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Use replication padding in Median filter#5329

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wyli merged 5 commits intoProject-MONAI:devfrom
dzenanz:properMedian
Oct 14, 2022
Merged

Use replication padding in Median filter#5329
wyli merged 5 commits intoProject-MONAI:devfrom
dzenanz:properMedian

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@dzenanz dzenanz commented Oct 13, 2022

Ref #5264. Follow-up to #5307. This is a more normal, intuitive variant of median filtering.

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dzenanz commented Oct 13, 2022 •
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Docs for padding are the same in both version 1.9 and 1.12. Yet torch versions 1.9 and lower complain. Ideas?

======================================================================
FAIL: test_value_2 (tests.test_median_smoothd.TestMedianSmoothd)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/opt/hostedtoolcache/Python/3.8.14/x64/lib/python3.8/site-packages/parameterized/parameterized.py", line 533, in standalone_func
    return func(*(a + p.args), **p.kwargs)
  File "/home/runner/work/MONAI/MONAI/tests/test_median_smoothd.py", line 58, in test_value
    result = MedianSmoothd(**arguments)(image)
  File "/home/runner/work/MONAI/MONAI/monai/transforms/intensity/dictionary.py", line 1020, in __call__
    d[key] = self.converter(d[key])
  File "/home/runner/work/MONAI/MONAI/monai/transforms/intensity/array.py", line 1164, in __call__
    out_t: torch.Tensor = median_filter_instance(img_t)
  File "/opt/hostedtoolcache/Python/3.8.14/x64/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/runner/work/MONAI/MONAI/monai/networks/layers/simplelayers.py", line 555, in forward
    x = median_filter(x, kernel=self.kernel, spatial_dims=self.spatial_dims)
  File "/home/runner/work/MONAI/MONAI/monai/networks/layers/simplelayers.py", line 505, in median_filter
    padded_input: torch.Tensor = F.pad(in_tensor, pad=padding, mode="replicate")
  File "/opt/hostedtoolcache/Python/3.8.14/x64/lib/python3.8/site-packages/torch/nn/functional.py", line 4157, in _pad
    assert len(pad) == 2, "3D tensors expect 2 values for padding"
AssertionError: 3D tensors expect 2 values for padding

======================================================================
FAIL: test_value_3 (tests.test_median_smoothd.TestMedianSmoothd)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/opt/hostedtoolcache/Python/3.8.14/x64/lib/python3.8/site-packages/parameterized/parameterized.py", line 533, in standalone_func
    return func(*(a + p.args), **p.kwargs)
  File "/home/runner/work/MONAI/MONAI/tests/test_median_smoothd.py", line 58, in test_value
    result = MedianSmoothd(**arguments)(image)
  File "/home/runner/work/MONAI/MONAI/monai/transforms/intensity/dictionary.py", line 1020, in __call__
    d[key] = self.converter(d[key])
  File "/home/runner/work/MONAI/MONAI/monai/transforms/intensity/array.py", line 1164, in __call__
    out_t: torch.Tensor = median_filter_instance(img_t)
  File "/opt/hostedtoolcache/Python/3.8.14/x64/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/runner/work/MONAI/MONAI/monai/networks/layers/simplelayers.py", line 555, in forward
    x = median_filter(x, kernel=self.kernel, spatial_dims=self.spatial_dims)
  File "/home/runner/work/MONAI/MONAI/monai/networks/layers/simplelayers.py", line 505, in median_filter
    padded_input: torch.Tensor = F.pad(in_tensor, pad=padding, mode="replicate")
  File "/opt/hostedtoolcache/Python/3.8.14/x64/lib/python3.8/site-packages/torch/nn/functional.py", line 4168, in _pad
    assert len(pad) == 4, "4D tensors expect 4 values for padding"
AssertionError: 4D tensors expect 4 values for padding

@dzenanz
Use replication padding in Median filter
a825531 
By making a contribution to this project, I certify that:

(a) The contribution was created in whole or in part by me and I
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    indicated in the file; or

(b) The contribution is based upon previous work that, to the best
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Signed-off-by: Dženan Zukić <[email protected]>
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dzenanz commented Oct 14, 2022

@wyli any suggestions? Or take over the PR?

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wyli commented Oct 14, 2022 •
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sure @dzenanz, it should be just minor issues I 'll modify the PR directly...

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wyli commented Oct 14, 2022

/build

@wyli wyli enabled auto-merge (squash) October 14, 2022 18:50
@wyli wyli merged commit e081510 into Project-MONAI:dev Oct 14, 2022
@dzenanz dzenanz deleted the properMedian branch October 14, 2022 21:30
bhashemian pushed a commit to JHancox/MONAI that referenced this pull request Oct 20, 2022
@dzenanz @wyli @bhashemian
Use replication padding in Median filter (Project-MONAI#5329)
6426ed0 
Ref Project-MONAI#5264. Follow-up to Project-MONAI#5307. This is a more normal, intuitive variant
of median filtering.

Signed-off-by: Dženan Zukić <[email protected]>
Signed-off-by: Wenqi Li <[email protected]>
Co-authored-by: Wenqi Li <[email protected]>
Co-authored-by: Wenqi Li <[email protected]>
Signed-off-by: Behrooz <[email protected]>
wyli added a commit that referenced this pull request Oct 24, 2022
@dzenanz @wyli
Use replication padding in Median filter (#5329)
aed8fe5 
Ref #5264. Follow-up to #5307. This is a more normal, intuitive variant
of median filtering.

Signed-off-by: Dženan Zukić <[email protected]>
Signed-off-by: Wenqi Li <[email protected]>
Co-authored-by: Wenqi Li <[email protected]>
Co-authored-by: Wenqi Li <[email protected]>
wyli added a commit that referenced this pull request Oct 24, 2022
@dzenanz @wyli
Use replication padding in Median filter (#5329)
e33b2ac 
Ref #5264. Follow-up to #5307. This is a more normal, intuitive variant
of median filtering.

Signed-off-by: Dženan Zukić <[email protected]>
Signed-off-by: Wenqi Li <[email protected]>
Co-authored-by: Wenqi Li <[email protected]>
Co-authored-by: Wenqi Li <[email protected]>
KumoLiu pushed a commit that referenced this pull request Nov 2, 2022
@dzenanz @wyli @KumoLiu
Use replication padding in Median filter (#5329)
615a43b 
Ref #5264. Follow-up to #5307. This is a more normal, intuitive variant
of median filtering.

Signed-off-by: Dženan Zukić <[email protected]>
Signed-off-by: Wenqi Li <[email protected]>
Co-authored-by: Wenqi Li <[email protected]>
Co-authored-by: Wenqi Li <[email protected]>
Signed-off-by: KumoLiu <[email protected]>
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