azithromycin/younghyopark_pick_tblock_mp_centered_debug5

Pick TBlock MP Centered Debug5 TsFile

This is an Apache TsFile conversion of younghyopark/pick_tblock_mp_centered_debug5, a LeRobot v2.1 Dual-Panda manipulation dataset for a centered T-block pick task.

Source and Attribution

• Original dataset: younghyopark/pick_tblock_mp_centered_debug5
• Original repository creator and uploader: Younghyo Park (younghyopark)
• License: Apache-2.0
• Robot type: DualPanda
• Task metadata: pick something up
• Split: train
• Sampling rate: 50 fps
• Scale: 10 episodes, 6,389 frame rows, 1 task, 10 source Parquet files
• Source frame layout: data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet

The source card provides no paper or completed citation. Cite the original Hugging Face dataset and Younghyo Park when using this conversion.

TsFile Data

• TsFile: data/younghyopark_pick_tblock_mp_centered_debug5_train.tsfile
• Table: younghyopark_pick_tblock_mp_centered_debug5_train
• Rows: 6,389
• Episode/task devices: 10
• FIELD columns: 299
• Time precision: milliseconds
• Source Parquet size: 8,977,839 bytes
• TsFile size: 5,634,387 bytes
• TsFile/source size ratio: 0.6276

The 10 train episode shards are merged into one table-model TsFile. Filter the episode_index and task_index TAG columns to select a device/episode.

Schema

Columns	TsFile role	Type	Source mapping
Time	TIME	INT64	round(timestamp * 1000) ms
episode_index, task_index	TAG/device	STRING	Preserved source indexes
frame_index, sample_index, observation_environment_tblock_center_x, observation_environment_tblock_center_y, observation_environment_tblock_center_z	FIELD	Source numeric type	Scalar fields
observation_joint_0 ... observation_joint_15	FIELD	FLOAT	observation.joint row-major flattening (16 values)
observation_state_0 ... observation_state_29	FIELD	FLOAT	observation.state row-major flattening (30 values)
observation_environment_state_0 ... observation_environment_state_6	FIELD	FLOAT	observation.environment_state row-major flattening (7 values)
observation_environment_block_xy_0 ... observation_environment_block_xy_1	FIELD	FLOAT	observation.environment.block_xy row-major flattening (2 values)
observation_right_arm_joint_0 ... observation_right_arm_joint_6	FIELD	FLOAT	observation.right_arm.joint row-major flattening (7 values)
observation_right_joint_0 ... observation_right_joint_7	FIELD	FLOAT	observation.right.joint row-major flattening (8 values)
observation_left_arm_joint_0 ... observation_left_arm_joint_6	FIELD	FLOAT	observation.left_arm.joint row-major flattening (7 values)
observation_qvel_0 ... observation_qvel_29	FIELD	FLOAT	observation.qvel row-major flattening (30 values)
observation_env_qvel_0 ... observation_env_qvel_5	FIELD	FLOAT	observation.env_qvel row-major flattening (6 values)
observation_ee_pose_0 ... observation_ee_pose_15	FIELD	FLOAT	observation.ee_pose row-major flattening (16 values)
action_ctrl_0 ... action_ctrl_15	FIELD	FLOAT	action.ctrl row-major flattening (16 values)
action_joint_0 ... action_joint_15	FIELD	FLOAT	action.joint row-major flattening (16 values)
action_ee_pose_0 ... action_ee_pose_15	FIELD	FLOAT	action.ee_pose row-major flattening (16 values)
action_right_arm_joint_0 ... action_right_arm_joint_6	FIELD	FLOAT	action.right_arm.joint row-major flattening (7 values)
action_right_joint_0 ... action_right_joint_7	FIELD	FLOAT	action.right.joint row-major flattening (8 values)
action_left_arm_joint_0 ... action_left_arm_joint_6	FIELD	FLOAT	action.left_arm.joint row-major flattening (7 values)
action_right_arm_joint_relative_0 ... action_right_arm_joint_relative_6	FIELD	FLOAT	action.right_arm.joint.relative row-major flattening (7 values)
action_left_arm_joint_relative_0 ... action_left_arm_joint_relative_6	FIELD	FLOAT	action.left_arm.joint.relative row-major flattening (7 values)
action_joint_relative_0 ... action_joint_relative_15	FIELD	FLOAT	action.joint.relative row-major flattening (16 values)
observation_environment_tblock_center_xy_0 ... observation_environment_tblock_center_xy_1	FIELD	FLOAT	observation.environment.tblock.center.xy row-major flattening (2 values)
observation_environment_tblock_center_xyz_0 ... observation_environment_tblock_center_xyz_2	FIELD	FLOAT	observation.environment.tblock.center.xyz row-major flattening (3 values)
observation_environment_tblock_center_quat_0 ... observation_environment_tblock_center_quat_3	FIELD	FLOAT	observation.environment.tblock.center.quat row-major flattening (4 values)
observation_environment_tblock_center_euler_0 ... observation_environment_tblock_center_euler_2	FIELD	FLOAT	observation.environment.tblock.center.euler row-major flattening (3 values)
observation_environment_tblock_center_posquat_0 ... observation_environment_tblock_center_posquat_6	FIELD	FLOAT	observation.environment.tblock.center.posquat row-major flattening (7 values)
observation_environment_tblock_center_xaxis_0 ... observation_environment_tblock_center_xaxis_2	FIELD	FLOAT	observation.environment.tblock.center.xaxis row-major flattening (3 values)
observation_environment_tblock_center_yaxis_0 ... observation_environment_tblock_center_yaxis_2	FIELD	FLOAT	observation.environment.tblock.center.yaxis row-major flattening (3 values)
observation_environment_tblock_center_zaxis_0 ... observation_environment_tblock_center_zaxis_2	FIELD	FLOAT	observation.environment.tblock.center.zaxis row-major flattening (3 values)
observation_environment_tblock_center_mat_0 ... observation_environment_tblock_center_mat_8	FIELD	FLOAT	observation.environment.tblock.center.mat row-major flattening (9 values)
observation_environment_tblock_center_full_mat_0 ... observation_environment_tblock_center_full_mat_15	FIELD	FLOAT	observation.environment.tblock.center.full_mat row-major flattening (16 values)
observation_environment_tblock_center_reduced_mat_0 ... observation_environment_tblock_center_reduced_mat_11	FIELD	FLOAT	observation.environment.tblock.center.reduced_mat row-major flattening (12 values)

