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language:
- en
tags:
- 3d
- depth
- segmentation
- voxel-occupancy
pretty_name: PartProbe3D preprocessed datasets
configs:
- config_name: sage
data_files:
- split: test
path: catalog/sage/test.jsonl
- split: train
path: catalog/sage/train.jsonl
- config_name: 3dfront
data_files:
- split: test
path: catalog/3dfront/test.jsonl
- split: train
path: catalog/3dfront/train.jsonl
- config_name: ycbv
data_files:
- split: test
path: catalog/ycbv/test.jsonl
---
# PartProbe3D preprocessed datasets
Saved 64³ training and evaluation inputs for PartProbe3D. These archives preserve
RGB, visible object masks, depth and validity, camera calibration, posed meshes,
scene occupancy and independent per-object voxel occupancy. Targets describe mesh
triangle surfaces, including hidden surfaces and overlapping object channels.
| Dataset | Split | Views | Scenes |
| --- | --- | ---: | ---: |
| sage | test | 1,952 | 1,000 |
| sage | train | 17,456 | 8,931 |
| 3dfront | test | 10,066 | 935 |
| 3dfront | train | 39,930 | 3,703 |
| ycbv | test | 900 | 900 |
3D-FRONT uses the pinned last 1,000 MIDI rooms for testing and all other rooms
for training; all views of a room stay together. There is no validation split.
YCB-V is evaluation only. The viewer contains metadata indices; binary training
artifacts are in the archives.
## Upload status
| Dataset | Packaging complete | Upload complete | Packaged GiB | Transferred GiB |
| --- | --- | --- | ---: | ---: |
| sage | False | False | 317.76 | 317.76 |
| 3dfront | True | True | 273.53 | 273.53 |
| ycbv | True | True | 3.60 | 3.60 |
SAGE-10k keeps every room and view of a source layout in the same split,
using the saved SHA-256 layout split with a 10% test fraction and no validation split.
The completed extent dataset retains 19,408 training/evaluation views;
592 source captures were rejected by target preparation.
Archive inventories and SHA-256 checksums are in `bundles/<dataset>/index.json`.
FoundationPose currently has raw archives only. Diagnostic subsets, raw downloads,
model weights and model-specific feature caches are not included.
## Restore on another server
Use the PartProbe3D checkout containing `preprocess/huggingface.py` and install its
preprocessing dependencies plus `huggingface-hub`. Run from the repository root:
```bash
python -m preprocess.huggingface download --repo cubec/PartProbe3D-preprocessed --dataset sage --cleanup
python -m preprocess.huggingface download --repo cubec/PartProbe3D-preprocessed --dataset 3dfront --cleanup
python -m preprocess.huggingface download --repo cubec/PartProbe3D-preprocessed --dataset ycbv --cleanup
```
Downloads resume through Hugging Face. Restoration verifies every archive SHA-256
and refuses to replace different existing data. `--revision <commit>` pins a release.
The extracted roots are `datasets/<dataset>/extent/point_cloud`. `--cleanup` downloads
and restores one archive at a time, deleting each only after checksum verification and
successful extraction. Temporary archives use `datasets/<dataset>/archives/huggingface/`.
Without `--cleanup`, all downloaded archives are retained for reuse.
The loaders resolve `sample`, camera, geometry and target paths relative to the
dataset root. Historical absolute `file` and raw asset paths remain provenance;
loading saved samples and geometry does not require those paths or raw assets.
Prepare the model-specific features on the destination server, then train:
```bash
python -m ss_multiobj_depth.prepare --config ss_multiobj_depth/configs/front3d.json
python -m ss_multiobj_depth.train --config ss_multiobj_depth/configs/front3d.json
```
The mixed 32³ SLAT training config reads the saved 64³ datasets and pools grids online:
```bash
python -m slat_segmentation.train --config slat_segmentation/configs/front3d_sage_32.json
```
## Provenance
Original manifests, artifact completion markers, checksums, identities and split
policies are retained byte-for-byte inside the archives. Generation settings and
code hashes are also available under `metadata/<dataset>/conversion_policy.json`.
No model checkpoint was used for this upload; no checkpoint weights are included.
Source datasets retain their original licenses and access terms.
## Input and geometry previews
### sage: test
View: `0078d732045c32e0e3c2`.
[Posed prompted GT geometry (GLB)](previews/sage/test-geometry.glb)
### sage: train
View: `0002c10ce97a86f789fd`.
[Posed prompted GT geometry (GLB)](previews/sage/train-geometry.glb)
### 3dfront: test
View: `0001acce61c945bf4470`.
[Posed prompted GT geometry (GLB)](previews/3dfront/test-geometry.glb)
### 3dfront: train
View: `0000b002995b4131d534`.
[Posed prompted GT geometry (GLB)](previews/3dfront/train-geometry.glb)
### ycbv: test
View: `003c09039641a2b2efa1`.
[Posed prompted GT geometry (GLB)](previews/ycbv/test-geometry.glb)
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