mirror of
https://github.com/python-pillow/Pillow.git
synced 2024-09-21 19:38:57 +03:00
545 lines
21 KiB
Python
545 lines
21 KiB
Python
from __future__ import division, print_function
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from contextlib import contextmanager
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from helper import unittest, PillowTestCase, hopper
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from PIL import Image, ImageDraw
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class TestImagingResampleVulnerability(PillowTestCase):
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# see https://github.com/python-pillow/Pillow/issues/1710
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def test_overflow(self):
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im = hopper('L')
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xsize = 0x100000008 // 4
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ysize = 1000 # unimportant
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with self.assertRaises(MemoryError):
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# any resampling filter will do here
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im.im.resize((xsize, ysize), Image.BILINEAR)
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def test_invalid_size(self):
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im = hopper()
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# Should not crash
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im.resize((100, 100))
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with self.assertRaises(ValueError):
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im.resize((-100, 100))
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with self.assertRaises(ValueError):
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im.resize((100, -100))
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def test_modify_after_resizing(self):
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im = hopper('RGB')
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# get copy with same size
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copy = im.resize(im.size)
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# some in-place operation
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copy.paste('black', (0, 0, im.width // 2, im.height // 2))
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# image should be different
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self.assertNotEqual(im.tobytes(), copy.tobytes())
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class TestImagingCoreResampleAccuracy(PillowTestCase):
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def make_case(self, mode, size, color):
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"""Makes a sample image with two dark and two bright squares.
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For example:
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e0 e0 1f 1f
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e0 e0 1f 1f
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1f 1f e0 e0
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1f 1f e0 e0
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"""
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case = Image.new('L', size, 255 - color)
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rectangle = ImageDraw.Draw(case).rectangle
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rectangle((0, 0, size[0] // 2 - 1, size[1] // 2 - 1), color)
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rectangle((size[0] // 2, size[1] // 2, size[0], size[1]), color)
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return Image.merge(mode, [case] * len(mode))
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def make_sample(self, data, size):
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"""Restores a sample image from given data string which contains
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hex-encoded pixels from the top left fourth of a sample.
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"""
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data = data.replace(' ', '')
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sample = Image.new('L', size)
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s_px = sample.load()
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w, h = size[0] // 2, size[1] // 2
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for y in range(h):
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for x in range(w):
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val = int(data[(y * w + x) * 2:(y * w + x + 1) * 2], 16)
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s_px[x, y] = val
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s_px[size[0] - x - 1, size[1] - y - 1] = val
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s_px[x, size[1] - y - 1] = 255 - val
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s_px[size[0] - x - 1, y] = 255 - val
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return sample
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def check_case(self, case, sample):
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s_px = sample.load()
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c_px = case.load()
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for y in range(case.size[1]):
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for x in range(case.size[0]):
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if c_px[x, y] != s_px[x, y]:
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message = '\nHave: \n{}\n\nExpected: \n{}'.format(
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self.serialize_image(case),
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self.serialize_image(sample),
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)
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self.assertEqual(s_px[x, y], c_px[x, y], message)
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def serialize_image(self, image):
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s_px = image.load()
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return '\n'.join(
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' '.join(
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'{:02x}'.format(s_px[x, y])
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for x in range(image.size[0])
