Home › AI & machine learning › Grid Mapper - Substation Detector
Grid Mapper - Substation Detector QGIS 4 compatibility
QGIS 4 ready Active
Yes — Grid Mapper - Substation Detector supports QGIS 4 (declared max version 4.99.0).
Map electricity-grid assets and detect candidate substations, including resumable country-scale segment scanning, human-reviewed continual learning and safe model versioning.
About
Grid Mapper turns the MSc Data Science workflow "Investigating the use of Deep learning tools to Map substations in Kenya" (University of East London, 2023) into QGIS Processing tools. It maps grid assets from OpenStreetMap, optionally detects candidate substations from imagery, captures human-reviewed TP/FP/corrected/missed examples, exports fixed train/validation/test snapshots, and maintains a local model registry with conservative promotion gates. The default Map the grid mode is OpenStreetMap-only and needs no AI runtime or model. Optional local ONNX inference requires the external Python package onnxruntime. Optional TFLite inference requires ai-edge-litert, tflite-runtime or tensorflow. These runtimes and model weights are not bundled. Roboflow mode requires a Roboflow API key and uploads image tiles to Roboflow for inference. Grid Mapper also contacts OpenStreetMap Nominatim/Overpass and whichever imagery service the user selects. See the README and docs/NETWORK_AND_PRIVACY.md before using third-party services or imagery commercially.
| Author | Danson Mugambi (Bohemian Renewables) |
|---|---|
| Downloads | 135 |
| Latest version | 1.5.1 |
| Last updated | 2026-09-26 (20 days ago) |
| Min QGIS | 3.22.0 |
| Max QGIS | 4.99.0 |
| QGIS 4 ready | Yes |
| Maintenance | Active |
| Categories | AI & machine learning, Remote sensing |
| Tags | substation, grid, power, electricity, energy, deep learning, object detection, tflite, onnx, rf-detr, roboflow, remote sensing, satellite, renewable energy, active learning, continual learning |
Homepage · Repository · Issue tracker · Official page
Alternatives in AI & machine learning
Raster classification in QGIS with 11 machine learning algorithms, Optuna hyperparameter search, SHAP explanations, class imbalance handling
- ArcGeek CalculatorQGIS 4 ready
ArcGeek Calculator is a QGIS plugin that provides a comprehensive set of tools for coordinate calculations, conversions, spatial operations,
- Bunting Labs AI VectorizerQGIS 4 ready
Autocomplete for vectorizing and georeferencing raster maps.
Related plugins
- YOLO-MODNot QGIS 4 ready
Deep learning-based object detection in raster data using YOLO models within QGIS.
- AI Edit by TerraLabQGIS 4 ready
Generative AI image editing for QGIS 3.22 to 4. Show a redevelopment, a planted street, a flood or an orthophoto redrawn as a clean site pla
- AI Segmentation by TerraLabQGIS 4 ready
AI segmentation in QGIS 3.22 to 4. Draw a zone, name an object and get every building footprint, tree or solar panel as vector polygons, or
- Deepness: Deep Neural Remote SensingNot QGIS 4 ready
Inference of deep neural network models (ONNX) for segmentation, detection and regression
- QGIS Full Motion VideoQGIS 4 ready
Full Motion Video plugin for QGIS 4.
- TreeEyedNot QGIS 4 ready
TreeEyed is a QGIS plugin for tree monitoring using AI.
Maintenance: Active = updated within 1 year, Quiet = 1–3 years, Likely abandoned = over 3 years.