Update README.md

README.md

@@ -1,107 +1,122 @@
-# Retargeted AMASS for Robotics
-
-## Project Overview
-
-This project aims to retarget motion data from the AMASS dataset to various robot models and open-source the retargeted data to facilitate research and applications in robotics and human-robot interaction. AMASS (Archive of Motion Capture as Surface Shapes) is a high-quality human motion capture dataset, and the SMPL-X model is a powerful tool for generating realistic human motion data.
-
-By adapting the motion data from AMASS to different robot models, we hope to provide a more diverse and accessible motion dataset for robot training and human-robot interaction.
-
-## Dataset Content
-
-This open-source project includes the following:
-1. **Retargeted Motions**: Motion files retargeted from AMASS to various robot models.
-   - **FFTAI FourierN1**: 
-
-     The retargeted motions for the FFTAI GRMini1T2 robot are generated based on the official open-source model: 
-
-     https://github.com/FFTAI/Wiki-GRx-Models/blob/FourierN1/GRMini1T2/urdf/GRMini1T2_rotor.urdf
-
-     The joint positions is not limited, you should limit them during use.
-
-     data shape：[-1,30]
-
-     ​		0:3 	root world position
-
-     ​		3:7	 root quaternion rotation, order: xyzw
-
-     ​		7:30   joint positions
-
-     joint order:
-
-     ```txt
-        left_hip_pitch_joint
-        left_hip_roll_joint
-        left_hip_yaw_joint
-        left_knee_pitch_joint
-        left_ankle_roll_joint
-        left_ankle_pitch_joint 
-        right_hip_pitch_joint
-        right_hip_roll_joint
-        right_hip_yaw_joint
-        right_knee_pitch_joint
-        right_ankle_roll_joint
-        right_ankle_pitch_joint
-        waist_yaw_joint
-        left_shoulder_pitch_joint
-        left_shoulder_roll_joint
-        left_shoulder_yaw_joint
-        left_elbow_pitch_joint
-        left_wrist_yaw_joint,
-        right_shoulder_pitch_joint
-        right_shoulder_roll_joint
-        right_shoulder_yaw_joint
-        right_elbow_pitch_joint
-        right_wrist_yaw_joint
-     ```
-
-2. **Usage Examples**: Code examples and tutorials on how to use the retargeted data.
-
-   ./visualize.py
-
-
-3. **License Files**: Original license information for each sub-dataset within AMASS.
-
-
-## License
-
-The retargeted data in this project is derived from the AMASS dataset and therefore adheres to the original license terms of AMASS. Each sub-dataset within AMASS may have different licenses, so please ensure compliance with the following requirements when using the data:
-- **Propagate Original Licenses**: When using or distributing the retargeted data, you must include and comply with the original licenses of the sub-datasets within AMASS.
-- **Attribution Requirements**: Properly cite this work and the original authors and sources of the AMASS dataset and its sub-datasets.
-
-For detailed license information, please refer to the `LICENSE` file in this project.
-
-
-
-## Acknowledgments
-
-This project is built on the AMASS dataset and the SMPL-X model. Special thanks to the research team at the Max Planck Institute for Intelligent Systems for providing this valuable resource.
-
-## Citation
-
-If you use the data or code from this project, please cite this work and relevant papers for AMASS and SMPL-X:
-```bibtex
-@misc{Retargeted_AMASS_R,
-  title={Retargeted AMASS for Robotics},
-  author={Kun Zhao},
-  url={https://huggingface.co/datasets/fleaven/Retargeted_AMASS_for_robotics}
-}
-
-@inproceedings{AMASS2019,
-  title={AMASS: Archive of Motion Capture as Surface Shapes},
-  author={Mahmood, Naureen and Ghorbani, Nima and Troje, Nikolaus F. and Pons-Moll, Gerard and Black, Michael J.},
-  booktitle={International Conference on Computer Vision (ICCV)},
-  year={2019}
-}
-
-@inproceedings{SMPL-X2019,
-  title={Expressive Body Capture: 3D Hands, Face, and Body from a Single Image},
-  author={Pavlakos, Georgios and Choutas, Vasileios and Ghorbani, Nima and Bolkart, Timo and Osman, Ahmed A. A. and Tzionas, Dimitrios and Black, Michael J.},
-  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
-  year={2019}
-}
-```
-
-## Contact
-
-For any questions or suggestions, please contact:
-- **Kun Zhao**: [email protected]
+---
+license: cc-by-4.0
+task_categories:
+- robotics
+- reinforcement-learning
+language:
+- en
+tags:
+- AMASS
+- Retarget
+- Robotics
+- Humanoid
+size_categories:
+- 10K<n<100K
+---
+# Retargeted AMASS for Robotics
+
+## Project Overview
+
+This project aims to retarget motion data from the AMASS dataset to various robot models and open-source the retargeted data to facilitate research and applications in robotics and human-robot interaction. AMASS (Archive of Motion Capture as Surface Shapes) is a high-quality human motion capture dataset, and the SMPL-X model is a powerful tool for generating realistic human motion data.