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)
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for y in range(image.size[1])
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)
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def test_reduce_box(self):
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for mode in ['RGBX', 'RGB', 'La', 'L']:
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case = self.make_case(mode, (8, 8), 0xe1)
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case = case.resize((4, 4), Image.BOX)
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data = ('e1 e1'
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'e1 e1')
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for channel in case.split():
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self.check_case(channel, self.make_sample(data, (4, 4)))
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def test_reduce_bilinear(self):
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for mode in ['RGBX', 'RGB', 'La', 'L']:
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case = self.make_case(mode, (8, 8), 0xe1)
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case = case.resize((4, 4), Image.BILINEAR)
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data = ('e1 c9'
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'c9 b7')
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for channel in case.split():
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self.check_case(channel, self.make_sample(data, (4, 4)))
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def test_reduce_hamming(self):
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for mode in ['RGBX', 'RGB', 'La', 'L']:
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case = self.make_case(mode, (8, 8), 0xe1)
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case = case.resize((4, 4), Image.HAMMING)
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data = ('e1 da'
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'da d3')
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for channel in case.split():
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self.check_case(channel, self.make_sample(data, (4, 4)))
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def test_reduce_bicubic(self):
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for mode in ['RGBX', 'RGB', 'La', 'L']:
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case = self.make_case(mode, (12, 12), 0xe1)
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case = case.resize((6, 6), Image.BICUBIC)
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data = ('e1 e3 d4'
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'e3 e5 d6'
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'd4 d6 c9')
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for channel in case.split():
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self.check_case(channel, self.make_sample(data, (6, 6)))
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def test_reduce_lanczos(self):
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for mode in ['RGBX', 'RGB', 'La', 'L']:
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case = self.make_case(mode, (16, 16), 0xe1)
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case = case.resize((8, 8), Image.LANCZOS)
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data = ('e1 e0 e4 d7'
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'e0 df e3 d6'
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'e4 e3 e7 da'
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'd7 d6 d9 ce')
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for channel in case.split():
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self.check_case(channel, self.make_sample(data, (8, 8)))
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def test_enlarge_box(self):
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for mode in ['RGBX', 'RGB', 'La', 'L']:
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case = self.make_case(mode, (2, 2), 0xe1)
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case = case.resize((4, 4), Image.BOX)
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data = ('e1 e1'
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'e1 e1')
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for channel in case.split():
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self.check_case(channel, self.make_sample(data, (4, 4)))
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def test_enlarge_bilinear(self):
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for mode in ['RGBX', 'RGB', 'La', 'L']:
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case = self.make_case(mode, (2, 2), 0xe1)
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case = case.resize((4, 4), Image.BILINEAR)
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data = ('e1 b0'
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'b0 98')
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for channel in case.split():
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self.check_case(channel, self.make_sample(data, (4, 4)))
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def test_enlarge_hamming(self):
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for mode in ['RGBX', 'RGB', 'La', 'L']:
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case = self.make_case(mode, (2, 2), 0xe1)
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case = case.resize((4, 4), Image.HAMMING)
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data = ('e1 d2'
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'd2 c5')
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for channel in case.split():
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self.check_case(channel, self.make_sample(data, (4, 4)))
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def test_enlarge_bicubic(self):
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for mode in ['RGBX', 'RGB', 'La', 'L']:
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case = self.make_case(mode, (4, 4), 0xe1)
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case = case.resize((8, 8), Image.BICUBIC)
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data = ('e1 e5 ee b9'
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'e5 e9 f3 bc'
