""" Tests for resize functionality. """ from itertools import permutations from .helper import PillowTestCase, hopper from PIL import Image class TestImagingCoreResize(PillowTestCase): def resize(self, im, size, f): # Image class independent version of resize. im.load() return im._new(im.im.resize(size, f)) def test_nearest_mode(self): for mode in [ "1", "P", "L", "I", "F", "RGB", "RGBA", "CMYK", "YCbCr", "I;16", ]: # exotic mode im = hopper(mode) r = self.resize(im, (15, 12), Image.NEAREST) self.assertEqual(r.mode, mode) self.assertEqual(r.size, (15, 12)) self.assertEqual(r.im.bands, im.im.bands) def test_convolution_modes(self): self.assertRaises( ValueError, self.resize, hopper("1"), (15, 12), Image.BILINEAR ) self.assertRaises( ValueError, self.resize, hopper("P"), (15, 12), Image.BILINEAR ) self.assertRaises( ValueError, self.resize, hopper("I;16"), (15, 12), Image.BILINEAR ) for mode in ["L", "I", "F", "RGB", "RGBA", "CMYK", "YCbCr"]: im = hopper(mode) r = self.resize(im, (15, 12), Image.BILINEAR) self.assertEqual(r.mode, mode) self.assertEqual(r.size, (15, 12)) self.assertEqual(r.im.bands, im.im.bands) def test_reduce_filters(self): for f in [ Image.NEAREST, Image.BOX, Image.BILINEAR, Image.HAMMING, Image.BICUBIC, Image.LANCZOS, ]: r = self.resize(hopper("RGB"), (15, 12), f) self.assertEqual(r.mode, "RGB") self.assertEqual(r.size, (15, 12)) def test_enlarge_filters(self): for f in [ Image.NEAREST, Image.BOX, Image.BILINEAR, Image.HAMMING, Image.BICUBIC, Image.LANCZOS, ]: r = self.resize(hopper("RGB"), (212, 195), f) self.assertEqual(r.mode, "RGB") self.assertEqual(r.size, (212, 195)) def test_endianness(self): # 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. # The R and A channels should not swap, which is indicative of # an endianness issues. samples = { "blank": Image.new("L", (2, 2), 0), "filled": Image.new("L", (2, 2), 255), "dirty": Image.new("L", (2, 2), 0), } samples["dirty"].putpixel((1, 1), 128) for f in [ Image.NEAREST, Image.BOX, Image.BILINEAR, Image.HAMMING, Image.BICUBIC, Image.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 self.assert_image_equal(ch, references[channels[i]]) def test_enlarge_zero(self): for f in [ Image.NEAREST, Image.BOX, Image.BILINEAR, Image.HAMMING, Image.BICUBIC, Image.LANCZOS, ]: r = self.resize(Image.new("RGB", (0, 0), "white"), (212, 195), f) self.assertEqual(r.mode, "RGB") self.assertEqual(r.size, (212, 195)) self.assertEqual(r.getdata()[0], (0, 0, 0)) def test_unknown_filter(self): self.assertRaises(ValueError, self.resize, hopper(), (10, 10), 9) class TestImageResize(PillowTestCase): def test_resize(self): def resize(mode, size): out = hopper(mode).resize(size) self.assertEqual(out.mode, mode) self.assertEqual(out.size, size) for mode in "1", "P", "L", "RGB", "I", "F": resize(mode, (112, 103)) resize(mode, (188, 214)) # Test unknown resampling filter im = hopper() self.assertRaises(ValueError, im.resize, (10, 10), "unknown")