OME-Zarr

Kiln supports two input formats:

Format	Preprocessing	Use Case
OME-Zarr (NGFF v0.4/v0.5)	None — no Kiln-specific conversion	Standard scientific imaging format, chunked arrays
Kiln sharded binary	Requires conversion script	Gzip-compressed bricks, HTTP Range streaming

Kiln can load compatible multiscale OME-Zarr volumes directly over HTTP, with no Kiln-specific conversion. Point it at a .ome.zarr URL and it streams chunk data on demand.

Requirements

• OME-NGFF v0.4 and v0.5 with multiscales metadata in group attributes
• Single-channel or multichannel — up to 4 channels (see Multichannel)
• 3D arrays with dimensions ordered [z, y, x] (standard C-order); multichannel datasets use a c axis
• Supported dtypes: uint8, uint16, float32 input (signed integers and float64 not supported)
• Multiple resolution levels (datasets within multiscales) are used as LODs
• Voxel spacing is read from coordinateTransformations if present
• OMERO metadata is used for per-channel window auto-leveling when available

Note: Currently unsupported: more than 4 channels, signed integer types (int8, int16), and float64. uint16 and float32 volumes are stored internally as r16float (WebGPU filterable-float32 is not universally available, and there's no native 16-bit-integer alternative in use here); this is not bit-exact across the full uint16 range. min/max range is read from metadata and used to normalise values in the shader.

Usage

Pass the .ome.zarr URL directly to KilnViewer.create():

import { KilnViewer } from 'kiln-render';

const viewer = await KilnViewer.create(canvas, 'https://example.com/data/scan.ome.zarr');

Kiln auto-detects the format from the URL. Brick assembly (fetching Zarr chunks, decompressing, and re-chunking into 66³ bricks with ghost borders) runs in a Web Worker pool off the main thread.

Public OME-Zarr datasets

The OME-Zarr Open SciVis Datasets on AWS provide ready-to-use test volumes:

const viewer = await KilnViewer.create(
  canvas,
  'https://ome-zarr-scivis.s3.us-east-1.amazonaws.com/v0.5/96x2/beechnut.ome.zarr',
);

Axis convention

Zarr stores dimensions as [z, y, x] (C-order, x fastest-varying). Kiln uses [x, y, z] in its metadata. Only metadata tuples are swapped; no data transposition is needed since the memory layout is identical.