ITK version: NOT INSTALLED or UNKNOWN VERSION

[Sebagam]

Dear all,

After pip installing ITK or SimpleITK the "print_config()" prompt does not find the installed ITK version.
Moreover, while executing the "densenet_training.array.ipynb" tutorial I get this error:

Load and cache transformed data: 0%| | 0/9 [00:00<?, ?it/s]

OptionalImportError Traceback (most recent call last)
/usr/local/lib/python3.6/dist-packages/monai/transforms/utils.py in apply_transform(transform, data, map_items)
308 return [transform(item) for item in data]
--> 309 return transform(data)
310 except Exception as e:

35 frames
OptionalImportError: import itk (No module named 'itk').

For details about installing the optional dependencies, please visit:
https://docs.monai.io/en/latest/installation.html#installing-the-recommended-dependencies

During handling of the above exception, another exception occurred:

OptionalImportError Traceback (most recent call last)
/usr/local/lib/python3.6/dist-packages/monai/utils/module.py in optional_import(module, version, version_checker, name, descriptor, version_args, allow_namespace_pkg)
165 actual_cmd = f"import {module}"
166 try:
--> 167 pkg = import(module) # top level module
168 the_module = import_module(module)
169 if not allow_namespace_pkg:

OptionalImportError: Applying transform <monai.transforms.io.dictionary.LoadImaged object at 0x7f7d33d66860>.

Regards,
Sebastian

[Nic-Ma]

Hi @Sebagam ,

I think you are using MONAI 0.3 and run the example in 0.3 tag.
Could you please help uninstall and use the below command to install again?

pip install -q "monai[itk]"

Thanks.

[Sebagam]

Thanks, now Monai recognizes ITK.

However, now I get this error while executing that tutorial:

---

ValueError Traceback (most recent call last)
in ()
33 check_ds = NiftiDataset(image_files=images, labels=labels, transform=train_transforms)
34 check_loader = DataLoader(check_ds, batch_size=2, num_workers=2, pin_memory=torch.cuda.is_available())
---> 35 im, label = monai.utils.misc.first(check_loader)
36 print(type(im), im.shape, label)
37

4 frames
/usr/local/lib/python3.6/dist-packages/torch/_utils.py in reraise(self)
426 # have message field
427 raise self.exc_type(message=msg)
--> 428 raise self.exc_type(msg)
429
430

