| # Multi-GraspLLM: A Multimodal LLM for Multi-Hand Semantic-Guided Grasp Generation | |
| **[Project Page](https://multi-graspllm.github.io/)** | **[arXiv](https://arxiv.org/abs/2412.08468)** | |
| --- | |
| ## Updates | |
| - **2025.3**: We add the Jaco hand data which is our final version. | |
| - **2025.1**: We add the Barrett hand data. | |
| - **2024.12**: Released the Multi-GraspSet dataset with meshes of objects. | |
| - **2024.12**: Released the Multi-GraspSet dataset with contact annotations. | |
| --- | |
| ## Overview | |
| We introduce **Multi-GraspSet**, the first large-scale multi-hand grasp dataset enriched with automatic contact annotations. | |
| <table style="margin: auto; text-align: center;"> | |
| <tr> | |
| <td> | |
| <img src="./assets/picture/dataset_construction_new.png" alt="Structure of Multi-GraspLLM" width="1000"> | |
| </td> | |
| </tr> | |
| <tr> | |
| <td> | |
| <p>The Construction process of Multi-GraspSet</p> | |
| </td> | |
| </tr> | |
| </table> | |
| <table style="margin: auto; text-align: center;"> | |
| <tr> | |
| <td> | |
| <img src="./assets/picture/vis_dataset_grasp_output_01_new.png" alt="Structure of Multi-GraspLLM" width="600"> | |
| </td> | |
| </tr> | |
| <tr> | |
| <td> | |
| <p>Visualization of Multi-GraspSet with contact annotations</p> | |
| </td> | |
| </tr> | |
| </table> | |
| --- | |
| ## Installation | |
| Follow these steps to set up the evaluation environment: | |
| 1. **Create the Environment** | |
| ```bash | |
| conda create --name eval python=3.9 | |
| ``` | |
| 2. **Install PyTorch and Dependencies** | |
| ```bash | |
| pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 | |
| ``` | |
| > ⚠️ Ensure the CUDA toolkit version matches your installed PyTorch version. | |
| 3. **Install Pytorch Kinematics** | |
| ```bash | |
| cd ./pytorch_kinematics | |
| pip install -e . | |
| ``` | |
| 4. **Install Remaining Requirements** | |
| ```bash | |
| pip install -r requirements_eval.txt | |
| ``` | |
| --- | |
| ## Visualize the Dataset | |
| 1. **Run the Visualization Code** | |
| Open and execute the `vis_mid_dataset.ipynb` file to visualize the dataset. | |