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annotate bioimage_inference.xml @ 4:2b61d8fcfa52 draft

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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/bioimaging commit f038722c21eaa3018e1cef0004ac7bd283d15269
author bgruening
date Mon, 07 Apr 2025 14:46:13 +0000
parents bc28236f407b
children 37b9ead209da
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1 <tool id="bioimage_inference" name="Process image using a BioImage.IO model" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="23.0">
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2 <description>with PyTorch</description>
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3 <macros>
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4 <token name="@TOOL_VERSION@">2.4.1</token>
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5 <token name="@VERSION_SUFFIX@">2</token>
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6 </macros>
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7 <creator>
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8 <organization name="European Galaxy Team" url="https://galaxyproject.org/eu/" />
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9 <person givenName="Anup" familyName="Kumar" email="kumara@informatik.uni-freiburg.de" />
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10 <person givenName="Beatriz" familyName="Serrano-Solano" email="beatriz.serrano.solano@eurobioimaging.eu" />
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11 <person givenName="Leonid" familyName="Kostrykin" email="leonid.kostrykin@bioquant.uni-heidelberg.de" />
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12 </creator>
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13 <edam_operations>
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14 <edam_operation>operation_3443</edam_operation>
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15 </edam_operations>
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16 <xrefs>
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17 <xref type="bio.tools">pytorch</xref>
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18 <xref type="biii">pytorch</xref>
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19 </xrefs>
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20 <requirements>
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21 <requirement type="package" version="3.9.12">python</requirement>
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22 <requirement type="package" version="@TOOL_VERSION@">pytorch</requirement>
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23 <requirement type="package" version="0.19.1">torchvision</requirement>
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24 <requirement type="package" version="2.35.1">imageio</requirement>
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25 </requirements>
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26 <version_command>echo "@VERSION@"</version_command>
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27 <command detect_errors="aggressive">
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28 <![CDATA[
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29 python '$__tool_directory__/main.py'
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30 --imaging_model '$input_imaging_model'
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31 --image_file '$input_image_file'
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32 --image_size '$input_image_input_size'
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33 --image_axes '$input_image_input_axes'
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34 ]]>
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35 </command>
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36 <inputs>
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37 <param name="input_imaging_model" type="data" format="zip" label="BioImage.IO model" help="Please upload a BioImage.IO model."/>
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38 <param name="input_image_file" type="data" format="tiff,png" label="Input image" help="Please provide an input image for the analysis."/>
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39 <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."/>
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40 <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'">
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41 <option value="bczyx">bczyx</option>
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42 <option value="bcyx">bcyx</option>
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43 <option value="byxc">byxc</option>
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44 </param>
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45 </inputs>
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46 <outputs>
4
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47 <data format="tiff" name="output_predicted_image" from_work_dir="output_predicted_image.tiff" label="Predicted image"></data>
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48 <data format="npy" name="output_predicted_image_matrix" from_work_dir="output_predicted_image_matrix.npy" label="Predicted image tensor"></data>
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49 </outputs>
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50 <tests>
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51 <test>
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52 <param name="input_imaging_model" value="input_imaging_model.zip" location="https://zenodo.org/api/records/6647674/files/weights-torchscript.pt/content"/>
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53 <param name="input_image_file" value="input_image_file.tif" location="https://zenodo.org/api/records/6647674/files/sample_input_0.tif/content"/>
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54 <param name="input_image_input_size" value="256,256,1,1"/>
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55 <param name="input_image_input_axes" value="bcyx"/>
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56 <output name="output_predicted_image" ftype="tiff">
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57 <assert_contents>
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58 <has_size size="524846" delta="110" />
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59 </assert_contents>
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60 </output>
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61 <output name="output_predicted_image_matrix" ftype="npy">
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62 <assert_contents>
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63 <has_size size="524416" delta="110" />
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64 </assert_contents>
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65 </output>
0
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66 </test>
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67 <test>
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68 <param name="input_imaging_model" value="input_imaging_model.zip" location="https://zenodo.org/api/records/6647674/files/weights-torchscript.pt/content"/>
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69 <param name="input_image_file" value="input_nucleisegboundarymodel.png"/>
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70 <param name="input_image_input_size" value="256,256,1,1"/>
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71 <param name="input_image_input_axes" value="bcyx"/>
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72 <output name="output_predicted_image" ftype="tiff">
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73 <assert_contents>
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74 <has_size size="524846" delta="110" />
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75 </assert_contents>
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76 </output>
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77 <output name="output_predicted_image_matrix" ftype="npy">
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78 <assert_contents>
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79 <has_size size="524416" delta="110" />
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80 </assert_contents>
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81 </output>
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82 </test>
