introduced an abstraction layer for all N5 dataset parameters and to … #201
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StephanPreibisch
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Hi @tpietzsch, the pre-fetching is extremely useful also for N5's on the cloud so I added it here ... it really makes a difference for datasets such as |
StephanPreibisch
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…potentially expose parts of the image (5D -> 3D for OME-ZARR), this allows us to directly use the N5ImageLoader for example for reading OME-ZARR based datasets. It also supports pre-fetching of all dataset attributes, which can slow down cloud processing if not done. I also added an instantiateN5Reader() method.
StephanPreibisch
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* BdvN5Format doesn't have to extend N5Properties. Added DefaultN5Properties instead. * 5D container slicing happens by overriding the (now exposed) N5ImageLoader.prepareCachedImage(...) method. * N5ImageLoader.prefetch() must be called by the client if desired. This will open a N5Reader if necessary, so can happen independent of N5ImageLoader.open().
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This pull request has been mentioned on Image.sc Forum. There might be relevant details there: https://forum.image.sc/t/fiji-friends-weekly-dev-update-thread/103718/16 |
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…potentially expose parts of the image (5D -> 3D for OME-ZARR), this allows us to directly use the N5ImageLoader for example for reading OME-ZARR based datasets.
I tested it on N5 and the Allen OME-ZARR implementation ...