CellSeg3D
CellSeg3D copied to clipboard
Published
20 hours ago •
AdaptiveMotorControlLab
AdaptiveMotorControlLab
TypeError: reshape() got an unexpected keyword argument 'newshape' when running inference
Hello,
I am getting the error TypeError: reshape() got an unexpected keyword argument 'newshape' when I use CellSeg3D to perform inference on my data using a pretrained model.
My sequence of actions:
- Open Napari on a folder that consists of an image stack
- Go to Plugins -> CellSeg3D -> Inference
- In the widget that pops up, without changing any of the default parameters, click "Start"
Then after about 30 seconds, napari might crash with a segmentation fault. Even in the case that napari doesn't crash, nothing seems to change (no inferred images are created). This is the log in the terminal:
(cellseg) ┌─[yul4024@wulab-precision1] - [~/Documents/downsample_stack] - [229]
└─[$] napari cellseg_test_stack [8:24:32]
/home/yul4024/miniforge3/envs/cellseg/lib/python3.9/site-packages/pytools/persistent_dict.py:63: RecommendedHashNotFoundWarning: Unable to import recommended hash 'siphash24.siphash13', falling back to 'hashlib.sha256'. Run 'python3 -m pip install siphash24' to install the recommended hash.!
08:24:48 INFO pydensecrf not installed, CRF post-processing will not be available. Please install by running : pip install pydensecrf@git+https://github.com/lucasb-eyer/pydensecrf.git#egg=masterThis is not a hard requirement, you do not need it to install it unless you want to use the CRF post-processing step.
08:24:48 INFO wandb not installed, wandb config will not be taken into account
08:24:50 INFO Starting...
08:24:50 INFO ********************
08:24:50 INFO Worker started at 08:24:50
08:24:50 INFO Saving results to : /home/yul4024/cellseg3d/inference
08:24:50 INFO Worker is running...
08:24:50 INFO MODEL DIMS : 64
08:24:50 INFO Model name : SegResNet
08:24:50 INFO Instantiating model...
08:24:50 INFO ********************
08:24:50 INFO Weight file SegResNet_latest.pth already exists, skipping download
08:24:50 INFO Loading weights...
08:24:51 ERROR reshape() got an unexpected keyword argument 'newshape'
Traceback (most recent call last):
File "/home/yul4024/miniforge3/envs/cellseg/lib/python3.9/site-packages/napari_cellseg3d/code_models/worker_inference.py", line 969, in inference
input_image = self.load_layer()
File "/home/yul4024/miniforge3/envs/cellseg/lib/python3.9/site-packages/napari_cellseg3d/code_models/worker_inference.py", line 283, in load_layer
volume = np.reshape(volume, newshape=(1, *volume.shape))
File "/home/yul4024/miniforge3/envs/cellseg/lib/python3.9/site-packages/dask/array/core.py", line 1753, in __array_function__
return da_func(*args, **kwargs)
TypeError: reshape() got an unexpected keyword argument 'newshape'
08:24:51 INFO Weights status : <All keys matched successfully>
08:24:51 INFO Done
08:24:51 INFO --------------------
08:24:51 INFO Parameters summary :
08:24:51 INFO Model is : SegResNet
08:24:51 INFO Window inference is disabled
08:24:51 INFO Dataset loaded on cuda:0 device
08:24:51 INFO --------------------
08:24:51 INFO Loading layer
08:24:51 INFO
Worker finished at 08:24:51
08:24:51 INFO ********************
08:24:51 INFO Emptying cache...