Conversion Details

• Time = round(timestamp * 1000) in milliseconds. Time starts at zero in each episode.
• Source timestamp is dropped because it is exactly represented by Time / 1000 seconds.
• Source index is renamed to sample_index; frame_index is preserved.
• Vector and matrix columns are flattened in row-major order, preserving their source prefix with . replaced by _.
• No numeric rows or numeric dimensions are intentionally dropped.
• No source Parquet files are copied under meta/; meta/ contains only source JSON/JSONL metadata updated for TsFile.

Encoding and Compression

• FLOAT/DOUBLE FIELD values: GORILLA + LZ4
• INT32/INT64 FIELD values: TS_2DIFF + LZ4
• BOOLEAN FIELD values: RLE + LZ4
• Time: TS_2DIFF + LZ4
• TAG values: TsFile table device/TAG storage (STRING, PLAIN + LZ4 physically)

These are verified from the generated TsFile schema and Time chunk metadata, not inferred from configuration text.

Videos

There are no source videos to include or link. The Hugging Face file tree contains no video files or videos/ directory, and source meta/info.json declares total_videos: 0 and video_path: null. Accordingly, this converted dataset contains no video copies and no fabricated video path. Numeric rows are self-contained and retain episode_index plus frame_index.

Integrity Checks

The Apache TsFile Java 2.2.1 reader successfully read all 6,389 rows back. Staged/source/TsFile row counts match, Time is monotonic within all 10 episode devices, TAG columns are queryable, and every physical codec matches the policy above. Local JSON and Markdown reports are kept outside the upload-ready dataset folder.

Minimal Read Example

from tsfile import TsFileReader

reader = TsFileReader("data/younghyopark_pick_tblock_mp_centered_debug5_train.tsfile")
table_name = "younghyopark_pick_tblock_mp_centered_debug5_train"
columns = [
    "episode_index",
    "task_index",
    "frame_index",
    "sample_index",
    "action_ctrl_0",
    "observation_environment_tblock_center_x",
]

with reader.query_table(table_name, columns, batch_size=65536) as result:
    print(result.read_arrow_batch().to_pandas().head())
reader.close()