def test_as_greyscale_average():
ones = np.ones([3, 120, 120])
image = Image(ones, copy=True)
image.pixels[0].fill(0.5)
new_image = image.as_greyscale(mode='average')
assert (new_image.shape == image.shape)
assert (new_image.n_channels == 1)
assert_allclose(new_image.pixels[0], ones[0] * 0.83333333)
def test_as_greyscale_average():
ones = np.ones([3, 120, 120])
image = Image(ones, copy=True)
image.pixels[0].fill(0.5)
new_image = image.as_greyscale(mode="average")
assert new_image.shape == image.shape
assert new_image.n_channels == 1
assert_allclose(new_image.pixels[0], ones[0] * 0.83333333)
def test_as_greyscale_luminosity():
ones = np.ones([3, 120, 120])
image = Image(ones, copy=True)
image.pixels[0].fill(0.5)
new_image = image.as_greyscale(mode='luminosity')
assert (new_image.shape == image.shape)
assert (new_image.n_channels == 1)
assert_allclose(new_image.pixels[0], ones[0] * 0.850532)
def test_as_greyscale_luminosity():
ones = np.ones([3, 120, 120])
image = Image(ones, copy=True)
image.pixels[0].fill(0.5)
new_image = image.as_greyscale(mode="luminosity")
assert new_image.shape == image.shape
assert new_image.n_channels == 1
assert_allclose(new_image.pixels[0], ones[0] * 0.850532)
def test_as_greyscale_channels():
image = Image(np.random.randn(3, 120, 120), copy=False)
new_image = image.as_greyscale(mode='channel', channel=0)
assert (new_image.shape == image.shape)
assert (new_image.n_channels == 1)
assert_allclose(new_image.pixels[0], image.pixels[0])
def test_as_greyscale_channels():
image = Image(np.random.randn(3, 120, 120), copy=False)
new_image = image.as_greyscale(mode="channel", channel=0)
assert new_image.shape == image.shape
assert new_image.n_channels == 1
assert_allclose(new_image.pixels[0], image.pixels[0])
