) + im = gradients_image.resize( + (52, 34), Image.Resampling.BICUBIC, box=box, reducing_gap=8.0 + ) + + assert_image_equal(ref, im) + + @pytest.mark.parametrize( + "box, epsilon", + (((0, 0, 512, 512), 5.5), ((0.9, 1.7, 128, 128), 9.5)), + ) + def test_box_filter(self, gradients_image, box, epsilon): + ref = gradients_image.resize((52, 34), Image.Resampling.BOX, box=box) + im = gradients_image.resize( + (52, 34), Image.Resampling.BOX, box=box, reducing_gap=1.0 + ) + + assert_image_similar(ref, im, epsilon) class TestImageResize: @@ -264,15 +276,14 @@ class TestImageResize: im = im.resize((64, 64)) assert im.size == (64, 64) - def test_default_filter(self): - for mode in "L", "RGB", "I", "F": - im = hopper(mode) - assert im.resize((20, 20), Image.Resampling.BICUBIC) == im.resize((20, 20)) + @pytest.mark.parametrize("mode", ("L", "RGB", "I", "F")) + def test_default_filter_bicubic(self, mode): + im = hopper(mode) + assert im.resize((20, 20), Image.Resampling.BICUBIC) == im.resize((20, 20)) - for mode in "1", "P": - im = hopper(mode) - assert im.resize((20, 20), Image.Resampling.NEAREST) == im.resize((20, 20)) - - for mode in "I;16", "I;16L", "I;16B", "BGR;15", "BGR;16": - im = hopper(mode) - assert im.resize((20, 20), Image.Resampling.NEAREST) == im.resize((20, 20)) + @pytest.mark.parametrize( + "mode", ("1", "P", "I;16", "I;16L", "I;16B", "BGR;15", "BGR;16") + ) + def test_default_filter_nearest(self, mode): + im = hopper(mode) + assert im.resize((20, 20), Image.Resampling.NEAREST) == im.resize((20, 20))