====== ContextInsights ======

This page describes how to use the extension "ContextInsights"\\

{{orbit_desktop:how_to_find.png?25&nolink  |}} [[221:desktop:workspace:main_toolbar|Main Toolbar]] > Extensions > Context Insights

The "ContextInsights" extension makes it possible to use Context Insights detectors on mapping resources and pointcloud resources. The detectors are Image 2D Annotations and 2D Segmentations. 


===== Concepts =====

Running Context Insights detectors requires Python version 3.6, ContextCapture Centure and original images from any mapping resource. The results can be directly imported in the mapping resources via the Annotations procedure. Install the [[external:contextinsights|]] before running Context Insights jobs. 
===== Preferences =====

Configure the directories to Python, the virtual environment and the Context Insights detectors.
The detectors and specs are listed underneath. 

===== Action =====

Create a new job and enter the target location of the results. 

Open an existing job and browse to the location of the results. 

Drag and drop a directory from file explorer into Orbit. 

===== Annotation Type =====

Depending on the added detectors, the following annotation types will be selectable.

==== Image 2D Objects ====

  * Import the scene xml file as 2D Object annotations to overlay the results on original or optimized images

==== Image 2D Segmentation ====

  * Apply Segmentation at optimize imagery to display the result on optimized images

==== Pointcloud 3D Segmentation ====

===== Analyze =====

Delegate the process to the task manager or start now. Running the Context Capture Engine is required before starting the process. 

===== Import =====

==== Open Procedure ====

Open the Annotations procedure where the result xml file is already pre-filled as source object annotation file.

Import 2D Objects or 2D Segmentations, depending on the chosen Annotation Type. 

==== Open File Location ====

Open the target directory to verify the results.