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Image transformation, compression, and decompression codecs

Imagecodecs is a Python library that provides block-oriented, in-memory buffer transformation, compression, and decompression functions for use in tifffile, liffile, czifile, zarr, and other scientific image input/output packages.

Decode and/or encode functions are implemented for Byte compressors: AEC, Blosc, Blosc2, Brotli, BZ2, CZI ZSTD1 and CHUNKED (with hilo filter), DEFLATE (zlib, isa-l, libdeflate, zlib-ng), GZIP, LZ4, LZ4F, LZ4H5, LZF, LZFSE, LZHAM, LZMA, LZO, LZW, OpenZL, PackBits, PGLZ (PostgreSQL LZ), Snappy, Szip, Zopfli, and ZStandard (ZSTD); Image formats: APNG, AVIF, BCn, BMP, DDS, EXR, GIF, HEIF, High-throughput JPEG 2000 (HTJ2K, JPH), JPEG (2 to 16-bit), JPEG 2000 (JP2, J2K), JPEG LS, JPEG XR, JPEG XS, Lossless JPEG (LJPEG, LJ92, JPEGLL), MOZJPEG, PCX, PNG, QOI, RGBE (HDR), TGA (TARGA), TIFF, Ultra HDR (JPEG_R), WebP, and WIC (Windows Imaging Component); Image compressors: CCITT (RLE, T.4 and T.6), DICOM RLE, and PixarLog; Scientific compressors: B2ND, EER, HCOMP, Jetraw, LERC, NPZ, Pcodec, PLIO, RCOMP (Rice), SPERR, SZ3, and ZFP; Filters: Bitorder reversal, CMS (color space transformations), Delta, Quantize (Scale, BitGroom, BitRound, GranularBR), and XOR Delta; Shufflers: Bitshuffle, Byteshuffle, Floating Point Predictor, Meshopt, Packed Integers (TIFF, MONO p and packed), and WavPack, Type conversions: Bfloat16 (brain floating point), and Float24 (24-bit floating point); and Checksums: CRC-32, Adler-32, Fletcher-32, and Jenkins lookup3.

Author:

Christoph Gohlke

License:

BSD-3-Clause

Version:

2026.10.10

DOI:

10.5281/zenodo.6915978

Quickstart

Install the imagecodecs package and all dependencies from the Python Package Index:

python -m pip install -U "imagecodecs[all]"

Imagecodecs is also available in other package repositories such as Anaconda, MSYS2, and MacPorts.

See Requirements and Notes for building from source.

See Examples for using the programming interface.

Source code and support are available on GitHub.

Requirements

This revision was tested with the following requirements and dependencies (other versions may work):

  • CPython 3.12.10, 3.13.16, 3.14.8, 3.15.0 64-bit

  • numpy 2.5.3

  • zarr 3.4.1 (optional, for Zarr 3 compatible codecs)

  • numcodecs 0.17.0 (optional, for Zarr file format 2 compatible codecs)

Build requirements:

Unmaintained or discontinued build requirements:

Bundled source files:

Test requirements:

Revisions

2026.10.10

  • Reject 0-D input to array codecs (#151, breaking).

  • Reject bitspersample outside dtype range (breaking).

  • Reject dtype too wide for bitspersample (#153, breaking).

  • Reject big-endian arrays in many codecs.

  • Add skipres parameter to jpeg2k_decode (#155).

  • Add bitspersample parameter to htj2k_encode (#153).

  • Add bitspersample and color transformation parameter to jpegls_encode (#150).

  • Add option to write SPIFF header in jpegls_encode (breaking).

  • Add perceptualheuristics parameter to jpegxl_encode (#149).

  • Add numthreads parameter to zstd_encode and zstd1_encode.

  • Add gainmap_gamma, gainmap_level, and multichannel to ultrahdr_encode.

  • Add ultrahdr_encode_jpeg and ultrahdr_decode_jpeg functions.

  • Add colorinteropid parameter to exr_encode.

