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Improved zarr to multidimensional tiff converter #13
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Ziet er goed uit, met een paar opmerkingen.
Ik zal 'm binnenkort eens testen
resources/convert_zarr_to_tiff.py
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if output_file is None: | ||
output_file = os.path.splitext(zarr_file_path)[0] + f".{key}.tif" | ||
if output_file is None: | ||
#to make it easier to work with current BIOMERO workflow save as tif instead of ome.tif |
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Hebben we geen support voor .ome.tiff files?
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Die dubbele extensies zijn niet erg handig om mee te werken, dus voor convenience sla ik nu op als .tif, zodat het werkt met de current workflow. Ik weet niet of wat ik doe ook volledig voldoet aan de ome.tif standaard. Ik voeg alleen axes
metadata toe.
dask_image_data.persist() | ||
# to imagej tiff to be handled by cellprofiler wf wrt multiple channels | ||
tf.imwrite(output_file, dask_image_data, | ||
planarconfig='contig', imagej=True) |
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wordt dit een probleem, dat het geen multipage imagej tiff meer is? Had je 'm al getest met de cellprofiler pipelines?
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Ik zal hem testen met Cellprofiler. Heb hem nu getest met de originele stardist en cellpose containers, dat ging goed (met 2D images dan).
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Het werkt met de cellprofiler spot analyse, behalve dat de output van Cellprofiler bij mij .txt files geeft ipv .csv's. Maar dat lijkt me iets anders.
Wel kom ik er nu achter dat de converter nog niet goed werkt met multichannel 2D tiffs met Cellpose...
Ik ga erna kijken...
…larity and functionality
…omero into 5d-zarr-converter
Enhanced OME-Zarr to TIFF Conversion for Microscopy Images
This PR enhances the zarr-to-tiff conversion tool by adding robust dimension handling for OME-Zarr files.
Key Changes:
Added OME-Zarr metadata extraction:
get_dimension_order()
to extract dimension ordering from OME-Zarr metadataImproved dimension handling:
Enhanced metadata preservation:
This approach results in more accurate conversions, especially for time series and multi-channel files, while maintaining backward compatibility with existing workflows.