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.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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