- **Description**: Franka preparing dumplings with various tools - **Homepage** : - **Source code** : [`tfds.robotics.rtx.StanfordRobocookConvertedExternallyToRlds`](https://github.com/tensorflow/datasets/tree/master/tensorflow_datasets/robotics/rtx/rtx.py) - **Versions**: - **`0.1.0`** (default): Initial release. - **Download size** : `Unknown size` - **Dataset size** : `124.59 GiB` - **Auto-cached** ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)): No - **Splits**: | Split | Examples | |---|---| | `'train'` | 2,460 | - **Feature structure**: FeaturesDict({ 'episode_metadata': FeaturesDict({ 'extrinsics_1': Tensor(shape=(4, 4), dtype=float32, description=Camera 1 Extrinsic Matrix.), 'extrinsics_2': Tensor(shape=(4, 4), dtype=float32, description=Camera 2 Extrinsic Matrix.), 'extrinsics_3': Tensor(shape=(4, 4), dtype=float32, description=Camera 3 Extrinsic Matrix.), 'extrinsics_4': Tensor(shape=(4, 4), dtype=float32, description=Camera 4 Extrinsic Matrix.), 'file_path': Text(shape=(), dtype=string), }), 'steps': Dataset({ 'action': Tensor(shape=(7,), dtype=float32, description=Robot action, consists of [3x robot end-effector velocities, 3x robot end-effector angular velocities, 1x gripper velocity].), 'discount': Scalar(shape=(), dtype=float32, description=Discount if provided, default to 1.), 'is_first': bool, 'is_last': bool, 'is_terminal': bool, 'language_embedding': Tensor(shape=(512,), dtype=float32, description=Kona language embedding. See https://tfhub.dev/google/universal-sentence-encoder-large/5), 'language_instruction': Text(shape=(), dtype=string), 'observation': FeaturesDict({ 'depth_1': Tensor(shape=(256, 256), dtype=float32, description=Camera 1 Depth observation.), 'depth_2': Tensor(shape=(256, 256), dtype=float32, description=Camera 2 Depth observation.), 'depth_3': Tensor(shape=(256, 256), dtype=float32, description=Camera 3 Depth observation.), 'depth_4': Tensor(shape=(256, 256), dtype=float32, description=Camera 4 Depth observation.), 'image_1': Image(shape=(256, 256, 3), dtype=uint8, description=Camera 1 RGB observation.), 'image_2': Image(shape=(256, 256, 3), dtype=uint8, description=Camera 2 RGB observation.), 'image_3': Image(shape=(256, 256, 3), dtype=uint8, description=Camera 3 RGB observation.), 'image_4': Image(shape=(256, 256, 3), dtype=uint8, description=Camera 4 RGB observation.), 'state': Tensor(shape=(7,), dtype=float32, description=Robot state, consists of [3x robot end-effector position, 3x robot end-effector euler angles, 1x gripper position].), }), 'reward': Scalar(shape=(), dtype=float32, description=Reward if provided, 1 on final step for demos.), }), }) - **Feature documentation**: | Feature | Class | Shape | Dtype | Description | |---|---|---|---|---| | | FeaturesDict | | | | | episode_metadata | FeaturesDict | | | | | episode_metadata/extrinsics_1 | Tensor | (4, 4) | float32 | Camera 1 Extrinsic Matrix. | | episode_metadata/extrinsics_2 | Tensor | (4, 4) | float32 | Camera 2 Extrinsic Matrix. | | episode_metadata/extrinsics_3 | Tensor | (4, 4) | float32 | Camera 3 Extrinsic Matrix. | | episode_metadata/extrinsics_4 | Tensor | (4, 4) | float32 | Camera 4 Extrinsic Matrix. | | episode_metadata/file_path | Text | | string | Path to the original data file. | | steps | Dataset | | | | | steps/action | Tensor | (7,) | float32 | Robot action, consists of \[3x robot end-effector velocities, 3x robot end-effector angular velocities, 1x gripper velocity\]. | | steps/discount | Scalar | | float32 | Discount if provided, default to 1. | | steps/is_first | Tensor | | bool | | | steps/is_last | Tensor | | bool | | | steps/is_terminal | Tensor | | bool | | | steps/language_embedding | Tensor | (512,) | float32 | Kona language embedding. See https://tfhub.dev/google/universal-sentence-encoder-large/5 | | steps/language_instruction | Text | | string | Language Instruction. | | steps/observation | FeaturesDict | | | | | steps/observation/depth_1 | Tensor | (256, 256) | float32 | Camera 1 Depth observation. | | steps/observation/depth_2 | Tensor | (256, 256) | float32 | Camera 2 Depth observation. | | steps/observation/depth_3 | Tensor | (256, 256) | float32 | Camera 3 Depth observation. | | steps/observation/depth_4 | Tensor | (256, 256) | float32 | Camera 4 Depth observation. | | steps/observation/image_1 | Image | (256, 256, 3) | uint8 | Camera 1 RGB observation. | | steps/observation/image_2 | Image | (256, 256, 3) | uint8 | Camera 2 RGB observation. | | steps/observation/image_3 | Image | (256, 256, 3) | uint8 | Camera 3 RGB observation. | | steps/observation/image_4 | Image | (256, 256, 3) | uint8 | Camera 4 RGB observation. | | steps/observation/state | Tensor | (7,) | float32 | Robot state, consists of \[3x robot end-effector position, 3x robot end-effector euler angles, 1x gripper position\]. | | steps/reward | Scalar | | float32 | Reward if provided, 1 on final step for demos. | - **Supervised keys** (See [`as_supervised` doc](https://www.tensorflow.org/datasets/api_docs/python/tfds/load#args)): `None` - **Figure** ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)): Not supported. - **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)): - **Citation**: @article{shi2023robocook, title={RoboCook: Long-Horizon Elasto-Plastic Object Manipulation with Diverse Tools}, author={Shi, Haochen and Xu, Huazhe and Clarke, Samuel and Li, Yunzhu and Wu, Jiajun}, journal={arXiv preprint arXiv:2306.14447}, year={2023} }