ValueError: Caught ValueError in DataLoader worker process 0.
Original Traceback (most recent call last):
File "/usr/local/lib/python3.6/dist-packages/monai/transforms/utils.py", line 309, in apply_transform
return transform(data)
File "/usr/local/lib/python3.6/dist-packages/monai/transforms/spatial/array.py", line 360, in call
align_corners=self.align_corners if align_corners is None else align_corners,
File "/usr/local/lib/python3.6/dist-packages/monai/transforms/spatial/array.py", line 54, in _torch_interp
return torch.nn.functional.interpolate(recompute_scale_factor=True, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py", line 3110, in interpolate
raise ValueError("recompute_scale_factor is not meaningful with an explicit size.")
ValueError: recompute_scale_factor is not meaningful with an explicit size.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "/usr/local/lib/python3.6/dist-packages/monai/transforms/utils.py", line 309, in apply_transform
return transform(data)
File "/usr/local/lib/python3.6/dist-packages/monai/transforms/compose.py", line 233, in call
input_ = apply_transform(transform, input)
File "/usr/local/lib/python3.6/dist-packages/monai/transforms/utils.py", line 311, in apply_transform
raise type(e)(f"Applying transform {transform}.").with_traceback(e.traceback)
File "/usr/local/lib/python3.6/dist-packages/monai/transforms/utils.py", line 309, in apply_transform
return transform(data)
File "/usr/local/lib/python3.6/dist-packages/monai/transforms/spatial/array.py", line 360, in call
align_corners=self.align_corners if align_corners is None else align_corners,
File "/usr/local/lib/python3.6/dist-packages/monai/transforms/spatial/array.py", line 54, in _torch_interp
return torch.nn.functional.interpolate(recompute_scale_factor=True, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py", line 3110, in interpolate
raise ValueError("recompute_scale_factor is not meaningful with an explicit size.")
ValueError: Applying transform <monai.transforms.spatial.array.Resize object at 0x7fb425cfdb70>.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/worker.py", line 198, in _worker_loop
data = fetcher.fetch(index)
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/utils/fetch.py", line 44, in
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/usr/local/lib/python3.6/dist-packages/monai/data/nifti_reader.py", line 102, in getitem
img = apply_transform(self.transform, img)
File "/usr/local/lib/python3.6/dist-packages/monai/transforms/utils.py", line 311, in apply_transform
raise type(e)(f"Applying transform {transform}.").with_traceback(e.traceback)
File "/usr/local/lib/python3.6/dist-packages/monai/transforms/utils.py", line 309, in apply_transform
return transform(data)
File "/usr/local/lib/python3.6/dist-packages/monai/transforms/compose.py", line 233, in call
input = apply_transform(transform, input)
File "/usr/local/lib/python3.6/dist-packages/monai/transforms/utils.py", line 311, in apply_transform
raise type(e)(f"Applying transform {transform}.").with_traceback(e.traceback)
File "/usr/local/lib/python3.6/dist-packages/monai/transforms/utils.py", line 309, in apply_transform
return transform(data)
File "/usr/local/lib/python3.6/dist-packages/monai/transforms/spatial/array.py", line 360, in call
align_corners=self.align_corners if align_corners is None else align_corners,
File "/usr/local/lib/python3.6/dist-packages/monai/transforms/spatial/array.py", line 54, in _torch_interp
return torch.nn.functional.interpolate(recompute_scale_factor=True, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py", line 3110, in interpolate
raise ValueError("recompute_scale_factor is not meaningful with an explicit size.")
ValueError: Applying transform <monai.transforms.compose.Compose object at 0x7fb425cfdc18>.

[Nic-Ma]

Are you using MONAI docker or installed all the requirements.txt locally?
Could you please help call below code to provide the env details?

from monai.config import print_config
print_config()

Thanks.

[Sebagam]

Sure, this is my config

MONAI version: 0.3.0
Python version: 3.6.9 (default, Oct 8 2020, 12:12:24) [GCC 8.4.0]
OS version: Linux (4.19.112+)
Numpy version: 1.18.5
Pytorch version: 1.7.0+cu101
MONAI flags: HAS_EXT = False, USE_COMPILED = False

Optional dependencies:
Pytorch Ignite version: NOT INSTALLED or UNKNOWN VERSION.
Nibabel version: 3.0.2
scikit-image version: 0.16.2
Pillow version: 7.0.0
Tensorboard version: 2.3.0
gdown version: 3.6.4
TorchVision version: 0.8.1+cu101
ITK version: 5.1.2
tqdm version: 4.54.1

[Nic-Ma]

Hi @Sebagam ,

I think Wenqi's PR can fix your problem.
Could you please update to use the latest MONAI master code and latest tutorial example?
You can install from latest source by command:

pip install git+https://github.com/Project-MONAI/MONAI#egg=MONAI

Thanks.

[Sebagam]

Hi, one last thing. I'm trying to run the code on Google Colab. I have been also executing that line to install the latest version. Maybe you could consider uploading the tutorials to Colab and testing them there? Thanks, Sebastian

…

On Wed, Dec 9, 2020 at 12:20 AM Nic Ma ***@***.***> wrote: Hi @Sebagam <https://github.com/Sebagam> , I think Wenqi's PR can fix your problem. Could you please update to use the latest MONAI master code and latest tutorial example? You can install from latest source by command: pip install git+https://github.com/Project-MONAI/MONAI#egg=MONAI Thanks. — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub <#82 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AB7M2ONEKPQVURBRPX3CBBTST3UF7ANCNFSM4UR7RSSQ> .

