bioio_conversion.converters package

Submodules

bioio_conversion.converters.batch_converter module

class bioio_conversion.converters.batch_converter.BatchConverter(*, converter_key: str = 'ome-zarr', default_opts: Dict[str, Any] | None = None)

Bases: object

BatchConverter orchestrates bulk conversions of image files using a specified converter backend.

Supports three input modes:

• CSV-driven: each row defines a conversion job

• Directory-driven: scan up to max_depth for matching files

• List-driven: explicit list of file paths

Default parameters for all jobs may be provided via default_opts.

from_csv(csv_path: str | Path) → List[Dict[str, Any]]

Parse a CSV file into a list of job option dicts.

Each column maps to a converter parameter. Empty cells are skipped. Values that decode as JSON become native Python objects.

from_directory(directory: str | Path, *, max_depth: int = 0, pattern: str = '*') → List[Dict[str, Any]]

Recursively find files matching pattern up to max_depth levels.

max_depth=0 → only top-level files max_depth=1 → include one subdirectory level, etc.

from_list(paths: List[str | Path]) → List[Dict[str, Any]]

Build jobs from an explicit list of file paths.

Each path yields one job dict; default_opts are merged in.

run_jobs(jobs: List[Dict[str, Any]]) → None

Execute each job: must include ‘source’; merges defaults and job params.

bioio_conversion.converters.ome_zarr_converter module

class bioio_conversion.converters.ome_zarr_converter.OmeZarrConverter(*, source: str, destination: str | None = None, scenes: int | List[int] | None = None, name: str | None = None, level_shapes: Sequence[int] | Sequence[Sequence[int]] | None = None, chunk_shape: Sequence[int] | Sequence[Sequence[int]] | None = None, shard_shape: Sequence[int] | Sequence[Sequence[int]] | None = None, compressor: BloscCodec | Codec | None = None, zarr_format: int | None = None, image_name: str | None = None, channels: List[Channel] | None = None, rdefs: Dict[str, Any] | None = None, creator_info: Dict[str, Any] | None = None, root_transform: Dict[str, Any] | None = None, axes_names: List[str] | None = None, axes_types: List[str] | None = None, axes_units: List[str | None] | None = None, physical_pixel_size: List[float] | None = None, num_levels: int | None = None, downsample_z: bool = False, memory_target: int | None = None, start_T_src: int | None = None, start_T_dest: int | None = None, tbatch: int | None = None, dtype: str | dtype | None = None, auto_dask_cluster: bool = False)

Bases: object

OmeZarrConverter handles conversion of any BioImage‐supported format (TIFF, CZI, etc.) into OME-Zarr stores. Supports exporting one, many, or all scenes from a multi-scene file.

convert() → None

Module contents

Converters package initialization. Exposes available converters and batch utilities.

class bioio_conversion.converters.BatchConverter(*, converter_key: str = 'ome-zarr', default_opts: Dict[str, Any] | None = None)

Bases: object

BatchConverter orchestrates bulk conversions of image files using a specified converter backend.

Supports three input modes:

• CSV-driven: each row defines a conversion job

• Directory-driven: scan up to max_depth for matching files

• List-driven: explicit list of file paths

Default parameters for all jobs may be provided via default_opts.

from_csv(csv_path: str | Path) → List[Dict[str, Any]]

Parse a CSV file into a list of job option dicts.

Each column maps to a converter parameter. Empty cells are skipped. Values that decode as JSON become native Python objects.

from_directory(directory: str | Path, *, max_depth: int = 0, pattern: str = '*') → List[Dict[str, Any]]

Recursively find files matching pattern up to max_depth levels.

max_depth=0 → only top-level files max_depth=1 → include one subdirectory level, etc.

from_list(paths: List[str | Path]) → List[Dict[str, Any]]

Build jobs from an explicit list of file paths.

Each path yields one job dict; default_opts are merged in.

run_jobs(jobs: List[Dict[str, Any]]) → None

Execute each job: must include ‘source’; merges defaults and job params.

class bioio_conversion.converters.OmeZarrConverter(*, source: str, destination: str | None = None, scenes: int | List[int] | None = None, name: str | None = None, level_shapes: Sequence[int] | Sequence[Sequence[int]] | None = None, chunk_shape: Sequence[int] | Sequence[Sequence[int]] | None = None, shard_shape: Sequence[int] | Sequence[Sequence[int]] | None = None, compressor: BloscCodec | Codec | None = None, zarr_format: int | None = None, image_name: str | None = None, channels: List[Channel] | None = None, rdefs: Dict[str, Any] | None = None, creator_info: Dict[str, Any] | None = None, root_transform: Dict[str, Any] | None = None, axes_names: List[str] | None = None, axes_types: List[str] | None = None, axes_units: List[str | None] | None = None, physical_pixel_size: List[float] | None = None, num_levels: int | None = None, downsample_z: bool = False, memory_target: int | None = None, start_T_src: int | None = None, start_T_dest: int | None = None, tbatch: int | None = None, dtype: str | dtype | None = None, auto_dask_cluster: bool = False)

Bases: object

OmeZarrConverter handles conversion of any BioImage‐supported format (TIFF, CZI, etc.) into OME-Zarr stores. Supports exporting one, many, or all scenes from a multi-scene file.

convert() → None