22122025-foldclo-09_lerobot_format
收藏Hugging Face2026-05-28 更新2026-05-28 收录
下载链接:
https://huggingface.co/datasets/leokswang/22122025-foldclo-09_lerobot_format
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资源简介:
该数据集是一个机器人控制数据集,使用LeRobot工具创建。数据集包含10个episodes,总计29210帧图像,帧率为30fps。数据以parquet格式存储,每个episode分为多个chunks。数据集特征包括:来自顶部、左侧和右侧摄像头的观测图像(分辨率为360x640x3,RGB通道),14维的浮点数状态观测,14维的浮点数动作,以及时间戳、帧索引、episode索引、索引和任务索引等元数据。机器人类型为“yam”。数据集主要用于机器人学习任务,如模仿学习或强化学习。
This dataset is a robot control dataset created using the LeRobot tool. It contains 10 episodes, totaling 29210 image frames with a frame rate of 30fps. The data is stored in parquet format, with each episode divided into multiple chunks. Dataset features include: observation images from top, left, and right cameras (resolution 360x640x3, RGB channels), 14-dimensional floating-point state observations, 14-dimensional floating-point actions, and metadata such as timestamps, frame indices, episode indices, indices, and task indices. The robot type is yam. The dataset is primarily used for robot learning tasks, such as imitation learning or reinforcement learning.
提供机构:
leokswang创建时间:
2026-05-28
原始信息汇总
数据集概述
基本信息
- 数据集名称: 22122025-foldclo-09_lerobot_format
- 许可证: Apache-2.0
- 任务类别: 机器人学 (Robotics)
- 创建工具: LeRobot
数据集规模
- 总片段数 (Episodes): 10
- 总帧数 (Frames): 29,210
- 总任务数 (Tasks): 1
- 总视频数: 0
- 总块数 (Chunks): 1
- 块大小: 1,000
- 帧率 (FPS): 30
- 机器人类型: yam
数据集划分
- 训练集: 片段 0 至 9 (共10个片段)
数据结构与特征
特征维度
| 特征名称 | 数据类型 | 形状 | 说明 |
|---|---|---|---|
| observation.images.top | image | (360, 640, 3) | 顶部摄像头图像 (高×宽×通道) |
| observation.images.left | image | (360, 640, 3) | 左侧摄像头图像 (高×宽×通道) |
| observation.images.right | image | (360, 640, 3) | 右侧摄像头图像 (高×宽×通道) |
| observation.state | float32 | (14,) | 机器人状态 (14维) |
| action | float32 | (14,) | 机器人动作 (14维) |
| timestamp | float32 | (1,) | 时间戳 |
| frame_index | int64 | (1,) | 帧索引 |
| episode_index | int64 | (1,) | 片段索引 |
| index | int64 | (1,) | 全局索引 |
| task_index | int64 | (1,) | 任务索引 |
数据文件路径格式
- 数据文件:
data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet - 视频文件:
videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4(本数据集无视频)



