metadata
license: mit
task_categories:
- robotics
- object-detection
- image-segmentation
tags:
- robotics
- grasping
- grasp-detection
- multi-object
- depth
pretty_name: Multi-Object Grasp Detection Dataset
size_categories:
- n<1K
Multi-Object Grasp Detection Dataset
Dataset for robotic grasping with multiple objects per scene. Contains RGB images, depth maps, and grasp annotations for various objects.
Dataset Details
- Total samples: 96 scenes
- Objects: Various household items (screwdriver, pliers, scissors, wrench, etc. - in russian)
- Grasps per scene: Multiple grasp poses per object
- Image resolution: 640x480 pixels
Grasp Annotation Format. Each grasp is represented as a quadrilateral with 4 vertices:
{
'grasp_id': int,
'center': [xc, yc], # Center of grasp rectangle
'opening_point': [xo, yo] # Gripper opening point
}
Usage
from datasets import load_dataset
ds = load_dataset("vadim-vlm4vla/grasp_multiObject_upgrade")
example = ds['test'][0]
print(f"Image ID: {example['image_id']}")
print(f"Number of objects: {example['num_objects']}")
print(f"Total grasps: {example['num_grasps']}")
example['image'].show()
for obj in example['objects']:
print(f"\nObject: {obj['object_name']}")
print(f" Grasps: {len(obj['grasps'])}")
for grasp in obj['grasps']:
print(f" Grasp {grasp['grasp_id']}:")
print(f" Center: {grasp['center']}")
print(f" Opening: {grasp['opening_point']}")
Visualization Example
import matplotlib.pyplot as plt
import numpy as np
example = ds['test'][0]
image = np.array(example['image'])
fig, ax = plt.subplots(1, 1, figsize=(10, 8))
ax.imshow(image)
colors = plt.cm.rainbow(np.linspace(0, 1, example['num_objects']))
for obj_idx, obj in enumerate(example['objects']):
color = colors[obj_idx]
for grasp in obj['grasps']:
center = grasp['center']
opening = grasp['opening_point']
# Draw center point
ax.plot(center[0], center[1], 'o', color=color, markersize=8)
# Draw line to opening point
ax.plot([center[0], opening[0]], [center[1], opening[1]],
'-', color=color, linewidth=2)
# Draw opening point
ax.plot(opening[0], opening[1], 's', color=color, markersize=6)
plt.title(f"Image {example['image_id']} - {example['num_objects']} objects, {example['num_grasps']} grasps")
plt.axis('off')
plt.show()
Citation
If you use this dataset, please cite:
@dataset{multiobject_grasp_2025,
title={Multi-Object Grasp Detection Dataset},
author={Vadim Pyatochkin},
year={2025},
publisher={Hugging Face},
url={https://huggingface.co/datasets/vadim-vlm4vla/grasp_multiObject_upgrade}
}
If you find it helpful for your research, please also consider citing the foundational work on which this dataset is based:
@inproceedings{chu2018deep,
title = {Real-World Multiobject, Multigrasp Detection},
author = {F. Chu and R. Xu and P. A. Vela},
journal = {IEEE Robotics and Automation Letters},
year = {2018},
volume = {3},
number = {4},
pages = {3355-3362},
DOI = {10.1109/LRA.2018.2852777},
ISSN = {2377-3766},
month = {Oct}
}
License
MIT License
Contact
For questions or issues, please open an issue on the dataset repository.