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Deep-MI / FatSegNet

Deep CNN for Abdominal Adipose Tissue Segmentation on Dixon MRI
Apache License 2.0
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ImageFileError #5

Closed AkhilaPerumalla123 closed 4 years ago

AkhilaPerumalla123 commented 4 years ago

Hi, When trying to run paper implementation using GPU compatible docker image with below command. nvidia-docker run --rm -v ~/Akhila/FatSegNet/example_data_folder/:/tool/Data -v ~/Akhila/FatSegNet/temp/:/tool/Output adipose_tool:v1 -loc I am facing below issue.

/usr/local/lib/python3.5/dist-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from float to np.floating is deprecated. In future, it will be treated as np.float64 == np.dtype(float).type.
  from ._conv import register_converters as _register_converters
Using TensorFlow backend.
Traceback (most recent call last):
  File "./run_FatSegNet.py", line 168, in <module>
    run_fatsegnet(args,FLAGS)
  File "./run_FatSegNet.py", line 135, in run_fatsegnet
    run_adipose_pipeline(args=args, flags=FLAGS, save_path=save_path,data_path=path[0],id=str(id))
  File "/tool/Code/adipose_pipeline.py", line 191, in run_adipose_pipeline
    fat_img = nib.load(fat_file[0])
  File "/usr/local/lib/python3.5/dist-packages/nibabel/loadsave.py", line 53, in load
    filename)
nibabel.filebasedimages.ImageFileError: Cannot work out file type of "/tool/Data/subject_1/FatImaging_F.nii.gz"
/tool/Data/participants.csv
------------------------------
 Loading Subject
subject_1
------------------------------
Loading Fat Image
/tool/Data/subject_1/FatImaging_F.nii.gz

any leads would be so helpful.

santiestrada32 commented 4 years ago

Hi, You have to provided your own fat images, the images in the folder are just illustrative of how the folder has to be organized.

AkhilaPerumalla123 commented 4 years ago

Thank you for the reply. Will check with other data.