Pillow/Tests/test_image_reduce.py

from PIL import Image, ImageMath, ImageMode

from .helper import PillowTestCase, convert_to_comparable


class TestImageReduce(PillowTestCase):
    # There are several internal implementations
    remarkable_factors = [
        # special implementations
        1,
        2,
        3,
        4,
        5,
        6,
        # 1xN implementation
        (1, 2),
        (1, 3),
        (1, 4),
        (1, 7),
        # Nx1 implementation
        (2, 1),
        (3, 1),
        (4, 1),
        (7, 1),
        # general implementation with different paths
        (4, 6),
        (5, 6),
        (4, 7),
        (5, 7),
        (19, 17),
    ]

    @classmethod
    def setUpClass(cls):
        cls.gradients_image = Image.open("Tests/images/radial_gradients.png")
        cls.gradients_image.load()

    def test_args_factor(self):
        im = Image.new("L", (10, 10))

        self.assertEqual((4, 4), im.reduce(3).size)
        self.assertEqual((4, 10), im.reduce((3, 1)).size)
        self.assertEqual((10, 4), im.reduce((1, 3)).size)

        with self.assertRaises(ValueError):
            im.reduce(0)
        with self.assertRaises(TypeError):
            im.reduce(2.0)
        with self.assertRaises(ValueError):
            im.reduce((0, 10))

    def test_args_box(self):
        im = Image.new("L", (10, 10))

        self.assertEqual((5, 5), im.reduce(2, (0, 0, 10, 10)).size)
        self.assertEqual((1, 1), im.reduce(2, (5, 5, 6, 6)).size)

        with self.assertRaises(TypeError):
            im.reduce(2, "stri")
        with self.assertRaises(TypeError):
            im.reduce(2, 2)
        with self.assertRaises(ValueError):
            im.reduce(2, (0, 0, 11, 10))
        with self.assertRaises(ValueError):
            im.reduce(2, (0, 0, 10, 11))
        with self.assertRaises(ValueError):
            im.reduce(2, (-1, 0, 10, 10))
        with self.assertRaises(ValueError):
            im.reduce(2, (0, -1, 10, 10))
        with self.assertRaises(ValueError):
            im.reduce(2, (0, 5, 10, 5))
        with self.assertRaises(ValueError):
            im.reduce(2, (5, 0, 5, 10))

    def test_unsupported_modes(self):
        im = Image.new("P", (10, 10))
        with self.assertRaises(ValueError):
            im.reduce(3)

        im = Image.new("1", (10, 10))
        with self.assertRaises(ValueError):
            im.reduce(3)

        im = Image.new("I;16", (10, 10))
        with self.assertRaises(ValueError):
            im.reduce(3)

    def get_image(self, mode):
        mode_info = ImageMode.getmode(mode)
        if mode_info.basetype == "L":
            bands = [self.gradients_image]
            for _ in mode_info.bands[1:]:
                # rotate previous image
                band = bands[-1].transpose(Image.ROTATE_90)
                bands.append(band)
            # Correct alpha channel by transforming completely transparent pixels.
            # Low alpha values also emphasize error after alpha multiplication.
            if mode.endswith("A"):
                bands[-1] = bands[-1].point(lambda x: int(85 + x / 1.5))
            im = Image.merge(mode, bands)
        else:
            assert len(mode_info.bands) == 1
            im = self.gradients_image.convert(mode)
        # change the height to make a not-square image
        return im.crop((0, 0, im.width, im.height - 5))

    def compare_reduce_with_box(self, im, factor):
        box = (11, 13, 146, 164)
        reduced = im.reduce(factor, box=box)
        reference = im.crop(box).reduce(factor)
        self.assertEqual(reduced, reference)

    def compare_reduce_with_reference(self, im, factor, average_diff=0.4, max_diff=1):
        """Image.reduce() should look very similar to Image.resize(BOX).

