THULab/easonjcc_so100_test-04

SO100 Test-04 TsFile

This Apache TsFile dataset contains the numeric trajectories from easonjcc/so100_test-04, a LeRobot v2.1 SO100 dataset for the task "Grasp a lego block and put it in the bin."

Source Dataset

• Author, repository owner, uploader, and latest commit author: easonjcc
• License: Apache-2.0
• Robot: so100; LeRobot codebase version: v2.1
• Split: train; sampling rate: 30 fps
• Numeric data: 30 episode Parquet shards, 19,608 rows, 643 to 661 rows per episode
• Task index 0: "Grasp a lego block and put it in the bin."
• Source frame layout: data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet
• Source video layout: videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4
• The source card provides no homepage, paper, or completed citation

TsFile Data

• File: data/easonjcc_so100_test_04_train.tsfile
• Table: easonjcc_so100_test_04_train
• Rows/devices: 19,608 rows across 30 episode/task TAG combinations
• Size: 0.29 MiB
• Time: round(timestamp * 1000) milliseconds, starting at 0 in every episode and ranging from 0 to 22,000 ms
• The 30 source Parquet shards are merged into this single train TsFile

Source	TsFile columns	Role	Type
timestamp	Time	TIME	INT64 milliseconds
episode_index	episode_index	TAG	STRING device segment
task_index	task_index	TAG	STRING device segment
frame_index	frame_index	FIELD	INT64
index	sample_index	FIELD	INT64
action[6]	action_0 ... action_5	FIELD	FLOAT
observation.state[6]	observation_state_0 ... observation_state_5	FIELD	FLOAT

Vector names retain the source prefix with . replaced by _. The six action and state dimensions are, in order, main_shoulder_pan, main_shoulder_lift, main_elbow_flex, main_wrist_flex, main_wrist_roll, and main_gripper. The source timestamp field is omitted after Time synthesis because it equals Time / 1000. Every numeric row and every other numeric dimension is retained.

Videos

Videos are not included here. All 90 source MP4 files remain under the original videos/ tree, totaling 642,241,112 bytes:

• observation.images.c1: 30 files, 201,127,816 bytes
• observation.images.c2: 30 files, 247,493,168 bytes
• observation.images.c3: 30 files, 193,620,128 bytes

The numeric rows align to each episode video through episode_index and frame_index.

Read Example

from tsfile import TsFileReader

reader = TsFileReader("data/easonjcc_so100_test_04_train.tsfile")
columns = ["episode_index", "task_index", "frame_index", "action_0", "observation_state_0"]
with reader.query_table("easonjcc_so100_test_04_train", columns, batch_size=65536) as result:
    print(result.read_arrow_batch().to_pandas().head())
reader.close()

Attribution

The source repository and its current commits identify easonjcc as the publisher. Cite the original dataset and its owner when using this TsFile dataset.