PolusAI · vanlam2308 · Mar 19, 2026
@@ -0,0 +1,16 @@
+[bumpversion]
+current_version = 0.3.6
+commit = False
+tag = False
+
+[bumpversion:file:VERSION]
+
+[bumpversion:file:pyproject.toml]
+search = version = "{current_version}"
+replace = version = "{new_version}"
+
+[bumpversion:file:plugin.json]
+
+[bumpversion:file:ict.yaml]
+
+[bumpversion:file:imageregistration.cwl]
@@ -1,21 +1,16 @@
-
-FROM polusai/bfio:2.1.9
-
-ARG EXEC_DIR="/opt/executables"
-ARG DATA_DIR="/data"
-
-RUN mkdir -p ${EXEC_DIR} \
-    && mkdir -p ${DATA_DIR}/inputs \
-    && mkdir ${DATA_DIR}/outputs
-
-RUN apt-get update && \
-    apt-get -y install libglib2.0-0
-
-COPY src ${EXEC_DIR}/
+# Build from repo root (monorepo) or from this tool directory — both work.
+FROM polusai/bfio:2.5.0
+ENV EXEC_DIR="/opt/executables" POLUS_IMG_EXT=".ome.tif" POLUS_TAB_EXT=".csv" POLUS_LOG="INFO"
 WORKDIR ${EXEC_DIR}
-
-RUN pip3 install -r ${EXEC_DIR}/requirements.txt --no-cache-dir
-
-COPY VERSION /
-
-ENTRYPOINT ["python3", "/opt/executables/main.py"]
+ENV TOOL_DIR="transforms/images/polus-image-registration-plugin"
+RUN mkdir -p image-tools
+COPY . ${EXEC_DIR}/image-tools
+RUN apt-get update && apt-get install -y --no-install-recommends libglib2.0-0 \
+  && rm -rf /var/lib/apt/lists/*
+RUN pip3 install -U pip setuptools wheel \
+  && python3 -c 'import sys; assert sys.version_info>=(3,11)' \
+  && R="${EXEC_DIR}/image-tools" && M="$R/$TOOL_DIR" \
+  && if [ -f "$M/pyproject.toml" ]; then pip3 install --no-cache-dir "$M"; \
+     else pip3 install --no-cache-dir "$R"; fi
+ENTRYPOINT ["python3", "-m", "main"]
+CMD ["--help"]
@@ -1,60 +1,60 @@
 # Polus Projective Transformation Image Registration Plugin
 
-WIPP Plugin Title : Image Registration Plugin 
+WIPP Plugin Title : Image Registration Plugin
 
 Contact [Gauhar Bains](mailto:gauhar.bains@labshare.org) for more information.
 
 For more information on WIPP, visit the [official WIPP page](https://isg.nist.gov/deepzoomweb/software/wipp).
 
 ## Description
 
-This plugin registers an image collection. First it parses the image collection using `parser.py` into registration sets. Each registration set consists of: moving image, template image, similiar transformation images. The registration algorithm(explained in the next section, can be found in `image_registration.py`) registers the moving image with template image and stores the transformation required to do so. This stored transformation is used to transform each image in similar transformation list. 
+This plugin registers an image collection. First it parses the image collection using `parser.py` into registration sets. Each registration set consists of: moving image, template image, similiar transformation images. The registration algorithm(explained in the next section, can be found in `image_registration.py`) registers the moving image with template image and stores the transformation required to do so. This stored transformation is used to transform each image in similar transformation list.
 
 ## Algorithm
 
 ### To do
-1. Find a better way to handle poorly correlated transforms. 
+1. Find a better way to handle poorly correlated transforms.
 2. Find a more scalable approach to do rough transformation. The algorithm has been tested on images of size around 1.2 Gigapixel but a better approach may be needed for images significantly larger than these.
 
-### Parsing 
-The parsing algorithm uses the functions from the `file_pattern utility`. It takes the following inputs : Filename pattern, registration variable, similar transformation variable. The registration variable helps determine the moving and the template images where as the similar transformation variable helps determine the similar transformation images. Note: The code produces the expected output when len(registration_variable)==len(similarity_variable)==1. The code will NOT spit out an error when the more than one variable is passed as registration or similarity variable, but additional testing needs to be done for this usecase.  
+### Parsing
+The parsing algorithm uses the functions from the `file_pattern utility`. It takes the following inputs : Filename pattern, registration variable, similar transformation variable. The registration variable helps determine the moving and the template images where as the similar transformation variable helps determine the similar transformation images. Note: The code produces the expected output when len(registration_variable)==len(similarity_variable)==1. The code will NOT spit out an error when the more than one variable is passed as registration or similarity variable, but additional testing needs to be done for this usecase.
 
