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README.md

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+# GraspGen: Scaling Simulated Grasping
+GraspGen is a large-scale simulated grasp dataset for multiple robot embodiments and grippers 
+
+<img src="assets/cover.png" width="1000" height="250" title="readme1"> 
+
+
+We release over 57 million grasps, computed for a subset of 8515 objects from the [Objaverse XL](https://objaverse.allenai.org/) (LVIS) dataset. We release grasps for three grippers: Franka Panda, the Robotiq-2f-140 industrial gripper, and suction. 
+
+<img src="assets/montage2.png" width="1000" height="500" title="readme2"> 
+
+## Dataset Format
+The dataset is released in the [WebDataset](https://github.com/webdataset/webdataset) format. The folder structure of the dataset is as follows:
+```
+grasp_data/
+	franka/shard_{0-7}.tar
+	robotiq2f140/shard_{0-7}.tar
+	suction/shard_{0-7}.tar
+splits/
+	franka/{train/valid}_scenes.json
+	robotiq2f140/{train/valid}_scenes.json
+	suction/{train/valid}_scenes.json
+```
+We release test-train splits along with the grasp dataset. 
+
+Each json file in the shard has the following data in a python dictionary. Note that `num_grasps=2000` per object.
+```
+‘object’/
+	‘scale’ # This is the scale of the asset
+‘grasps’/
+	‘object_in_gripper’ # boolean mask indicating grasp success, [num_grasps X 1]
+	‘transforms’ # Pose of the gripper in homogenous matrices, [num_grasps X 4 X 4]
+```
+
+## Visualizing the dataset
+
+We have provided some standalone scripts for visualizing this dataset. See the header of the [visualize_dataset.py](scripts/visualize_dataset.py) for installation instructions
+
+Before running any of the visualization scripts, remember to start meshcat-server in a separate terminal:
+``` shell
+meshcat-server
+```
+
+To visualize a single object from the dataset, alongside its grasps:
+```shell
+cd scripts/ && python visualize_dataset.py --dataset_path /path/to/dataset --object_uuid {object_uuid} --object_file /path/to/mesh --gripper_name {choose from: franka, suction, robotiq2f140}
+```
+
+## Objaverse dataset
+Please download the Objaverse XL (LVIS) objects separately. See the helper script [download_objaverse.py](scripts/download_objaverse.py) for instructions and usage.
+
+## License
+License Copyright © 2025, NVIDIA Corporation & affiliates. All rights reserved.
+
+
+The dataset is released under a CC-BY 4.0 License.
+
+The visualization code is released under the [NVIDIA source code license](LICENSE).
+
+## Contact
+
+Please reach out to [Adithya Murali](adithyamurali.com) (admurali@nvidia.com) and [Clemens Eppner](https://clemense.github.io/) (ceppner@nvidia.com) for further enquiries
+