abhi4ssj / few-shot-segmentation Goto Github PK

Hi,

Thanks for sharing the code with the community. I have one quick question. In convert_h5.py, how do you prepare those corresponding data? i.e., what is the FS mean? Could you leave us with the data preparation instruction? Hopefully, the guidance will make us easier to run your architecture.
Thanks much!

--Ruida

"""
Convert to h5 utility.
Sample command to create new dataset - python utils/convert_h5.py -dd /home/masterthesis/shayan/nas_drive/Data_Neuro/OASISchallenge/FS -ld /home/masterthesis/shayan/nas_drive/Data_Neuro/OASISchallenge -trv datasets/train_volumes.txt -tev datasets/test_volumes.txt -rc Neo -o COR -df datasets/MALC/coronal
- python utils/convert_h5.py -dd /home/masterthesis/shayan/nas_drive/Data_Neuro/IXI/IXI_FS -ld /home/masterthesis/shayan/nas_drive/Data_Neuro/IXI/IXI_FS -ds 98,2 -rc FS -o COR -df datasets/IXI/coronal
- python3.6 utils/convert_h5.py -dd /home/deeplearning/Abhijit/nas_drive/Abhijit/WholeBody/CT_ce/Data/SilverCorpus -ld /home/deeplearning/Abhijit/nas_drive/Abhijit/WholeBody/CT_ce/Data/SilverCorpus -trv datasets/test_volumes_silver.txt -tev datasets/test_volumes_silver.txt -rc WholeBody -o AXI -df datasets/silver_corpus
"""

Hi,

Thanks for sharing the code with the community. I have one quick question. In few_shot_segmentor.py line 81, there should be
e4, _, ind4 = self.encode4(e3)
but not
e4, _, ind4 = self.encode3(e3)
right?
Or is there any special meaning?
Thanks!

Hi,

I am trying to the code on Google Colab but I get this error:

Traceback (most recent call last):
File "/content/drive/MyDrive/sofa/few-shot-segmentation/run.py", line 7, in
import few_shot_segmentor as fs
File "/content/drive/MyDrive/sofa/few-shot-segmentation/few_shot_segmentor.py", line 6, in
from nn_common_modules import modules as sm
File "/usr/local/lib/python3.9/dist-packages/nn_common_modules/modules.py", line 526
else:abdominal_segmentation_2] - 1) / 2)
^
SyntaxError: unmatched ']'

Hi, I'm using my dataset and trying to run this code, but i haven't figured it out, what should the data format look like. It would be very helpful for me if you can share how to adjust the format of the data to run "run.py". Truly thx :P

In paper "Recalibrating Fully Convolutional Networks withSpatial and Channel ‘Squeeze & Excitation’ Blocks", we can find that using scSE block can get better performance ,but this paper didn't do experiments about it, has anyone tried this?

Why does the author only use sSE instead of scSE? Is it because scSE has too many parameters？

Hello! Thank you very much for sharing the code.
Could you share the download link and data processing of the datasets, which will help me a lot. Thank you!