-Some sample text files can be found in the examples folder. Short example shown below:    
+Some sample text files can be found in the examples folder. Short example shown below:
 
-Parsing example :   
-
-`Inputs:`  
-Filepattern :   `x{xxx}_y{yyy}_z{zzz}_c{ccc}_t{ttt}.ome.tif`  
-Registration_variable :  `t`   
-similar_transformation_variable : `c`  
-template_ :  `x001_y001_z001_c001_t001.ome.tif`    
+Parsing example :
 
-`Output set 1 :`   
-Template Image:  x001_y001_z001_c001_t001.ome.tif  
-Moving Image:  x001_y001_z001_c001_t002.ome.tif  
-Similar Transformation Images :   [ x001_y001_z001_c002_t002.ome.tif , x001_y001_z001_c003_t002.ome.tif ]  
+`Inputs:`
+Filepattern :   `x{xxx}_y{yyy}_z{zzz}_c{ccc}_t{ttt}.ome.tif`
+Registration_variable :  `t`
+similar_transformation_variable : `c`
+template_ :  `x001_y001_z001_c001_t001.ome.tif`
 
-`Output set 2:`    
-Template Image:  x001_y002_z001_c001_t001.ome.tif    
-Moving Image:   x001_y002_z001_c001_t002.ome.tif    
-Similar Transformation Images :  [ x001_y002_z001_c002_t002.ome.tif , x001_y002_z001_c003_t002.ome.tif ]      
+`Output set 1 :`
+Template Image:  x001_y001_z001_c001_t001.ome.tif
+Moving Image:  x001_y001_z001_c001_t002.ome.tif
+Similar Transformation Images :   [ x001_y001_z001_c002_t002.ome.tif , x001_y001_z001_c003_t002.ome.tif ]
 
+`Output set 2:`
+Template Image:  x001_y002_z001_c001_t001.ome.tif
+Moving Image:   x001_y002_z001_c001_t002.ome.tif
+Similar Transformation Images :  [ x001_y002_z001_c002_t002.ome.tif , x001_y002_z001_c003_t002.ome.tif ]
 
 
-### Registration 
-The registration algorithm is present in `image_registration.py`. It uses projective transformation(Homography matrix) to alter the moving image and align it with the reference image. Background information about homography can be found here: https://en.wikipedia.org/wiki/Homography .    
-The moving image undergoes 2 transformations:     
+
+### Registration
+The registration algorithm is present in `image_registration.py`. It uses projective transformation(Homography matrix) to alter the moving image and align it with the reference image. Background information about homography can be found here: https://en.wikipedia.org/wiki/Homography .
+The moving image undergoes 2 transformations:
 1. `Rough Transformation` : In this the whole moving image is transformed using the homography matrix calculated between the entire moving and template image.
-2. `Fine Transformation` : To carry out fine transformation ,the homography matrix is found between the corresponding tiles of the roughly transformed moving image and the template image. Each image is divided into 4 tiles. 
+2. `Fine Transformation` : To carry out fine transformation ,the homography matrix is found between the corresponding tiles of the roughly transformed moving image and the template image. Each image is divided into 4 tiles.
+
+To find the homography matrix(for fine or rough tranformation), we need coordinates of atleast 4 matching points in the template and the moving image. To do this the ORB feature detector has been used. However, its computationally very expensive to run feature matching on large images(our test data consists of 1.3 gigapixel images). To overcome this, the homography matrix at every step of our algorithm has been calculated between scaled down versions( 16 * 16 times smaller) of the respective images. To use this homography matrix on actual sized images, the matrix is scaled up using a scale matrix.  The proof for upscaling a homography matrix is shown below.
 
