Comments (4)
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)
from fewshot_gan-unet3d.
@hassaanmahmood can you share iseg2017 to me? thanks very much [email protected]
from fewshot_gan-unet3d.
@abmBashir13 can you share iseg2017 to me? thanks very much [email protected]
from fewshot_gan-unet3d.
'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)
from fewshot_gan-unet3d.
Related Issues (20)
- Predicted Output Groundtruth Images is 0 HOT 6
- Could anyone share dataset? I fail to register and download the dataset. Thanks. HOT 16
- Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR HOT 5
- How did you find class weights?
- ValueError: could not broadcast input array from shape (144,192,256,1) into shape (144,192,256) HOT 3
- N4BiasField
- Why do I get the same loss every validation ?Doesn't the model change? HOT 1
- using my own dataset
- def_init_(dump)
- I appreciate this is a great work, I'd like to konw what data used to train the model? 1 labeled subject and another one unlabeled subject, is it right? and the unlabeled subject also used to train the GAN? HOT 1
- ImportError: cannot import name 'extract_patches' from 'sklearn.feature_extraction.image' (/home/nakayama/.local/lib/python3.9/site-packages/sklearn/feature_extraction/image.py)
- CUDA error: device-side assert triggered, The loss here is a tensor, and no value is returned.
- Num_Spatial_Dims argument missing
- Use which command to test the proposed model? I thibk there are some fauts in the text. It should be $ python main.py --testing not $ python main_unet.py --testing, is it right? HOT 1
- when I 'run main.py --testing' have some errors FailedPreconditionError (see above for traceback): Attempting to use uninitialized value D/d_up3_deconv/g [[node D/d_up3_deconv/g/read (defined at ../lib/operations.py:87) = Identity[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:GPU:0"](D/d_up3_deconv/g)]] [[{{node ArgMax/_3}} = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_491_ArgMax", tensor_type=DT_INT64, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]] HOT 6
- Replacing U-Net with Isensee Model
- .nii is mising from iSEG2017 dataset HOT 3
- How to interepret results ? HOT 2
- ่ฟ่กmain_unet.pyๅบ้
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from fewshot_gan-unet3d.