def test_lab2xyz(self):
assert_array_almost_equal(lab2xyz(self.lab_array),
self.xyz_array,
decimal=3)
# Test the conversion with the rest of the illuminants.
for I in ["A", "B", "C", "d50", "d55", "d65"]:
I = I.lower()
for obs in ["2", "10", "R"]:
obs = obs.lower()
fname = "color/tests/data/lab_array_{0}_{1}.npy".format(I, obs)
lab_array_I_obs = np.load(fetch(fname))
assert_array_almost_equal(lab2xyz(lab_array_I_obs, I, obs),
self.xyz_array,
decimal=3)
for I in ["d75", "e"]:
fname = "color/tests/data/lab_array_{0}_2.npy".format(I)
lab_array_I_obs = np.load(fetch(fname))
assert_array_almost_equal(lab2xyz(lab_array_I_obs, I, "2"),
self.xyz_array,
decimal=3)
# And we include a call to test the exception handling in the code.
try:
xs = lab2xyz(lab_array_I_obs, "NaI", "2") # Not an illuminant
except ValueError:
pass
try:
xs = lab2xyz(lab_array_I_obs, "d50", "42") # Not a degree
except ValueError:
pass
def test_lab2xyz(self):
assert_array_almost_equal(lab2xyz(self.lab_array),
self.xyz_array,
decimal=3)
# Test the conversion with the rest of the illuminants.
for I in ["d50", "d55", "d65", "d75"]:
for obs in ["2", "10"]:
fname = "lab_array_{0}_{1}.npy".format(I, obs)
lab_array_I_obs = np.load(
os.path.join(os.path.dirname(__file__), 'data', fname))
assert_array_almost_equal(lab2xyz(lab_array_I_obs, I, obs),
self.xyz_array,
decimal=3)
for I in ["a", "e"]:
fname = "lab_array_{0}_2.npy".format(I, obs)
lab_array_I_obs = np.load(
os.path.join(os.path.dirname(__file__), 'data', fname))
assert_array_almost_equal(lab2xyz(lab_array_I_obs, I, "2"),
self.xyz_array,
decimal=3)
# And we include a call to test the exception handling in the code.
try:
xs = lab2xyz(lab_array_I_obs, "NaI", "2") # Not an illuminant
except ValueError:
pass
try:
xs = lab2xyz(lab_array_I_obs, "d50", "42") # Not a degree
except ValueError:
pass
def test_lab2xyz(self):
assert_array_almost_equal(lab2xyz(self.lab_array),
self.xyz_array, decimal=3)
# Test the conversion with the rest of the illuminants.
for I in ["d50", "d55", "d65", "d75"]:
for obs in ["2", "10"]:
fname = "lab_array_{0}_{1}.npy".format(I, obs)
lab_array_I_obs = np.load(
os.path.join(os.path.dirname(__file__), 'data', fname))
assert_array_almost_equal(lab2xyz(lab_array_I_obs, I, obs),
self.xyz_array, decimal=3)
for I in ["a", "e"]:
fname = "lab_array_{0}_2.npy".format(I, obs)
lab_array_I_obs = np.load(
os.path.join(os.path.dirname(__file__), 'data', fname))
assert_array_almost_equal(lab2xyz(lab_array_I_obs, I, "2"),
self.xyz_array, decimal=3)
# And we include a call to test the exception handling in the code.
try:
xs = lab2xyz(lab_array_I_obs, "NaI", "2") # Not an illuminant
except ValueError:
pass
try:
xs = lab2xyz(lab_array_I_obs, "d50", "42") # Not a degree
except ValueError:
pass
def test_lab_full_gamut(self):
a, b = np.meshgrid(np.arange(-100, 100), np.arange(-100, 100))
L = np.ones(a.shape)
lab = np.dstack((L, a, b))
for value in [0, 10, 20]:
lab[:, :, 0] = value
with expected_warnings(['Color data out of range']):
lab2xyz(lab)
def test_lab_full_gamut(self):
a, b = np.meshgrid(np.arange(-100, 100), np.arange(-100, 100))
L = np.ones(a.shape)
lab = np.dstack((L, a, b))
for value in [0, 10, 20]:
lab[:, :, 0] = value
with expected_warnings(['Color data out of range']):
lab2xyz(lab)
def test_lab2xyz_user_warning():
"""
Show how the xyz color space is not a complete superset of all possible L*a*b combinations.
z should always be greater than zero but are not in this example.
See: https://github.com/scikit-image/scikit-image/issues/4506
"""
with pytest.warns(UserWarning):
xyz_array = lab2xyz(numpy.array([[[0, -13.70470524, 27.88690567]]]))
x, y, z = xyz_array[0, 0, :]
expected_x = -0.00334555
expected_y = 0
expected_z = -0.01928643
assert math.isclose(x, expected_x, rel_tol=1e-06)
assert math.isclose(y, expected_y)
assert math.isclose(z, expected_z, rel_tol=1e-06)
def preserve_color_cielch(content, stylized, image_name):
# extract info and convert to CIE-LCh for each image
rgbContent = io.imread(content)
labContent = color.lab2lch(
color.xyz2lab(color.rgb2xyz(numpy.asarray(rgbContent))))
labContentArray = numpy.array(labContent)
rgbStyle = io.imread(stylized)
labStyle = color.lab2lch(
color.xyz2lab(color.rgb2xyz(numpy.asarray(rgbStyle))))
labStyleArray = numpy.array(labStyle)
# color transfer
for i in range(len(labContentArray)):
for j in range(len(labContentArray[0])):
labContentArray[i][j][0] = labStyleArray[i][j][0]
labContentArray = color.xyz2rgb(
color.lab2xyz(color.lch2lab(labContentArray)))
viewer = ImageViewer(labContentArray)
viewer.show()
def test_lab2xyz_dtype(self):
img = self.lab_array.astype('float64')
img32 = img.astype('float32')
assert lab2xyz(img).dtype == img.dtype
assert lab2xyz(img32).dtype == img32.dtype
def test_lab2xyz(self):
assert_array_almost_equal(lab2xyz(self.lab_array),
self.xyz_array, decimal=3)
def test_lab_to_xyz_against_skimage(random_lab):
assert np.allclose(random_lab.to_xyz(),
skcolor.lab2xyz(random_lab),
rtol=1e-2)
def test_lab2xyz(self):
assert_array_almost_equal(lab2xyz(self.lab_array),
self.xyz_array,
decimal=3)
def test_lab2xyz_channel_axis(self, channel_axis):
# test conversion with channels along a specified axis
lab = np.moveaxis(self.lab_array, source=-1, destination=channel_axis)
xyz = lab2xyz(lab, channel_axis=channel_axis)
xyz = np.moveaxis(xyz, source=channel_axis, destination=-1)
assert_array_almost_equal(xyz, self.xyz_array, decimal=3)
def to_xyz_from_lab(self):
return Image(lab2xyz(self)).convert_type(self.dtype)