08:24:51 INFO Attempt complete : Cache emptied
Here is how I installed these packages. I uninstalled and reinstalled this environment in this exact manner to make sure it was not a one-time corrupt install of Numpy:
(base) ┌─[yul4024@wulab-precision1] - [~/Documents/downsample_stack] - [206]
└─[$] mamba create -n cellseg python=3.9 napari=0.4 pyqt [8:01:37]
Looking for: ['python=3.9', 'napari=0.4', 'pyqt']
conda-forge/linux-64 Using cache
conda-forge/noarch Using cache
Transaction
Prefix: /home/yul4024/miniforge3/envs/cellseg
Updating specs:
- python=3.9
- napari=0.4
- pyqt
Package Version Build Channel Size
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Install:
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+ numpydoc 1.8.0 pyhd8ed1ab_0 conda-forge Cached
+ scikit-image 0.24.0 py39h5114956_2 conda-forge Cached
+ napari 0.4.19.post1 pyh9208f05_0 conda-forge Cached
Summary:
Install: 304 packages
Total download: 24MB
──────────────────────────────────────────────────────────────────────────────────────────────
Confirm changes: [Y/n]
python 23.7MB @ 46.2MB/s 0.5s
Downloading and Extracting Packages:
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
To activate this environment, use
$ mamba activate cellseg
To deactivate an active environment, use
$ mamba deactivate
(base) ┌─[yul4024@wulab-precision1] - [~/Documents/downsample_stack] - [207]
└─[$] conda activate cellseg [8:02:24]
(cellseg) ┌─[yul4024@wulab-precision1] - [~/Documents/downsample_stack] - [209]
└─[$] mamba install pytorch torchvision torchaudio pytorch-cuda=12.4 -c pytorch -c nvidia [8:02:33]
Looking for: ['pytorch', 'torchvision', 'torchaudio', 'pytorch-cuda=12.4']
conda-forge/linux-64 Using cache
conda-forge/noarch Using cache
pytorch/noarch No change
nvidia/linux-64 No change
nvidia/noarch No change
pytorch/linux-64 No change
Pinned packages:
- python 3.9.*
Transaction
Prefix: /home/yul4024/miniforge3/envs/cellseg
Updating specs:
- pytorch
- torchvision
- torchaudio
- pytorch-cuda=12.4
- ca-certificates
- certifi
- openssl
Package Version Build Channel Size
───────────────────────────────────────────────────────────────────────────────────────────────────────────
Install:
───────────────────────────────────────────────────────────────────────────────────────────────────────────
+ pytorch-mutex 1.0 cuda pytorch Cached
+ llvm-openmp 15.0.7 h0cdce71_0 conda-forge Cached
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+ torchtriton 3.0.0 py39 pytorch 245MB
+ torchaudio 2.4.0 py39_cu124 pytorch 7MB
+ torchvision 0.19.0 py39_cu124 pytorch 8MB
Change:
───────────────────────────────────────────────────────────────────────────────────────────────────────────
- _openmp_mutex 4.5 2_gnu conda-forge Cached
+ _openmp_mutex 4.5 2_kmp_llvm conda-forge Cached
- libblas 3.9.0 24_linux64_openblas conda-forge Cached
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- libcblas 3.9.0 24_linux64_openblas conda-forge Cached
+ libcblas 3.9.0 16_linux64_mkl conda-forge Cached
- liblapack 3.9.0 24_linux64_openblas conda-forge Cached
+ liblapack 3.9.0 16_linux64_mkl conda-forge Cached
Summary:
Install: 64 packages
Change: 4 packages
Total download: 2GB
───────────────────────────────────────────────────────────────────────────────────────────────────────────
Confirm changes: [Y/n]
torchvision 8.3MB @ 50.2MB/s 0.2s
torchaudio 6.6MB @ 29.7MB/s 0.2s
torchtriton 244.9MB @ 42.3MB/s 5.8s
pytorch 1.4GB @ 91.8MB/s 15.7s
Downloading and Extracting Packages:
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
(cellseg) ┌─[yul4024@wulab-precision1] - [~/Documents/downsample_stack] - [213]
└─[$] pip install napari-cellseg3d [8:07:20]
Collecting napari-cellseg3d
Using cached napari_cellseg3d-0.2.0-py3-none-any.whl.metadata (10 kB)
(omitted due to github comment length limit)
Installing collected packages: napari-cellseg3d
Successfully installed napari-cellseg3d-0.2.0
Thanks in advance.
