build: bumped patch version for all imagej tools

segmentation/imagej-threshold-apply-tool/.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.5.1
+current_version = 0.5.2-dev0
 commit = True
 tag = False
 parse = (?P<major>\d+)\.(?P<minor>\d+)\.(?P<patch>\d+)(\-(?P<release>[a-z]+)(?P<dev>\d+))?

segmentation/imagej-threshold-apply-tool/README.md

@@ -1,4 +1,4 @@
-# ImageJ threshold apply (v0.5.1)
+# ImageJ threshold apply (v0.5.2-dev0)
 
 This plugin applies a constant manual threshold value to an input collection.
 (Thresholding)[https://en.wikipedia.org/wiki/Thresholding_(image_processing)] converts all pixel values in an image to either 1 or 0 depending on

segmentation/imagej-threshold-apply-tool/VERSION

@@ -1 +1 @@
-0.5.1
+0.5.2-dev0

segmentation/imagej-threshold-apply-tool/plugin.json

@@ -1,14 +1,14 @@
 {
   "name": "ImageJ threshold apply",
-  "version": "0.5.1",
+  "version": "0.5.2-dev0",
   "title": "ImageJ threshold apply",
   "description": "This plugin applies a constant or manual threshold to an input collection.",
   "author": "Nick Schaub ([email protected]), Anjali Taneja, Benjamin Houghton ([email protected]), Najib Ishaq ([email protected])",
   "institution": "National Center for Advancing Translational Sciences, National Institutes of Health",
   "repository": "https://github.com/polusai/image-tools",
   "website": "https://ncats.nih.gov/preclinical/core/informatics",
   "citation": "",
-  "containerId": "polusai/imagej-threshold-apply-tool:0.5.1",
+  "containerId": "polusai/imagej-threshold-apply-tool:0.5.2-dev0",
   "baseCommand": [
     "python3",
     "-m",

segmentation/imagej-threshold-apply-tool/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "polus-images-segmentation-imagej-threshold-apply"
-version = "0.5.1"
+version = "0.5.2-dev0"
 description = ""
 authors = [
     "Nick Schaub <[email protected]>",

segmentation/imagej-threshold-apply-tool/src/polus/images/segmentation/imagej_threshold_apply/__init__.py

@@ -1,7 +1,7 @@
 """Provides the ImageJ Threshold Apply tool."""
 
 
-__version__ = "0.5.1"
+__version__ = "0.5.2-dev0"
 
 
 import logging

segmentation/imagej-threshold-huang-tool/.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.5.1
+current_version = 0.5.2-dev0
 commit = True
 tag = False
 parse = (?P<major>\d+)\.(?P<minor>\d+)\.(?P<patch>\d+)(\-(?P<release>[a-z]+)(?P<dev>\d+))?

segmentation/imagej-threshold-huang-tool/README.md

@@ -1,4 +1,4 @@
-# ImageJ threshold huang (v0.5.1)
+# ImageJ threshold huang (v0.5.2-dev0)
 
 This plugin implements Huang's threshold method proposed in Image Thresholding by Minimizing the Measures of Fuzziness, Huang (1995).
 This method determines an optimal thresholding value such that the fuzziness measure between the original image and its binary version is minimized.

segmentation/imagej-threshold-huang-tool/VERSION

@@ -1 +1 @@
-0.5.1
+0.5.2-dev0

segmentation/imagej-threshold-huang-tool/plugin.json

@@ -1,14 +1,14 @@
 {
   "name": "ImageJ threshold huang",
-  "version": "0.5.1",
+  "version": "0.5.2-dev0",
   "title": "ImageJ threshold huang",
   "description": "This plugin implements Huang's threshold method by Huang Wang.",
   "author": "Nick Schaub ([email protected]), Anjali Taneja, Benjamin Houghton ([email protected]), Najib Ishaq ([email protected])",
   "institution": "National Center for Advancing Translational Sciences, National Institutes of Health",
   "repository": "https://github.com/polusai/image-tools",
   "website": "https://ncats.nih.gov/preclinical/core/informatics",
   "citation": "",
-  "containerId": "polusai/imagej-threshold-huang-tool:0.5.1",
+  "containerId": "polusai/imagej-threshold-huang-tool:0.5.2-dev0",
   "inputs": [
     {
       "name": "inpDir",

