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license: mit

Datacard

This is the official fine-tuning dataset provided by VLABench (raw data), with 500 episodes each task. The current version includes 10 primitive tasks.

Source

Uses

Download all archive files and use the following command to extract:

cat vlabench_primitive.tar.gz.* | tar -xzvf -

In the resulting VLABench_release folder, there will be two folders: primitive(release now) and composite(under management). In primitive folder, there are ten sub-folders and the dataset HDF5 files can be listed as:

VLABench_release
└── primitive
    ├── add_condiment
        └── episode_0.hdf5
        ...
    ├── insert_flower
        └── episode_0.hdf5
        ...
    ├── select_book
        └── ...
    ├── select_chemistry_tube
        └── ...
    ├── select_drink
        └── ...
    ├── select_fruit
        └── ...
    ├── select_mahjong
        └── ...
    ├── select_painting
        └── ...
    ├── select_poker
        └── ...
    └── select_toy
        └── ...

An example of the single episode data is:

data
    2025-02-23 20:46:40
        instruction
         (1,) |S38
         ['Please put the striped_10 in any hole.']
        meta_info
            entities
             (6,) |S15
             ['billiards_table', 'striped_10', 'striped_14', 'striped_11', 'striped_12', 'solid_1']
            episode_config
             () | S1879
            target_entity
             (1,) |S10
             ['striped_10']
        observation
            depth
             (212, 4, 480, 480) float32
            ee_state
             (212, 8) float32
            point_cloud_colors
             (212, 11905, 3) float32
            point_cloud_points
             (212, 11905, 3) float32
            q_acceleration
             (212, 7, 1) float32
            q_state
             (212, 7, 1) float32
            q_velocity
             (212, 7, 1) float32
            rgb
             (212, 4, 480, 480, 3) uint8
            robot_mask
             (212, 4, 480, 480) float32
        trajectory
         (212, 8) float32

Citation

If you find our work helps,please cite us:

@misc{zhang2024vlabench,
      title={VLABench: A Large-Scale Benchmark for Language-Conditioned Robotics Manipulation with Long-Horizon Reasoning Tasks}, 
      author={Shiduo Zhang and Zhe Xu and Peiju Liu and Xiaopeng Yu and Yuan Li and Qinghui Gao and Zhaoye Fei and Zhangyue Yin and Zuxuan Wu and Yu-Gang Jiang and Xipeng Qiu},
      year={2024},
      eprint={2412.18194},
      archivePrefix={arXiv},
      primaryClass={cs.RO},
      url={https://arxiv.org/abs/2412.18194}, 
}