  • Add compression level parameter to snappy_encode (require Snappy 1.3).

  • Add contentsize parameter to lz4f_encode.

  • Add chunked decoder to lz4f_decode, used when content size not in header.

  • Add ZSTD and LJ2K compression to EXR codec (require OpenEXR 3.5).

  • Add colorspace parameter to qoi_encode.

  • Add codec parameter to avif_decode.

  • Add numthreads parameter to heif_encode and heif_decode.

  • Add rgbe_info function, and orientation field to rgbe_header_info C struct.

  • Set GIF background alpha to 0 when alpha channel is present (breaking).

  • Set JPEG8 lossless data precision to 16 for uint16 by default.

  • Set AVIF encoder default speed to match avifenc (breaking).

  • Enable writing lossy monochrome AVIF images.

  • Update OPENZL codec to FrameInfo API (require OpenZL 0.3.0).

  • Support more pixelformats in jpegxr_decode.

  • Avoid copy of non-planar input in jpeg2k_encode.

  • Avoid extra copy in CZI hilo unpacking.

  • Avoid memset on CLEAR in lzw_encode.

  • Improve lzw_decode using literal table.

  • Improve inner loops in bmp_encode.

  • Improve HTJ2K error handling.

  • Use uint64 accumulators in imcd_delta, imcd_xor, and imcd_packints_decode.

  • Fix issues in static Pyodide builds.

2026.8.16

  • Add CHUNKED codec for experimental chunked compression in CZI files.

  • Change zarr Byteshuffle, Bitshuffle, Floatpred to ArrayByteCodec (breaking).

  • Remove axis parameter from Packbits zarr codecs (breaking).

  • Remove height and width parameters from Ccitt zarr codecs (breaking).

  • Fix codecs failing on empty or small input (#146, #147).

  • Fix zarr codecs squeezing planar dimension (#145).

  • Fix sperr_encode fails with non-contiguous input.

  • Fix lzw_decode writes to truncated output.

  • Fix tiff_decode fails to read 12-bit JPEG compressed TIFF files.

  • Fix jpegxl_encode fails to set distance=0 required by libjxl 0.12.

  • Add option to specify primaries and transferfunction in (a)png_encode (#142).

  • Map htj2k_encode level >= 1.0 to qfactor (breaking; require OpenJPH 0.31).

  • Accept float32 input in htj2k_encode (experimental).

  • Return HTJ2K images with nonlinear transform as float32 (breaking).

  • Improve EXR error handling.

  • Update JPEGXS codec to libjxs 3.0.2-ED3.

  • Add experimental support for Pyodide (core codecs only).

2026.6.26

  • Add B2ND codec based on Blosc2 library.

  • Add ISAL codec based on ISA-L library (handles deflate, zlib, and gzip).

  • Add OPENZL codec based on OpenZL library (currently Windows and decode only).

  • Add block_size, prog_order, and profile parameters to htj2k_encode.

  • Add fancyupsampling parameter to jpeg decoder functions.

  • Fix tiff_encode modifies input array.

  • Avoid unnecessary memory initialization.

  • Optimize LZW codec.

2026.6.6

  • Limit IntEnum parameters to documented values (breaking).

  • Optimize lzw_decode and remove buffersize parameter (breaking).

  • Fix floatpred_encode for zero-stride data (#138).

  • Add ZSTD1 codec with optional hilo byte shuffle and BGR to RGB conversion.

  • Add cms_info function.

  • Add spng_encode filter parameter.

  • Add Zarr 3 compatible PCX and TGA codecs.

  • Support Python 3.15.

2026.5.10

  • Add Zarr 3 compatible codecs.

  • Add WIC codec based on Windows Imaging Component.

  • Add EXR codec based on OpenEXRCore library.

  • Add WAVPACK codec based on WavPack library.

  • Add HCOMP and PLIO codecs based on modified cfitsio library.

  • Add TGA and PCX/DCX legacy codecs.

