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running python main.py --training getting error. #8

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hassaanmahmood opened this issue Mar 28, 2019 · 4 comments
Open

running python main.py --training getting error. #8

hassaanmahmood opened this issue Mar 28, 2019 · 4 comments

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@hassaanmahmood
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I am getting error . What can be the problem here.

`Training
1
../data/iSEG_preprocessed/Training/T1/subject-1-T1.nii
../data/iSEG_preprocessed/Training/T2/subject-1-T2.nii
../data/iSEG_preprocessed/Training/label/subject-1-label.nii
Extracting Patches from Image 1 ....
Total Extracted Labelled Patches Shape: (2605, 32, 32, 32, 2) (2605, 32, 32, 32)
../data/iSEG_preprocessed/Testing/T1/subject-11-T1.nii
../data/iSEG_preprocessed/Testing/T2/subject-11-T2.nii
../data/iSEG_preprocessed/Training/label/subject-1-label.nii
Processing the Image 11 ....
Traceback (most recent call last):
File "main.py", line 81, in
tf.app.run()
File "/home/hmahmood/anaconda3/envs/pi352/lib/python3.5/site-packages/tensorflow/python/platform/app.py", line 126, in run
_sys.exit(main(argv))
File "main.py", line 73, in main
network.train()
File "/home/hmahmood/FewShot_GAN-Unet3D/proposed_model/model.py", line 223, in train
data_directory=F.data_directory)
File "../preprocess/preprocess.py", line 311, in init
patch_shape, number_unlab_images_training)

File "../preprocess/preprocess.py", line 246, in preprocess_dynamic_unlab
x=get_patches_unlab(T1_vols, T2_vols, extraction_step, patch_shape,dir)
File "../preprocess/preprocess.py", line 205, in get_patches_unlab
label_patches = extract_patches(label_ref, patch_shape, extraction_step)
File "../preprocess/preprocess.py", line 81, in extract_patches
dstride_d:(dstride_d)+patch_d]
ValueError: could not broadcast input array from shape (32,32,32,1) into shape (32,32,32)`

@abmBashir13
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Almost same problem here.

Training
1
../data/iSEG_preprocessed/Training/T1/subject-1-T1.nii
../data/iSEG_preprocessed/Training/T2/subject-1-T2.nii
../data/iSEG_preprocessed/Training/label/subject-1-label.nii
Traceback (most recent call last):
File "main.py", line 80, in
tf.app.run()
File "/home/abm/.local/lib/python3.5/site-packages/tensorflow/python/platform/app.py", line 40, in run
_run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)
File "/home/abm/.local/lib/python3.5/site-packages/absl/app.py", line 299, in run
_run_main(main, args)
File "/home/abm/.local/lib/python3.5/site-packages/absl/app.py", line 250, in _run_main
sys.exit(main(argv))
File "main.py", line 73, in main
network.train()
File "/home/abm/codeGAN/proposed_model/model.py", line 223, in train
data_directory=F.data_directory)
File "../preprocess/preprocess.py", line 306, in init
patch_shape,number_images_training)
File "../preprocess/preprocess.py", line 164, in preprocess_dynamic_lab
label_vols[(case_idx-c-1), :, :, :] = read_vol(case_idx, 'label', dir)
ValueError: could not broadcast input array from shape (144,192,256,1) into shape (144,192,256)

@arm-stronger
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@hassaanmahmood can you share iseg2017 to me? thanks very much [email protected]

@arm-stronger
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@abmBashir13 can you share iseg2017 to me? thanks very much [email protected]

@huanqingxu
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'relu_slope': 0.2,
'seed': 1,
'validation_every_epoch': 1,
'volume_shape': [144, 192, 256],
'weight_decay': 0,
'x_test': '',
'x_train': '',
'x_valid': '',
'y_test': '',
'y_train': '',
'y_valid': ''}


The experiment name is unet_experiment


[INFO]: Hi, This is root.
[INFO]: After the configurations are successfully processed and dirs are created.
[INFO]: The pipeline of the project will begin now.
Training
1
./data/iSEG_preprocessed/Training/T1/subject-1-T1.nii
(1, 144, 192, 256, 1)
./data/iSEG_preprocessed/Training/T2/subject-1-T2.nii
(1, 144, 192, 256, 1)
./data/iSEG_preprocessed/Training/label/subject-1-label.nii
(1, 144, 192, 256)
Extracting Patches from Image 1 ....
Traceback (most recent call last):
File "main.py", line 31, in
main()
File "main.py", line 26, in main
agent = agent_class(config)
File "/media/lab549/CE56C94660FE3E83/semantic segmentation_xhq/code_xhq/FewShot_GAN-Unet3D-master/pytorch/agents/supervised_baseline.py", line 35, in init
self.trainloader = Supervised_Dataset(self.config, "training")
File "/media/lab549/CE56C94660FE3E83/semantic segmentation_xhq/code_xhq/FewShot_GAN-Unet3D-master/pytorch/datasets/dataloader.py", line 57, in init
self.dataset = Supervised_Dataloader(config, phase)
File "/media/lab549/CE56C94660FE3E83/semantic segmentation_xhq/code_xhq/FewShot_GAN-Unet3D-master/pytorch/datasets/dataloader.py", line 24, in init
config.number_images_training)
File "/media/lab549/CE56C94660FE3E83/semantic segmentation_xhq/code_xhq/FewShot_GAN-Unet3D-master/pytorch/utils/preprocess.py", line 173, in preprocess_dynamic_lab
testing=testing,num_images_training=num_images_training)
File "/media/lab549/CE56C94660FE3E83/semantic segmentation_xhq/code_xhq/FewShot_GAN-Unet3D-master/pytorch/utils/preprocess.py", line 111, in get_patches_lab
T1_train = extract_patches(T1_vols[idx], patch_shape, extraction_step,datype="float32")
File "/media/lab549/CE56C94660FE3E83/semantic segmentation_xhq/code_xhq/FewShot_GAN-Unet3D-master/pytorch/utils/preprocess.py", line 68, in extract_patches
dstride_d:(dstride_d)+patch_d]
ValueError: could not broadcast input array from shape (32,32,32,1) into shape (32,32,32)

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4 participants