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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    IndexError
Message:      list index out of range
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1898, in _prepare_split_single
                  original_shard_lengths[original_shard_id] += len(table)
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^
              IndexError: list index out of range
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1347, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 884, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 947, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1736, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1919, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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robot_type
string
codebase_version
string
total_episodes
int64
total_frames
int64
total_tasks
int64
total_videos
int64
total_chunks
int64
chunks_size
int64
fps
int64
splits
dict
data_path
string
video_path
string
features
dict
so-100
v2.1
0
0
1
0
1
1,000
30
{ "train": "0:0" }
data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet
videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4
{ "action": { "dtype": "float32", "shape": [ 6 ], "names": [ "motor_1", "motor_2", "motor_3", "motor_4", "motor_5", "motor_6" ] }, "observation.state": { "dtype": "float32", "shape": [ 6 ], "names": [ "motor_1", "motor_2", "motor_3", "motor_4", "motor_5", "motor_6" ] }, "timestamp": { "dtype": "float32", "shape": [ 1 ], "names": null }, "episode_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "frame_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "task_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "observation.images.main": { "dtype": "video", "shape": [ 1080, 1920, 3 ], "names": [ "height", "width", "channel" ], "info": { "video.fps": 30, "video.codec": "avc1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } } }

coffee_arm

This dataset was generated using phosphobot.

This dataset contains a series of episodes recorded with a robot and multiple cameras. It can be directly used to train a policy using imitation learning. It's compatible with LeRobot.

To get started in robotics, get your own phospho starter pack..

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