jp15

Python bindings for OpenJPH HTJ2K encode/decode, with an optional Zarr v3 codec.

Installation

pip install "jp15[zarr]"   # with Zarr codec support
pip install jp15           # encode/decode only

Basic usage

import jp15
import numpy as np

data = np.random.randint(0, 60000, (64, 128), dtype=np.uint16)

encoded = jp15.encode(
    data,
    irreversible=False,
    qstep=None,
    num_decompositions=5,
    block_size=(64, 64),
    progression_order="LRCP",
    color_transform=False,
    planar=True,
)
decoded = jp15.decode(encoded)

np.testing.assert_array_equal(decoded, data)

decode requires no dtype or shape hint from the caller. HTJ2K codestreams carry a SIZ (image size) marker in their header that records the image dimensions, number of components, bit depth, and signedness at encode time. decode reads this marker and uses it to allocate the output buffer and select the correct element type, so the reconstructed array always matches the original without any extra bookkeeping on the caller's side.

Zarr v3 codec

OpenJPHCodec is a Zarr v3 array-to-bytes codec passed in the array's codecs pipeline.

from jp15.codecs.zarr import OpenJPHCodec
import numpy as np
import zarr

data = np.arange(64 * 96, dtype=np.uint16).reshape(64, 96)

array = zarr.create(
    store="example.zarr",
    shape=data.shape,
    chunks=data.shape,
    dtype=data.dtype,
    codecs=[OpenJPHCodec(layout="yx")],
    zarr_format=3,
)

array[:] = data
np.testing.assert_array_equal(array[:], data)

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0.2.0

Jul 28, 2026

0.1.0

Jul 23, 2026

jp15 0.2.0

jp15

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Zarr v3 codec

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