{"id":13728192,"url":"https://berkeleyautomation.github.io/gqcnn/","last_synced_at":"2025-05-08T00:31:26.245Z","repository":{"id":55191165,"uuid":"89445494","full_name":"BerkeleyAutomation/gqcnn","owner":"BerkeleyAutomation","description":"Python module for GQ-CNN training and deployment with ROS integration.","archived":false,"fork":false,"pushed_at":"2024-04-25T17:52:06.000Z","size":162871,"stargazers_count":312,"open_issues_count":23,"forks_count":149,"subscribers_count":33,"default_branch":"master","last_synced_at":"2024-11-01T01:27:20.370Z","etag":null,"topics":["deep-learning","gqcnn","grasping","machine-learning","python","robotics","ros"],"latest_commit_sha":null,"homepage":"https://berkeleyautomation.github.io/gqcnn","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/BerkeleyAutomation.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2017-04-26T06:22:27.000Z","updated_at":"2024-10-31T14:31:10.000Z","dependencies_parsed_at":"2022-08-14T15:33:19.770Z","dependency_job_id":null,"html_url":"https://github.com/BerkeleyAutomation/gqcnn","commit_stats":null,"previous_names":[],"tags_count":5,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BerkeleyAutomation%2Fgqcnn","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BerkeleyAutomation%2Fgqcnn/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BerkeleyAutomation%2Fgqcnn/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BerkeleyAutomation%2Fgqcnn/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/BerkeleyAutomation","download_url":"https://codeload.github.com/BerkeleyAutomation/gqcnn/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":224679840,"owners_count":17351876,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["deep-learning","gqcnn","grasping","machine-learning","python","robotics","ros"],"created_at":"2024-08-03T02:00:38.414Z","updated_at":"2024-11-14T19:30:45.483Z","avatar_url":"https://github.com/BerkeleyAutomation.png","language":"Python","funding_links":[],"categories":["[Libraries](#libraries)"],"sub_categories":[],"readme":"## Note: Python 2.x support has officially been dropped.\n\n# Berkeley AUTOLAB's GQCNN Package\n\u003cp\u003e\n   \u003ca href=\"https://travis-ci.org/BerkeleyAutomation/gqcnn/\"\u003e\n       \u003cimg alt=\"Build Status\" src=\"https://travis-ci.org/BerkeleyAutomation/gqcnn.svg?branch=master\"\u003e\n   \u003c/a\u003e\n   \u003ca href=\"https://github.com/BerkeleyAutomation/gqcnn/releases/latest\"\u003e\n       \u003cimg alt=\"Release\" src=\"https://img.shields.io/github/release/BerkeleyAutomation/gqcnn.svg?style=flat\"\u003e\n   \u003c/a\u003e\n   \u003ca href=\"https://github.com/BerkeleyAutomation/gqcnn/blob/master/LICENSE\"\u003e\n       \u003cimg alt=\"Software License\" src=\"https://img.shields.io/badge/license-REGENTS-brightgreen.svg\"\u003e\n   \u003c/a\u003e\n   \u003ca\u003e\n       \u003cimg alt=\"Python 3 Versions\" src=\"https://img.shields.io/badge/python-3.5%20%7C%203.6%20%7C%203.7-yellow.svg\"\u003e\n   \u003c/a\u003e\n\u003c/p\u003e\n\n## Package Overview\nThe 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.\n\n## Installation and Usage\nPlease see the [docs](https://berkeleyautomation.github.io/gqcnn/) for installation and usage instructions.\n\n## Citation\nIf 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).\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/berkeleyautomation.github.io%2Fgqcnn%2F","html_url":"https://awesome.ecosyste.ms/projects/berkeleyautomation.github.io%2Fgqcnn%2F","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/berkeleyautomation.github.io%2Fgqcnn%2F/lists"}