-To find the homography matrix(for fine or rough tranformation), we need coordinates of atleast 4 matching points in the template and the moving image. To do this the ORB feature detector has been used. However, its computationally very expensive to run feature matching on large images(our test data consists of 1.3 gigapixel images). To overcome this, the homography matrix at every step of our algorithm has been calculated between scaled down versions( 16 * 16 times smaller) of the respective images. To use this homography matrix on actual sized images, the matrix is scaled up using a scale matrix.  The proof for upscaling a homography matrix is shown below.   
+`Proof` :
 
-`Proof` :  
+Credit for proof : https://stackoverflow.com/questions/21019338/how-to-change-the-homography-with-the-scale-of-the-image/56623249
+
+![homography](https://user-images.githubusercontent.com/48079888/78402511-b04d8200-75c8-11ea-9d22-cee13f3912db.gif)
 
-Credit for proof : https://stackoverflow.com/questions/21019338/how-to-change-the-homography-with-the-scale-of-the-image/56623249    
-
-![homography](https://user-images.githubusercontent.com/48079888/78402511-b04d8200-75c8-11ea-9d22-cee13f3912db.gif)  
-
 
 
 
@@ -83,4 +83,3 @@ This plugin takes one input argument and one output argument:
 | `--template` | Template image to be used for image registration | Input | string |
 | `--TransformationVariable` | variable to help identify which images have similar transformation | Input | string |
 | `--outDir` | Output collection | Output | collection |
-
@@ -1 +1 @@
-0.3.5
+0.3.6
@@ -1,4 +1,4 @@
 #!/bin/bash
 
 version=$(<VERSION)
-docker build . -t polusai/image-registration-plugin:${version}
+docker build . -t polusai/image-registration-plugin:${version}
@@ -2,7 +2,7 @@ author:
 - Gauhar Bains
 - Nick Schaub
 contact: gauhar.bains@labshare.org
-container: polusai/image-registration-plugin:0.3.5
+container: polusai/image-registration-plugin:0.3.6
 description: This plugin registers an image collection
 entrypoint: '[python3, main.py]'
 inputs:
@@ -86,4 +86,4 @@ ui:
   key: inputs.method
   title: Deformation method
   type: select
-version: 0.3.5
+version: 0.3.6
@@ -36,7 +36,7 @@ outputs:
     type: Directory
 requirements:
   DockerRequirement:
-    dockerPull: polusai/image-registration-plugin:0.3.5
+    dockerPull: polusai/image-registration-plugin:0.3.6
   InitialWorkDirRequirement:
     listing:
     - entry: $(inputs.outDir)