  • Add option to pass SDR image to ultrahdr_encode.

  • Add option to specify primaries and transferfunction in jpegxl_encode (#137).

  • Add animated WebP encoding and decoding of all frames (breaking).

  • Remove cms_encode and cms_decode aliases for cms_transform (breaking).

  • Determine colorspace/pixeltype from profiles in cms_transform.

  • Allow to pass IntEnum parameters as strings except for levels.

  • Support decoding RLE8 and RLE4 compressed BMP.

  • Link zopfli_encode level to numiterations parameter.

  • Unify image layout handling in encode functions.

  • Fix code review issues.

  • Drop support for numpy 2.0 (SPEC0), Python 3.11, and macosx_x86_64.

2026.3.6

  • …

Refer to the CHANGES file for older revisions.

Objectives

Many scientific image storage formats, such as TIFF, CZI, XLIF, DICOM, HDF, and Zarr are containers that store numerous small data segments (chunks, tiles, stripes). These segments are encoded using various compression and pre-filtering methods. Metadata common to all data segments are typically stored separately from the segments.

The purpose of the Imagecodecs library is to support Python modules in encoding and decoding such data segments. The specific aims are:

  • Provide functions for encoding and decoding small image data segments in-memory (as opposed to in-file) from and to bytes or numpy arrays for many compression and filtering methods.

  • Support image formats and compression methods that are not available elsewhere in the Python ecosystem.

  • Reduce the runtime dependency on numerous, large, inapt, or unmaintained Python packages. The Imagecodecs package only depends on numpy.

  • Implement codecs as Cython wrappers of third-party libraries with a C API and permissive license if available; otherwise use own C library. Provide Cython definition files for the wrapped C libraries.

  • Release the Python global interpreter lock (GIL) during extended native/C function calls for multi-threaded use.

Accessing parts of large data segments and reading metadata from segments are outside the scope of this library.

Notes

This library is largely a work in progress.

The API is not stable yet and might change between revisions.

Works on little-endian platforms only.

Supported platforms are win_amd64, win_arm64, win32, macosx_arm64, manylinux_x86_64, and manylinux_aarch64.

Wheels may not be available for all platforms and all releases.

Not all features are available on all platforms.

The bcn, ccittfax3, ccittfax4, ccittrle, dds, dicomrle, eer, jpegsof3, lzo, and openzl codecs are currently decode-only.

The brunsli codec is distributed as source code only because the underlying library is unstable.

The heif, jetraw, and jpegxs codecs are distributed as source code only due to license and possible patent usage issues.

The latest Microsoft Visual C++ Redistributable for Visual Studio 2017-2026 is required on Windows.

Refer to the imagecodecs/licenses folder for 3rd-party library licenses.

This software is based in part on the work of the Independent JPEG Group.

When building against libjpeg or libjpeg_turbo < 3, set the environment variable IMAGECODECS_JPEG8_LEGACY=1 to enable legacy API support.

Before building imagecodecs from source code, install required tools and libraries. For example, on latest Ubuntu Linux distributions:

sudo apt-get install build-essential python3-dev cython3 python3-pip \
python3-setuptools python3-wheel python3-numpy \
libbrotli-dev libcharls-dev libdeflate-dev liblerc-dev libjpeg-dev \
libjxr-dev liblcms2-dev liblz4-dev liblzma-dev libopenjp2-7-dev \
libpng-dev libtiff-dev libwebp-dev libz-dev libzstd-dev

To build and install imagecodecs from source code, run:

python -m pip install .

Many extensions are disabled by default when building from source.

To define which extensions are built, or to modify build settings such as library names and compiler arguments, provide a imagecodecs_distributor_setup.customize_build function, which is imported and executed during setup. See setup.py for pre-defined customize_build functions.

