Episodes Preview LeRobot Visualizer
4k episodes · 30 fps · 3 cameras · 640×360 av1

This dataset was created using LeRobot.

Note on normalization statistics

On 2026-10-17 the quantile entries (q01, q10, q50, q90, q99) in meta/stats.json were replaced for all numeric, non-index features (observation.state, action and the labels.* features).

LeRobot's recompute_stats aggregates quantiles as the frame-count-weighted mean of per-episode quantiles. With 90-frame episodes this gives quantiles far narrower than the data: under QUANTILES normalization (the pi0.5 default) 37-92% of frames per dimension fell outside [-1, 1]. The new values are exact quantiles over all 360,000 frames, so about 2% of frames per dimension fall outside [-1, 1].

min, max, mean, std, count and the image stats are unchanged. The action stats are for absolute actions; recompute them (and fix the quantiles again) before training with relative actions. The episode_index and index stats were not touched and are not used for training. Previous stats.json: commit 112d8d5.

Dataset Structure

meta/info.json:

{
    "codebase_version": "v3.0",
    "fps": 30,
    "features": {
        "observation.images.middle_left_camera": {
            "dtype": "video",
            "shape": [
                3,
                360,
                640
            ],
            "names": [
                "channels",
                "height",
                "width"
            ],
            "info": {
                "video.height": 360,
                "video.width": 640,
                "video.codec": "av1",
                "video.pix_fmt": "yuv420p",
                "video.fps": 30,
                "video.channels": 3,
                "has_audio": false,
                "video.g": 2,
                "video.crf": 30,
                "video.preset": 12,
                "video.fast_decode": 0,
                "video.video_backend": "pyav",
                "video.extra_options": {},
                "is_depth_map": false
            }
        },
        "observation.images.top_center_camera": {
            "dtype": "video",
            "shape": [
                3,
                360,
                640
            ],
            "names": [
                "channels",
                "height",
                "width"
            ],
            "info": {
                "video.height": 360,
                "video.width": 640,
                "video.codec": "av1",
                "video.pix_fmt": "yuv420p",
                "video.fps": 30,
                "video.channels": 3,
                "has_audio": false,
                "video.g": 2,
                "video.crf": 30,
                "video.preset": 12,
                "video.fast_decode": 0,
                "video.video_backend": "pyav",
                "video.extra_options": {},
                "is_depth_map": false
            }
        },
        "observation.images.top_left_camera": {
            "dtype": "video",
            "shape": [
                3,
                360,
                640
            ],
            "names": [
                "channels",
                "height",
                "width"
            ],
            "info": {
                "video.height": 360,
                "video.width": 640,
                "video.codec": "av1",
                "video.pix_fmt": "yuv420p",
                "video.fps": 30,
                "video.channels": 3,
                "has_audio": false,
                "video.g": 2,
                "video.crf": 30,
                "video.preset": 12,
                "video.fast_decode": 0,
                "video.video_backend": "pyav",
                "video.extra_options": {},
                "is_depth_map": false
            }
        },
        "labels.delta_robot_pose": {
            "dtype": "float32",
            "shape": [
                6
            ],
            "names": [
                "delta_robot_pose.x",
                "delta_robot_pose.y",
                "delta_robot_pose.z",
                "delta_robot_pose.rx",
                "delta_robot_pose.ry",
                "delta_robot_pose.rz"
            ]
        },
        "labels.hand_pose": {
            "dtype": "float32",
            "shape": [
                9
            ],
            "names": [
                "hand_pose.x",
                "hand_pose.y",
                "hand_pose.z",
                "hand_pose.r11",
                "hand_pose.r21",
                "hand_pose.r31",
                "hand_pose.r12",
                "hand_pose.r22",
                "hand_pose.r32"
            ]
        },
        "labels.target_joint_positions": {
            "dtype": "float32",
            "shape": [
                6
            ],
            "names": [
                "target_joint_positions.0",
                "target_joint_positions.1",
                "target_joint_positions.2",
                "target_joint_positions.3",
                "target_joint_positions.4",
                "target_joint_positions.5"
            ]
        },
        "action": {
            "dtype": "float32",
            "shape": [
                9
            ],
            "names": [
                "target_robot_pose.x",
                "target_robot_pose.y",
                "target_robot_pose.z",
                "target_robot_pose.r11",
                "target_robot_pose.r21",
                "target_robot_pose.r31",
                "target_robot_pose.r12",
                "target_robot_pose.r22",
                "target_robot_pose.r32"
            ]
        },
        "labels.target_robot_pose": {
            "dtype": "float32",
            "shape": [
                9
            ],
            "names": [
                "target_robot_pose.x",
                "target_robot_pose.y",
                "target_robot_pose.z",
                "target_robot_pose.r11",
                "target_robot_pose.r21",
                "target_robot_pose.r31",
                "target_robot_pose.r12",
                "target_robot_pose.r22",
                "target_robot_pose.r32"
            ]
        },
        "labels.pickup_error": {
            "dtype": "float32",
            "shape": [
                7
            ],
            "names": [
                "pickup_error.x",
                "pickup_error.y",
                "pickup_error.z",
                "pickup_error.quat_w",
                "pickup_error.quat_x",
                "pickup_error.quat_y",
                "pickup_error.quat_z"
            ]
        },
        "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
        },
        "observation.state": {
            "dtype": "float32",
            "shape": [
                9
            ],
            "names": [
                "current_robot_pose.x",
                "current_robot_pose.y",
                "current_robot_pose.z",
                "current_robot_pose.r11",
                "current_robot_pose.r21",
                "current_robot_pose.r31",
                "current_robot_pose.r12",
                "current_robot_pose.r22",
                "current_robot_pose.r32"
            ]
        }
    },
    "total_episodes": 4000,
    "total_frames": 360000,
    "total_tasks": 1,
    "chunks_size": 1000,
    "data_files_size_in_mb": 100,
    "video_files_size_in_mb": 200,
    "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",
    "robot_type": null,
    "splits": {
        "train": "0:4000"
    }
}

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