        A reference image is compiled from a large source area
        and possible last column and last row.
        +-----------+
        |..........c|
        |..........c|
        |..........c|
        |rrrrrrrrrrp|
        +-----------+
        """
        reduced = im.reduce(factor)

        if not isinstance(factor, (list, tuple)):
            factor = (factor, factor)

        reference = Image.new(im.mode, reduced.size)
        area_size = (im.size[0] // factor[0], im.size[1] // factor[1])
        area_box = (0, 0, area_size[0] * factor[0], area_size[1] * factor[1])
        area = im.resize(area_size, Image.BOX, area_box)
        reference.paste(area, (0, 0))

        if area_size[0] < reduced.size[0]:
            self.assertEqual(reduced.size[0] - area_size[0], 1)
            last_column_box = (area_box[2], 0, im.size[0], area_box[3])
            last_column = im.resize((1, area_size[1]), Image.BOX, last_column_box)
            reference.paste(last_column, (area_size[0], 0))

        if area_size[1] < reduced.size[1]:
            self.assertEqual(reduced.size[1] - area_size[1], 1)
            last_row_box = (0, area_box[3], area_box[2], im.size[1])
            last_row = im.resize((area_size[0], 1), Image.BOX, last_row_box)
            reference.paste(last_row, (0, area_size[1]))

        if area_size[0] < reduced.size[0] and area_size[1] < reduced.size[1]:
            last_pixel_box = (area_box[2], area_box[3], im.size[0], im.size[1])
            last_pixel = im.resize((1, 1), Image.BOX, last_pixel_box)
            reference.paste(last_pixel, area_size)

        self.assert_compare_images(reduced, reference, average_diff, max_diff)

    def assert_compare_images(self, a, b, max_average_diff, max_diff=255):
        self.assertEqual(a.mode, b.mode, "got mode %r, expected %r" % (a.mode, b.mode))
        self.assertEqual(a.size, b.size, "got size %r, expected %r" % (a.size, b.size))

        a, b = convert_to_comparable(a, b)

        bands = ImageMode.getmode(a.mode).bands
        for band, ach, bch in zip(bands, a.split(), b.split()):
            ch_diff = ImageMath.eval("convert(abs(a - b), 'L')", a=ach, b=bch)
            ch_hist = ch_diff.histogram()

            average_diff = sum(i * num for i, num in enumerate(ch_hist)) / float(
                a.size[0] * a.size[1]
            )
            self.assertGreaterEqual(
                max_average_diff,
                average_diff,
                (
                    "average pixel value difference {:.4f} > expected {:.4f} "
                    "for '{}' band"
                ).format(average_diff, max_average_diff, band),
            )

            last_diff = [i for i, num in enumerate(ch_hist) if num > 0][-1]
            self.assertGreaterEqual(
                max_diff,
                last_diff,
                "max pixel value difference {} > expected {} for '{}' band".format(
                    last_diff, max_diff, band
                ),
            )

    def test_mode_L(self):
        im = self.get_image("L")
        for factor in self.remarkable_factors:
            self.compare_reduce_with_reference(im, factor)
            self.compare_reduce_with_box(im, factor)

    def test_mode_LA(self):
        im = self.get_image("LA")
        for factor in self.remarkable_factors:
            self.compare_reduce_with_reference(im, factor, 0.8, 5)

        # With opaque alpha, an error should be way smaller.
        im.putalpha(Image.new("L", im.size, 255))
        for factor in self.remarkable_factors:
            self.compare_reduce_with_reference(im, factor)
            self.compare_reduce_with_box(im, factor)

    def test_mode_La(self):
        im = self.get_image("La")
        for factor in self.remarkable_factors:
            self.compare_reduce_with_reference(im, factor)
            self.compare_reduce_with_box(im, factor)

    def test_mode_RGB(self):
        im = self.get_image("RGB")
        for factor in self.remarkable_factors:
            self.compare_reduce_with_reference(im, factor)
            self.compare_reduce_with_box(im, factor)

    def test_mode_RGBA(self):
        im = self.get_image("RGBA")
        for factor in self.remarkable_factors:
            self.compare_reduce_with_reference(im, factor, 0.8, 5)

        # With opaque alpha, an error should be way smaller.
        im.putalpha(Image.new("L", im.size, 255))
        for factor in self.remarkable_factors:
            self.compare_reduce_with_reference(im, factor)
            self.compare_reduce_with_box(im, factor)

    def test_mode_RGBa(self):
        im = self.get_image("RGBa")
        for factor in self.remarkable_factors:
            self.compare_reduce_with_reference(im, factor)
            self.compare_reduce_with_box(im, factor)

    def test_mode_I(self):
        im = self.get_image("I")
        for factor in self.remarkable_factors:
            self.compare_reduce_with_reference(im, factor)
            self.compare_reduce_with_box(im, factor)

    def test_mode_F(self):
        im = self.get_image("F")
        for factor in self.remarkable_factors:
            self.compare_reduce_with_reference(im, factor, 0, 0)
            self.compare_reduce_with_box(im, factor)