Examples

Import the JPEG2K codec:

>>> from imagecodecs import (
...     jpeg2k_encode,
...     jpeg2k_decode,
...     jpeg2k_check,
...     jpeg2k_version,
...     JPEG2K,
... )

Check that the JPEG2K codec is available in the imagecodecs build:

>>> JPEG2K.available
True

Print the version of the JPEG2K codec’s underlying OpenJPEG library:

>>> jpeg2k_version()
'openjpeg 2.5.4'

Encode a numpy array in lossless JP2 format:

>>> import numpy
>>> array = numpy.random.randint(100, 200, (256, 256, 3), numpy.uint8)
>>> encoded = jpeg2k_encode(array, level=0)
>>> bytes(encoded[:12])
b'\x00\x00\x00\x0cjP  \r\n\x87\n'

Check that the encoded bytes likely contain a JPEG 2000 stream:

>>> jpeg2k_check(encoded)
True

Decode the JP2 encoded bytes to a numpy array:

>>> decoded = jpeg2k_decode(encoded)
>>> numpy.array_equal(decoded, array)
True

Decode the JP2 encoded bytes to an existing numpy array:

>>> out = numpy.empty_like(array)
>>> _ = jpeg2k_decode(encoded, out=out)
>>> numpy.array_equal(out, array)
True

Not all codecs are fully implemented, raising exceptions at runtime:

>>> from imagecodecs import dicomrle_encode
>>> dicomrle_encode(array)
Traceback (most recent call last):
 ...
NotImplementedError: dicomrle_encode

Write the numpy array to a JP2 file:

>>> from imagecodecs import imwrite, imread
>>> imwrite('_test.jp2', array)

Read the image from the JP2 file as numpy array:

>>> image = imread('_test.jp2')
>>> numpy.array_equal(image, array)
True

Create a JPEG 2000 compressed Zarr format 2 (legacy) array using numcodecs:

>>> import zarr
>>> from imagecodecs.numcodecs import register_codecs, Jpeg2k
>>> register_codecs()
>>> zarr.zeros(
...     (4, 5, 512, 512, 3),
...     chunks=(1, 1, 256, 256, 3),
...     dtype='u2',
...     compressor=Jpeg2k(bitspersample=10),
...     zarr_format=2,
... )
<Array ... shape=(4, 5, 512, 512, 3) dtype=uint16>

Create a Delta-LZW compressed Zarr format 3 array using native zarr codecs:

>>> from imagecodecs.zarr import register_codecs, Delta, Lzw
>>> register_codecs()
>>> zarr.zeros(
...     (4, 5, 512, 512, 3),
...     chunks=(1, 1, 256, 256, 3),
...     dtype='u1',
...     codecs=[Delta(), zarr.codecs.BytesCodec(), Lzw()],
... )
<Array ... shape=(4, 5, 512, 512, 3) dtype=uint8>

Access image data in a sequence of JP2 files via tifffile.FileSequence and dask.array:

>>> import tifffile
>>> import dask.array
>>> def jp2_read(filename):
...     with open(filename, 'rb') as fh:
...         data = fh.read()
...     return jpeg2k_decode(data)
...
>>> with tifffile.FileSequence(jp2_read, '*.jp2') as ims:
...     with ims.aszarr() as store:
...         dask.array.from_zarr(store)
...
dask.array<from-zarr, shape=(1, 256, 256, 3)...chunksize=(1, 256, 256, 3)...

Write the Zarr store to a fsspec ReferenceFileSystem in JSON format and open it as a Zarr array using kerchunk:

>>> store.write_fsspec(
...     'temp.json', url='file://', codec_id='imagecodecs_jpeg2k'
... )
>>> from kerchunk.utils import refs_as_store
>>> zarr.open(refs_as_store('temp.json'), mode='r')
<Array <FsspecStore(ReferenceFileSystem, /)> shape=(1, 256, 256, 3)...

View the image in the JP2 file from the command line:

python -m imagecodecs _test.jp2

Metadata

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Release files / imagecodecs-2026.10.10-cp312-abi3-win_arm64.whl

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Release files / imagecodecs-2026.10.10-cp312-abi3-win_amd64.whl

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