segmentation/imagej-threshold-huang-tool/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "polus-images-segmentation-imagej-threshold-huang"
-version = "0.5.1"
+version = "0.5.2-dev0"
 description = ""
 authors = [
     "Nick Schaub <[email protected]>",

segmentation/imagej-threshold-huang-tool/src/polus/images/segmentation/imagej_threshold_huang/__init__.py

@@ -1,7 +1,7 @@
 """Provides the ImageJ Threshold Huang tool."""
 
 
-__version__ = "0.5.1"
+__version__ = "0.5.2-dev0"
 
 
 import logging

segmentation/imagej-threshold-ij1-tool/.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.5.0
+current_version = 0.5.1-dev0
 commit = True
 tag = False
 parse = (?P<major>\d+)\.(?P<minor>\d+)\.(?P<patch>\d+)(\-(?P<release>[a-z]+)(?P<dev>\d+))?

segmentation/imagej-threshold-ij1-tool/README.md

@@ -1,4 +1,4 @@
-# ImageJ threshold huang (v0.5.0)
+# ImageJ threshold huang (v0.5.1-dev0)
 
 This plugin implements the [default thresholding method](https://imagej.net/plugins/auto-threshold#default) from ImageJ 1.x. The
 default method as explained by ImageJ is a variation of the IsoData algorithm.

segmentation/imagej-threshold-ij1-tool/VERSION

@@ -1 +1 @@
-0.5.0
+0.5.1-dev0

segmentation/imagej-threshold-ij1-tool/plugin.json

@@ -1,14 +1,14 @@
 {
   "name": "ImageJ threshold huang",
-  "version": "0.5.0",
+  "version": "0.5.1-dev0",
   "title": "ImageJ threshold huang",
   "description": "This plugin implements Huang's threshold method by Huang Wang.",
   "author": "Nick Schaub ([email protected]), Anjali Taneja, Benjamin Houghton ([email protected]), Najib Ishaq ([email protected])",
   "institution": "National Center for Advancing Translational Sciences, National Institutes of Health",
   "repository": "https://github.com/polusai/image-tools",
   "website": "https://ncats.nih.gov/preclinical/core/informatics",
   "citation": "",
-  "containerId": "polusai/imagej-threshold-huang-tool:0.5.0",
+  "containerId": "polusai/imagej-threshold-huang-tool:0.5.1-dev0",
   "inputs": [
     {
       "name": "inpDir",

segmentation/imagej-threshold-ij1-tool/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "polus-images-segmentation-imagej-threshold-ij1"
-version = "0.5.0"
+version = "0.5.1-dev0"
 description = ""
 authors = [
     "Nick Schaub <[email protected]>",

segmentation/imagej-threshold-ij1-tool/src/polus/images/segmentation/imagej_threshold_ij1/__init__.py

@@ -1,7 +1,7 @@
 """Provides the ImageJ Threshold IJ1 tool."""
 
 
-__version__ = "0.5.0"
+__version__ = "0.5.1-dev0"
 
 
 import logging

segmentation/imagej-threshold-intermodes-tool/.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.5.0
+current_version = 0.5.1-dev0
 commit = True
 tag = False
 parse = (?P<major>\d+)\.(?P<minor>\d+)\.(?P<patch>\d+)(\-(?P<release>[a-z]+)(?P<dev>\d+))?

segmentation/imagej-threshold-intermodes-tool/README.md

@@ -1,4 +1,4 @@
-# ImageJ threshold intermodes (v0.5.0)
+# ImageJ threshold intermodes (v0.5.1-dev0)
 
