← mep

The eval-and-policy-composition pipeline

every stage from an IFC building model to a surface-coverage recall@K number · hover any node to trace its inputs (cyan) and outputs (amber) · click to open an explainer
The two amber FIX nodes are the methodology contribution: scanner-z anchoring + raycast floor filter in pose sampling, and the scene-full GT denominator in the recall metric. The second was a metric pathology in our own eval harness that inflated oracle 5-50×. Fixing it dropped oracle on gni_model_173 from 1.0 to 0.0093.
hover → trace links
click → open explainer · FIX = methodology contribution

what this is

role / number
real class / function
DATA · IFC scene
SIMULATOR · Open3D raycast
ROLLOUT · K steps
MODEL · learned scorer
EVAL · per-step metric
OUTPUT · curves + headline
🏛
IFC scene file
manifest entry
typology + path
📋
manifest.json
scene_ids · splits
iou_threshold
📦
learned_ckpt.pt
JointInfoGain weights
+ sibling config.json
eval config
K=rollout steps
n_candidates · seed
📐
Open3DSimulator.load_scene
IFC → Scene
AABB · mesh · instance_class
🏗
Scene
aabb · mesh · graph
instance_class[i] = MEPClass
FIX
🎯
sample_feasible_poses
fixed scanner-z (MEP-anchored)
+ raycast floor filter
candidates ×N
📡
scan_from_pose
5-DoF raycast bundle
→ LabeledCloud (xyz,cls,inst)
🧩
partial_cloud + history
union of scans so far
+ chosen pose idx list
🧵
BaselineContext
scene · sim · extractor
score_fn
🎲
policy.pick
→ next pose idx
🔁
scan + union
partial' = partial ∪ scan
history.append(idx)
final partial_cloud
after K steps
xyz · class_id · instance_id
🧮
GeometricExtractor
cloud → predicted
(pred_class, pred_instance)
📍
predicted instances
🧠
JointInfoGainPredictor
(partial_cloud + history,
candidates) → scores
FIX
📊
compute_mep_recall
Hungarian-matched, IoU≥τ
denom = scene.instance_class
RecallResult.overall
🧊
surface_coverage
vs dense-GT voxels
🔗
edge_recall
graph endpoints
≥min_pts both sides
📈
recall@K curves
per-policy · per-scene
data / training flow derived signal / eval ● win · headline FIX · methodology contribution