Inference Overlay: Difference between revisions
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foliage_inference_masks.jpg|Pixel Masks | foliage_inference_masks.jpg|Pixel Masks | ||
foliage_inference_boxes.jpg|Bounding Boxes | foliage_inference_boxes.jpg|Bounding Boxes | ||
foliage_inference_foliage_height.jpg|DSM DTM on identified features | foliage_inference_foliage_height.jpg|[[DSM]] subtracted by [[DTM]] on identified features | ||
foliage_inference_iterative_max_5_iterations_d0_25m.jpg|Max neighboring height within 0.25m, iterated 5 times | foliage_inference_iterative_max_5_iterations_d0_25m.jpg|Max neighboring height within 0.25m, iterated 5 times | ||
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Revision as of 14:19, 15 October 2024
The AI Inference Overlay is a Grid Overlay which can spatially identify features using one or more Prequel Grids. Features are identified using a Convolution Neural Network. This neural network takes a subsection (window) of the input grid and either classifies or detects one or more objects in that window. The window of detection marches over the input grid with a configurable stride.
Foliage Example
Using a Satellite Overlay of 0.1m detail, foliage features can be identified using an Inference Overlay and enhanced with a DTM, DSM, Combo Overlay to combine these and an optional iterative Max Overlay. For more information, see this how-to.
Labeled features on 0.1m satellite image
Label Scores
Pixel Masks
Bounding Boxes
Max neighboring height within 0.25m, iterated 5 times
How-to's
- How to import trees based on an Inference Overlay
- How to use the Inference Overlay to detect and add solar panels to buildings based on a Satellite Overlay
See also
