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Stardist error when create dataset obeject #256

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mdoaskndfweon opened this issue Apr 1, 2023 · 4 comments
Closed

Stardist error when create dataset obeject #256

mdoaskndfweon opened this issue Apr 1, 2023 · 4 comments

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@mdoaskndfweon
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input image size is 500500, patch size = 128 or 256 or 64, batch size is 1, but when create dataset object, it cause gpu crash for unknown reason, I tried backbone = UNet and grid size increase (8,8) but still failed, does some way can solved this, my image is too big? I had already divided 10001000 into 5*5, that's my parameter below and bug
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To Reproduce
Steps to reproduce the behavior:

  1. Go to '...'
  2. Click on '....'
    <img width="1623" alt="Screenshot 2023-03-31 at 9 42 43 PM" src="https://user

Screenshot 2023-03-31 at 9 54 33 PM

-images.githubusercontent.com/88061206/229260122-720faa15-8715-45bf-b19a-355af5a22aea.png">

Screenshot 2023-03-31 at 9 54 12 PM

Screenshot 2023-03-31 at 9 54 49 PM

Screenshot 2023-03-31 at 9 55 13 PM

always reach out GPU memory 3. Scroll down to '....' 4. See error

Expected behavior
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  • Version [e.g. 22]

Smartphone (please complete the following information):

  • Device: [e.g. iPhone6]
  • OS: [e.g. iOS8.1]
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@mdoaskndfweon
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@esgomezm

@mdoaskndfweon
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image is 32-bit

@mdoaskndfweon
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hello, sorry for that confusing , I had already solve above those problem, but I have question relate my result for the nuclei segmentation , suppose that input image size is 1000,
Screenshot 2023-04-01 at 6 42 41 PM
this is the test result ,
Screenshot 2023-04-01 at 6 43 42 PM
for example , right hand side of the grapth is segmentation result, but when I try to predict new image without label,
Screenshot 2023-04-01 at 6 45 31 PM

the result are showed below
Screenshot 2023-04-01 at 6 45 07 PM
you see, totally differnt from the test data, but i want the format look like the same for the test data format.

my input block size x and y is 756, min overlap is256, When I decrease of block size or decrease of lin overlap, it show error and can't output the grapth

@mdoaskndfweon
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@mdoaskndfweon

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