maxlo24/amasss_cbct

Automatic segmentation of CBCT scans with a 3D Unet

amasss_cbct's Issues

Request to povide more document for using code

Hi.
tank you for Interesting code.
can you provide more example of using this ? i'm begginer in segmentation and need to see video of using this.

RuntimeError UNETR

Hey there!

I follow the documentation, install all packs on Ubuntu 20.04, and even running on different python versions, the error is the same.

The command:
python3 ~/Programs/AMASSS_CBCT-main/MULTI_SEG/src/predict_CBCTSeg.py -i ~/del/GRAVALOS/4_NII_GZ -o ~/del/GRAVALOS/4_NII_GZ_OUT/ -dm /home/xxx/Programs/AMASSS_CBCT-main/Models -ss MAND MAX CB CV UAW -vtk True

ERROR Python3.7

Loading model /home/xxx/Programs/AMASSS_CBCT-main/Models/seg_FF_model.pth
Traceback (most recent call last):
File "/home/xxx/Programs/AMASSS_CBCT-main/MULTI_SEG/src/predict_CBCTSeg.py", line 498, in
main(args)
File "/home/xxx/Programs/AMASSS_CBCT-main/MULTI_SEG/src/predict_CBCTSeg.py", line 371, in main
net.load_state_dict(torch.load(model_path,map_location=DEVICE))
File "/home/xxx/Programs/OrtogOnBlender/Blender291/2.91/python/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1224, in load_state_dict
self.class.name, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for UNETR:
Unexpected key(s) in state_dict: "vit.patch_embedding.cls_token", "encoder2.blocks.0.1.conv3.conv.weight", "encoder2.blocks.1.1.conv3.conv.weight", "encoder3.blocks.0.1.conv3.conv.weight".

ERROR Python 3.8

Loading model /home/xxx/Programs/AMASSS_CBCT-main/Models/seg_FF_model.pth
Traceback (most recent call last):
File "/home/xxx/Programs/AMASSS_CBCT-main/MULTI_SEG/src/predict_CBCTSeg.py", line 498, in
main(args)
File "/home/xxx/Programs/AMASSS_CBCT-main/MULTI_SEG/src/predict_CBCTSeg.py", line 371, in main
net.load_state_dict(torch.load(model_path,map_location=DEVICE))
File "/home/xxx/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1497, in load_state_dict
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for UNETR:
Unexpected key(s) in state_dict: "vit.patch_embedding.cls_token", "encoder2.blocks.0.1.conv3.conv.weight", "encoder2.blocks.1.1.conv3.conv.weight", "encoder3.blocks.0.1.conv3.conv.weight".

train data

Hello, may I ask which dataset you trained the model based on? Can you share it? Thank you.