Mercurial > repos > bgruening > bioimage_inference

diff bioimage_inference.xml @ 3:bc28236f407b draft

Find changesets by keywords (author, files, the commit message), revision number or hash, or revset expression.
planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/bioimaging commit e08711c242a340a1671dfca35f52d3724086e968
author bgruening
date Wed, 26 Feb 2025 10:27:28 +0000
parents 0c0de5546fe1
children 2b61d8fcfa52
line wrap: on
line diff
--- a/bioimage_inference.xml	Tue Oct 15 12:57:33 2024 +0000
+++ b/bioimage_inference.xml	Wed Feb 26 10:27:28 2025 +0000
@@ -2,7 +2,7 @@
     <description>with PyTorch</description>
     <macros>
         <token name="@TOOL_VERSION@">2.4.1</token>
-        <token name="@VERSION_SUFFIX@">0</token>
+        <token name="@VERSION_SUFFIX@">1</token>
     </macros>
     <creator>
         <organization name="European Galaxy Team" url="https://galaxyproject.org/eu/" />
@@ -30,12 +30,18 @@
             --imaging_model '$input_imaging_model'
             --image_file '$input_image_file'
             --image_size '$input_image_input_size'
+            --image_axes '$input_image_input_axes'
     ]]>
     </command>
     <inputs>
         <param name="input_imaging_model" type="data" format="zip" label="BioImage.IO model" help="Please upload a BioImage.IO model."/>
         <param name="input_image_file" type="data" format="tiff,png" label="Input image" help="Please provide an input image for the analysis."/>
-        <param name="input_image_input_size" type="text" label="Size of the input image" help="Provide the size of the input image. See the chosen model's RDF file to find the correct input size. For example: for the BioImage.IO model MitochondriaEMSegmentationBoundaryModel, the input size is 256 x 256 x 32 x 1. Enter the size as 256,256,32,1."/>
+        <param name="input_image_input_size" type="text" optional="false" label="Size of the input image" help="Provide the size of the input image. See the chosen model's RDF file to find the correct input size. For example: for the BioImage.IO model MitochondriaEMSegmentationBoundaryModel, the input size is 256 x 256 x 32 x 1. Enter the size as 256,256,32,1."/>
+        <param name="input_image_input_axes" type="select" label="Axes of the input image" optional="false" help="Provide the input axes of the input image. See the chosen model's RDF file to find the correct axes. For example: for the BioImage.IO model MitochondriaEMSegmentationBoundaryModel, the input axes is 'bczyx'">
+            <option value="bczyx">bczyx</option>
+            <option value="bcyx">bcyx</option>
+            <option value="byxc">byxc</option>
+        </param>
     </inputs>
     <outputs>
         <data format="tif" name="output_predicted_image" from_work_dir="output_predicted_image.tif" label="Predicted image"></data>
@@ -46,15 +52,97 @@
             <param name="input_imaging_model" value="input_imaging_model.zip" location="https://zenodo.org/api/records/6647674/files/weights-torchscript.pt/content"/>
             <param name="input_image_file" value="input_image_file.tif" location="https://zenodo.org/api/records/6647674/files/sample_input_0.tif/content"/>
             <param name="input_image_input_size" value="256,256,1,1"/>
-            <output name="output_predicted_image" file="output_nucleisegboundarymodel.tif" compare="sim_size" delta="100" />
-            <output name="output_predicted_image_matrix" file="output_nucleisegboundarymodel_matrix.npy" compare="sim_size" delta="100" />
+            <param name="input_image_input_axes" value="bcyx"/>
+            <output name="output_predicted_image" ftype="tif">
+                <assert_contents>
+                    <has_size size="524846" delta="110" />
+                </assert_contents>
+            </output>
+            <output name="output_predicted_image_matrix" ftype="npy">
+                <assert_contents>
+                    <has_size size="524416" delta="110" />
+                </assert_contents>
+            </output>
         </test>
         <test>
             <param name="input_imaging_model" value="input_imaging_model.zip" location="https://zenodo.org/api/records/6647674/files/weights-torchscript.pt/content"/>
             <param name="input_image_file" value="input_nucleisegboundarymodel.png"/>
             <param name="input_image_input_size" value="256,256,1,1"/>
-            <output name="output_predicted_image" file="output_nucleisegboundarymodel.tif" compare="sim_size" delta="100" />
-            <output name="output_predicted_image_matrix" file="output_nucleisegboundarymodel_matrix.npy" compare="sim_size" delta="100" />
+            <param name="input_image_input_axes" value="bcyx"/>
+            <output name="output_predicted_image" ftype="tif">
+                <assert_contents>
+                    <has_size size="524846" delta="110" />
+                </assert_contents>
+            </output>
+            <output name="output_predicted_image_matrix" ftype="npy">
+                <assert_contents>
+                    <has_size size="524416" delta="110" />
+                </assert_contents>
+            </output>
+        </test>
+        <test>
+            <param name="input_imaging_model" value="input_imaging_model.zip" location="https://uk1s3.embassy.ebi.ac.uk/public-datasets/bioimage.io/emotional-cricket/1.1/files/torchscript_tracing.pt"/>
+            <param name="input_image_file" value="input_image_file.tif" location="https://uk1s3.embassy.ebi.ac.uk/public-datasets/bioimage.io/emotional-cricket/1.1/files/sample_input_0.tif"/>
