post-rebase (#38)

* removed old structure set code

* fixed label handling in image statistics computation

* fixed label handling in image statistics computation

* [In Progress] Adding documentation to ops.py

* added support for dynamic path specification in writers

* image CSV loader now accepts pandas DataFrames

* fixed indentation error

* fixed index column handling in ImageCSVLoader

* Revert "fixed index column handling in ImageCSVLoader"

This reverts commit ac9b8d1.

* fixed index column handling in ImageCSVLoader

* fixed index column handling in ImageCSVLoader

* ImageCSVLoader now returns correct keys

* ImageCSVLoader now correctly handles globbing in paths

* more informative exception handling in pipeline

* pipeline can now warn on error instead of raising exception

* [Docs] Cleaned up extra whitespace in ops.py

* Added convenience method to get all ops in a pipeline

* Fix empty array check in structure set conversion

* Fix segmentation to label image conversion

* Update README.md

* Fix spurious mixin in ops

* Fix type error when passing Numpy array to rotate

* [Bugfix] Fix slice number rounding when generating a mask from RTSTRUCT

* Fix crop size issue in crop_to_bounding_box

* Make imports easier

* Improved handling of regular expressions in structure set

* Fix slice matching issue when generating binary mask from RTStruct

* Fix binary mask generation from RTStruct when missing labels are present

* little updates

* added seg.nrrd compatibility

* supports RTSTRUCT processing without roi_names

* Fixed contour (RTSTRUCT) handling to rasterize multiple contours better.

* Fixed contour (RTSTRUCT) handling to rasterize multiple contours better.

* fixed structureset.py:148

* RT dose pipeline completed and tested. Error in segmentation not resolved

* PET readability added

* PET readability added

* Head-Neck-PET-CT pipeline + `read_dicom_auto`

* final pipeline working for doses and PET

* corrected the view

* reading in sitk format from beginning

* Completed PET overlay

* Modified RT dose, pipeline working for PET_CT quebec dataset

* Added DataGraph, now fetching subset of dataset is supported using graph query

* added crawl.py

* Introduced changes in DataGraph. Made the pipeline fully general. Made wrapper classes

* Rectified some bugs, added reference to rtplan in the crawler

* Now missing RTDOSE references are completed by RTPLAN

* small change

* Fixed dataset.csv writing issues

* major refactoring

* more refactoring

* Update radcure_simple.py

* Update loaders.py

* Update pet.py

* Delete .DS_Store

* Delete .DS_Store

* Delete .DS_Store

* Delete .DS_Store

* Delete .DS_Store

* Delete .DS_Store

* Delete .DS_Store

* ignore .DS_Store

* Update README.md

* quick README under ops

* tcia_sample

* example bash script with path parsing, fixed reference_frame

* housekeeping

* fixed dataset.csv

* sanity changes before purging dev-20200414

* Added test autopipeline and modalities, solved some autopipeline bugs, read_dicom_series and pet now supports series_id


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* PT/RTDOSE metadata to csv


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* fixed some bugs in autopipeline.py


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* now the pipeline saves on exit


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* deleted data


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* now checks for existing subject id


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* uncommented one line pytest


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* uncommented one line pytest


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* self.existing, dataset.csv fixed (#10)

* Added test autopipeline and modalities, solved some autopipeline bugs, read_dicom_series and pet now supports series_id

* PT/RTDOSE metadata to csv

* fixed some bugs in autopipeline.py

* now the pipeline saves on exit

* deleted data

* now checks for existing subject id

* uncommented one line pytest

* uncommented one line pytest

Co-authored-by: Vishwesh <vishweshramanathan@gmail.com>

* Added dataset class which can load from nrrds or directly from the dataset and convert to pytorch dataset


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* Create build-ci.yml

* Update build-ci.yml

* Update requirements.txt

* bug fixes_1.0


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* test and autopipe fixed


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* bug fixes 2


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* bug fixes 2


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* added visualizations and some more bug fixes


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* Create manual-test.yml

* Update build-ci.yml

* Update manual-test.yml

* PR tests - macos/ubuntu failing (#13)

* Added test autopipeline and modalities, solved some autopipeline bugs, read_dicom_series and pet now supports series_id