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83 <test>
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84 <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"/>
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85 <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"/>
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86 <param name="input_image_input_size" value="128,128,100,1"/>
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87 <param name="input_image_input_axes" value="bczyx"/>
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88 <output name="output_predicted_image" ftype="tiff">
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89 <assert_contents>
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90 <has_size size="6572778" delta="100" />
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91 </assert_contents>
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92 </output>
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93 <output name="output_predicted_image_matrix" ftype="npy">
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94 <assert_contents>
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95 <has_size size="6572778" delta="100" />
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96 </assert_contents>
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97 </output>
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98 </test>
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99 <test>
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100 <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"/>
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101 <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"/>
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102 <param name="input_image_input_size" value="128,128,100,1"/>
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103 <param name="input_image_input_axes" value="bczyx"/>
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104 <output name="output_predicted_image" ftype="tiff">
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105 <assert_contents>
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106 <has_size size="6572778" delta="100" />
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107 </assert_contents>
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108 </output>
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109 <output name="output_predicted_image_matrix" ftype="npy">
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110 <assert_contents>
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111 <has_size size="6572778" delta="100" />
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112 </assert_contents>
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113 </output>
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114 </test>
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115 <test>
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116 <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"/>
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117 <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"/>
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118 <param name="input_image_input_size" value="256,256,32,1"/>
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119 <param name="input_image_input_axes" value="bczyx"/>
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120 <output name="output_predicted_image" ftype="tiff">
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121 <assert_contents>
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122 <has_size size="16789714" delta="100" />
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123 </assert_contents>
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124 </output>
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125 <output name="output_predicted_image_matrix" ftype="npy">
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126 <assert_contents>
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127 <has_size size="16777344" delta="100" />
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128 </assert_contents>
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129 </output>
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130 </test>
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131 <test>
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132 <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"/>
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133 <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"/>
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134 <param name="input_image_input_size" value="128,128,100,1"/>
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135 <param name="input_image_input_axes" value="bczyx"/>
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136 <output name="output_predicted_image" ftype="tiff">
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137 <assert_contents>
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138 <has_size size="6572778" delta="100" />
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139 </assert_contents>
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140 </output>
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141 <output name="output_predicted_image_matrix" ftype="npy">
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142 <assert_contents>
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143 <has_size size="6553728" delta="100" />
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144 </assert_contents>
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145 </output>
0
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146 </test>
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147 </tests>
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148 <help>
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149 <![CDATA[
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150 **What it does**
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151
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152 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.
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153
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154 **Input files**
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155 - BioImage.IO model: Add one of the model from Galaxy file uploader by choosing a "remote" file at "ML Models/bioimaging-models"
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156 - Image to be analyzed: Provide an image as TIF/PNG file
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157 - 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)
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158 - 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
0
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159
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160 **Output files**
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161 - Predicted image: Predicted image using the BioImage.IO model
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162 - Predicted image matrix: Predicted image matrix in original dimensions
0
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163 ]]>
9f9ae2ac7820 planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/bioimaging commit 57f46739f4365f59cd52c515bdd3fae2e01b734e
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164 </help>
9f9ae2ac7820 planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/bioimaging commit 57f46739f4365f59cd52c515bdd3fae2e01b734e
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165 <citations>
9f9ae2ac7820 planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/bioimaging commit 57f46739f4365f59cd52c515bdd3fae2e01b734e
bgruening
parents:
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166 <citation type="doi">10.1145/3620665.3640366</citation>
9f9ae2ac7820 planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/bioimaging commit 57f46739f4365f59cd52c515bdd3fae2e01b734e
bgruening
parents:
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167 <citation type="doi">10.1101/2022.06.07.495102</citation>
9f9ae2ac7820 planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/bioimaging commit 57f46739f4365f59cd52c515bdd3fae2e01b734e
bgruening
parents:
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168 </citations>
9f9ae2ac7820 planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/bioimaging commit 57f46739f4365f59cd52c515bdd3fae2e01b734e
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169 </tool>