+            <param name="input_image_input_size" value="128,128,100,1"/>
+            <param name="input_image_input_axes" value="bczyx"/>
+            <output name="output_predicted_image" ftype="tif">
+                <assert_contents>
+                    <has_size size="6572778" delta="100" />
+                </assert_contents>
+            </output>
+            <output name="output_predicted_image_matrix" ftype="npy">
+                <assert_contents>
+                    <has_size size="6572778" delta="100" />
+                </assert_contents>
+            </output>
+        </test>
+        <test>
+            <param name="input_imaging_model" value="input_imaging_model.zip" location="https://uk1s3.embassy.ebi.ac.uk/public-datasets/bioimage.io/emotional-cricket/1.1/files/torchscript_tracing.pt"/>
+            <param name="input_image_file" value="input_3d-unet-arabidopsis-apical-stem-cells.png" location="https://uk1s3.embassy.ebi.ac.uk/public-datasets/bioimage.io/emotional-cricket/1.1/files/raw.png"/>
+            <param name="input_image_input_size" value="128,128,100,1"/>
+            <param name="input_image_input_axes" value="bczyx"/>
+            <output name="output_predicted_image" ftype="tif">
+                <assert_contents>
+                    <has_size size="6572778" delta="100" />
+                </assert_contents>
+            </output>
+            <output name="output_predicted_image_matrix" ftype="npy">
+                <assert_contents>
+                    <has_size size="6572778" delta="100" />
+                </assert_contents>
+            </output>
+        </test>
+        <test>
+            <param name="input_imaging_model" value="input_imaging_model.zip" location="https://uk1s3.embassy.ebi.ac.uk/public-datasets/bioimage.io/organized-badger/1/files/weights-torchscript.pt"/>
+            <param name="input_image_file" value="input_platynereisemnucleisegmentationboundarymodel.tif" location="https://uk1s3.embassy.ebi.ac.uk/public-datasets/bioimage.io/organized-badger/1/files/sample_input_0.tif"/>
+            <param name="input_image_input_size" value="256,256,32,1"/>
+            <param name="input_image_input_axes" value="bczyx"/>
+            <output name="output_predicted_image" ftype="tif">
+                <assert_contents>
+                    <has_size size="16789714" delta="100" />
+                </assert_contents>
+            </output>
+            <output name="output_predicted_image_matrix" ftype="npy">
+                <assert_contents>
+                    <has_size size="16777344" delta="100" />
+                </assert_contents>
+            </output>
+        </test>
+        <test>
+            <param name="input_imaging_model" value="input_imaging_model.zip" location="https://uk1s3.embassy.ebi.ac.uk/public-datasets/bioimage.io/thoughtful-turtle/1/files/torchscript_tracing.pt"/>
+            <param name="input_image_file" value="input_3d-unet-lateral-root-primordia-cells.tif" location="https://uk1s3.embassy.ebi.ac.uk/public-datasets/bioimage.io/thoughtful-turtle/1/files/sample_input_0.tif"/>
+            <param name="input_image_input_size" value="128,128,100,1"/>
+            <param name="input_image_input_axes" value="bczyx"/>
+            <output name="output_predicted_image" ftype="tif">
+                <assert_contents>
+                    <has_size size="6572778" delta="100" />
+                </assert_contents>
+            </output>
+            <output name="output_predicted_image_matrix" ftype="npy">
+                <assert_contents>
+                    <has_size size="6553728" delta="100" />
+                </assert_contents>
+            </output>
         </test>
     </tests>
     <help>
@@ -64,13 +152,14 @@
             The tool takes a BioImage.IO model and an image (as TIF or PNG) to be analyzed. The analysis is performed by the model. The model is used to obtain a prediction of the result of the analysis, and the predicted image becomes available as a TIF file in the Galaxy history.
 
             **Input files**
-            - BioImage.IO model: Add one of the model from Galaxy file uploader by choosing a "remote" file at "ML Models/bioimaging-models"
-            - Image to be analyzed: Provide an image as TIF/PNG file
-            - Provide the necessary input size for the model. This information can be found in the RDF file of each model (RDF file > config > test_information > inputs > size)
+                - BioImage.IO model: Add one of the model from Galaxy file uploader by choosing a "remote" file at "ML Models/bioimaging-models"
+                - Image to be analyzed: Provide an image as TIF/PNG file
+                - Provide the necessary input size for the model. This information can be found in the RDF file of each model (RDF file > config > test_information > inputs > size)
+                - Provide axes of input image. This information can also be found in the RDF file of each model (RDF file > inputs > axes). An example value of axes is 'bczyx' for 3D U-Net Arabidopsis Lateral Root Primordia model
 
             **Output files**
-            - Predicted image: Predicted image using the BioImage.IO model
-            - Predicted image matrix: Predicted image matrix in original dimensions
+                - Predicted image: Predicted image using the BioImage.IO model
+                - Predicted image matrix: Predicted image matrix in original dimensions
         ]]>
     </help>
     <citations>