I installed CellSeg via pip install -e ., edited the erroneous line
volume = np.reshape(volume, newshape=(1, *volume.shape))
to
volume = np.reshape(volume, (1, *volume.shape))
which should be equivalent to the original code since newshape is also a positional argument. And now I am getting a different error trying to run the inference function:
(cellseg) ┌─[yul4024@wulab-precision1] - [~/Documents/downsample_stack] - [236]
└─[$] napari cellseg_test_stack [8:28:25]
/home/yul4024/miniforge3/envs/cellseg/lib/python3.9/site-packages/pytools/persistent_dict.py:63: RecommendedHashNotFoundWarning: Unable to import recommended hash 'siphash24.siphash13', falling back to 'hashlib.sha256'. Run 'python3 -m pip install siphash24' to install the recommended hash.!
08:28:34 INFO pydensecrf not installed, CRF post-processing will not be available. Please install by running : pip install pydensecrf@git+https://github.com/lucasb-eyer/pydensecrf.git#egg=masterThis is not a hard requirement, you do not need it to install it unless you want to use the CRF post-processing step.
08:28:34 INFO wandb not installed, wandb config will not be taken into account
08:28:36 INFO Starting...
08:28:36 INFO ********************
08:28:36 INFO Worker started at 08:28:36
08:28:36 INFO Saving results to : /home/yul4024/cellseg3d/inference
08:28:36 INFO Worker is running...
08:28:36 INFO MODEL DIMS : 64
08:28:36 INFO Model name : SegResNet
08:28:36 INFO Instantiating model...
08:28:36 INFO ********************
08:28:36 INFO Weight file SegResNet_latest.pth already exists, skipping download
08:28:36 INFO Loading weights...
Numpy version: 1.26.4
08:28:36 INFO Weights status : <All keys matched successfully>
Numpy source: /home/yul4024/miniforge3/envs/cellseg/lib/python3.9/site-packages/numpy/__init__.py
08:28:36 WARNING Warning : a very large dimension for automatic padding has been computed.
Ensure your images are of an appropriate size and/or that you have enough memory.The padding value is currently 1024.
08:28:36 WARNING Warning : a very large dimension for automatic padding has been computed.
Ensure your images are of an appropriate size and/or that you have enough memory.The padding value is currently 2048.
08:28:36 WARNING Warning : a very large dimension for automatic padding has been computed.
Ensure your images are of an appropriate size and/or that you have enough memory.The padding value is currently 4096.
08:28:36 WARNING Warning : a very large dimension for automatic padding has been computed.
Ensure your images are of an appropriate size and/or that you have enough memory.The padding value is currently 8192.
08:28:36 WARNING Warning : a very large dimension for automatic padding has been computed.
Ensure your images are of an appropriate size and/or that you have enough memory.The padding value is currently 1024.
08:28:36 WARNING Warning : a very large dimension for automatic padding has been computed.
Ensure your images are of an appropriate size and/or that you have enough memory.The padding value is currently 2048.
08:28:36 WARNING Warning : a very large dimension for automatic padding has been computed.
Ensure your images are of an appropriate size and/or that you have enough memory.The padding value is currently 4096.
08:28:36 WARNING Warning : a very large dimension for automatic padding has been computed.
Ensure your images are of an appropriate size and/or that you have enough memory.The padding value is currently 8192.
08:28:36 WARNING Warning : a very large dimension for automatic padding has been computed.
Ensure your images are of an appropriate size and/or that you have enough memory.The padding value is currently 16384.
