nd-image-codecs
Composable Zarr v3 codecs for ND scientific images — Python binding.
A family of Zarr v3 codecs that capture correlation along z, time, and channel axes explicitly — as ordinary, independently specified array-to-array and array-to-bytes codecs — then store the result with a fast entropy backend, High-Throughput JPEG 2000 (ISO/IEC 15444-15) coefficient planes, or ZFP blocks. Built for OME-Zarr / OME-NGFF.
No JPEG 2000 Part 2 (MCT) syntax anywhere — cross-axis decorrelation is an explicit Zarr codec, sidestepping Part 2 IP entirely.
The three codec families
codec_series assembles a series (pipeline) of Zarr v3 codecs from an array's
axis metadata:
| Family | Series (pipeline) | Built for |
|---|---|---|
| nd-delta | transpose → numcodecs.delta → bitshuffle → zstd/lz4 |
Fast lossless storage from existing Zarr codecs only |
| nd-lift-ht | transpose → nd_lift → htj2k |
Scalable microscopy & volume visualization |
| nd-zfp | transpose → reshape → zfp |
GPU volume rendering, random access, fixed-rate memory |
Install
pip install nd-image-codecs # NumPy only
pip install "nd-image-codecs[zarr]" # + zarr-python v3, for the codec pipeline
Wheels cover manylinux, musllinux, macOS, and Windows on x86-64 and arm64.
The base install requires only NumPy, so codec_series and the htj2k,
zfp, and nd_lift codecs are usable anywhere that wheel lands; the zarr
extra adds zarr-python (and, through it, numcodecs) to run pipelines.
Usage
from nd_image_codecs import codec_series
codecs = codec_series(["t", "c", "z", "y", "x"], [8, 1, 32, 256, 256],
"uint16", "nd-lift-ht")
The three codec classes (NdLift, Htj2k, NdZfp) register with zarr-python
v3 through the zarr.codecs entry-point group, so pipelines produced by
codec_series resolve by name.
Status
Alpha. nd_lift, htj2k, and zfp encode and decode for real, and the
codec_series builder is cross-checked byte-identical against the Rust and
TypeScript implementations in CI. The API is not stable before 1.0.
Links
License
MIT — Copyright (c) Fideus Labs LLC.
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