Unity-Technologies / Robotics-Object-Pose-Estimation

A complete end-to-end demonstration in which we collect training data in Unity and use that data to train a deep neural network to predict the pose of a cube. This model is then deployed in a simulated robotic pick-and-place task.

Date Created 2021-02-19 (3 years ago)

Commits 102 (last one 2 years ago)

Stargazers 288 (1 this week)

Watchers 15 (0 this week)

Forks 75

License apache-2.0

Ranking

RepositoryStats indexes 565,279 repositories, of these Unity-Technologies/Robotics-Object-Pose-Estimation is ranked #134,169 (76th percentile) for total stargazers, and #144,213 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #22,936/111,292.

Unity-Technologies/Robotics-Object-Pose-Estimation is also tagged with popular topics, for these it's ranked: deep-learning (#2,821/8171), machine-learning (#2,677/7698), computer-vision (#945/2976), unity (#551/1940), tutorial (#537/1473), robotics (#345/1180), simulation (#215/962), ros (#182/716), pose-estimation (#98/319), physics-simulation (#36/144), motion-planning (#41/136)

Other Information

Unity-Technologies/Robotics-Object-Pose-Estimation has Github issues enabled, there are 7 open issues and 26 closed issues.

There have been 1 release, the latest one was published on 2021-02-19 (3 years ago) with the name Object Pose Estimation Tutorial.

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5 commits on the default branch (main) since jan '22

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The primary language is Python but there's also others...

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Unity-Technologies/Robotics-Object-Pose-Estimation

updated: 2024-09-23 @ 02:26am, id: 340219153 / R_kgDOFEdVEQ