+
+By adapting the motion data from AMASS to different robot models, we hope to provide a more diverse and accessible motion dataset for robot training and human-robot interaction.
+
+## Dataset Content
+
+This open-source project includes the following:
+1. **Retargeted Motions**: Motion files retargeted from AMASS to various robot models.
+   - **FFTAI FourierN1**: 
+
+     The retargeted motions for the FFTAI GRMini1T2 robot are generated based on the official open-source model: 
+
+     https://github.com/FFTAI/Wiki-GRx-Models/blob/FourierN1/GRMini1T2/urdf/GRMini1T2_rotor.urdf
+
+     The joint positions is not limited, you should limit them during use.
+
+     data shape：[-1,30]
+
+     ​		0:3 	root world position
+
+     ​		3:7	 root quaternion rotation, order: xyzw
+
+     ​		7:30   joint positions
+
+     joint order:
+
+     ```txt
+        left_hip_pitch_joint
+        left_hip_roll_joint
+        left_hip_yaw_joint
+        left_knee_pitch_joint
+        left_ankle_roll_joint
+        left_ankle_pitch_joint 
+        right_hip_pitch_joint
+        right_hip_roll_joint
+        right_hip_yaw_joint
+        right_knee_pitch_joint
+        right_ankle_roll_joint
+        right_ankle_pitch_joint
+        waist_yaw_joint
+        left_shoulder_pitch_joint
+        left_shoulder_roll_joint
+        left_shoulder_yaw_joint
+        left_elbow_pitch_joint
+        left_wrist_yaw_joint,
+        right_shoulder_pitch_joint
+        right_shoulder_roll_joint
+        right_shoulder_yaw_joint
+        right_elbow_pitch_joint
+        right_wrist_yaw_joint
+     ```
+
+2. **Usage Examples**: Code examples and tutorials on how to use the retargeted data.
+
+   ./visualize.py
+
+
+3. **License Files**: Original license information for each sub-dataset within AMASS.
+
+
+## License
+
+The retargeted data in this project is derived from the AMASS dataset and therefore adheres to the original license terms of AMASS. Each sub-dataset within AMASS may have different licenses, so please ensure compliance with the following requirements when using the data:
+- **Propagate Original Licenses**: When using or distributing the retargeted data, you must include and comply with the original licenses of the sub-datasets within AMASS.
+- **Attribution Requirements**: Properly cite this work and the original authors and sources of the AMASS dataset and its sub-datasets.
+
+For detailed license information, please refer to the `LICENSE` file in this project.
+
+
+
+## Acknowledgments
+
+This project is built on the AMASS dataset and the SMPL-X model. Special thanks to the research team at the Max Planck Institute for Intelligent Systems for providing this valuable resource.
+
+## Citation
+
+If you use the data or code from this project, please cite this work and relevant papers for AMASS and SMPL-X:
+```bibtex
+@misc{Retargeted_AMASS_R,
+  title={Retargeted AMASS for Robotics},
+  author={Kun Zhao},
+  url={https://huggingface.co/datasets/fleaven/Retargeted_AMASS_for_robotics}
+}
+
+@inproceedings{AMASS2019,
+  title={AMASS: Archive of Motion Capture as Surface Shapes},
+  author={Mahmood, Naureen and Ghorbani, Nima and Troje, Nikolaus F. and Pons-Moll, Gerard and Black, Michael J.},
+  booktitle={International Conference on Computer Vision (ICCV)},
+  year={2019}
+}
+
+@inproceedings{SMPL-X2019,
+  title={Expressive Body Capture: 3D Hands, Face, and Body from a Single Image},
+  author={Pavlakos, Georgios and Choutas, Vasileios and Ghorbani, Nima and Bolkart, Timo and Osman, Ahmed A. A. and Tzionas, Dimitrios and Black, Michael J.},
+  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
+  year={2019}
+}
+```
+
+## Contact
+
+For any questions or suggestions, please contact:
+- **Kun Zhao**: [email protected]