Solar panels (Neural Network)
This functionality is deprecated and will be removed in the future.
The Solar panels Neural Network is a Convolution Neural Network that identifies solar panels, mainly situated on roofs of buildings.
An Inference Overlay can be configured with this Neural Network. Its default settings are:
- Preferred grid cell size: 0.1m
- Inference mode: BBox Detection
- Mask threshold: 0.9
- Score threshold: 0.2
- Stride fraction: 0.50 (50%)
Identifiable features:
- Solar panel blue (oldest type)
- Solar panel gray (mid-aged type)
- Solar panel black (newest type)
-
Labeled features on 0.1m satellite image
How-to's
- How to detect solar panels using an Inference Overlay
- How to update Buildings's solar panel attribute based on an Inference Overlay