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'ee f3 fd c1'
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'b9 bc c1 a2')
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for channel in case.split():
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self.check_case(channel, self.make_sample(data, (8, 8)))
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def test_enlarge_lanczos(self):
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for mode in ['RGBX', 'RGB', 'La', 'L']:
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case = self.make_case(mode, (6, 6), 0xe1)
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case = case.resize((12, 12), Image.LANCZOS)
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data = ('e1 e0 db ed f5 b8'
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'e0 df da ec f3 b7'
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'db db d6 e7 ee b5'
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'ed ec e6 fb ff bf'
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'f5 f4 ee ff ff c4'
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'b8 b7 b4 bf c4 a0')
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for channel in case.split():
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self.check_case(channel, self.make_sample(data, (12, 12)))
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class CoreResampleConsistencyTest(PillowTestCase):
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def make_case(self, mode, fill):
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im = Image.new(mode, (512, 9), fill)
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return (im.resize((9, 512), Image.LANCZOS), im.load()[0, 0])
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def run_case(self, case):
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channel, color = case
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px = channel.load()
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for x in range(channel.size[0]):
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for y in range(channel.size[1]):
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if px[x, y] != color:
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message = "{} != {} for pixel {}".format(
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px[x, y], color, (x, y))
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self.assertEqual(px[x, y], color, message)
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def test_8u(self):
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im, color = self.make_case('RGB', (0, 64, 255))
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r, g, b = im.split()
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self.run_case((r, color[0]))
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self.run_case((g, color[1]))
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self.run_case((b, color[2]))
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self.run_case(self.make_case('L', 12))
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def test_32i(self):
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self.run_case(self.make_case('I', 12))
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self.run_case(self.make_case('I', 0x7fffffff))
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self.run_case(self.make_case('I', -12))
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self.run_case(self.make_case('I', -1 << 31))
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def test_32f(self):
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self.run_case(self.make_case('F', 1))
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self.run_case(self.make_case('F', 3.40282306074e+38))
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self.run_case(self.make_case('F', 1.175494e-38))
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self.run_case(self.make_case('F', 1.192093e-07))
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class CoreResampleAlphaCorrectTest(PillowTestCase):
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def make_levels_case(self, mode):
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i = Image.new(mode, (256, 16))
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px = i.load()
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for y in range(i.size[1]):
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for x in range(i.size[0]):
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pix = [x] * len(mode)
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pix[-1] = 255 - y * 16
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px[x, y] = tuple(pix)
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return i
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def run_levels_case(self, i):
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px = i.load()
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for y in range(i.size[1]):
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used_colors = {px[x, y][0] for x in range(i.size[0])}
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self.assertEqual(256, len(used_colors),
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'All colors should present in resized image. '
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'Only {} on {} line.'.format(len(used_colors), y))
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@unittest.skip("current implementation isn't precise enough")
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def test_levels_rgba(self):
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case = self.make_levels_case('RGBA')
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self.run_levels_case(case.resize((512, 32), Image.BOX))
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self.run_levels_case(case.resize((512, 32), Image.BILINEAR))
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self.run_levels_case(case.resize((512, 32), Image.HAMMING))
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self.run_levels_case(case.resize((512, 32), Image.BICUBIC))
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self.run_levels_case(case.resize((512, 32), Image.LANCZOS))
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@unittest.skip("current implementation isn't precise enough")
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def test_levels_la(self):
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case = self.make_levels_case('LA')