* PT/RTDOSE metadata to csv

* fixed some bugs in autopipeline.py

* now the pipeline saves on exit

* deleted data

* now checks for existing subject id

* uncommented one line pytest

* uncommented one line pytest

* Added dataset class which can load from nrrds or directly from the dataset and convert to pytorch dataset

* bug fixes_1.0

* test and autopipe fixed

* bug fixes 2

* fixed pipeline tests

* clean tests

* added workflow

* yml

* yml

* matplotlib

* trying other patient to avoid memoryerror

* set roi_names to avoid memoryerror

* cave

* indents

* Update manual-test.yml

Co-authored-by: Vishwesh <vishweshramanathan@gmail.com>

* fixed bugs regarding multiple connections, saving of metadata and loading of metadata


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* small bug fix


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* added demo.py


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* Ready for

* Create main.yml (#15)

* Changed dataset class returns


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* fix conflicts


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* fixed test autopipe


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* merging new features (#16)

* Added test autopipeline and modalities, solved some autopipeline bugs, read_dicom_series and pet now supports series_id

* PT/RTDOSE metadata to csv

* fixed some bugs in autopipeline.py

* now the pipeline saves on exit

* deleted data

* now checks for existing subject id

* uncommented one line pytest

* uncommented one line pytest

* Added dataset class which can load from nrrds or directly from the dataset and convert to pytorch dataset

* bug fixes_1.0

* test and autopipe fixed

* bug fixes 2

* bug fixes 2

* added visualizations and some more bug fixes

* fixed bugs regarding multiple connections, saving of metadata and loading of metadata

* small bug fix

* added demo.py

* Changed dataset class returns

* fix conflicts

* fixed test autopipe

Co-authored-by: Vishwesh <vishweshramanathan@gmail.com>

* fix path backslash issues


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* fix path backslashes (#17)

* Added test autopipeline and modalities, solved some autopipeline bugs, read_dicom_series and pet now supports series_id

* PT/RTDOSE metadata to csv

* fixed some bugs in autopipeline.py

* now the pipeline saves on exit

* deleted data

* now checks for existing subject id

* uncommented one line pytest

* uncommented one line pytest

* Added dataset class which can load from nrrds or directly from the dataset and convert to pytorch dataset

* bug fixes_1.0

* test and autopipe fixed

* bug fixes 2

* bug fixes 2

* added visualizations and some more bug fixes

* fixed bugs regarding multiple connections, saving of metadata and loading of metadata

* small bug fix

* added demo.py

* Changed dataset class returns

* fix conflicts

* fixed test autopipe

* fix path backslash issues

Co-authored-by: Vishwesh <vishweshramanathan@gmail.com>

* Update main.yml

* Update main.yml

* Update README.md

* Update main.yml (#18)

* Update main.yml

* Update requirements.txt

* Update main.yml

* Update main.yml

* build binary/dist

* removed linter

* Update setup.py

* Update README.md

* Update README.md (#19)

* Update README.md

* added tests for Dataset class


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* added tests for Dataset class


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* Create LICENSE (#20)

* Create LICENSE

* Update setup.py

* Seg.nrrd quick fix

* Minor bug fixes


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* test fix


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* Added demo


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* Update setup.py (#23)



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* updated README


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* Update README.md (#24)



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* preliminary MRI functionality (MR-RTSTRUCT pairs)


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* Skim2257 quick fix (#26)

* Updated crawler to force String on all meta fields

* Update setup.py

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* first commit


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* removed test files, changed gitignore


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* changed file directory structure for imageautooutput


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* split mask up into each contour


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* change kwargs in put for basesubjectwriter


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* still kinda failing...


