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vanvalenlab / deepcell-label

Cloud-based data annotation tools for biological images
https://label.deepcell.org
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Cannot upload 16-bit, 4.6GB, 3.55X3.42mm, .tif of 29 channel multiplex image #527

Closed smith6jt-cop closed 11 months ago

smith6jt-cop commented 11 months ago

Describe the bug Getting "undefined" error after hitting upload button on website.

To Reproduce Steps to reproduce the behavior:

Upload by drag and drop or by choosing file. Choose any of the available dimension options in the dropdown menu.

Expected behavior The file to upload.

Screenshots The image I am trying to upload as it appears in FIJI: image image

Desktop (please complete the following information):

Additional context My image opens in QuPath as a single plane, single timepoint image with 29 channels.

ykevu commented 11 months ago

What is the dimension order of your image? It might be difficult to diagnose the problem without the file itself also, do you have a smaller example file of the same format?

smith6jt-cop commented 11 months ago

Thank you for your response. I believe the dimension order is XYC although sometimes different programs interpret dimension order differently (see https://forum.image.sc/t/multichannel-ome-tiff-import-order-xyzct-vs-xyczt/45960) so I tried uploading with each available option in the dropdown menu. 20_008-SP_CC2-B_11092020_reg001_chsNEWcropsmall.zip

rossbar commented 11 months ago

From the OP it looks like this is a 9.4k x 9k pixel image; currently the maximum supported size by deepcell-label is 2048 x 2048 pixels.

ykevu commented 11 months ago

Since the smaller cropped image seems to work, I think @rossbar is right that this is an issue of exceeding the supported size.

rossbar commented 11 months ago

Sorry, I got my wires crossed a bit - the explicit 2048x2048 limitation is for deepcell.org, not label.deepcell.org. Nevertheless, this is almost certainly a data size issue. In terms of workarounds, pre-tiling the image and uploading the tiles separately is probably the easiest workaround (quadrants should work). We'd like to support arbitrarily large images but it's not on the immediate roadmap.