Bridge Classification¶
USGS LiDAR Bridge Point Cloud Classification Pipeline
Overview¶
An end-to-end pipeline for classifying 3D LiDAR point clouds around bridges from USGS 3DEP data into 4 semantic classes using a sparse 3D U-Net. The pipeline covers data acquisition through inference, with automated weak supervision for scalable training data generation (550K+ bridges).
See Architecture for the classification schema and system design.
Documentation¶
| Document | Description |
|---|---|
| Architecture | System design, classification schema, full algorithm details |
| Data Pipeline | Step-by-step data flow with shapes at each stage |
| AWS Batch Inference | Scaling inference with AWS Batch array jobs |
| Deployment Runbook | End-to-end guide: setup, deploy, train, run inference, troubleshoot |
| API Reference | Auto-generated API documentation from source docstrings |
| Design Decisions | Rationale for key architectural choices |
Getting Started¶
See the README for full installation and pipeline run commands.