def configure(self):
if isinstance(nib, UnsupportedPackage):
nib.raise_error(self.__provider__)
self.channels_first = self.get_value_from_config('channels_first')
self.multi_infer = self.get_value_from_config('multi_infer')
if not self.data_source:
raise ConfigError(
'data_source parameter is required to create "{}" '
'data reader and read data'.format(self.__provider__))
def configure(self):
if isinstance(nib, UnsupportedPackage):
nib.raise_error(self.__provider__)
self.channels_first = self.get_value_from_config('channels_first')
self.multi_infer = self.get_value_from_config('multi_infer')
self.frame_axis = int(self.get_value_from_config('frame_axis'))
self.frame_separator = self.get_value_from_config('frame_separator')
self.multi_frame = self.get_value_from_config('multi_frame')
self.to_4D = self.get_value_from_config('to_4D')
if not self.data_source:
if not self._postpone_data_source:
raise ConfigError('data_source parameter is required to create "{}" '
'data reader and read data'.format(self.__provider__))
else:
self.data_source = get_path(self.data_source, is_directory=True)
def convert(self, check_content=False, **kwargs):
if self.multi_frame and isinstance(nib, UnsupportedPackage):
nib.raise_error(self.__provider__)
if self.as_regression:
annotation_class = NiftiRegressionAnnotation
reader_config = {
'to_4D': False,
'multi_frame': self.multi_frame,
'separator': self.frame_separator,
'frame_axis': self.frame_axis
}
else:
annotation_class = BrainTumorSegmentationAnnotation
reader_config = {
'loader':
GTMaskLoader.NIFTI_CHANNELS_FIRST
if self.mask_channels_first else GTMaskLoader.NIFTI
}
mask_folder = Path(self.mask_folder)
image_folder = Path(self.image_folder)
image_dir = get_path(self.data_dir / image_folder, is_directory=True)
mask_dir = get_path(self.data_dir / mask_folder, is_directory=True)
content_check_errors = [] if check_content else None
annotations = []
for file_in_dir in image_dir.iterdir():
file_name = file_in_dir.parts[-1]
mask_file_name = (file_name.rsplit('.', 1)[0] + '.nii.gz' if
not file_name.endswith('.nii.gz') else file_name)
if not self.relaxed_names:
mask = mask_dir / mask_file_name
else:
mask = self.find_file_by_id(mask_dir, mask_file_name)
mask_file_name = mask.parts[-1]
if not mask.exists():
if not check_content:
warnings.warn(
'Annotation mask for {} does not exist. File will be ignored.'
.format(file_name))
else:
content_check_errors.append(
'{}: annotation mask does not exist, please remove this file or add gt mask ({})'
.format(file_in_dir, mask))
continue
if self.multi_frame:
nib_image = nib.load(file_in_dir)
total_frames = nib_image.dataobj.shape[self.frame_axis]
for frame_cnt in range(total_frames):
annotation = annotation_class(
"{}{}{}".format(str(image_folder / file_name),
self.frame_separator, frame_cnt),
"{}{}{}".format(str(mask_folder / mask_file_name),
self.frame_separator, frame_cnt),
**reader_config)
annotations.append(annotation)
else:
annotation = annotation_class(
str(image_folder / file_name),
str(mask_folder / mask_file_name), **reader_config)
annotations.append(annotation)
return ConverterReturn(annotations, self.get_meta(),
content_check_errors)