Package: napari-aicsimageio
napari-aicsimageioAICSImageIO bindings for napariFeaturesSupports reading metadata and imaging data for:OME-TIFFTIFFCZI(Zeiss)LIF(Leica)ND2(Nikon)DV(DeltaVision)Any formats supported byaicsimageioAny formats supported bybioformatsSLD(Slidebook)SVS(Aperio)Full ListAny additional format supported byimageioPNGJPGGIFAVIFull ListWhile upstreamaicsimageiois released under BSD-3 license, this plugin is released under GPLv3 license because it installs all format reader dependencies.InstallationStable Release:pip install napari-aicsimageioorconda install napari-aicsimageio -c conda-forgeDevelopment Head:pip install git+https://github.com/AllenCellModeling/napari-aicsimageio.gitReading Mode ThresholdThis image reading plugin will load the provided image directly into memory if it meets
the following two conditions:The filesize is less than 4GB.The filesize is less than 30% of machine memory available.If either of these conditions isn't met, the image is loaded in chunks only as needed.Use napari-aicsimageio as the Reader for All File FormatsIf you want to force napari to always use this plugin as the reader for all file formats,
try running this snippet:fromnapari.settingsimportget_settingsget_settings().plugins.extension2reader={'*':'napari-aicsimageio',**get_settings().plugins.extension2reader}For more details, see#37.Examples of FeaturesGeneral Image ReadingAll image file formats supported byaicsimageiowill be read and all
raw data will be available in the napari viewer.In addition, when reading an OME-TIFF, you can view all OME metadata directly in the
napari viewer thanks toome-types.Multi-Scene SelectionWhen reading a multi-scene file, a widget will be added to the napari viewer to manage
scene selection (clearing the viewer each time you change scene or adding the
scene content to the viewer) and a list of all scenes in the file.Access to the AICSImage Object and MetadataYou can access theAICSImageobject used to load the image pixel data and
image metadata using the built-in napari console:img=viewer.layers[0].metadata["aicsimage"]img.dims.order# TCZYXimg.channel_names# ["Bright", "Struct", "Nuc", "Memb"]img.get_image_dask_data("ZYX")# dask.array.ArrayThe napari layer metadata dictionary also stores a shorthand
for the raw image metadata:viewer.layers[0].metadata["raw_image_metadata"]The metadata is returned in whichever format is used by the underlying
file format reader, i.e. for CZI the raw metadata is returned as
anxml.etree.ElementTree.Element, for OME-TIFF the raw metadata is returned
as anOMEobject fromome-types.Lastly, if the underlying file format reader has an OME metadata conversion function,
you may additionally see a key in the napari layer metadata dictionary
called"ome_types". For example, because the AICSImageIOCZIReaderandBioformatsReaderboth support converting raw image metadata
to OME metadata, you will see an"ome_types"key that stores the metadata transformed
into the OME metadata model.viewer.layers[0].metadata["ome_types"]# OME object from ome-typesMosaic ReadingWhen reading CZI or LIF images, if the image is a mosaic tiled image,napari-aicsimageiowill return the reconstructed image:DevelopmentSeeCONTRIBUTING.mdfor information related to developing the code.For additional file format support, contributed directly toAICSImageIO.
New file format support will become directly available in this
plugin on newaicsimageioreleases.CitationIf you findaicsimageio(ornapari-aicsimageio)useful, please cite as:AICSImageIO Contributors (2021). AICSImageIO: Image Reading, Metadata Conversion, and Image Writing for Microscopy Images in Pure Python [Computer software]. GitHub.https://github.com/AllenCellModeling/aicsimageioFree software: GPLv3