HumanoidEverywhere/simple_dataset

SIMPLE Dataset

Permanent backup of the heavy data/ assets for SIMPLE (the simulation backend of the HumanoidEverywhere Real2Sim pipeline). These are the assets that don't live in git because of their size.

Contents

Path	Size	What
data/assets/	~5.6 GB	Scene meshes, 3DGS PLYs, graspnet poses (incl. composed_bedroom_v2)
data/robots/	~645 MB	G1 MJCF + per-link 3DGS gaussians for robot rendering
data/training/	~1.4 GB	LeRobot-format episodes (output of SIMPLE Stage 5 postprocess)

The layout matches the on-disk layout expected by SIMPLE, so files extract directly into the repo root.

Download

From the SIMPLE repo root:

# Full mirror — places files under ./data/...
hf download HumanoidEverywhere/simple_dataset --repo-type dataset --local-dir .

Grab one subtree only:

hf download HumanoidEverywhere/simple_dataset --repo-type dataset \
    --local-dir . --include "data/robots/*"

hf download HumanoidEverywhere/simple_dataset --repo-type dataset \
    --local-dir . --include "data/training/*"

Upload — incremental (most common)

You generated new episodes or added a new scene. One command, one commit, lands at the exact remote path:

# new training folder
hf upload HumanoidEverywhere/simple_dataset \
    data/training/new_task   data/training/new_task \
    --repo-type=dataset \
    --commit-message "Add new_task episodes"

# new scene under data/assets/
hf upload HumanoidEverywhere/simple_dataset \
    data/assets/objects/composed_kitchen   data/assets/objects/composed_kitchen \
    --repo-type=dataset \
    --commit-message "Add composed_kitchen scene"

For incremental folder uploads from Python (handles Xet automatically and preserves the target path):

from huggingface_hub import HfApi
HfApi().upload_folder(
    folder_path="data/training/new_task",
    path_in_repo="data/training/new_task",
    repo_id="HumanoidEverywhere/simple_dataset",
    repo_type="dataset",
    commit_message="Add new_task episodes",
)

Upload — full re-sync (maintainers)

For first-time mirroring or large bulk pushes. hf upload-large-folder chunks

• resumes properly for large binaries, but dumps folder contents at the repo root and doesn't accept a path-in-repo argument, so stage the desired layout with hard links first:

# from the SIMPLE repo root
STAGE=$(mktemp -d -p /data2)   # same filesystem as data/ so cp -al works
mkdir -p "$STAGE/data"
cp -al data/assets   "$STAGE/data/assets"
cp -al data/robots   "$STAGE/data/robots"
cp -al data/training "$STAGE/data/training"

hf upload-large-folder HumanoidEverywhere/simple_dataset "$STAGE" \
    --repo-type=dataset --num-workers=4

rm -rf "$STAGE"

upload-large-folder and the Python API both handle Xet storage automatically for large .ply files (plain hf upload rejects binaries above the inline-storage threshold). cp -al hard-links rather than copying — no extra disk usage, but $STAGE must be on the same filesystem as data/.

Rate limits: HF caps commits at 128/hour per repo. Each hf upload invocation is one commit; upload-large-folder may issue many and can 429 mid-run — it retries automatically with backoff.