def test_as_greyscale_average(): ones = np.ones([3, 120, 120]) image = MaskedImage(ones) image.pixels[0] *= 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 = MaskedImage(ones) image.pixels[0] *= 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 = MaskedImage(np.random.randn(120, 120, 3)) 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_no_index(): image = MaskedImage(np.ones([120, 120, 3])) new_image = image.as_greyscale(mode='channel') assert (new_image.shape == image.shape) assert (new_image.n_channels == 1)
def test_as_greyscale_average(): image = MaskedImage(np.ones([120, 120, 3])) new_image = image.as_greyscale(mode='average') assert (new_image.shape == image.shape) assert (new_image.n_channels == 1)
def test_as_greyscale_luminosity(): image = MaskedImage(np.ones([120, 120, 3])) new_image = image.as_greyscale(mode='luminosity') assert (new_image.shape == image.shape) assert (new_image.n_channels == 1)