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9 part a adding test intensity normalisation transform #33

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wyli
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@wyli wyli commented Jan 21, 2020

  • merge master branch's testing code into 9-intensity-normalisation-transform
  • adding a unit test for intensity normalisation

ericspod and others added 7 commits January 17, 2020 12:11
Adding script to run unit tests and example test cases
* initial unit tests for 2d/3d unet
* unit tests update
 - triggering unit tests via github workflow
 - renamed testconvolutions.py to test_convolutions.py
 - test unet test cases as variables for readability
* initial unit tests for 2d/3d unet
* unit tests update
 - triggering unit tests via github workflow
 - renamed testconvolutions.py to test_convolutions.py
 - test unet test cases as variables for readability
* fixes cardiac example

* update example cardiac segmentation
an initial step towards #19
- revised to support both `[key]` and `key` as an input for apply_keys
- added `NumpyImageTestCase2D` and `TorchImageTestCase2D`
@wyli wyli requested a review from Nic-Ma January 21, 2020 13:45
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Have 3 comments inline, others look good to me.
Thanks.

- adding copyright notice
- validate user input before setting class member
- one line space after copyright
- testing multiple keys input data
@wyli wyli requested a review from Nic-Ma January 21, 2020 15:02
@Nic-Ma Nic-Ma merged commit e31ec10 into 9-intensity-normalisation-transform Jan 21, 2020
ericspod added a commit that referenced this pull request Jan 22, 2020
* [DLMED] implement intensity normalization transform

design according to our latest discussion:
1. input data is dict format with keys for fields.
2. only based on PyTorch and data shape is channel_last.

* 9 part a adding test intensity normalisation transform (#33)

* Adding script to run unit tests and example test cases (#29)

Adding script to run unit tests and example test cases

* initial unit tests for dice loss (#27)

* initial unit tests for 2d/3d unet
* unit tests update
 - triggering unit tests via github workflow
 - renamed testconvolutions.py to test_convolutions.py
 - test unet test cases as variables for readability

* initial unit tests for 2d/3d unet (#26)

* initial unit tests for 2d/3d unet
* unit tests update
 - triggering unit tests via github workflow
 - renamed testconvolutions.py to test_convolutions.py
 - test unet test cases as variables for readability

* 14 code examples of monai input data pipeline (#24)

* fixes cardiac example

* update example cardiac segmentation

* Create .gitlab-ci.yml (#30)

an initial step towards #19

* tests intensity normalizer

- revised to support both `[key]` and `key` as an input for apply_keys
- added `NumpyImageTestCase2D` and `TorchImageTestCase2D`

* style updates and new test cases:

- adding copyright notice
- validate user input before setting class member
- one line space after copyright
- testing multiple keys input data

Co-authored-by: Eric Kerfoot <[email protected]>
Co-authored-by: Isaac Yang <[email protected]>

* [DLMED] simplify intensity normalization transform for MVP

Co-authored-by: Wenqi Li <[email protected]>
Co-authored-by: Eric Kerfoot <[email protected]>
Co-authored-by: Isaac Yang <[email protected]>
@wyli wyli deleted the 9-part-a-adding-test-intensity-normalisation-transform branch April 6, 2020 13:35
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4 participants