[patriciacs1994]

Hello @Nic-Ma.
I am getting the same error when I try to use Resize transformation like this:

    train_imtrans = Compose(
        [
            LoadImage(image_only=True),
            ScaleIntensity(),
            Resize(spatial_size = (192,192), mode = "nearest")
            AddChannel(), 
            ToTensor(),
        ]
    )

ValueError: Caught ValueError in DataLoader worker process 0.
Original Traceback (most recent call last):
File "C:\Users\PASI\AppData\Local\Programs\Python\Python36\lib\site-packages\monai\transforms\utils.py", line 309, in apply_transform
return transform(data)
File "C:\Users\PASI\AppData\Local\Programs\Python\Python36\lib\site-packages\monai\transforms\spatial\array.py", line 360, in call
align_corners=self.align_corners if align_corners is None else align_corners,
File "C:\Users\PASI\AppData\Local\Programs\Python\Python36\lib\site-packages\monai\transforms\spatial\array.py", line 54, in _torch_interp
return torch.nn.functional.interpolate(recompute_scale_factor=True, **kwargs)
File "C:\Users\PASI\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\functional.py", line 3110, in interpolate
raise ValueError("recompute_scale_factor is not meaningful with an explicit size.")
ValueError: recompute_scale_factor is not meaningful with an explicit size.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "C:\Users\PASI\AppData\Local\Programs\Python\Python36\lib\site-packages\monai\transforms\utils.py", line 309, in apply_transform
return transform(data)
File "C:\Users\PASI\AppData\Local\Programs\Python\Python36\lib\site-packages\monai\transforms\compose.py", line 233, in call
input_ = apply_transform(transform, input)
File "C:\Users\PASI\AppData\Local\Programs\Python\Python36\lib\site-packages\monai\transforms\utils.py", line 311, in apply_transform
raise type(e)(f"Applying transform {transform}.").with_traceback(e.traceback)
File "C:\Users\PASI\AppData\Local\Programs\Python\Python36\lib\site-packages\monai\transforms\utils.py", line 309, in apply_transform
return transform(data)
File "C:\Users\PASI\AppData\Local\Programs\Python\Python36\lib\site-packages\monai\transforms\spatial\array.py", line 360, in call
align_corners=self.align_corners if align_corners is None else align_corners,
File "C:\Users\PASI\AppData\Local\Programs\Python\Python36\lib\site-packages\monai\transforms\spatial\array.py", line 54, in _torch_interp
return torch.nn.functional.interpolate(recompute_scale_factor=True, **kwargs)
File "C:\Users\PASI\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\functional.py", line 3110, in interpolate
raise ValueError("recompute_scale_factor is not meaningful with an explicit size.")
ValueError: Applying transform <monai.transforms.spatial.array.Resize object at 0x00000000563826A0>.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "C:\Users\PASI\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\utils\data_utils\worker.py", line 198, in worker_loop
data = fetcher.fetch(index)
File "C:\Users\PASI\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\utils\data_utils\fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "C:\Users\PASI\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\utils\data_utils\fetch.py", line 44, in
data = [self.dataset[idx] for idx in possibly_batched_index]
File "C:\Users\PASI\AppData\Local\Programs\Python\Python36\lib\site-packages\monai\data\dataset.py", line 725, in getitem
return self.dataset[index]
File "C:\Users\PASI\AppData\Local\Programs\Python\Python36\lib\site-packages\monai\data\dataset.py", line 622, in getitem
data.extend(to_list(dataset[index]))
File "C:\Users\PASI\AppData\Local\Programs\Python\Python36\lib\site-packages\monai\data\dataset.py", line 66, in getitem
data = apply_transform(self.transform, data)
File "C:\Users\PASI\AppData\Local\Programs\Python\Python36\lib\site-packages\monai\transforms\utils.py", line 311, in apply_transform
raise type(e)(f"Applying transform {transform}.").with_traceback(e.traceback)
File "C:\Users\PASI\AppData\Local\Programs\Python\Python36\lib\site-packages\monai\transforms\utils.py", line 309, in apply_transform
return transform(data)
File "C:\Users\PASI\AppData\Local\Programs\Python\Python36\lib\site-packages\monai\transforms\compose.py", line 233, in call
input = apply_transform(transform, input)
File "C:\Users\PASI\AppData\Local\Programs\Python\Python36\lib\site-packages\monai\transforms\utils.py", line 311, in apply_transform
raise type(e)(f"Applying transform {transform}.").with_traceback(e.traceback)
File "C:\Users\PASI\AppData\Local\Programs\Python\Python36\lib\site-packages\monai\transforms\utils.py", line 309, in apply_transform
return transform(data)
File "C:\Users\PASI\AppData\Local\Programs\Python\Python36\lib\site-packages\monai\transforms\spatial\array.py", line 360, in call
align_corners=self.align_corners if align_corners is None else align_corners,
File "C:\Users\PASI\AppData\Local\Programs\Python\Python36\lib\site-packages\monai\transforms\spatial\array.py", line 54, in _torch_interp
return torch.nn.functional.interpolate(recompute_scale_factor=True, **kwargs)
File "C:\Users\PASI\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\functional.py", line 3110, in interpolate
raise ValueError("recompute_scale_factor is not meaningful with an explicit size.")
ValueError: Applying transform <monai.transforms.compose.Compose object at 0x0000000019110AC8>.