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* brought back basesubjectwriter


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* .imgtools directory


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* changed absolute paths to relative paths


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* changed os.path.join to pathlib.Path.as_posix()


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* removed unused cv2 import


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* removed cv2 import


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* appened is deprecated, changed to concat


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* debug print


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* removed debug print


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* added sparse mask class and generating function


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* testing out sparse mask


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* funky NaN problem


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* commented sparse mask


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* overwrite all subjects


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* space


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* overwrite false


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* metadata stuffs


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* metadata in dataset.csv


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* added modalities, num rtstruct and pixel size to metadata


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* metadata bugfix


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* a


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* fixed wrong variable names for metadata stuff


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* fixed pathlib float error


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* relative paths and output folder paths for dataset.csv


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* put metadata stuff into a util file


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* deal with empty metadata


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* messing around with sparse mask


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* tried to save sparse mask, did some stuff with nnunet output format


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* compliant with nnunet directory structure


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* CLI Interface, argparse moved to utils


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* fixed formatting problems with folder names


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* train test split


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* train size and random state optional


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* merge conflicts


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* changed warnings to not interrupt


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* changed to warnings.warn for generate_sparse_mask


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* merge


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* resolving conflicts?


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* args


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* changes for roi names as a dict


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* added regex dictionary option for non nnunet runs


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* sparse mask global labelling for contour name: index


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* got rid of file_name_convention stuff


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* conflicts resolved


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* yaml thing


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* added list capabilities for the roi names dictionary


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* dataset.json for nnunet


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* CLI "autonew"


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* changed all mutable defaults to None


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* moved autotest changes to autopipeline and addede a few CLI args


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* getting ready for merge to live


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* test_components, test_modalities works with new AutoPipeline


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* overwrite changes and error fix for nan paths again


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* fixed if statement


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* joblib parallel


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* warnings for missing patients


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* summary messages


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* updated, passing tests. Updated version to 0.4


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* update test


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* yaml path cli


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* yaml error check


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* pandas error


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* Fixed read_dicom_auto


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* skips series check if seris is None


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* updated readme to reflect v0.4 changes


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* updated readme


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* minor change


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* remove .idea


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* remote .idea


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* git ignore


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* refactor nnunetutils to nnunet


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* updated versions

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* new experimental segmentation class

* minor fixes in segmentation module

* matching roi names in StructureSet.to_segmentation is now case-insensitive

* StructureSet now correctly handles ROIs with no contour data

* Segmentation object now correctly handles indexing

* Fix empty array check in structure set conversion

* [Bugfix] Fix slice number rounding when generating a mask from RTSTRUCT

* Fix slice matching issue when generating binary mask from RTStruct

* CLI "autonew"


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* changed all mutable defaults to None


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* remote .idea


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* git ignore


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Co-authored-by: mkazmier <mkazmierski.poznan@gmail.com>
Co-authored-by: Minoru Nakano <minoru.nakano@gmail.com>
Co-authored-by: Sejin Kim <sejinkim@uhnslurmbuildbox.uhnh4h.cluster>
Co-authored-by: Sejin Kim <sejinkim@node88.uhnh4h.cluster>
Co-authored-by: Sejin Kim <sejinkim@node40.uhnh4h.cluster>
Co-authored-by: Sejin Kim <sejinkim@node97.uhnh4h.cluster>
Co-authored-by: Sejin Kim <sejinkim@h4huhnlogin2.uhnh4h.cluster>
Co-authored-by: Vishwesh Ramanathan <vishwesh@Vishweshs-Air.uhn.ca>
Co-authored-by: Sejin Kim <sejinkim@node38.uhnh4h.cluster>
Co-authored-by: Vishwesh Ramanathan <ramanav@node49.uhnh4h.cluster>
Co-authored-by: Vishwesh Ramanathan <ramanav@node53.uhnh4h.cluster>
Co-authored-by: Vishwesh <vishweshramanathan@gmail.com>
Co-authored-by: Benjamin Haibe-Kains <bhaibeka@bhaibek1.uhn.ca>
Co-authored-by: Sejin Kim <sejinkim@node89.uhnh4h.cluster>
Co-authored-by: Vishwesh Ramanathan <vishwesh@Vishweshs-MacBook-Air.local>
Co-authored-by: fishingguy456 <qukevin99@gmail.com>
Co-authored-by: Kevin Qu <kqu@uhnslurmbuildbox.uhnh4h.cluster>
Co-authored-by: Kevin Qu <kqu@node90.uhnh4h.cluster>

.gitignore

@@ -5,6 +5,9 @@ examples/adsf.py
 #vscode files
 /.idea
 
+#vscode files
+/.idea
+
 # data
 data
 examples/data/tcia_n*