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labeling_tools [2013/01/07 12:27] – [Functionality] tenorthlabeling_tools [2013/03/05 14:15] – [Installation] admin
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 ====== Labeling tool for human activity data ====== ====== Labeling tool for human activity data ======
  
-[[Image:Labeling-tool.png|690px|center]]+{{ :labeling-tool.png?700 |}}
  
 ===== Installation ===== ===== Installation =====
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 The program has been created using [processing] and [controlP5] in Java and is available for Linux, Windows and MacOS. After download, just unpack the archive and start the DatalabelingCogwatch file. The program has been created using [processing] and [controlP5] in Java and is available for Linux, Windows and MacOS. After download, just unpack the archive and start the DatalabelingCogwatch file.
  
-  * [[https://dl.dropbox.com/u/51957850/application.linux.zip|Linux]] +  * {{:application.linux.zip|Linux}} 
-  * [[https://dl.dropbox.com/u/51957850/application.macosx.zip|MacOS X]] +  * {{:application.macosx.zip|MacOS X}} 
-  * [[https://dl.dropbox.com/u/51957850/application.windows.zip|Windows]]+  * {{:application.windows.zip|Windows}}
  
 To provide some test data to start with, the following archive contains a sample folder structure including a show video, some first dummy annotations, and some configuration files. To provide some test data to start with, the following archive contains a sample folder structure including a show video, some first dummy annotations, and some configuration files.
  
-  * [[https://dl.dropbox.com/u/51957850/example-sequence.zip|Example data]]+  * {{:example-sequence.zip|Example data}}
  
-For comments, questions and support queries please contact [[http://ias.cs.tum.edu/people/tenorth|Moritz Tenorth]].+For comments, questions and support queries please contact [[http://ai.uni-bremen.de/team/moritz_tenorth|Moritz Tenorth]].
  
  
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-==== Annotation file formats ====+===== Annotation file formats =====
  
 All labels are stored as the concatenation of the different label-categories with a hyphen (-) in between. The annotation using a kind of 'restricted natural language' (i.e. action, object, and possibly preposition and another object) can easily be translated into relational representations and ontology-based annotations by defining a mapping between the identifiers in the ontology and the labels used by the human annotator. All labels are stored as the concatenation of the different label-categories with a hyphen (-) in between. The annotation using a kind of 'restricted natural language' (i.e. action, object, and possibly preposition and another object) can easily be translated into relational representations and ontology-based annotations by defining a mapping between the identifiers in the ontology and the labels used by the human annotator.
  
-=== labels.dat ===+==== labels.dat ====
 <code> <code>
  1 32 Put-Sugar-Into-Cup_1-Sequence_omission  1 32 Put-Sugar-Into-Cup_1-Sequence_omission
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-=== labels.dat.frames ===+==== labels.dat.frames ====
 <code> <code>
  ...  ...
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-=== OWL export ===+==== OWL export ====
  
-Not yet implemented, will output a description of the task in terms of action instances in OWL, linked to the respective objects and additional information. This will be directly usable for reasoning in KnowRob, e.g. using mod_ham or visualization in mod_vis.+The OWL exporter outputs a description of the task in terms of action instances in OWL, linked to the respective objects and additional information. This file can be loaded into KnowRob and used for reasoning, e.g. using the mod_ham package from the [[https://github.com/knowrob/knowrob_human.git|knowrob_human repository]] or visualizations using mod_vis. For more information on the OWL representation of actions, have a look [[Modeling_tasks_and_actions|here]].
  
-[[Modeling_tasks_and_actions]] 
  
  
-=== BLOG export ===+ 
 +==== BLOG export ====
  
 This exporter outputs the data in terms of BLOG files that can be used for training Bayesian Logic Networks (BLN). It relies on having a complete mapping of all labels that appear in the data to OWL classes, properties or individual (see [[#owl-mapping.yaml]]) This exporter outputs the data in terms of BLOG files that can be used for training Bayesian Logic Networks (BLN). It relies on having a complete mapping of all labels that appear in the data to OWL classes, properties or individual (see [[#owl-mapping.yaml]])