 As described by [ImageJ](https://imagej.net/plugins/auto-threshold#intermodes) this plugin implements the threshold method described in
 Prewitt, J. M. S., & Mendelsohn, M. L. (2006). THE ANALYSIS OF CELL IMAGES*.

segmentation/imagej-threshold-intermodes-tool/VERSION

@@ -1 +1 @@
-0.5.0
+0.5.1-dev0

segmentation/imagej-threshold-intermodes-tool/plugin.json

@@ -1,14 +1,14 @@
 {
   "name": "ImageJ threshold intermodes",
-  "version": "0.5.0",
+  "version": "0.5.1-dev0",
   "title": "ImageJ threshold intermodes",
   "description": "This plugin implements the Intermodes thresholding operation, where it is assumed the input image has bimodal distribution of pixel values",
   "author": "Nick Schaub ([email protected]), Anjali Taneja, Benjamin Houghton ([email protected]), Najib Ishaq ([email protected])",
   "institution": "National Center for Advancing Translational Sciences, National Institutes of Health",
   "repository": "https://github.com/polusai/image-tools",
   "website": "https://ncats.nih.gov/preclinical/core/informatics",
   "citation": "",
-  "containerId": "polusai/imagej-threshold-intermodes-tool:0.5.0",
+  "containerId": "polusai/imagej-threshold-intermodes-tool:0.5.1-dev0",
   "inputs": [
     {
       "name": "inpDir",

segmentation/imagej-threshold-intermodes-tool/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "polus-images-segmentation-imagej-threshold-intermodes"
-version = "0.5.0"
+version = "0.5.1-dev0"
 description = ""
 authors = [
     "Nick Schaub <[email protected]>",

segmentation/imagej-threshold-intermodes-tool/src/polus/images/segmentation/imagej_threshold_intermodes/__init__.py

@@ -1,7 +1,7 @@
 """Provides the ImageJ Threshold intermodes tool."""
 
 
-__version__ = "0.5.0"
+__version__ = "0.5.1-dev0"
 
 
 import logging

segmentation/imagej-threshold-isodata-tool/.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.5.0
+current_version = 0.5.1-dev0
 commit = True
 tag = False
 parse = (?P<major>\d+)\.(?P<minor>\d+)\.(?P<patch>\d+)(\-(?P<release>[a-z]+)(?P<dev>\d+))?

segmentation/imagej-threshold-isodata-tool/README.md

@@ -1,4 +1,4 @@
-# ImageJ threshold isodata (v0.5.0)
+# ImageJ threshold isodata (v0.5.1-dev0)
 
 Iterative procedure based on the isodata algorithm of:  Picture Thresholding
 Using an Iterative Selection Method. (1978). IEEE Transactions on Systems, Man,

segmentation/imagej-threshold-isodata-tool/VERSION

@@ -1 +1 @@
-0.5.0
+0.5.1-dev0

segmentation/imagej-threshold-isodata-tool/plugin.json

@@ -1,14 +1,14 @@
 {
   "name": "ImageJ threshold isodata",
-  "version": "0.5.0",
+  "version": "0.5.1-dev0",
   "title": "ImageJ threshold isodata",
   "description": "This plugin implements the isodata thresholding operation",
   "author": "Nick Schaub ([email protected]), Anjali Taneja, Benjamin Houghton ([email protected]), Najib Ishaq ([email protected])",
   "institution": "National Center for Advancing Translational Sciences, National Institutes of Health",
   "repository": "https://github.com/polusai/image-tools",
   "website": "https://ncats.nih.gov/preclinical/core/informatics",
   "citation": "",
-  "containerId": "polusai/imagej-threshold-isodata-tool:0.5.0",
+  "containerId": "polusai/imagej-threshold-isodata-tool:0.5.1-dev0",
   "inputs": [
     {
       "name": "inpDir",

segmentation/imagej-threshold-isodata-tool/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "polus-images-segmentation-imagej-threshold-isodata"
-version = "0.5.0"
+version = "0.5.1-dev0"
 description = ""
 authors = [
     "Nick Schaub <[email protected]>",

segmentation/imagej-threshold-isodata-tool/src/polus/images/segmentation/imagej_threshold_isodata/__init__.py

@@ -1,7 +1,7 @@
 """Provides the ImageJ Threshold isodata tool."""
 
