Document Arbor evaluation outputs

README.md

@@ -40,10 +40,38 @@ conda activate arbor
 conda install pytorch==2.4.0 torchvision==0.19.0 pytorch-cuda=11.8 -c pytorch -c nvidia -y
 ./setup.sh --basic --xformers --spconv
 
+hf auth login
+hf auth whoami
 python scripts/download_model_from_hf.py --repo-id StabilityLabs/arbor --output-dir artifacts/model
-python examples/run_manual_example.py --example bus_013 --output-root outputs/manual_examples
+python examples/run_manual_example.py --example bus_013 --output-root outputs/manual_examples --evaluate
 ```
 
+For non-interactive shells, store a read token with:
+
+```bash
+read -s HF_TOKEN
+hf auth login --token "$HF_TOKEN"
+unset HF_TOKEN
+hf auth whoami
+```
+
+## Evaluation Outputs
+
+The GitHub release includes a public `arbor-evaluate` command that computes condition-following metrics and renders inspection panels without training code or the benchmark runner.
+
+```bash
+arbor-evaluate \
+  --prediction outputs/manual_examples/bus_013/mesh.ply \
+  --hull examples/constraints/bus__bus_013__19cbb410/hull_constraint.ply \
+  --avoidance examples/constraints/bus__bus_013__19cbb410/avoidance_constraint.ply \
+  --touch examples/constraints/bus__bus_013__19cbb410/touchable_constraint.ply \
+  --source-mesh examples/constraints/bus__bus_013__19cbb410/gt_mesh.ply \
+  --sparse-structure outputs/manual_examples/bus_013/ss_surface.npz \
+  --output-dir outputs/manual_examples/bus_013/evaluation
+```
+
+The evaluator writes `metrics.json`, `metrics_flat.json`, and `condition_panel.png`; pass `--save-gif` to also write `condition_orbit.gif`.
+
 ## Intended Uses
 
 Intended uses include research and creative workflows involving constrained 3D asset generation, design exploration, and assessment of text plus geometry conditioned generation methods.