Hi Stefanie,

Thanks for the insight, it's really helpful. It will be great to see some of code, do you have it available in some repo?

Thnx a lot,
Sasha

El viernes, 25 de octubre de 2019, Stefanie Lück <luecks@gmail.com> escribió:
> Hi Sasha,,
> I am working with CZI files too and could share some experience. I am using Christophs czifile package with parallel processing and it works great. I highly recommend not to convert the CZI files because it will become a nightmare (we did that before) and you will loose many information's (e.g. region ID, polygon points...). I can share some code if you like.
> Unfortunately I am using OpenCV for image processing because it's much faster compared to scikit-image and we have a large amount of data (200 GB per run).
> Cheers
> Stefanie
>
>
>
>
> Am Fr., 25. Okt. 2019 um 02:38 Uhr schrieb Cedric Espenel <cedric.espenel@gmail.com>:
>>
>> Hi Sasha,
>> Did you try PIMS bioformats for you data?
>> http://soft-matter.github.io/pims/v0.4.1/bioformats.html
>> Best,
>> Cedric
>> On Thu, Oct 24, 2019 at 5:28 PM Augusto Kielbowicz <augusto.kiel@gmail.com> wrote:
>>>
>>> Hi,
>>>
>>> I just started a new project analyzing some images that are in czi format and looking around there is not much support for them. I found that there is a czifile package in which there is a function to transform the file into a memory mappable tiff file. This comes very handy given that the images are big enough (~7gb) to cause trouble being in memory, but it's not working perfectly for me.
>>>
>>> I wanted to know what it's the common way to work with this kind of large images. It's normal to convert it to TIFF and work with that? Or is there a better format to work with?
>>>
>>> It's my first time working with image data and files this big so I'm learning a lot,  it's being great and I'm loving all the cool stuff that skimage can do.
>>> Now I'm starting to look into dask-image and it seems promising.
>>>
>>> Thank you,
>>> Sasha
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