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122 lines
4.6 KiB
Python
122 lines
4.6 KiB
Python
"""
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Tests for resize functionality.
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"""
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from itertools import permutations
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from helper import unittest, PillowTestCase, hopper
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from PIL import Image
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class TestImagingCoreResize(PillowTestCase):
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def resize(self, im, size, f):
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# Image class independent 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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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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"I;16"]: # exotic mode
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im = hopper(mode)
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r = self.resize(im, (15, 12), Image.NEAREST)
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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_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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for f in [Image.NEAREST, Image.BOX, Image.BILINEAR,
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Image.HAMMING, Image.BICUBIC, Image.LANCZOS]:
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r = self.resize(hopper("RGB"), (15, 12), f)
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self.assertEqual(r.mode, "RGB")
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self.assertEqual(r.size, (15, 12))
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def test_enlarge_filters(self):
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for f in [Image.NEAREST, Image.BOX, Image.BILINEAR,
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Image.HAMMING, Image.BICUBIC, Image.LANCZOS]:
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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.size, (212, 195))
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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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# 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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# The R and A channels should not swap, which is indicative of
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# an endianness issues.
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samples = {
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'blank': Image.new('L', (2, 2), 0),
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'filled': Image.new('L', (2, 2), 255),
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'dirty': Image.new('L', (2, 2), 0),
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}
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samples['dirty'].putpixel((1, 1), 128)
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for f in [Image.NEAREST, Image.BOX, Image.BILINEAR,
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Image.HAMMING, Image.BICUBIC, Image.LANCZOS]:
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# samples resized with current filter
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references = {
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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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}
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for mode, channels_set in [
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('RGB', ('blank', 'filled', 'dirty')),
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('RGBA', ('blank', 'blank', 'filled', 'dirty')),
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('LA', ('filled', 'dirty')),
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]:
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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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im = Image.merge(mode, [samples[ch] for ch in channels])
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resized = self.resize(im, (4, 4), f)
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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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# as separately resized channel
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self.assert_image_equal(ch, references[channels[i]])
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def test_enlarge_zero(self):
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for f in [Image.NEAREST, Image.BOX, Image.BILINEAR,
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Image.HAMMING, Image.BICUBIC, Image.LANCZOS]:
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r = self.resize(Image.new('RGB', (0, 0), "white"), (212, 195), f)
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self.assertEqual(r.mode, "RGB")
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self.assertEqual(r.size, (212, 195))
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self.assertEqual(r.getdata()[0], (0, 0, 0))
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def test_unknown_filter(self):
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self.assertRaises(ValueError, self.resize, hopper(), (10, 10), 9)
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class TestImageResize(PillowTestCase):
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def test_resize(self):
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def resize(mode, size):
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out = hopper(mode).resize(size)
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self.assertEqual(out.mode, mode)
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self.assertEqual(out.size, size)
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for mode in "1", "P", "L", "RGB", "I", "F":
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resize(mode, (112, 103))
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resize(mode, (188, 214))
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# Test unknown resampling filter
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im = hopper()
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self.assertRaises(ValueError, im.resize, (10, 10), "unknown")
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if __name__ == '__main__':
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unittest.main()
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