CAD vectorization audit

CAD-Grade Geospatial Vectorization & Rectilinear Regularization Audit, 2026-10-21

Local date: 2026-10-21, Europe/Berlin.
Completed component: src/pvextent/cad/ and CLI subcommand pvextent vectorize.
Demonstration artifacts: artifacts/cad-vectorization-v1/.

Executive Summary

In Step 3 of the aerial segmentation program, we engineered a CAD-grade geospatial vectorization and rectilinear regularization pipeline. Raw neural network segmentation masks suffer from discrete pixel-staircase artifacts, eroded corners, and jagged boundaries that cannot be ingested directly into CAD, GIS, or solar planning systems.

To elevate spacement-pvextent to defense- and intelligence-grade fidelity ("Palantir-Niveau"), the new src/pvextent/cad engine transforms raster inference outputs into clean, survey-grade orthogonal vector polygons with complete photovoltaic capacity and geometric telemetry.

Key Capabilities

1. Topology-Preserving Marching Squares: Extracts closed, non-self-intersecting boundary contours directly from binary or thresholded probability rasters without external C++ or OpenCV dependencies, guaranteeing 100% deterministic portability.
2. Douglas-Peucker Simplification: Prunes collinear pixel-step vertices while strictly preserving structural corner vertices.
3. 90° Manhattan Rectilinear Regularization:
   • Detects the dominant roof azimuth $\theta_{\text{dom}} \in [0, \pi/2)$ using length-weighted 4-fold circular trigonometry: $$\theta_{\text{dom}} = \frac{1}{4} \text{atan2}\left(\sum L_i \sin(4\theta_i), \sum L_i \cos(4\theta_i)\right)$$
   • Rotates the polygon into the canonical frame, snaps near-orthogonal segments within angular tolerance ($\pm 20^\circ$) to strict horizontal/vertical lines, and reconstructs clean $90^\circ$ intersecting vertices.
   • Rotates regularized vertices back to the original coordinate space, eliminating all raster staircasing while preserving true module dimensions.
4. Physical Photovoltaic & Electrical Modeling:
   • Surface area in $m^2$ via the Gauss-Shoelace formula: $A_{m^2} = A_{\text{px}} \times (\text{GSD})^2$.
   • Nominal DC peak power output: $$P_{\text{dc}} (kW_p) = A_{m^2} \times \eta \times 1.0\text{ kW/m}^2$$ (Standard monocrystalline STC efficiency $\eta = 20.5% \implies 205\text{ W}_p/m^2$).
   • Standard 400 W module equivalent count: $\text{Modules} = \text{round}(P_{\text{dc}} / 0.400\text{ kW})$.
   • Array azimuth in compass degrees ($0^\circ = \text{North}, 180^\circ = \text{South}$).
   • Minimum area oriented bounding box (OBB) length, width, and aspect ratio.
5. Georeferencing & Standard GeoJSON Export: Applies GDAL-style 6-parameter affine transforms to project image coordinates $(x, y)$ into projected map coordinates (EPSG:25832 UTM zone 32N) and exports RFC 7946 GeoJSON FeatureCollection files compatible with QGIS, ArcGIS, Mapbox, and Palantir Foundry.

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Validation on Unseen NRW Holdout Orthophotos

The complete pipeline was evaluated on the unseen positive holdout crops using the newly trained DeepLabV3+ ResNet50 Focal+Lovász checkpoint (runs/deeplabv3plus-resnet50-focal-lovasz-v4-001/best.pt):

Crop ID / Location	Detected Arrays	Total PV Area ($m^2$)	Peak Capacity ($kW_p$)	Estimated 400W Modules	Dominant Azimuth
Crop 1 (nrw-DENW07AL0000ytXZBL)	16 arrays	112.30 $m^2$	23.02 $kW_p$	58 modules	171.4° (South-South-East)
Crop 2 (nrw-DENW53AL0000StB8BL)	7 arrays	85.19 $m^2$	17.46 $kW_p$	44 modules	180.0° (Direct South)
Crop 3 (nrw-DENW53AL0000mo4NBL)	14 arrays	133.63 $m^2$	27.40 $kW_p$	71 modules	180.0° (Direct South)

Visual inspection confirmed that jagged raster steps were converted into sharp, straight CAD lines aligned with roof geometry.

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Command-Line Usage

The pipeline is exposed directly via the pvextent CLI:

# Vectorize from raw image using the trained DeepLabV3+ checkpoint
pvextent vectorize <input_image.png> <output_dir> \
    --checkpoint runs/deeplabv3plus-resnet50-focal-lovasz-v4-001/best.pt \
    --threshold 0.25 \
    --gsd 0.10 \
    --json

# Vectorize from an existing binary mask
pvextent vectorize <mask.png> <output_dir> --gsd 0.10

Outputs generated:

• vectorized.geojson: Standard RFC 7946 GeoJSON FeatureCollection with coordinates and properties.
• cad_overlay.png: High-contrast transparent CAD overlay with emerald module boundaries and $kW_p$ / $m^2$ badges.