My config is the following one:
_MONAI version: 0.3.0
Python version: 3.6.5 (v3.6.5:f59c0932b4, Mar 28 2018, 17:00:18) [MSC v.1900 64 bit (AMD64)]
OS version: Windows (10)
Numpy version: 1.19.3
Pytorch version: 1.7.0+cu101
MONAI flags: HAS_EXT = False, USE_COMPILED = False

Optional dependencies:
Pytorch Ignite version: 0.4.2
Nibabel version: 3.2.1
scikit-image version: 0.17.2
Pillow version: 8.0.1
Tensorboard version: 2.3.0
gdown version: 3.12.2
TorchVision version: 0.8.1+cu101
ITK version: 5.1.2
tqdm version: 4.51.0_

And when I try to use the following command with Anaconda:
pip install git+https://github.com/Project-MONAI/MONAI#egg=MONAI

I am getting the following error:

ERROR: Command errored out with exit status 1:
command: 'c:\users\pasi\appdata\local\programs\python\python36\python.exe' 'c:\users\pasi\appdata\local\programs\python\python36\lib\site-packages\pip' install --ignore-installed --no-user --prefix 'C:\Users\PASI\AppData\Local\Temp\pip-build-env-alugcjow\overlay' --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- wheel setuptools 'torch>=1.5' ninja
cwd: None
Complete output (7 lines):
Collecting ninja
Using cached ninja-1.10.0.post2-py3-none-win_amd64.whl (250 kB)
Collecting setuptools
Using cached setuptools-51.0.0-py3-none-any.whl (785 kB)
Collecting torch>=1.5
Using cached torch-1.7.0-cp36-cp36m-win_amd64.whl (184.0 MB)
ERROR: torch has an invalid wheel, .dist-info directory not found

ERROR: Command errored out with exit status 1: 'c:\users\pasi\appdata\local\programs\python\python36\python.exe' 'c:\users\pasi\appdata\local\programs\python\python36\lib\site-packages\pip' install --ignore-installed --no-user --prefix 'C:\Users\PASI\AppData\Local\Temp\pip-build-env-alugcjow\overlay' --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- wheel setuptools 'torch>=1.5' ninja Check the logs for full command output.

Do you know how to solve this?

Thank you in advance

[Nic-Ma]

Hi @patriciacs1994 ,

I think you may have some compatible issue in your python env.
The easiest solution is to use the latest MONAI docker:

# with docker v19.03+
docker run --gpus all --rm -ti --ipc=host projectmonai/monai:latest

Thanks.

[Nic-Ma]

Hi @Sebagam ,

Thanks for your suggestion, I will update the notebook to add the Colab link soon.