ManiSoft

ManiSoft is a soft-robot manipulation dataset and benchmark for vision-language-action learning. It contains expert demonstrations for four manipulation tasks:

• COLL: Collection
• ALN: Alignment
• ARR: Arrangement
• STK: Stacking

This upload directory currently provides:

• assets.tar: simulator assets required for replay and training
• clean/: task data packaged as .tar shards for efficient download and upload
• data_extract.sh: a utility script for recursively extracting all dataset shards

Task Layout in This Repository

The files hosted in the dataset repository are organized as tar shards rather than already-extracted case folders.

.
├── assets.tar
├── clean
│   ├── ALN
│   │   ├── train_bottle_0_9.tar
│   │   ├── train_bottle_10_19.tar
│   │   ├── eval_bottle_0_9.tar
│   │   └── ...
│   ├── ARR
│   │   ├── eval_bottle_0_9.tar
│   │   └── ...
│   ├── COLL
│   │   ├── train_pencup_0_9.tar
│   │   ├── eval_boxdrink_0_9.tar
│   │   └── ...
│   └── STK
│       ├── train_default_0_9.tar
│       ├── eval_default_0_9.tar
│       └── ...
└── data_extract.sh

For ALN, ARR, and COLL, shard names follow:

<split>_<object_category>_<start_case_id>_<end_case_id>.tar

For STK, shard names follow:

<split>_default_<start_case_id>_<end_case_id>.tar

Extracted Dataset Format

After extraction, each shard restores the original directory structure. A typical case directory looks like this:

clean/
└── ALN/
    ├── train/
    │   └── bottle/
    │       └── 0/
    │           ├── environment.yaml
    │           ├── instructions.txt
    │           ├── trajectory.pkl
    │           └── visual/
    └── eval/
        └── bottle/
            └── 0/
                ├── environment.yaml
                ├── instructions.txt
                ├── trajectory.pkl
                └── visual/

Each case is typically organized by:

<setting>/<task>/<split>/<object_category>/<case_id>/

Common files inside one case:

• instructions.txt: language instructions for the manipulation case
• environment.yaml: scene and task configuration
• trajectory.pkl: expert trajectory stored as a time-indexed dictionary
• visual/: visualization assets such as rendered frames or videos

Quick Download Example

If you use the Hugging Face CLI, you can download the dataset to a local directory like this:

hf download JobsWei/ManiSoft --local-dir ./ManiSoft --repo-type dataset

If you only need the benchmark data without simulator assets:

hf download JobsWei/ManiSoft --local-dir ./ManiSoft --repo-type dataset --exclude "assets.tar"

If you only need evaluation shards:

hf download JobsWei/ManiSoft --local-dir ./ManiSoft --repo-type dataset --include "**/eval/**"

data_extract.sh Usage

The repository includes data_extract.sh for recursively finding and extracting all .tar files under a root directory with parallel workers.

Command

bash data_extract.sh <tar_root_dir> <max_processes> <delete_tar_file>

Arguments

• tar_root_dir: root directory to recursively search for .tar files
• max_processes: number of parallel extraction processes, must be a positive integer
• delete_tar_file: whether to delete each .tar after successful extraction
  • 0: keep tar files
  • 1: delete tar files

Typical Examples

Extract all dataset shards under the downloaded directory and keep the original tar files:

bash data_extract.sh ./ManiSoft 8 0

Extract all dataset shards and delete each tar file after successful extraction:

bash data_extract.sh ./ManiSoft 8 1

Extract only the clean subset:

bash data_extract.sh ./ManiSoft/clean 8 1

What the Script Does

• recursively finds all .tar files under tar_root_dir
• extracts them in parallel
• restores files into the original relative paths stored in each tar shard
• optionally removes the source tar files after successful extraction

Recommended Workflow

hf download JobsWei/ManiSoft --local-dir ./ManiSoft --repo-type dataset --exclude "assets.tar"
cp /path/to/data_extract.sh ./ManiSoft/
cd ./ManiSoft
bash data_extract.sh ./clean 8 1

If you also need simulator assets:

tar -xvf assets.tar

Notes

• The extraction script requires a Unix-like shell environment with bash, find, tar, and standard job control support.
• Different shards may expand into the same train/ or eval/ directory tree. This is expected.
• trajectory.pkl is the main expert trajectory file used for imitation learning and replay.