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Datasets:
CSI-Agent
/
test4

Tasks:
Robotics
Modalities:
Tabular
Time-series
Video
Formats:
parquet
Size:
10K - 100K
Tags:
LeRobot
lerobot
so101_follower
Libraries:
Datasets
pandas
Polars
License:
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observation.state
list
action
list
timestamp
float32
0
21.8
frame_index
int64
0
654
episode_index
int64
0
29
index
int64
0
19.5k
task_index
int64
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3.233333
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3.3
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End of preview. Expand in Data Studio

This dataset was created using LeRobot.

Dataset Description

A robot manipulation dataset for imitation learning, compatible with LeRobot v3.0 format.

  • Robot Type: so101_follower
  • Total Episodes: 30
  • Total Frames: 19469
  • FPS: 30
  • Codebase Version: v3.0

Features

Feature Shape Type
observation.state [6] float32
action [6] float32
observation.images.realsense [480, 640, 3] video
observation.images.innomaker [480, 640, 3] video

Dataset Structure

meta/info.json:

{
  "codebase_version": "v3.0",
  "robot_type": "so101_follower",
  "total_episodes": 30,
  "total_frames": 19469,
  "total_tasks": 1,
  "chunks_size": 1000,
  "data_files_size_in_mb": 100,
  "video_files_size_in_mb": 200,
  "fps": 30,
  "splits": {
    "train": "0:30"
  },
  "data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
  "video_path": "videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4",
  "features": {
    "observation.state": {
      "dtype": "float32",
      "shape": [
        6
      ],
      "names": [
        "shoulder_pan.pos",
        "shoulder_lift.pos",
        "elbow_flex.pos",
        "wrist_flex.pos",
        "wrist_roll.pos",
        "gripper.pos"
      ]
    },
    "action": {
      "dtype": "float32",
      "shape": [
        6
      ],
      "names": [
        "shoulder_pan.pos",
        "shoulder_lift.pos",
        "elbow_flex.pos",
        "wrist_flex.pos",
        "wrist_roll.pos",
        "gripper.pos"
      ]
    },
    "observation.images.realsense": {
      "dtype": "video",
      "shape": [
        480,
        640,
        3
      ],
      "names": [
        "height",
        "width",
        "channels"
      ],
      "info": {
        "video.height": 480,
        "video.width": 640,
        "video.codec": "av1",
        "video.pix_fmt": "yuv420p",
        "video.is_depth_map": false,
        "video.fps": 30,
        "video.channels": 3,
        "has_audio": false
      }
    },
    "observation.images.innomaker": {
      "dtype": "video",
      "shape": [
        480,
        640,
        3
      ],
      "names": [
        "height",
        "width",
        "channels"
      ],
      "info": {
        "video.height": 480,
        "video.width": 640,
        "video.codec": "av1",
        "video.pix_fmt": "yuv420p",
        "video.is_depth_map": false,
        "video.fps": 30,
        "video.channels": 3,
        "has_audio": false
      }
    },
    "timestamp": {
      "dtype": "float32",
      "shape": [
        1
      ],
      "names": null
    },
    "frame_index": {
      "dtype": "int64",
      "shape": [
        1
      ],
      "names": null
    },
    "episode_index": {
      "dtype": "int64",
      "shape": [
        1
      ],
      "names": null
    },
    "index": {
      "dtype": "int64",
      "shape": [
        1
      ],
      "names": null
    },
    "task_index": {
      "dtype": "int64",
      "shape": [
        1
      ],
      "names": null
    }
  }
}

Usage 

from lerobot.datasets.lerobot_dataset import LeRobotDataset

# Load the dataset
dataset = LeRobotDataset("CSI-Agent/test4")

# Access a sample
sample = dataset[0]
print(sample.keys())

Citation 

@misc{test4,
  title = {test4},
  year = {2025},
  publisher = {Hugging Face},
  howpublished = {\url{https://huggingface.co/datasets/CSI-Agent/test4}}
}
Downloads last month
48
Size of downloaded dataset files:
1.07 MB
Size of the auto-converted Parquet files:
1.07 MB
Number of rows:
19,469

Models trained or fine-tuned on CSI-Agent/test4