Mercurial > repos > bgruening > 3dtrees_segmentanytree

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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/3dtrees_segmentanytree commit 7540181d97a24b5bf07dde308f6d79bee5f18c9c
author bgruening
date Thu, 30 Oct 2025 14:37:55 +0000
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0
6f80b2dfb7d4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/3dtrees_segmentanytree commit 7540181d97a24b5bf07dde308f6d79bee5f18c9c
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1 <tool id="3dtrees_segmentanytree" name="3Dtrees: SegmentAnyTree" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="24.2">
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2 <description>
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3 Forest instance segmentation.
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4 </description>
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5 <macros>
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6 <token name="@TOOL_VERSION@">1.1.0</token>
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7 <token name="@VERSION_SUFFIX@">0</token>
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8 </macros>
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9 <requirements>
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10 <container type="docker">
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11 ghcr.io/3dtrees-earth/3dtrees_sat:@TOOL_VERSION@
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12 </container>
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13 </requirements>
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14 <command detect_errors="exit_code"><![CDATA[
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15 export NUMBA_CACHE_DIR=\$TMPDIR &&
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16 #if $input.ext == "zip":
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17 ln -s '$input' input.zip &&
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18 python3.8 -u /src/run.py
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19 --dataset-path input.zip
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20 --output-dir .
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21 --log_file '$log_file' &&
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22 mv processed_files.zip '$output'
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23 #if $log_file:
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24 && mv resource_usage.log '$resource_usage'
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25 #end if
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26 #else:
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27 ln -s '$input' input.laz &&
6f80b2dfb7d4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/3dtrees_segmentanytree commit 7540181d97a24b5bf07dde308f6d79bee5f18c9c
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28 python3.8 -u /src/run.py
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29 --dataset-path input.laz
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30 --output-dir .
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31 --log_file '$log_file' &&
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32 mv segmented_pc.laz '$output'
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33 #if $log_file:
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34 && mv resource_usage.log '$resource_usage'
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35 #end if
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36 #end if
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37 ]]>
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38 </command>
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39 <inputs>
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40 <param argument="--input" type="data" format="zip,laz" label="Input Dataset" help="ZIP file containing point cloud data with required folder structure / single LAZ/LAS point cloud file."/>
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41 <param argument="--log_file" type="boolean" label="Resource log" help="If set to true, it returns a log file containing the CPU, RAM and GPU usage statistics"/>
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42 </inputs>
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43 <outputs>
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44 <data name="output" format="zip" label="Processed Files">
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45 <change_format>
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46 <when input="input.ext" value="laz" format="laz"/>
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47 </change_format>
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48 </data>
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49 <data name="resource_usage" format="txt" label="Resource Usage">
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50 <filter>log_file</filter>
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51 </data>
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52 </outputs>
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53 <tests>
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54 <test expect_num_outputs="2">
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55 <param name="input" value="prepared_files_mikro.zip"/>
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56 <param name="log_file" value="true"/>
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57 <output name="resource_usage">
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58 <assert_contents>
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59 <has_line line="timestamp,cpu_percent,cpu_cores_used,cpu_cores_total,mem_used_mb,mem_total_mb,gpu_mem_used_mb,gpu_mem_total_mb" n="1"/>
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60 </assert_contents>
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61 </output>
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62 <assert_stdout>
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63 <has_text text="Loading checkpoint from /src/SegmentAnyTree/model_file/PointGroup-PAPER.pt"/>
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64 <has_text text="Segmentation complete"/>
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65 </assert_stdout>
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66 </test>
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67 <test expect_exit_code="1" expect_failure="true">
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68 <param name="input" value="mikro.laz"/>
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69 <param name="log_file" value="false"/>
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70 <assert_stderr>
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71 <has_text text="RuntimeError: Found no NVIDIA driver"/>
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72 </assert_stderr>
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73 <assert_stdout>
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74 <has_text text="Loading checkpoint from /src/SegmentAnyTree/model_file/PointGroup-PAPER.pt"/>
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75 </assert_stdout>
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76 </test>
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77 </tests>
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78 <help format="markdown">
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79 **What it does**
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80
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81 This tool performs deep learning-based tree segmentation on LiDAR point clouds using the **SegmentAnyTree** algorithm (Wielgosz et al., 2024). It is sensor- and platform-agnostic, working across airborne (ALS/ULS), terrestrial (TLS), and mobile (MLS) laser scanning data.
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82
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83 -----
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84
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85
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86 **Input**
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87 - A **ZIP file** containing the following directory structure:
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88
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89 00_original/
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90 input.laz
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91 01_subsampled/
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92 input_subsampled.laz
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93 02_input_SAT/
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94 tile_1.laz
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95 tile_2.laz
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96 ...
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97
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98 - A single **LAZ/LAS file** containing a point cloud
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99
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100 -----
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101
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102 **Output**
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103
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104 The output depends on the input type:
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105 - **ZIP input** → ZIP output containing the complete processed folder structure.
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106 - **LAZ input** → Single LAZ output file `segmented_pc.laz` containing the segmented point cloud with tree instance IDs.
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107
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108 We recommend using the [3DTrees: Tile and Merge](https://usegalaxy.eu/?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Fbgruening%2F3dtrees_tile_merge%2F3dtrees_tile_merge%2F1.0.1%2Bgalaxy0&amp;version=latest) tool to preprocess and remap the segmented point cloud back to original resolution.
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109
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110 </help>
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111 <creator>
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112 <person name="Marc Wielgosz" email="maciej.wielgosz@nibio.no" url="https://maciej.wielgosz.info/"/>
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113 <person name="Kilian Gerberding" email="kilian.gerberding@geosense.uni-freiburg.de" url="https://orcid.org/0009-0002-5001-2571"/>
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114 <organization name="3Dtrees-Team, University of Freiburg" url="https://github.com/3dTrees-earth"/>
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115 </creator>
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116 <citations>
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117 <citation type="doi">10.1016/j.rse.2024.114367</citation>
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118 <citation type="bibtex">
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119 @misc{3dtrees_segmentanytree, title = {3Dtrees: SegmentAnyTree}, author = {3Dtrees-Project}, year = {2025}}
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120 </citation>
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121 </citations>
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122 </tool>