Add Google Scanned Objects 'Shoe' subset (254 meshes, CC-BY 4.0) - #1
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254 shoe scans from Scanned Objects by Google Research, downloaded from Gazebo Fuel (owner GoogleResearch, category Shoe, all CC-BY 4.0) and decimated to a 10k-face budget for voxelization workloads. Binary little-endian PLY, 46 MB total. Per-model attribution, source URLs, and original/stored face counts are in meshes/gso_shoes/ATTRIBUTION.json. The subset is reproducible with tools/curate_gso_shoes.py. Intended for the fvdb-core generative examples (shape VAE / completion, openvdb/fvdb-core#753): a single category with real intra-class variation for latent-space demos. Signed-off-by: Jonathan Swartz <jonathan@jswartz.info>
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Summary
Adds the complete 254-model Shoe category of Scanned Objects by Google Research (Gazebo Fuel, owner
GoogleResearch), curated for the fvdb-core generative examples (openvdb/fvdb-core#753): a single object category with real intra-class variation — runners, boat shoes, ballet flats, cleats, boots — which is what latent-space demos (shape VAE interpolation / prior sampling, shape completion) need.meshes/gso_shoes/ATTRIBUTION.json, and the README documents the licensing.point_cloud_utils(voxelization workloads at resolution 64–128 don't benefit from denser scan geometry): 46 MB total.tools/curate_gso_shoes.py(paginates the Fuel API, filters owner + category + license, downloads, decimates, writes PLYs + manifest).Format note for reviewers
These are binary little-endian PLYs, deviating from the ASCII convention established in a0f9d73 — binary keeps the snapshot tarball that
fvdb.utils.examples.fetch_data_repodownloads on every CI run ~3x smaller for this set. Happy to convert to ASCII if repo-wide consistency matters more.A follow-up fvdb-core PR will bump the pinned data revision and add a
load_gso_shoes()loader + switch the shape-VAE example/notebook to train on this set.🤖 Generated with Claude Code