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https://github.com/BerkeleyAutomation/gqcnn

Python module for GQ-CNN training and deployment with ROS integration.
https://github.com/BerkeleyAutomation/gqcnn

deep-learning gqcnn grasping machine-learning python robotics ros

Last synced: about 1 month ago
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Python module for GQ-CNN training and deployment with ROS integration.

Host: GitHub
URL: https://github.com/BerkeleyAutomation/gqcnn
Owner: BerkeleyAutomation
License: other
Created: 2017-04-26T06:22:27.000Z (over 7 years ago)
Default Branch: master
Last Pushed: 2024-04-25T17:52:06.000Z (8 months ago)
Last Synced: 2024-11-01T01:27:20.370Z (about 1 month ago)
Topics: deep-learning, gqcnn, grasping, machine-learning, python, robotics, ros
Language: Python
Homepage: https://berkeleyautomation.github.io/gqcnn
Size: 155 MB
Stars: 312
Watchers: 33
Forks: 149
Open Issues: 23
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

awesome-robotics - gqcnn - [Grasp Quality Convolutional Neural Networks (GQ-CNNs)](https://berkeleyautomation.github.io/gqcnn/info/info.html) for grasp planning using training datasets from the [Dexterity Network (Dex-Net)](https://berkeleyautomation.github.io/dex-net) (Uncategorized / Uncategorized)

README

        ## Note: Python 2.x support has officially been dropped.

# Berkeley AUTOLAB's GQCNN Package



   

       

   

   

       

   

   

       

   

   

       

   



## Package Overview

The gqcnn Python package is for training and analysis of Grasp Quality Convolutional Neural Networks (GQ-CNNs). It is part of the ongoing [Dexterity-Network (Dex-Net)](https://berkeleyautomation.github.io/dex-net/) project created and maintained by the [AUTOLAB](https://autolab.berkeley.edu) at UC Berkeley.

## Installation and Usage

Please see the [docs](https://berkeleyautomation.github.io/gqcnn/) for installation and usage instructions.

## Citation

If you use any part of this code in a publication, please cite [the appropriate Dex-Net publication](https://berkeleyautomation.github.io/gqcnn/index.html#academic-use).