@@ -1,95 +1,95 @@
 {
-    "name": "Image Registration",
-    "version": "0.3.5",
-    "title": "Image Registration",
-    "description": "This plugin registers an image collection",
-    "author": "Gauhar Bains (gauhar.bains@labshare.org), Nick Schaub (nick.schaub@nih.gov) ",
-    "institution": "National Center for Advancing Translational Sciences, National Institutes of Health",
-    "repository": "https://github.com/labshare/polus-plugins",
-    "website": "https://ncats.nih.gov/preclinical/core/informatics",
-    "citation": "",
-    "containerId": "polusai/image-registration-plugin:0.3.5",
-    "inputs": [
-      {
-        "name": "inpDir",
-        "type": "collection",
-        "description": "Input image collection to be processed by this plugin",
-        "required": true
-      },
-      {
-        "name": "filePattern",
-        "type": "string",
-        "description": "Filename pattern used to separate data",
-        "required": true
-      },
-      {
-        "name": "template",
-        "type": "string",
-        "description": "Template image to be used for image registration",
-        "required": true
-      },
-      {
-        "name": "registrationVariable",
-        "type": "string",
-        "description": "variable to help identify which images need to be registered to each other",
-        "required": true
-      },
-      {
-        "name": "TransformationVariable",
-        "type": "string",
-        "description": "variable to help identify which images have similar transformation",
-        "required": true
-      },
-      {
-        "name": "method",
-        "type": "enum",
-        "description": "Projective (8 degrees of freedom), Affine (6 degrees of freedom), Partial Affine (4 degrees of freedom)",
-        "options": {
-          "values": [
-                     "Projective",
-                     "Affine",
-                     "PartialAffine"
-          ]
-        }
+  "name": "Image Registration",
+  "version": "0.3.6",
+  "title": "Image Registration",
+  "description": "This plugin registers an image collection",
+  "author": "Gauhar Bains (gauhar.bains@labshare.org), Nick Schaub (nick.schaub@nih.gov) ",
+  "institution": "National Center for Advancing Translational Sciences, National Institutes of Health",
+  "repository": "https://github.com/labshare/polus-plugins",
+  "website": "https://ncats.nih.gov/preclinical/core/informatics",
+  "citation": "",
+  "containerId": "polusai/image-registration-plugin:0.3.6",
+  "inputs": [
+    {
+      "name": "inpDir",
+      "type": "collection",
+      "description": "Input image collection to be processed by this plugin",
+      "required": true
+    },
+    {
+      "name": "filePattern",
+      "type": "string",
+      "description": "Filename pattern used to separate data",
+      "required": true
+    },
+    {
+      "name": "template",
+      "type": "string",
+      "description": "Template image to be used for image registration",
+      "required": true
+    },
+    {
+      "name": "registrationVariable",
+      "type": "string",
+      "description": "variable to help identify which images need to be registered to each other",
+      "required": true
+    },
+    {
+      "name": "TransformationVariable",
+      "type": "string",
+      "description": "variable to help identify which images have similar transformation",
+      "required": true
+    },
+    {
+      "name": "method",
+      "type": "enum",
+      "description": "Projective (8 degrees of freedom), Affine (6 degrees of freedom), Partial Affine (4 degrees of freedom)",
+      "options": {
+        "values": [
+          "Projective",
+          "Affine",
+          "PartialAffine"
+        ]
       }
-    ],
-    "outputs": [
-      {
-        "name": "outDir",
-        "type": "collection",
-        "description": "Output collection"
-      }
-    ],
-    "ui": [
-      {
-        "key": "inputs.inpDir",
-        "title": "Input collection",
-        "description": "Input image collection to be processed by this plugin"
-      },
-      {
-        "key": "inputs.filePattern",
-        "title": "Filename pattern",
-        "description": "Filename pattern used to separate data"
-      },
-      {
-        "key": "inputs.template",
-        "title": "Template Image",
-        "description": "Template image to be used for image registration"
-      },
-      {
-        "key": "inputs.registrationVariable",
-        "title": "Registration Variable",
-        "description": "variable to help identify which images need to be registered to each other"
-      },
-      {
-        "key": "inputs.TransformationVariable",
-        "title": "Similar Transformation Variable",
-        "description": "variable to help identify which images have similar transformation"
-      },
-      {
-        "key": "inputs.method",
-        "title": "Deformation method",
-        "description": "Projective (8 degrees of freedom), Affine (6 degrees of freedom), Partial Affine (4 degrees of freedom)"
-      }
-    ]
-  }
+    }
+  ],
+  "outputs": [
+    {
+      "name": "outDir",
+      "type": "collection",
+      "description": "Output collection"
+    }
+  ],
+  "ui": [
+    {
+      "key": "inputs.inpDir",
+      "title": "Input collection",
+      "description": "Input image collection to be processed by this plugin"
+    },
+    {
+      "key": "inputs.filePattern",
+      "title": "Filename pattern",
+      "description": "Filename pattern used to separate data"
+    },
+    {
+      "key": "inputs.template",
+      "title": "Template Image",
+      "description": "Template image to be used for image registration"
+    },
+    {
+      "key": "inputs.registrationVariable",
+      "title": "Registration Variable",
+      "description": "variable to help identify which images need to be registered to each other"
+    },
+    {
+      "key": "inputs.TransformationVariable",
+      "title": "Similar Transformation Variable",
+      "description": "variable to help identify which images have similar transformation"
+    },
+    {
+      "key": "inputs.method",
+      "title": "Deformation method",
+      "description": "Projective (8 degrees of freedom), Affine (6 degrees of freedom), Partial Affine (4 degrees of freedom)"
+    }
+  ]
+}
@@ -0,0 +1,17 @@
+[project]
+name = "polus-image-registration-plugin"
+version = "0.3.6"
+description = "This plugin registers an image collection"
+requires-python = ">=3.11"
+dependencies = [
+    "numpy>=1.26.4",
+    "opencv-python-headless>=4.7.0",
+    "filepattern>=2.2.1",
+]
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[tool.hatch.build.targets.wheel]
+packages = ["src"]
@@ -0,0 +1 @@
+"""Image registration plugin."""