 
-__version__ = "0.5.0"
+__version__ = "0.5.1-dev0"
 
 
 import logging

segmentation/imagej-threshold-li-tool/.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.5.0
+current_version = 0.5.1-dev0
 commit = True
 tag = False
 parse = (?P<major>\d+)\.(?P<minor>\d+)\.(?P<patch>\d+)(\-(?P<release>[a-z]+)(?P<dev>\d+))?

segmentation/imagej-threshold-li-tool/README.md

@@ -1,4 +1,4 @@
-# ImageJ threshold li (v0.5.0)
+# ImageJ threshold li (v0.5.1-dev0)
 
 Implements Li’s Minimum Cross Entropy thresholding method based on the iterative
 version of the algorithm. This is an iterative method to find the threshold

segmentation/imagej-threshold-li-tool/VERSION

@@ -1 +1 @@
-0.5.0
+0.5.1-dev0

segmentation/imagej-threshold-li-tool/plugin.json

@@ -1,14 +1,14 @@
 {
   "name": "ImageJ threshold li",
-  "version": "0.5.0",
+  "version": "0.5.1-dev0",
   "title": "ImageJ threshold li",
   "description": "This plugin implements the li thresholding operation",
   "author": "Nick Schaub ([email protected]), Anjali Taneja, Benjamin Houghton ([email protected]), Najib Ishaq ([email protected])",
   "institution": "National Center for Advancing Translational Sciences, National Institutes of Health",
   "repository": "https://github.com/polusai/image-tools",
   "website": "https://ncats.nih.gov/preclinical/core/informatics",
   "citation": "",
-  "containerId": "polusai/imagej-threshold-li-tool:0.5.0",
+  "containerId": "polusai/imagej-threshold-li-tool:0.5.1-dev0",
   "inputs": [
     {
       "name": "inpDir",

segmentation/imagej-threshold-li-tool/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "polus-images-segmentation-imagej-threshold-li"
-version = "0.5.0"
+version = "0.5.1-dev0"
 description = ""
 authors = [
     "Nick Schaub <[email protected]>",

segmentation/imagej-threshold-li-tool/src/polus/images/segmentation/imagej_threshold_li/__init__.py

@@ -1,7 +1,7 @@
 """Provides the ImageJ Threshold li tool."""
 
 
-__version__ = "0.5.0"
+__version__ = "0.5.1-dev0"
 
 
 import logging

segmentation/imagej-threshold-maxentropy-tool/.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.5.0
+current_version = 0.5.1-dev0
 commit = True
 tag = False
 parse = (?P<major>\d+)\.(?P<minor>\d+)\.(?P<patch>\d+)(\-(?P<release>[a-z]+)(?P<dev>\d+))?

segmentation/imagej-threshold-maxentropy-tool/README.md

@@ -1,4 +1,4 @@
-# ImageJ threshold maxentropy (v0.5.0)
+# ImageJ threshold maxentropy (v0.5.1-dev0)
 
