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version string | method string | anchor_ids list | anchor_labels dict | background_ids list | instance_ids list | n_aug_anchor int64 | aug_seed int64 | eval_seed int64 | n_instances int64 | seed int64 |
|---|---|---|---|---|---|---|---|---|---|---|
PARAM-BENCH-EVAL v2.0 | random anchors (uniform, no type stratification, seed=42) | [
3279,
13435,
14593,
18290,
29257,
32099,
36049,
83811,
97501,
98220
] | {
"3279": "bspline",
"13435": "plane",
"14593": "plane",
"18290": "bspline",
"29257": "bspline",
"32099": "revolution",
"36049": "cylinder",
"83811": "bspline",
"97501": "bspline",
"98220": "bspline"
} | [
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54484,
102127,
76134,
73393,
79459,
36417,
81274,
77498,
3521,
32146,
21459,
10045,
89... | [
80863,
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66028,
85981,
45028,
47938,
51111,
33737,
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14051,... | 50 | 20,260,731 | 42 | 300 | 42 |
PARAM-BENCH — B-Rep NURBS Surface Benchmark
Parameterization-Agnostic B-Rep Representation Learning benchmark data. Built from the ABC Dataset (STEP format).
Important: This dataset is the canonical, frozen benchmark used for the PARAM-BENCH evaluation protocol. It is not reproducible from ABC by re-running the build pipeline (sampling is stochastic, OCC version matters). Use this uploaded artifact directly.
Contents
| File | Size | Description |
|---|---|---|
surfaces.db |
99 MB | 100,000 NURBS surfaces (SQLite, table surfaces) |
pca_augments.db |
3.8 MB | Pre-generated augmentations (10 anchors × 50 variants) |
eval_protocol_canonical.json |
58 KB | Frozen eval protocol (10 anchors / 5000 background / 300 instances) |
random_anchors.json |
0.5 KB | 10 uniform-random anchors (seed=42, no type stratification) |
manifest.json |
0.4 KB | Build manifest |
surface_vae.pt |
29 MB | NeuroNURBS checkpoint (parameter MSE loss) |
surface_geom_vae.pt |
29 MB | GeomVAE checkpoint (geometric L2 loss) |
Note: farthest_anchors.json (latent-FPS anchors) is deprecated and intentionally excluded.
Statistics
- 100,000 faces from 12 ABC chunks, all converted to NURBS (
BRepBuilderAPI_NurbsConvert) - All surfaces clamped (periodic surfaces unperiodized; original periodicity recorded in
is_periodic_u/vcolumns) - Dynamic stratified sampling: type × area × trim complexity
- Anchor faces: 3279, 13435, 14593, 18290, 29257, 32099, 36049, 83811, 97501, 98220
Quick Start
# Download the whole repo (~990 MB)
pip install huggingface_hub
huggingface-cli download Axiao1999/georep-benchmark --repo-type dataset \
--local-dir data/benchmark
# Or individual files
curl -L https://huggingface.co/datasets/Axiao1999/georep-benchmark/resolve/main/surfaces.db -o data/benchmark/surfaces.db
Checkpoints
Two VAE models (identical architecture, 7.37M params, fdim=32/edim=256, 100K faces / 200 epochs / 70-20-10 split), differing only in loss:
surface_vae.pt— NeuroNURBS: masked parameter MSE on control points/knotssurface_geom_vae.pt— GeomVAE: geometric L2 on UV-sampled points (differentiable NURBS)
Expected location after download:
benchmark_neuronurbs/outputs/surface_vae_200ep/surface_vae.pt
benchmark_nurbs_geom/outputs/surface_geom_vae_200ep/surface_geom_vae.pt
Eval Protocol
eval_protocol_canonical.json (PARAM-BENCH-EVAL v2.0) freezes:
- 10 uniform-random anchors (seed=42)
- 5000 background faces (real class distribution)
- 300 instances for invariance metrics
- Pre-generated augmentation database (50 variants/anchor)
License
ABC dataset: CC-BY. Derived data distributed under CC-BY-4.0.
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