def __init__(self, image_data, copy=True):
Landmarkable.__init__(self)
if not copy:
# Let's check we don't do a copy!
image_data_handle = image_data
self.pixels = np.require(image_data, requirements=['C'])
if self.pixels is not image_data_handle:
raise Warning('The copy flag was NOT honoured. '
'A copy HAS been made. Please ensure the data '
'you pass is C-contiguous.')
else:
image_data = np.array(image_data, copy=True, order='C')
# Degenerate case whereby we can just put the extra axis
# on ourselves
if image_data.ndim == 2:
image_data = image_data[..., None]
if image_data.ndim < 2:
raise ValueError(
"Pixel array has to be 2D (2D shape, implicitly "
"1 channel) or 3D+ (2D+ shape, n_channels) "
" - a {}D array "
"was provided".format(image_data.ndim))
self.pixels = np.require(image_data, requirements=['C'])
# add FeatureExtraction functionality
self.features = ImageFeatures(self)
def __init__(self, image_data):
Landmarkable.__init__(self)
image_data = np.array(image_data, copy=True, order='C')
# This is the degenerate case whereby we can just put the extra axis
# on ourselves
if image_data.ndim == 2:
image_data = image_data[..., None]
if image_data.ndim < 2:
raise ValueError("Pixel array has to be 2D (2D shape, implicitly "
"1 channel) or 3D+ (2D+ shape, n_channels) "
" - a {}D array "
"was provided".format(image_data.ndim))
self.pixels = image_data
# add FeatureExtraction functionality
self.features = FeatureExtraction(self)
def __init__(self, image_data):
Landmarkable.__init__(self)
image_data = np.array(image_data, copy=True, order='C')
# This is the degenerate case whereby we can just put the extra axis
# on ourselves
if image_data.ndim == 2:
image_data = image_data[..., None]
if image_data.ndim < 2:
raise ValueError("Pixel array has to be 2D (2D shape, implicitly "
"1 channel) or 3D+ (2D+ shape, n_channels) "
" - a {}D array "
"was provided".format(image_data.ndim))
self.pixels = image_data
# add FeatureExtraction functionality
self.features = FeatureExtraction(self)
