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resize test rework
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"""
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"""
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Tests for ImagingCore.stretch functionality.
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Tests for resize functionality.
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"""
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"""
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from itertools import permutations
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from itertools import permutations
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from helper import unittest, PillowTestCase
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from helper import unittest, PillowTestCase, hopper
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from PIL import Image
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from PIL import Image
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im = Image.open("Tests/images/hopper.ppm").copy()
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class TestImagingCoreResize(PillowTestCase):
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def resize(self, im, size, f):
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# Image class independend version of resize.
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im.load()
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return im._new(im.im.resize(size, f))
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class TestImagingStretch(PillowTestCase):
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def test_nearest_mode(self):
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for mode in ["1", "P", "L", "I", "F", "RGB", "RGBA", "CMYK", "YCbCr",
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def stretch(self, im, size, f):
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"I;16"]: # exotic mode
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return im._new(im.im.stretch(size, f))
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im = hopper(mode)
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r = self.resize(im, (15, 12), Image.NEAREST)
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def test_modes(self):
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self.assertRaises(ValueError, im.convert("1").im.stretch,
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(15, 12), Image.ANTIALIAS)
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self.assertRaises(ValueError, im.convert("P").im.stretch,
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(15, 12), Image.ANTIALIAS)
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for mode in ["L", "I", "F", "RGB", "RGBA", "CMYK", "YCbCr"]:
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s = im.convert(mode).im
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r = s.stretch((15, 12), Image.ANTIALIAS)
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self.assertEqual(r.mode, mode)
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self.assertEqual(r.mode, mode)
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self.assertEqual(r.size, (15, 12))
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self.assertEqual(r.size, (15, 12) )
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self.assertEqual(r.bands, s.bands)
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self.assertEqual(r.im.bands, im.im.bands)
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def test_convolution_modes(self):
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self.assertRaises(ValueError, self.resize, hopper("1"),
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(15, 12), Image.BILINEAR)
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self.assertRaises(ValueError, self.resize, hopper("P"),
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(15, 12), Image.BILINEAR)
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self.assertRaises(ValueError, self.resize, hopper("I;16"),
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(15, 12), Image.BILINEAR)
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for mode in ["L", "I", "F", "RGB", "RGBA", "CMYK", "YCbCr"]:
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im = hopper(mode)
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r = self.resize(im, (15, 12), Image.BILINEAR)
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self.assertEqual(r.mode, mode)
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self.assertEqual(r.size, (15, 12) )
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self.assertEqual(r.im.bands, im.im.bands)
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def test_reduce_filters(self):
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def test_reduce_filters(self):
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# There is no Image.NEAREST because im.stretch implementation
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for f in [Image.LINEAR, Image.BILINEAR, Image.BICUBIC, Image.ANTIALIAS]:
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# is not NEAREST for reduction. It should be removed
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r = self.resize(hopper("RGB"), (15, 12), f)
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# or renamed to supersampling.
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for f in [Image.BILINEAR, Image.BICUBIC, Image.ANTIALIAS]:
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r = im.im.stretch((15, 12), f)
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self.assertEqual(r.mode, "RGB")
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self.assertEqual(r.mode, "RGB")
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self.assertEqual(r.size, (15, 12))
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self.assertEqual(r.size, (15, 12))
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def test_enlarge_filters(self):
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def test_enlarge_filters(self):
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for f in [Image.BILINEAR, Image.BICUBIC, Image.ANTIALIAS]:
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for f in [Image.LINEAR, Image.BILINEAR, Image.BICUBIC, Image.ANTIALIAS]:
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r = im.im.stretch((764, 414), f)
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r = self.resize(hopper("RGB"), (212, 195), f)
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self.assertEqual(r.mode, "RGB")
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self.assertEqual(r.mode, "RGB")
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self.assertEqual(r.size, (764, 414))
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self.assertEqual(r.size, (212, 195))
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def test_endianness(self):
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def test_endianness(self):
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# Make an image with one colored pixel, in one channel.
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# Make an image with one colored pixel, in one channel.
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# When stretched, that channel should be the same as a GS image.
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# When resized, that channel should be the same as a GS image.
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# Other channels should be unaffected.
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# Other channels should be unaffected.
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# The R and A channels should not swap, which is indicitive of
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# The R and A channels should not swap, which is indicitive of
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# an endianness issues.
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# an endianness issues.
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@ -57,10 +64,10 @@ class TestImagingStretch(PillowTestCase):
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}
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}
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samples['dirty'].putpixel((1, 1), 128)
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samples['dirty'].putpixel((1, 1), 128)
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for f in [Image.BILINEAR, Image.BICUBIC, Image.ANTIALIAS]:
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for f in [Image.LINEAR, Image.BILINEAR, Image.BICUBIC, Image.ANTIALIAS]:
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# samples resized with current filter
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# samples resized with current filter
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resized = dict(
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references = dict(
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(name, self.stretch(ch, (4, 4), f))
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(name, self.resize(ch, (4, 4), f))
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for name, ch in samples.items()
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for name, ch in samples.items()
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)
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)
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@ -72,12 +79,12 @@ class TestImagingStretch(PillowTestCase):
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for channels in set(permutations(channels_set)):
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for channels in set(permutations(channels_set)):
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# compile image from different channels permutations
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# compile image from different channels permutations
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im = Image.merge(mode, [samples[ch] for ch in channels])
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im = Image.merge(mode, [samples[ch] for ch in channels])
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stretched = self.stretch(im, (4, 4), f)
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resized = self.resize(im, (4, 4), f)
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for i, ch in enumerate(stretched.split()):
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for i, ch in enumerate(resized.split()):
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# check what resized channel in image is the same
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# check what resized channel in image is the same
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# as separately resized channel
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# as separately resized channel
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self.assert_image_equal(ch, resized[channels[i]])
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self.assert_image_equal(ch, references[channels[i]])
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if __name__ == '__main__':
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if __name__ == '__main__':
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