Use patch_size instead of chunk_size as base shape for sampling

[fercer]

This change allows zarrdataset to extract samples using as reference the patch_size instead of the input's chunk size.
Basically, chunks are now considered as multiples of patch_size and therefore patches can be extracted without separation.
This is helpful when using zarrdataset for inference on larger-than-memory inputs.

No changes are needed ImageBase class since it can handle loading adjacent chunks. This will increase the memory usage if the patch size is not multiple of the chunk size due to multiple chunks being loaded.

There is no impact on the multi-thread capability of zarrdataset to use multiple workers.
That is because each worker has its own handler to access the zarr file, and chunks can be read safely without collisions.

[fercer]

I'm resuming the conversation from PR #6 here @ClementCaporal.

I'll be working in the next step to solving #3 and #5, by adding a way to extract overlapped patches.
My first attempt would be adding a stride parameter to the PatchSampler class that would allow to extract overlapped patches when stride < patch size.

The following step would be to allow ImageBase objects to add padding to patches retrieved from the cache when the requested slice is bigger than the actual image size. This is the case of edge chunks that are commonly smaller than the rest of the chunks in the image.

Padding is necessary because torch's DataLoader expects all samples to be of the same shape to collate them.

[ClementCaporal]

Hello @fercer.

Thank you for the explanations. I will try this new implementation as soon as the overlap sample is ready. (I have my own small patch meanwhile)

Have a good day,

Clément

[fercer]

Thanks for your contribution to improve ZarrDataset @ClementCaporal!
The fixes to allow sampling with padding for inference have been implemented in this PR.
I'll add this functionality into the documentation and create a notebook example before merging with main branch.

[ClementCaporal]

I think there is a typo here for group "0", should it be "4" in this example?

[fercer]

Thanks for noticing this @ClementCaporal! I considered this change and added it to a recent PR #8 that addresses an incorrect sampling of masked regions.

[ClementCaporal]

Oh Nice!
I was starting to use masked regions on friday and started noticing strange behavior so I just have to pull now thanks to you!

Have a good week,

Clément