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
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 _______________________________________________ scikit-image mailing list -- scikit-image@python.org To unsubscribe send an email to scikit-image-leave@python.org
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 _______________________________________________ scikit-image mailing list -- scikit-image@python.org To unsubscribe send an email to scikit-image-leave@python.org
_______________________________________________ scikit-image mailing list -- scikit-image@python.org To unsubscribe send an email to scikit-image-leave@python.org
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
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
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
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: per run). 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. 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 _______________________________________________ scikit-image mailing list -- scikit-image@python.org To unsubscribe send an email to scikit-image-leave@python.org
_______________________________________________ scikit-image mailing list -- scikit-image@python.org To unsubscribe send an email to scikit-image-leave@python.org
participants (3)
-
Augusto Kielbowicz -
Cedric Espenel -
Stefanie Lück