 Implements Kapur-Sahoo-Wong (Maximum Entropy) thresholding method as
 described in: Kapur, J. N., Sahoo, P. K., & Wong, A. K. C. (1985). A new method

segmentation/imagej-threshold-maxentropy-tool/VERSION

@@ -1 +1 @@
-0.5.0
+0.5.1-dev0

segmentation/imagej-threshold-maxentropy-tool/plugin.json

@@ -1,14 +1,14 @@
 {
   "name": "ImageJ threshold maxentropy",
-  "version": "0.5.0",
+  "version": "0.5.1-dev0",
   "title": "ImageJ threshold maxentropy",
   "description": "This plugin implements the maxentropy thresholding operation",
   "author": "Nick Schaub ([email protected]), Anjali Taneja, Benjamin Houghton ([email protected]), Najib Ishaq ([email protected])",
   "institution": "National Center for Advancing Translational Sciences, National Institutes of Health",
   "repository": "https://github.com/polusai/image-tools",
   "website": "https://ncats.nih.gov/preclinical/core/informatics",
   "citation": "",
-  "containerId": "polusai/imagej-threshold-maxentropy-tool:0.5.0",
+  "containerId": "polusai/imagej-threshold-maxentropy-tool:0.5.1-dev0",
   "inputs": [
     {
       "name": "inpDir",

segmentation/imagej-threshold-maxentropy-tool/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "polus-images-segmentation-imagej-threshold-maxentropy"
-version = "0.5.0"
+version = "0.5.1-dev0"
 description = ""
 authors = [
     "Nick Schaub <[email protected]>",

segmentation/imagej-threshold-maxentropy-tool/src/polus/images/segmentation/imagej_threshold_maxentropy/__init__.py

@@ -1,7 +1,7 @@
 """Provides the ImageJ Threshold li tool."""
 
 
-__version__ = "0.5.0"
+__version__ = "0.5.1-dev0"
 
 
 import logging

segmentation/imagej-threshold-maxlikelihood-tool/.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.5.0
+current_version = 0.5.1-dev0
 commit = True
 tag = False
 parse = (?P<major>\d+)\.(?P<minor>\d+)\.(?P<patch>\d+)(\-(?P<release>[a-z]+)(?P<dev>\d+))?

segmentation/imagej-threshold-maxlikelihood-tool/README.md

@@ -1,4 +1,4 @@
-# ImageJ threshold maxlikelihood (v0.5.0)
+# ImageJ threshold maxlikelihood (v0.5.1-dev0)
 
 Implements a maximum likelihood threshold method using the [EM algorithm](https://en.wikipedia.org/wiki/Expectation%E2%80%93maximization_algorithm)
 by Dempster, Laird, Rubin and Glasbey:

segmentation/imagej-threshold-maxlikelihood-tool/VERSION

@@ -1 +1 @@
-0.5.0
+0.5.1-dev0

segmentation/imagej-threshold-maxlikelihood-tool/plugin.json

@@ -1,14 +1,14 @@
 {
   "name": "ImageJ threshold maxlikelihood",
-  "version": "0.5.0",
+  "version": "0.5.1-dev0",
   "title": "ImageJ threshold maxlikelihood",
   "description": "This plugin implements the maxlikelihood thresholding operation",
   "author": "Nick Schaub ([email protected]), Anjali Taneja, Benjamin Houghton ([email protected]), Najib Ishaq ([email protected])",
   "institution": "National Center for Advancing Translational Sciences, National Institutes of Health",
   "repository": "https://github.com/polusai/image-tools",
   "website": "https://ncats.nih.gov/preclinical/core/informatics",
   "citation": "",
-  "containerId": "polusai/imagej-threshold-maxlikelihood-tool:0.5.0",
+  "containerId": "polusai/imagej-threshold-maxlikelihood-tool:0.5.1-dev0",
   "inputs": [
     {
       "name": "inpDir",

segmentation/imagej-threshold-maxlikelihood-tool/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "polus-images-segmentation-imagej-threshold-maxlikelihood"
-version = "0.5.0"
+version = "0.5.1-dev0"
 description = ""
 authors = [
     "Nick Schaub <[email protected]>",

segmentation/imagej-threshold-maxlikelihood-tool/src/polus/images/segmentation/imagej_threshold_maxlikelihood/__init__.py

@@ -1,7 +1,7 @@
 """Provides the ImageJ Threshold li tool."""
 
 
-__version__ = "0.5.0"
+__version__ = "0.5.1-dev0"
 
 
 import logging