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recordings:tutorials:videos:pointcloud_labeling [2024/02/06 15:08] arnaud |
recordings:tutorials:videos:pointcloud_labeling [2024/04/10 08:37] (current) arnaud |
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- | This page is about labeling pointcloud to serve custom AI-training jobs and create detectors to be used in the Analysis Engine | + | This page is about labeling pointcloud to serve custom AI-training jobs and create detectors to be used in the Analysis Engine. \\ |
==== Step by step ==== | ==== Step by step ==== | ||
- Create a trajectory file that will be used as a canvas to easily navigate through the scene and label all elements of interest | - Create a trajectory file that will be used as a canvas to easily navigate through the scene and label all elements of interest | ||
- | | + | * Drag & drop your mapping run {{ : |
- | - Select pointcloud to attribute to an asset object | + | * Create a vector resource for trajectory to constraint navigation {{ : |
- | - Generate consolidated classified pointcloud + assets to serve AI-detector training | + | * Copy trajectory file in installation folder {{ : |
- | | + | * Define trajectory as linear reference and lock it {{ : |
+ | | ||
+ | * Create asset ressource {{ : | ||
+ | * Pinpoint asset objects in mapping run {{ : | ||
+ | - Select pointcloud to attribute to an asset object | ||
+ | * Select associated pointcloud and add pointcloud selection to asset objects {{ : | ||
+ | * Measure next asset object until the entire dataset is reviewed {{ : | ||
+ | - Generate consolidated classified pointcloud + assets to serve AI-detector training | ||
+ | * Generate data and merge pointcloud selections {{ : | ||
+ | * Pointcloud selection to classification | ||
+ | - Upload classified pointcloud to enable detector training | ||
+ | * Upload classified OPC to Reality Management {{ : | ||
+ | * Bentley team takes it from here and will start detector training |
Last modified:: 2024/02/06 15:08