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The info cannot be fetched for the config 'default' of the dataset.
Error code:   InfoError
Exception:    ConnectionError
Message:      Couldn't reach https://huggingface.co/datasets/wentao-yuan/robopoint-data/resolve/aaa875d11859d8ad546d5208784dd62c6699842b/.huggingface.yaml (error 500)
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 211, in compute_first_rows_from_streaming_response
                  info = get_dataset_config_info(path=dataset, config_name=config, token=hf_token)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 478, in get_dataset_config_info
                  builder = load_dataset_builder(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 2266, in load_dataset_builder
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1914, in dataset_module_factory
                  raise e1 from None
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1889, in dataset_module_factory
                  return HubDatasetModuleFactoryWithoutScript(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1225, in get_module
                  standalone_yaml_path = cached_path(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 201, in cached_path
                  output_path = get_from_cache(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 635, in get_from_cache
                  raise ConnectionError(f"Couldn't reach {url} (error {response.status_code})")
              ConnectionError: Couldn't reach https://huggingface.co/datasets/wentao-yuan/robopoint-data/resolve/aaa875d11859d8ad546d5208784dd62c6699842b/.huggingface.yaml (error 500)

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RoboPoint Dataset Card

Dataset details

This dataset contains 1432K image-QA instances used to fine-tune RoboPoint, a VLM for spatial affordance prediction. It consists of the following parts:

  • 347K object reference instances from a synthetic data pipeline;
  • 320K free space reference instances from a synthetic data pipeline;
  • 100K object detection instaces from LVIS;
  • 150K GPT-generated instruction-following instances from liuhaotian/LLaVA-Instruct-150K;
  • 515K general-purpose VQA instances from various academic-oriented tasks including RefCOCO, GQA, OCR-VQA, TextVQA, and Visual Genome.

Dataset structure

robopoint_1432k.json contains a list of conversations with image references. An example looks like the following

{
    "id": "region_ref/1033888784-63bd2a7_cam05_obj5-obj18_left",
    "image": "region_ref/1033888784-63bd2a7_cam05_obj5-obj18.png",
    "conversations": [
        {
            "from": "human",
            "value": "<image>\nIn the image, there is an item encased within a red rectangle. Pinpoint several points within the vacant space situated to the left of the object that is highlighted. Your answer should be formatted as a list of tuples, i.e. [(x1, y1), (x2, y2), ...], where each tuple contains the x and y coordinates of a point satisfying the conditions above. The coordinates should be between 0 and 1, indicating the normalized pixel locations of the points in the image."
        },
        {
            "from": "gpt",
            "value": "[(0.461, 0.527), (0.498, 0.521), (0.481, 0.521), (0.445, 0.529)]"
        }
    ]
}

The images folder contains reference images in compressed files. To start training, first combine any multi-part files:

cat region_ref.tar.gz.part_* > region_ref.tar.gz

Then, decompress

tar -xzvf region_ref.tar.gz

Resources for More Information

Citation

If you find our work helpful, please consider citing our paper.

@article{yuan2024robopoint,
  title={RoboPoint: A Vision-Language Model for Spatial Affordance Prediction for Robotics},
  author={Yuan, Wentao and Duan, Jiafei and Blukis, Valts and Pumacay, Wilbert and Krishna, Ranjay and Murali, Adithyavairavan and Mousavian, Arsalan and Fox, Dieter},
  journal={arXiv preprint arXiv:2406.10721},
  year={2024}
}
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