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GraspClutter6D Dataset

GraspClutter6D: A Large-scale Real-world Dataset for Robust Perception and Grasping in Cluttered Scenes

Seunghyeok Back, Joosoon Lee, Kangmin Kim, Heeseon Rho, Geonhyup Lee, Raeyoung Kang, Sangbeom Lee, Sangjun Noh, Youngjin Lee, Taeyeop Lee, Kyoobin Lee

Accepted at IEEE Robotics and Automation Letters (RA-L)

[ArXiv] [Project Website] [Video] [Dataset Format] [GitHub]

To download the dataset, run the following commands:

mkdir GraspClutter6D && cd GraspClutter6D
export SRC=https://huggingface.co/datasets/GraspClutter6D/GraspClutter6D/resolve/main

# scene data
wget $SRC/split_info.7z
wget $SRC/scenes.7z.001
wget $SRC/scenes.7z.002
wget $SRC/scenes.7z.003
wget $SRC/scenes.7z.004
wget $SRC/scenes.7z.005
7z x split_info.7z
7z x scenes.7z.001

# for object pose estimation
wget $SRC/models.7z
wget $SRC/models_eval.7z
wget $SRC/models_obj.7z
wget $SRC/models_obj_eval.7z

7z x models.7z
7z x models_eval.7z
7z x models_obj.7z
7z x models_obj_eval.7z

# for grasp detection
wget $SRC/grasp_label.7z
wget $SRC/collision_label.7z
wget $SRC/dex_models.7z
wget $SRC/models_m.7z
wget $SRC/models_obj_m.7z

7z x grasp_label.7z
7z x collision_label.7z
7z x dex_models.7z
7z x models_m.7z
7z x models_obj_m.7z

Dataset Toolkit Usage

This dataset comes with a Python API and toolkit (graspclutter6dAPI) to facilitate loading, manipulating, and evaluating 6D grasp pose annotations.

Installation:

You can install the toolkit via pip:

pip install graspclutter6dAPI

Alternatively, install from source:

conda create -n gc6d python=3.8
conda activate gc6d
git clone https://github.com/SeungBack/graspclutter6dAPI.git
cd graspclutter6dAPI
pip install -e .

Environment Setup:

Before running examples, set the GC6D_ROOT environment variable to your dataset location:

export GC6D_ROOT='/path/to/graspclutter6d'

Usage Examples:

  • Validate Dataset Integrity:
    python examples/exam_check_data.py
    
  • Load Grasp Annotations:
    python examples/exam_loadGrasp.py
    
  • Visualize Grasp Annotations:
    python examples/exam_vis.py
    
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