liffile 2025.11.8

Read Leica image files (LIF, LOF, XLIF, XLCF, XLEF, and LIFEXT)

Liffile is a Python library to read image and metadata from Leica image files: LIF (Leica Image File), LOF (Leica Object File), XLIF (XML Image File), XLCF (XML Collection File), XLEF (XML Experiment File), and LIFEXT (Leica Image File Extension). These files are written by LAS X software to store collections of images and metadata from microscopy experiments.

Author:

Christoph Gohlke

License:

BSD-3-Clause

Version:

2025.11.8

DOI:

10.5281/zenodo.14740657

Quickstart

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

python -m pip install -U liffile[all]

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 3.11.9, 3.12.10, 3.13.9, 3.14.0 64-bit

• NumPy 2.3.4

• Imagecodecs 2025.8.2 (required for decoding TIFF, JPEG, PNG, and BMP)

• Xarray 2025.10.1 (recommended)

• Matplotlib 3.10.7 (optional)

• Tifffile 2025.10.16 (optional)

Revisions

2025.11.8

• Add option to find other LifImageSeries attributes than path.

• Return UniqueID in LifImage.attrs.

• Factor out BinaryFile base class.

2025.9.28

• Derive LifFileError from ValueError.

• Minor fixes.

• Drop support for Python 3.10.

2025.5.10

• Support Python 3.14.

2025.4.12

• Improve case_sensitive_path function.

2025.3.8

• Support LOF files without LMSDataContainerHeader XML element.

2025.3.6

• Support stride-aligned RGB images.

2025.2.20

• Rename LifFileFormat to LifFileType (breaking).

• Rename LifFile.format to LifFile.type (breaking).

2025.2.10

• Support case-sensitive file systems.

• Support OMETiffBlock, AiviaTiffBlock, and other memory blocks.

• Remove LifImageSeries.items and paths methods (breaking).

• Deprecate LifImage.xml_element_smd.

• Fix LifImage.parent_image and child_images properties for XML files.

• Work around reading float16 blocks from uint16 OME-TIFF files.

2025.2.8

• Support LIFEXT files.

• Remove asrgb parameter from LifImage.asarray (breaking).

• Do not apply BGR correction when using memory block frames.

• Avoid copying single frame to output array.

• Add LifImage.parent_image and child_images properties.

• Add LifImageSeries.find method.

2025.2.6

• Support XLEF and XLCF files.

• Rename LifFile.series property to images (breaking).

• Rename imread series argument to image (breaking).

• Remove LifImage.index property (breaking).

• Add parent and children properties to LifFile.

• Improve detection of XML codecs.

• Do not keep XML files open.

2025.2.5

• Support XLIF files.

• Revise LifMemoryBlock (breaking).

• Replace LifImage.is_lof property with format (breaking).

• Require imagecodecs for decoding TIF, JPEG, PNG, and BMP frames.

2025.2.2

• …

Refer to the CHANGES file for older revisions.

Notes

Leica Microsystems GmbH is a manufacturer of microscopes and scientific instruments for the analysis of micro and nanostructures.

This library is in its early stages of development. It is not feature-complete. Large, backwards-incompatible changes may occur between revisions.

Specifically, the following features are currently not supported: XLLF formats, image mosaics and pyramids, partial image reads, reading non-image data such as FLIM/TCSPC, heterogeneous channel data types, discontiguous storage, and bit increments.

The library has been tested with a limited number of version 2 files only.

The Leica image file formats are documented at:

• Leica Image File Formats - LIF, XLEF, XLLF, LOF. Version 3.2. Leica Microsystems GmbH. 21 September 2016.

• Annotations to Leica Image File Formats for LAS X Version 3.x. Version 1.4. Leica Microsystems GmbH. 24 August 2016.

• TSC SP8 FALCON File Format Description. LAS X Version 3.5.0.

Other implementations for reading Leica image files are readlif and Bio-Formats.

Examples

Read a FLIM lifetime image and metadata from a LIF file:

>>> with LifFile('tests/data/FLIM.lif') as lif:
...     for image in lif.images:
...         name = image.name
...     image = lif.images['Fast Flim']
...     assert image.shape == (1024, 1024)
...     assert image.dims == ('Y', 'X')
...     lifetimes = image.asxarray()
...
>>> lifetimes
<xarray.DataArray 'Fast Flim' (Y: 1024, X: 1024)> Size: 2MB
array([[...]],
      shape=(1024, 1024), dtype=float16)
Coordinates:
  * Y        (Y) float64... 0.0005564
  * X        (X) float64... 0.0005564
Attributes...
    path:           FLIM_testdata.lif/sample1_slice1/FLIM Compressed/Fast Flim
    UniqueID:       694efd02-95a9-436e-0fa6-f146120b1e15
    F16:            {'Name': 'F16',...
    TileScanInfo:   {'Tile': {'FieldX': 0,...
    ViewerScaling:  {'ChannelScalingInfo': {...

View the image and metadata in a LIF file from the console:

$ python -m liffile tests/data/FLIM.lif