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self.run_levels_case(case.resize((512, 32), Image.BOX))
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self.run_levels_case(case.resize((512, 32), Image.BILINEAR))
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self.run_levels_case(case.resize((512, 32), Image.HAMMING))
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self.run_levels_case(case.resize((512, 32), Image.BICUBIC))
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self.run_levels_case(case.resize((512, 32), Image.LANCZOS))
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def make_dirty_case(self, mode, clean_pixel, dirty_pixel):
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i = Image.new(mode, (64, 64), dirty_pixel)
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px = i.load()
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xdiv4 = i.size[0] // 4
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ydiv4 = i.size[1] // 4
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for y in range(ydiv4 * 2):
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for x in range(xdiv4 * 2):
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px[x + xdiv4, y + ydiv4] = clean_pixel
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return i
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def run_dirty_case(self, i, clean_pixel):
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px = i.load()
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for y in range(i.size[1]):
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for x in range(i.size[0]):
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if px[x, y][-1] != 0 and px[x, y][:-1] != clean_pixel:
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message = 'pixel at ({}, {}) is differ:\n{}\n{}'\
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.format(x, y, px[x, y], clean_pixel)
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self.assertEqual(px[x, y][:3], clean_pixel, message)
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def test_dirty_pixels_rgba(self):
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case = self.make_dirty_case('RGBA', (255, 255, 0, 128), (0, 0, 255, 0))
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self.run_dirty_case(case.resize((20, 20), Image.BOX), (255, 255, 0))
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self.run_dirty_case(case.resize((20, 20), Image.BILINEAR), (255, 255, 0))
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self.run_dirty_case(case.resize((20, 20), Image.HAMMING), (255, 255, 0))
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self.run_dirty_case(case.resize((20, 20), Image.BICUBIC), (255, 255, 0))
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self.run_dirty_case(case.resize((20, 20), Image.LANCZOS), (255, 255, 0))
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def test_dirty_pixels_la(self):
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case = self.make_dirty_case('LA', (255, 128), (0, 0))
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self.run_dirty_case(case.resize((20, 20), Image.BOX), (255,))
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self.run_dirty_case(case.resize((20, 20), Image.BILINEAR), (255,))
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self.run_dirty_case(case.resize((20, 20), Image.HAMMING), (255,))
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self.run_dirty_case(case.resize((20, 20), Image.BICUBIC), (255,))
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self.run_dirty_case(case.resize((20, 20), Image.LANCZOS), (255,))
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class CoreResamplePassesTest(PillowTestCase):
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@contextmanager
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def count(self, diff):
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count = Image.core.get_stats()['new_count']
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yield
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self.assertEqual(Image.core.get_stats()['new_count'] - count, diff)
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def test_horizontal(self):
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im = hopper('L')
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with self.count(1):
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im.resize((im.size[0] - 10, im.size[1]), Image.BILINEAR)
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def test_vertical(self):
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im = hopper('L')
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with self.count(1):
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im.resize((im.size[0], im.size[1] - 10), Image.BILINEAR)
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def test_both(self):
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im = hopper('L')
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with self.count(2):
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im.resize((im.size[0] - 10, im.size[1] - 10), Image.BILINEAR)
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def test_box_horizontal(self):
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im = hopper('L')
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box = (20, 0, im.size[0] - 20, im.size[1])
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with self.count(1):
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# the same size, but different box
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with_box = im.resize(im.size, Image.BILINEAR, box)
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with self.count(2):
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cropped = im.crop(box).resize(im.size, Image.BILINEAR)
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self.assert_image_similar(with_box, cropped, 0.1)
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def test_box_vertical(self):
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im = hopper('L')
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box = (0, 20, im.size[0], im.size[1] - 20)
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with self.count(1):
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# the same size, but different box
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with_box = im.resize(im.size, Image.BILINEAR, box)
