neu_vol.ops.ingest

Ingest an image stack into a multiscale OME-NGFF 0.5 zarr v3 volume.

The first vertical slice: image stack (TIFF/PNG glob or multipage TIFF) -> level-0 zarr array -> strict level-by-level pyramid -> OME group metadata. The heavy lifting is shared with convert in _multiscale.py.

Attributes

logger

Functions

ingest_image_stack(src, dst, voxel_size, *[, units, ...]) → dict

Ingest src image stack into a multiscale zarr v3 group at dst.

Module Contents

neu_vol.ops.ingest.ingest_image_stack(src: str, dst: str, voxel_size: Sequence[float], *, units: str = 'nm', axes: Sequence[str] = ('z', 'y', 'x'), offset: Sequence[float] | None = None, profile: str = 'local', chunk: Sequence[int] | None = None, shard: Sequence[int] | None = None, dtype: str | None = None, kind: str = 'image', encoding: str | None = None, compressed_segmentation_block_size: Sequence[int] = (8, 8, 8), multiscale: bool = True, factors: Sequence[Sequence[int]] | None = None, max_levels: int = 8, min_dim: int = 128, name: str = 'image', client: Any | None = None, npartitions: int | None = None, delete_existing: bool = False, resume: bool = False, verify: bool = False, progress_path: str | None = None, validate: bool = True) → dict

Ingest src image stack into a multiscale zarr v3 group at dst.

voxel_size/offset/axes are in canonical (z, y, x) order. Returns a summary dict (per-level paths, shapes, scales).

neu_vol.ops.ingest.logger