inference-cloud.md

Inference & Cloud

Production inference pipeline and S3 infrastructure. Implements Phase F (inference) plus the cloud storage layer for model I/O, output auditing, and the model registry.

!!! tip "See also" - Architecture: Phase F for the inference workflow - AWS Batch Inference for scaling with AWS Batch

---

::: src.inference

CLI Arguments (src/inference.py)

Argument	Default	Description
--input	None	Input LAS/LAZ file path (single-file mode)
--output	None	Output LAS/LAZ file path (single-file mode)
--pairs-file	None	TSV file with input/output pairs (batch mode)
--model	(required)	Path to .ckpt checkpoint
--voxel-size	0.1	Voxel size (must match training)
--bridge-timeout	150	Seconds before a hung bridge is skipped (batch mode)
--mode	masked	Output mode: masked, raw, or both

Modes:

• masked - bridge deck only (class 2 to ASPRS 17) overlaid on original classification
• raw - all model classes replace original classification via MODEL_TO_LAS_MAP
• both - saves _predicted (raw) and _bridge_masked (masked) files

Usage Examples

# Single file, masked mode (default)
python src/inference.py \
    --model ./experiments/my-model/checkpoints/epoch=35.ckpt \
    --input ./data/ml-data/testing/02050206/bridge_10598181.laz \
    --output ./data/ml-data/predictions/bridge_10598181_bridge_masked.laz

# Batch mode with pairs file (model loaded once, processes all pairs)
python src/inference.py \
    --pairs-file ./pairs.tsv \
    --model ./experiments/my-model/checkpoints/epoch=35.ckpt \
    --mode masked --bridge-timeout 150

# Both mode (saves _predicted and _bridge_masked side by side)
python src/inference.py \
    --model ./experiments/my-model/checkpoints/epoch=35.ckpt \
    --input ./bridge.laz --output ./bridge_predicted.laz \
    --mode both

---

::: src.s3_client

---

::: src.s3_paths

---

::: src.s3_audit

---

::: src.model_registry