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Pointcept2 processed point cloud datasets

Indoor scene datasets processed for Pointcept2: one .safetensors file per scene, a dataset.json card per dataset (fields, dtypes, roles, units, classes, provenance) and an index.json manifest (splits, point counts, byte sizes, sha256 of every file). Pointcept2 reads them directly; any safetensors reader can too.

folder source scenes content notes
scannet/ ScanNet v2 1,613 (train 1,201 / val 312 / test 100) coord (m, f32), color (u8), normal (f32), segment20, segment200 (i16, -1 ignore), instance (i32) Pointcept's preprocessing ported bit-identically (same labels and order)
structured3d-full/ Structured3D 21,821 rooms (all splits) coord, color, normal, segment, instance derived version: Pointcept's rooms pre-sampled to one point per 1.5 cm cell
s3dis/ S3DIS (Stanford 2D-3D-S) 272 rooms (Area_1 to Area_6) coord, color, normal, segment (13 classes), instance Pointcept's processed rooms (aligned, with normals), stored as-is
arkitscenes/ ARKitScenes (3DOD meshes) 5,047 scenes (Training / Validation) coord, color, normal Pointcept's processed scenes, stored as-is; no labels
hm3d/ HM3D v0.2 11,493 rooms (train / val) coord, color, normal; segment, instance where HM3D-Sem has them Pointcept's processed rooms, stored as-is
scannetpp/ ScanNet++ v2 956 scenes (train 856 / val 50 / test 50) coord, color, normal, segment, instance Pointcept's processed meshes, full resolution
scannetpp-g0.01/ ScanNet++ v2 956 scenes as scannetpp/ derived version: one point per 1 cm cell, for training

structured3d-full/ and hm3d/ are not complete yet: their train folders hold more files than the hub allows in one directory (10,000), and their layout here is still being decided. A folder is complete when its index.json is present. Each folder's dataset.json records the exact source, its hashes and the processing.

Terms of use

The data remain under the terms of their original datasets; this repository grants no additional rights. Read and accept them before use:

Reading a sample

from safetensors.numpy import load_file
scene = load_file("scannet/train/scene0000_00.safetensors")
coord, color = scene["coord"], scene["color"]  # (N, 3) float32 metres, (N, 3) uint8

Citation

Cite the original datasets (ScanNet, Structured3D, ...) and Pointcept.

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