Inference Overlay: Difference between revisions

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[[File:Treesmask.jpg|thumb|right|Trees detected with Inference Overlay.]]
[[File:Treesmask.jpg|thumb|right|Trees detected with Inference Overlay.]]
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 [[Stride fraction (Inference Overlay)|configurable stride]].  
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 [[Stride fraction (Inference Overlay)|configurable stride]].  


==Foliage Example==
[[File:inference_foliage_animated.gif|frame|right|Animation of inference with a moving window and Bounding Box detection.]]
Using a [[Satellite Overlay]] of 0.1m detail, foliage features can be identified using an [[Inference Overlay]] and enhanced with a [[Digital Terrain Model Overlay]] (DTM), a [[WCS Overlay|WCS Overlay]] representing the [[DSM]], [[Combo Overlay]] to combine these and an optionally an iterative [[Avg & interpolation (overlay)|Max Overlay]] to enhance the foliage height. For more information, see this [[How to detect foliage using an Inference Overlay|how-to]].
<gallery widths="200">
<gallery widths="200">
foliage_inference_labels.jpg|Labeled features on 0.1m satellite image
foliage_inference_labels.jpg|[[Labels result type (Inference Overlay)|Labeled features]] on 0.1m satellite image
foliage_inference_scores.jpg|Label Scores
foliage_inference_scores.jpg|[[Scores result type (Inference Overlay)|Label Scores]]
foliage_inference_masks.jpg|Pixel Masks
foliage_inference_masks.jpg|[[Masks result type (Inference Overlay)|Pixel Masks]]
foliage_inference_boxes.jpg|Bounding Boxes
foliage_inference_boxes.jpg|[[Boxes result type (Inference Overlay)|Bounding Boxes]]
foliage_inference_foliage_height.jpg|DSM DTM on identified features
foliage_inference_foliage_height.jpg|[[DSM]] subtracted by [[DTM]] on identified features
/home/frank/Pictures/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
</gallery>
</gallery>


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* [[PyTorch]]
* [[PyTorch]]
|howtos=
|howtos=
* [[How to detect foliage using an Inference Overlay]]
* [[How to create foliage height based on an Inference Overlay]]
* [[How to import trees based on an Inference Overlay]]
* [[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]]
* [[How to detect solar panels using an Inference Overlay]]
* [[How to update Buildings's solar panel attribute based on an Inference Overlay]]
}}
}}
{{InferenceOverlay nav}}
{{InferenceOverlay nav}}
{{Overlay nav}}
{{Overlay nav}}

Latest revision as of 16:29, 7 November 2024

Trees detected with Inference Overlay.

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

Animation of inference with a moving window and Bounding Box detection.

Using a Satellite Overlay of 0.1m detail, foliage features can be identified using an Inference Overlay and enhanced with a Digital Terrain Model Overlay (DTM), a WCS Overlay representing the DSM, Combo Overlay to combine these and an optionally an iterative Max Overlay to enhance the foliage height. For more information, see this how-to.