Update of apeer-ometiff-library to read & write OME-TIFF files from Python

Hi all,

our apeer-ometiff-library has been updated to version 1.7.0.

This update contains the following changes:

  • Update of the code to make it runs with the latest version of all dependencies.
  • scikit-image is no more a dependency of the library and the requirement file was consequently reduced.
  • New gen_xml() function in io.py file will automatically generate a valid omexml corresponding to the array provided.
  • Fixed some bugs in the processing.py file.

Feedback is welcome.

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Hi @sebi06 and all contributors of the apeer-ometiff-library,

First of all, thanks for all the great work put into this package and making it available to the community. In addition to the features listed above, we are glad to see the latest release also upgrades omexmlClass.py to use the current 2016-06 version of the OME metadata specification.

From our handling and publication of scientific imaging data as OME-TIFF in the context of IDR, two modalities of the file format that we are seeing increasingly used are:

  • the support for multi-resolution images using the TIFF SubIFDs for storing the pyramidal levels
  • the support for distributing data across multiple files, both for the binary data using multiple TIFFs and for the metadata using companion files

From an initial quick review of the library, is it correct that the current implementation is limited to writing (and reading) single mono-resolution OME-TIFF files with the embedded rich metadata. Has there been similar request from consumers and more generally, is there a place to follow the roadmap?

A second thought was inspired by our review of apeer-ometiff-library but also similar library’s like AICS aicsimageio. While tifffile is consistently used as the reference Python library for writing/reading TIFF data, all these codebase maintain their own copy of the code handling the metadata, with many of these implementations being derived from python-bioformats’s original implementation. We discussed this briefly mentioned during the 2020 Community meeting and there might be a common driver to defining as a community the requirements for a reference metadata Python library that could be consumed by all these projects.

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Hi @s.besson,

I agree with you views on this topic.

Multi-resolution Image Files

  • since at ZEISS we focus at correlative workflows (beyond EM+LM) we invest a lot in multi-resolution capabilities of the CZI file format incl. image pyramids
  • with respect to reading CZIs BioFormats or aicsimageio (via pylibCZI) are the tools of choice
  • the tricky part is to write those files in python in a suitable format - we know that OME-TIFF now offers “some” possibilities to write multi-resolution TIFFs etc.

An open question for us/me is related to what has been discussed on the latest OME-USER meeting regarding the Next Generation File format. We are not sure if it really “makes sense” to extend the apeer-ometiff-library in that respect.

Reference Metadata Library

  • I like your idea even I know it will be not so easy to find the time to do it (as we all sre already overloaded)

@sebi06,
Is it possible to convert a .jpg image into ome.tiff image into a pyramid structure using apeer-ometiff-library. Furthermore, later does is possible to read that converted image using python-bioformats so that I can check the image getSeriesCount and imagecount to verify whether the converted image is in pyramidal structure or not.

Thank you

For converting a jpeg into an OME-TIFF use the following workflow.

The apeer-ometiff-library does not support creating image pyramids.

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