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with self.count(2):
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cropped = im.crop(box).resize(im.size, Image.BILINEAR)
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self.assert_image_similar(with_box, cropped, 0.1)
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class CoreResampleCoefficientsTest(PillowTestCase):
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def test_reduce(self):
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test_color = 254
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# print()
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for size in range(400000, 400010, 2):
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# print(size)
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i = Image.new('L', (size, 1), 0)
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draw = ImageDraw.Draw(i)
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draw.rectangle((0, 0, i.size[0] // 2 - 1, 0), test_color)
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px = i.resize((5, i.size[1]), Image.BICUBIC).load()
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if px[2, 0] != test_color // 2:
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self.assertEqual(test_color // 2, px[2, 0])
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# print('>', size, test_color // 2, px[2, 0])
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def test_nonzero_coefficients(self):
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# regression test for the wrong coefficients calculation
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# due to bug https://github.com/python-pillow/Pillow/issues/2161
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im = Image.new('RGBA', (1280, 1280), (0x20, 0x40, 0x60, 0xff))
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histogram = im.resize((256, 256), Image.BICUBIC).histogram()
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self.assertEqual(histogram[0x100 * 0 + 0x20], 0x10000) # first channel
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self.assertEqual(histogram[0x100 * 1 + 0x40], 0x10000) # second channel
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self.assertEqual(histogram[0x100 * 2 + 0x60], 0x10000) # third channel
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self.assertEqual(histogram[0x100 * 3 + 0xff], 0x10000) # fourth channel
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class CoreResampleBoxTest(PillowTestCase):
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def test_wrong_arguments(self):
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im = hopper()
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for resample in (Image.NEAREST, Image.BOX, Image.BILINEAR, Image.HAMMING,
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Image.BICUBIC, Image.LANCZOS):
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im.resize((32, 32), resample, (0, 0, im.width, im.height))
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im.resize((32, 32), resample, (20, 20, im.width, im.height))
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im.resize((32, 32), resample, (20, 20, 20, 100))
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im.resize((32, 32), resample, (20, 20, 100, 20))
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with self.assertRaisesRegex(TypeError, "must be sequence of length 4"):
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im.resize((32, 32), resample, (im.width, im.height))
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with self.assertRaisesRegex(ValueError, "can't be negative"):
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im.resize((32, 32), resample, (-20, 20, 100, 100))
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with self.assertRaisesRegex(ValueError, "can't be negative"):
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im.resize((32, 32), resample, (20, -20, 100, 100))
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with self.assertRaisesRegex(ValueError, "can't be empty"):
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im.resize((32, 32), resample, (20.1, 20, 20, 100))
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with self.assertRaisesRegex(ValueError, "can't be empty"):
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im.resize((32, 32), resample, (20, 20.1, 100, 20))
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with self.assertRaisesRegex(ValueError, "can't be empty"):
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im.resize((32, 32), resample, (20.1, 20.1, 20, 20))
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with self.assertRaisesRegex(ValueError, "can't exceed"):
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im.resize((32, 32), resample, (0, 0, im.width + 1, im.height))
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with self.assertRaisesRegex(ValueError, "can't exceed"):
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im.resize((32, 32), resample, (0, 0, im.width, im.height + 1))
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def resize_tiled(self, im, dst_size, xtiles, ytiles):
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def split_range(size, tiles):
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scale = size / tiles
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for i in range(tiles):
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yield (int(round(scale * i)), int(round(scale * (i + 1))))
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tiled = Image.new(im.mode, dst_size)
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scale = (im.size[0] / tiled.size[0], im.size[1] / tiled.size[1])
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for y0, y1 in split_range(dst_size[1], ytiles):
|
|
for x0, x1 in split_range(dst_size[0], xtiles):
|
|
box = (x0 * scale[0], y0 * scale[1],
|
|
x1 * scale[0], y1 * scale[1])
|
|
tile = im.resize((x1 - x0, y1 - y0), Image.BICUBIC, box)
|
|
tiled.paste(tile, (x0, y0))
|
|
return tiled
|
|
|
|
def test_tiles(self):
|
|
im = Image.open("Tests/images/flower.jpg")
|
|
self.assertEqual(im.size, (480, 360))
|
|
dst_size = (251, 188)
|
|
reference = im.resize(dst_size, Image.BICUBIC)
|
|
|
|
for tiles in [(1, 1), (3, 3), (9, 7), (100, 100)]:
|
|
tiled = self.resize_tiled(im, dst_size, *tiles)
|
|
self.assert_image_similar(reference, tiled, 0.01)
|
|
|
|
def test_subsample(self):
