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bscan_image_and_mask_generation_algorithm

Algorithms and related functionality for simply outputting data to CSV.

Classes​

BscanImageAndMaskGenerationAlgorithm​

class BscanImageAndMaskGenerationAlgorithm(    datastructure: DataStructure,    segmentation_configs: list[SegmentationConfig],    save_path: Optional[Union[str, os.PathLike]] = None,    output_original_bscans: bool = False,    image_format: ImageFormats = ImageFormats.JPEG,    image_optimize: bool = True,    image_quality: int = 90,    image_subsampling: int = 0,    image_progressive: bool = True,    image_transparency: bool = False,    **kwargs: Any,):

Algorithm that outputs images of B-scans alongside their segmentation masks.

Initializes the BscanImageAndMaskGenerationAlgorithm.

Arguments

  • datastructure: DataStructure object describing the data.
  • segmentation_configs: List of segmentation configurations.
  • output_original_bscans: Flag to save original B-scans.
  • image_format: Format for saving images, JPEG and PNG are supported.
  • image_optimize: Flag to optimize images.
  • image_quality: Quality of saved images.
  • image_subsampling: Subsampling for saved images.
  • image_progressive: Flag for progressive saving.
  • image_transparency: Flag for transparency in PNG images.
  • save_path: Deprecated. Use the BITFOUNT_OUTPUT_DIR, BITFOUNT_TASK_RESULTS, or BITFOUNT_PRIMARY_RESULTS_DIR environment variables instead to determine output location.
  • ****kwargs**: Additional keyword arguments for the base class.

Note 'image_subsampling' and 'image_progressive' only apply to JPEG format and are ignored for PNG. 'image_transparency' only applies to PNG format and is ignored for JPEG.

Ancestors​

Variables​

Methods​

modeller​

def modeller(    self, *, context: ProtocolContext, **kwargs: Any,) ‑> NoResultsModellerAlgorithm:

Returns the modeller-side of the algorithm.

Arguments

  • context: Optional. Run-time protocol context details for running.
  • ****kwargs**: Additional keyword arguments.

Returns NoResultsModellerAlgorithm instance.

worker​

def worker(    self,    *,    context: ProtocolContext,    **kwargs: Any,) ‑> bitfount.federated.algorithms.ophthalmology.bscan_image_and_mask_generation_algorithm._WorkerSide:

Returns the worker-side of the algorithm.

Arguments

  • context: Optional. Run-time protocol context details for running.
  • ****kwargs**: Additional keyword arguments.

Returns _WorkerSide instance.

ImageFormats​

class ImageFormats(value, names=None, *, module=None, qualname=None, type=None, start=1):

Supported image formats for saving images.

Ancestors​

Variables​

  • static JPEG
  • static PNG

ImageSaveOptions​

class ImageSaveOptions(    image_format: ImageFormats = ImageFormats.JPEG,    image_optimize: bool = True,    image_quality: int = 90,    image_subsampling: int = 0,    image_progressive: bool = True,    image_transparency: bool = False,):

Options for saving images.

Note: 'image_subsampling' and 'image_progressive' only apply to JPEG format and are ignored for PNG. Note: 'image_transparency' only applies to PNG format and is ignored for JPEG.

Variables​

  • static image_optimize : bool
  • static image_progressive : bool
  • static image_quality : int
  • static image_subsampling : int
  • static image_transparency : bool

SegmentationConfig​

class SegmentationConfig(    id: str, color: tuple[int, int, int], label: Optional[str] = None,):

Configuration for a segmentation mask.

Ancestors​

  • bitfount.types.UsedForConfigSchemas

Variables​

  • static color : tuple[int, int, int]
  • static id : str
  • static label : Optional[str]

Methods​

validate_args​

def validate_args(self) ‑> None:

Validate a segmentation configuration.

Ensures that given config complies with the expected structure and types. If label is not provided, it defaults to the ID. Checks for color values that adhere to the RGB format.

SegmentationConfigList​

class SegmentationConfigList(segmentation_config_list: list[SegmentationConfig]):

Configuration for a list of segmentation masks.

Variables​

Methods​

get_segmentation_config​

def get_segmentation_config(    self,) ‑> tuple[dict[str, int], dict[str, tuple[int, int, int]], dict[str, str]]:

Get the segmentation configuration as a tuple of dictionaries.

Returns Tuple of dictionaries containing segmentation labels and colors.

validate_args​

def validate_args(self) ‑> None:

Validate the arguments in the segmentation config list.