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@bacetiner bacetiner released this 30 Sep 23:10
· 338 commits to master since this release
v3.0.0
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Learn about vigilant mode.

BRAILS version 3.0.0 contains a new interface that simplifies inventory generation and training image classification/semantic segmentation models.

In terms of inventory generation capabilities, BRAILS now contains modules that can predict: 1) roof type, 2) roof cover type, 3) occupancy class, 4) era of construction, 5) the number of floors, 6) building height, 7) roof eave height, 8) roof pitch, 9) facade window area, 10) first-floor height, 11) existence of chimneys, and 12) existence of garages.

The new InventoryGenerator workflow offers a convenient end-to-end workflow to create building inventories. InventoryGenerator

  1. Extracts location polynomials using Nominatim API,
  2. Parses footprint information from Microsoft Footprint Database or OpenStreetMaps,
  3. Downloads Google street-level or satellite imagery explicitly focused on each building in the region specified by the user,
  4. Passes these images through BRAILS modules, and
  5. Prints out simple CSV files for ingestion into many other platforms, such as R2D or QGIS.

All of this can now be performed in a few lines of code.

BRAILS now also offers automated pipelines for training image classification and semantic segmentation models. Using ImageClassifier and ImageSegmenter, it is possible to train state-of-the-art deep learning models without needing to spend developing time on the training step of the process.

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