jack635/grasp-dataset-curated

🖐️ Synthetic Grasp Dataset (Objaverse-LVIS Curated)

This dataset contains high-quality synthetic grasp data generated for robotic manipulation research. It focuses on the fusion of vision and tactile sensing by providing visibility and occlusion analysis for each contact point.

📊 Dataset Statistics

• —Number of objects: 10
• —Source: Curated objects from Objaverse-LVIS (categories: cup, bottle, hammer, screwdriver, wrench)
• —Grasp Strategies: front_back
• —Camera Resolution: 640x480

🛠️ Data Format

Each object folder contains:

• —rgb.png: Monocular RGB render.
• —grasp_<strategy>.json: Contact points with position, normal, tangent, and visibility status.
• —grasp_<strategy>.npz: NumPy version of the contact points.
• —grasp_<strategy>_overlay.png: Visual overlay of the grasp on the object.
• —metadata.json: Object-specific metadata (surface visibility, bounding box, complexity).

🔍 Visibility Classification

Every contact point is classified based on camera occlusion:

• —VISIBLE: Point is directly seen by the camera.
• —SILHOUETTE: Point is on the visual horizon (critical for tactile تکمیل).
• —OCCLUDED: Point is hidden by the object itself (back side or self-occlusion).

📜 How to use

This dataset is designed to train models that predict contact stability from visual data or to simulate-to-real transfer for tactile controllers.

from huggingface_hub import snapshot_download
path = snapshot_download("jack635/grasp-dataset-curated", repo_type="dataset")

Generated using the [Grasp Dataset Generator](https://github.com/635jack/grasp-dataset-gen) pipeline.