2024-10-01 08:28:36,724 - INFO - Apply pending transforms - lazy: False, pending: 0, upcoming 'QuantileNormalization', transform is not lazy
=== Transform input info -- QuantileNormalization ===
08:28:36 ERROR
=== Transform input info -- QuantileNormalization ===
Data statistics:
Type: <class 'dask.array.core.Array'> float32
Value: dask.array<reshape, shape=(1, 7489, 8804, 12), dtype=float32, chunksize=(1, 7489, 8804, 1), chunktype=numpy.ndarray>
08:28:36 INFO Data statistics:
Type: <class 'dask.array.core.Array'> float32
Value: dask.array<reshape, shape=(1, 7489, 8804, 12), dtype=float32, chunksize=(1, 7489, 8804, 1), chunktype=numpy.ndarray>
08:28:36 INFO Done
08:28:36 ERROR applying transform <napari_cellseg3d.code_models.workers_utils.QuantileNormalization object at 0x714353fb7790>
Traceback (most recent call last):
File "/home/yul4024/miniforge3/envs/cellseg/lib/python3.9/site-packages/monai/transforms/transform.py", line 141, in apply_transform
return _apply_transform(transform, data, unpack_items, lazy, overrides, log_stats)
File "/home/yul4024/miniforge3/envs/cellseg/lib/python3.9/site-packages/monai/transforms/transform.py", line 98, in _apply_transform
return transform(data, lazy=lazy) if isinstance(transform, LazyTrait) else transform(data)
File "/home/yul4024/Downloads/CellSeg3D/napari_cellseg3d/code_models/workers_utils.py", line 240, in __call__
return utils.quantile_normalization(img)
File "/home/yul4024/Downloads/CellSeg3D/napari_cellseg3d/utils.py", line 599, in quantile_normalization
raise TypeError("image needs to be torch tensor or numpy array")
TypeError: image needs to be torch tensor or numpy array
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/home/yul4024/Downloads/CellSeg3D/napari_cellseg3d/code_models/worker_inference.py", line 973, in inference
input_image = self.load_layer()
File "/home/yul4024/Downloads/CellSeg3D/napari_cellseg3d/code_models/worker_inference.py", line 321, in load_layer
input_image = load_transforms(volume)
File "/home/yul4024/miniforge3/envs/cellseg/lib/python3.9/site-packages/monai/transforms/compose.py", line 335, in __call__
result = execute_compose(
File "/home/yul4024/miniforge3/envs/cellseg/lib/python3.9/site-packages/monai/transforms/compose.py", line 111, in execute_compose
data = apply_transform(
File "/home/yul4024/miniforge3/envs/cellseg/lib/python3.9/site-packages/monai/transforms/transform.py", line 171, in apply_transform
raise RuntimeError(f"applying transform {transform}") from e
RuntimeError: applying transform <napari_cellseg3d.code_models.workers_utils.QuantileNormalization object at 0x714353fb7790>
08:28:36 INFO --------------------
08:28:36 INFO Parameters summary :
08:28:36 INFO Model is : SegResNet
08:28:36 INFO Window inference is disabled
08:28:36 INFO Dataset loaded on cuda:0 device
08:28:36 INFO --------------------
08:28:36 INFO Loading layer
08:28:36 INFO Checking dimensions...
08:28:36 INFO
Worker finished at 08:28:36
08:28:36 INFO ********************
08:28:36 INFO Emptying cache...
08:28:36 INFO Attempt complete : Cache emptied
Hello @longyuxi,
Thanks for trying the plugin !
To me it seems your issues are due to using dask. While it would be a great addition, I'm afraid we do not currently support it in the plugin.
Converting (a crop) of your volume to a numpy array should fix these; depending on what you're trying to segment you could also downsample your images a bit to reduce the memory requirements.
(Just to be thorough, your first error is due to the dask implementation of reshape not having the "newshape" keyword. It's interesting that it is being re-routed to the dask implementation however. Your second error is simply due to the quantile normalization not accepting dask arrays.)
Let me know if you need any further help !
Best,
Cyril
Hello, since this is a week old I will go ahead and close it. Feel free to reopen if you need further help !