|
|
# This test shows advantages of the subpixel resizing
|
|
# after supersampling (e.g. during JPEG decoding).
|
|
im = Image.open("Tests/images/flower.jpg")
|
|
self.assertEqual(im.size, (480, 360))
|
|
dst_size = (48, 36)
|
|
# Reference is cropped image resized to destination
|
|
reference = im.crop((0, 0, 473, 353)).resize(dst_size, Image.BICUBIC)
|
|
# Image.BOX emulates supersampling (480 / 8 = 60, 360 / 8 = 45)
|
|
supersampled = im.resize((60, 45), Image.BOX)
|
|
|
|
with_box = supersampled.resize(dst_size, Image.BICUBIC,
|
|
(0, 0, 59.125, 44.125))
|
|
without_box = supersampled.resize(dst_size, Image.BICUBIC)
|
|
|
|
# error with box should be much smaller than without
|
|
self.assert_image_similar(reference, with_box, 6)
|
|
with self.assertRaisesRegex(AssertionError, "difference 29\."):
|
|
self.assert_image_similar(reference, without_box, 5)
|
|
|
|
def test_formats(self):
|
|
for resample in [Image.NEAREST, Image.BILINEAR]:
|
|
for mode in ['RGB', 'L', 'RGBA', 'LA', 'I', '']:
|
|
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)
|
|
self.assert_image_similar(cropped, with_box, 0.4)
|
|
|
|
def test_passthrough(self):
|
|
# When no resize is required
|
|
im = hopper()
|
|
|
|
for size, box in [
|
|
((40, 50), (0, 0, 40, 50)),
|
|
((40, 50), (0, 10, 40, 60)),
|
|
((40, 50), (10, 0, 50, 50)),
|
|
((40, 50), (10, 20, 50, 70)),
|
|
]:
|
|
try:
|
|
res = im.resize(size, Image.LANCZOS, box)
|
|
self.assertEqual(res.size, size)
|
|
self.assert_image_equal(res, im.crop(box))
|
|
except AssertionError:
|
|
print('>>>', size, box)
|
|
raise
|
|
|
|
def test_no_passthrough(self):
|
|
# When resize is required
|
|
im = hopper()
|
|
|
|
for size, box in [
|
|
((40, 50), (0.4, 0.4, 40.4, 50.4)),
|
|
((40, 50), (0.4, 10.4, 40.4, 60.4)),
|
|
((40, 50), (10.4, 0.4, 50.4, 50.4)),
|
|
((40, 50), (10.4, 20.4, 50.4, 70.4)),
|
|
]:
|
|
try:
|
|
res = im.resize(size, Image.LANCZOS, box)
|
|
self.assertEqual(res.size, size)
|
|
with self.assertRaisesRegex(AssertionError, "difference \d"):
|
|
# check that the difference at least that much
|
|
self.assert_image_similar(res, im.crop(box), 20)
|
|
except AssertionError:
|
|
print('>>>', size, box)
|
|
raise
|
|
|
|
def test_skip_horizontal(self):
|
|
# Can skip resize for one dimension
|
|
im = hopper()
|
|
|
|
for flt in [Image.NEAREST, Image.BICUBIC]:
|
|
for size, box in [
|
|
((40, 50), (0, 0, 40, 90)),
|
|
((40, 50), (0, 20, 40, 90)),
|
|
((40, 50), (10, 0, 50, 90)),
|
|
((40, 50), (10, 20, 50, 90)),
|
|
]:
|
|
try:
|
|
res = im.resize(size, flt, box)
|
|
self.assertEqual(res.size, size)
|
|
# Borders should be slightly different
|
|
self.assert_image_similar(
|
|
res, im.crop(box).resize(size, flt), 0.4)
|
|
except AssertionError:
|
|
print('>>>', size, box, flt)
|
|
raise
|
|
|
|
def test_skip_vertical(self):
|
|
# Can skip resize for one dimension
|
|
im = hopper()
|
|
|
|
for flt in [Image.NEAREST, Image.BICUBIC]:
|
|
for size, box in [
|
|
((40, 50), (0, 0, 90, 50)),
|
|
((40, 50), (20, 0, 90, 50)),
|
|
((40, 50), (0, 10, 90, 60)),
|
|
((40, 50), (20, 10, 90, 60)),
|
|
]:
|
|
try:
|
|
res = im.resize(size, flt, box)
|
|
self.assertEqual(res.size, size)
|
|
# Borders should be slightly different
|
|
self.assert_image_similar(
|
|
res, im.crop(box).resize(size, flt), 0.4)
|
|
except AssertionError:
|
|
print('>>>', size, box, flt)
|
|
raise
|
|
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main()
|