PeopleSansPeople
ml-agents
PeopleSansPeople | ml-agents | |
---|---|---|
5 | 60 | |
294 | 16,394 | |
2.4% | 1.2% | |
3.0 | 8.0 | |
2 months ago | 11 days ago | |
C# | C# | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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PeopleSansPeople
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PI wants me to make a synthetic dataset.
Also, check this Unity repo out
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Generating human motion synthetic data ?
I was trying to train a model which goes on top of one of the pose estimation models(posenet, movenet, mediapipe) which detects the action performed(waving, swipe right, etc), and I was planning on generating synthetic data for it. I saw that there's a project for unity PeopleSansPeople, but it's not right to train a model for action recognition. I would like something that either simulates a human doing a simple action, to which I would be able to add randomness to it. I was thinking to either use Unity or maybe write something that would model the human keypoints(the output of pose estimation) and simulate them.. I am wondering if there already exists something that you guys might know about??
- [P] Can't finish my master's thesis. What to do?
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[R] PeopleSansPeople: Unity's Human-Centric Synthetic Data Generator. GitHub link in comments.
Source code: https://github.com/Unity-Technologies/PeopleSansPeople
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[R] PeopleSansPeople: Unity's Human-Centric Synthetic Data Generator
Webpage: https://unity-technologies.github.io/PeopleSansPeople/ Paper: https://arxiv.org/abs/2112.09290 Source code: https://github.com/Unity-Technologies/PeopleSansPeople Papers with code: https://paperswithcode.com/paper/peoplesanspeople-a-synthetic-data-generator https://paperswithcode.com/dataset/peoplesanspeople Demo video: https://youtu.be/mQ_DUdB70dc Summary: PeopleSansPeople is a human-centric data generator provided by Unity Technologies that contains highly-parametric and simulation-ready 3D human assets, parameterized lighting and camera system, parameterized environment generators, and fully-manipulable and extensible domain randomizers. PeopleSansPeople can generate RGB images with sub-pixel-perfect 2D/3D bounding box, COCO-compliant human keypoints, and semantic/instance segmentation masks in JSON annotation files. All packaged in macOS and Linux executable binaries capable of generating 1M+ datasets. In addition we release a template Unity environment for lowering the barrier of entry and getting you started with creating your own highly-parameterized human-centric synth data generator. We affectionately named our synthetic data generator PeopleSansPeople, as it is a data generator aimed at human-centric computer vision without using human data which bears serious privacy, safety, ethical, bias, and legal concerns. Benchmarks: The domain randomization we used for our benchmarks are naïve, brute-forced sweeps through the pre-chosen range of parameters; as such we end up generating psychedelic-looking scenes, which turned out to train more performant models for human-centric computer vision.Using PeopleSansPeople we benchmarked a Detectron2 Keypoint R-CNN variant. Results indicate synthetic pre-training with our data outperforms results of training on real data alone or pre-training with ImageNet, both in limited and abundant data regimes.We envisage that this freely-available data generator should enable a wide range of research into the emerging field of simulation to real transfer learning in the critical area of human-centric computer vision.
ml-agents
- How do I change the maximum number of steps for training
- are the install steps update to date?
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Help with regenerating new worker id
I am a beginner to using ML Agents to simulate an environment for DL i am trying to trial runs by tinkering through different values between the action space and keep encountering this issue when attempting to run a new trial. I've tried mlagents-learn --force and mlagents-learn --run-id=newtest but both prompt the same error message. Using linux, I am aware of a similar bug occuring in older versions (https://github.com/Unity-Technologies/ml-agents/issues/1505) but solutions didn't fix it.
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Trying to get into AI
The Github page for ML-Agents has a fairly straight forward example.
- Implement API to allow AI/ML to play your game, or is it not needed?
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Is there a good alternative to Unity ML Agents?
Very few commits in the last year and not many new features (https://github.com/Unity-Technologies/ml-agents/commits/develop)
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At least I put effort into the AI prompt to generate some code that people can refer to, whereas you do absolutely nothing to contribute to the community.
and PR content: https://github.com/Unity-Technologies/ml-agents/commit/ed212103e451449bf84711a4a8f7bf11dfb1211a
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I have some questions as an absolute beginner.
Unity can build a stand-alone application or be used as a library. Javascript is deprecated, and Boo along with it although it was never really supported to begin with. Various types of machine learning are supported through the ML-Agent Toolkit and pretty well documented. The toolkit has a Python API but you should be careful about doing anything too unusual in Unity because the documentation tends to have a lot of dead-ends.
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Could Somebody please help me figure this out ? been struggling with it for a week now
Op, I'd just pull the repo again to a new folder from https://github.com/Unity-Technologies/ml-agents (use SourceTree for simplicity if you don't know git).
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Unity ML-Agents documentation is wrong, I can't build an executable and run training as the docs state
My github issue on their documentation: https://github.com/Unity-Technologies/ml-agents/issues/5899
What are some alternatives?
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.
gym - A toolkit for developing and comparing reinforcement learning algorithms.
com.unity.perception - Perception toolkit for sim2real training and validation in Unity
AirSim - Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research
VirtualHumanBatchProcessing
carla - Open-source simulator for autonomous driving research.
tdk-demo - This is a collection of TDK demo projects that use different databases and options
AssetStudio - AssetStudio is a tool for exploring, extracting and exporting assets and assetbundles.
unity-avatar-generation - A minimal example of how to use Unity's AvatarBuilder.BuildHumanAvatar API.
ultimate-volleyball - 3D RL Volleyball environment built on Unity ML-Agents
tensortrade - An open source reinforcement learning framework for training, evaluating, and deploying robust trading agents.
recurrent-ppo-truncated-bptt - Baseline implementation of recurrent PPO using truncated BPTT