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224:desktop_ext:context_insights [2022/04/21 15:46] 127.0.0.1 external edit |
224:desktop_ext:context_insights [2022/06/22 16:13] 127.0.0.1 external edit |
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====== ContextInsights ====== | ====== ContextInsights ====== | ||
- | This page describes how to use the extension | + | This page describes how to use the " |
+ | Specific system requirements and installation guidelines, see [[224: | ||
{{orbit_desktop: | {{orbit_desktop: | ||
- | The " | + | ===== Concepts ===== |
+ | ==== Context Insights ==== | ||
- | ===== Concepts ===== | + | ContextInsights extension enables automatic detection on mapping and point cloud resources. \\ |
+ | It relies on detectors to identify objects or regions of interest. | ||
- | Running Context Insights detectors requires Python | + | Running Context Insights detectors requires Python, |
- | ===== Preferences ===== | + | |
- | Configure the directories | + | ==== Jobs ==== |
- | The detectors and specs are listed underneath. | + | |
+ | A ContextInsights job will leverage machine learning | ||
+ | There are various types of jobs available: | ||
+ | * Image 2D Objects: Will detect elements as regular 2D-bounding boxes in images. Regular 2D boxes around assets. | ||
+ | * Image 2D Segmentation: | ||
+ | * Point Cloud 3D Segmentation: | ||
- | ===== Action ===== | + | Each job type requires a suited detector to be executed on reality data. E.g: a 2D segmentation detector will only be usable for image based segmentation jobs |
- | Create a new job and enter the target location of the results. | + | ==== Detectors ==== |
- | Open an existing | + | A detector is a frozen model that is pre-trained by Bentley Systems. Running on your reality data through a ContextInsights |
+ | https:// | ||
- | Drag and drop a directory from file explorer into Orbit. | + | A detector is specific to a certain job type. The quality of the detection will depend on the similarity between your dataset and the training dataset’s description. |
- | ===== Annotation Type ===== | + | ===== Launch Context Isnights Engine |
- | Depending on the added detectors, the following annotation types will be selectable. | + | Launch ContextInsights Engine \\ |
+ | {{: | ||
- | ==== Image 2D Objects | + | ===== Context Inisghts Sidebar ===== |
- | * Import the scene xml file as 2D Object annotations to overlay the results on original or optimized images | + | ==== Preferences ==== |
- | ==== Image 2D Segmentation ==== | + | Configure the directories to Python, the virtual environment, |
+ | The detectors and specs are listed underneath. | ||
- | * Apply Segmentation at optimize imagery to display the result on optimized images | + | ==== Action ==== |
- | ==== Pointcloud 3D Segmentation ==== | + | Define whether you want to create a new job or open existing one |
+ | * Create a new job and enter the target location of the results. | ||
+ | * Open an existing job and browse to the location of the results. | ||
- | ===== Analyze ===== | + | ==== Detecor |
- | Delegate | + | Depending on the added detectors, |
- | ===== Import ===== | + | <note important> |
- | ==== Open Procedure | + | ==== Analyze |
- | Open the Annotations procedure where the result xml file is already pre-filled as source object annotation file. | + | Delegate |
+ | |||
+ | ==== 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, | Import 2D Objects or 2D Segmentations, | ||
- | ==== Open File Location | + | === Open File Location === |
Open the target directory to verify the results. | Open the target directory to verify the results. | ||
+ | |||
+ | === 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 | ||
Last modified:: 2022/06/23 09:38