Coder Social home page Coder Social logo

gazeml-keras's Introduction

πŸ‘‹Hello, I'm Shao-An!

Twitter Badge Linkedin Badge Wordpress Badge

  • πŸ”­ Working as a Control Software Engineer.
  • 🌏 Grew up in Taiwan, residing in the vibrant city of Tokyo, Japan.
  • ⭐ Interested in Control Systems, Optimization, and Deep Generative Models.
  • 🌱 Currently engaged in the exploration of Software Architecture within Robotic Systems.

Recent Activity

  1. πŸŽ‰ Merged PR #1 in shaoanlu/CBF_QP_safety_filter
  2. πŸ’ͺ Opened PR #1 in shaoanlu/CBF_QP_safety_filter
  3. πŸ’ͺ Opened PR #234 in qpsolvers/qpsolvers
  4. πŸŽ‰ Merged PR #6 in shaoanlu/qpsolvers
  5. πŸ’ͺ Opened PR #6 in shaoanlu/qpsolvers

Projects

gazeml-keras's People

Contributors

shaoanlu avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar

gazeml-keras's Issues

Perfomance diff bw GazeML vs GazeML-Keras?

Hi .

Thanks for great work.

Since I am beginner, I would like to know what is the performance diff bw this GazeML-Keras vs GazeML(swook).

Is there any significant reason to choose this repo?

please advise.

Also, I convert demo_colab.ipynb to .py file and then run on the ubuntu But it seems Not running.

How to get gaze estimation from landmarks?

i have 4 questions about the paper:
1.The original paper says that the author trained a SVR model from MPIIGaze datasite. How to do with that? Useing the GazeML model to predict landmarks on MPII Gaze data images and use the detection landmarks results as the ground truth to train a SVR?
2.why not directly using Unityeyes dataset 's landmark and its gaze vector ground truth to train the SVR?
3.why use SVR? using several FC layers to regress result is ok or not?
4. what does the "calabration with 20 or more samples" mean in author's paper, calabrating to get
camera paramters or get what? don't understand exactlly.

i would appreciate very very very much if you could answer my question,thank you.

What is the license for this project?

Could you please update a License for this project?

The previous project GazeML use MIT license. Do you think that we can continue to research on this project with MIT license?

Thanks.

How to convert trained model from GazeML to Keras?

Hi @shaoanlu ,
sorry for disturbing. I am wondering that how to convert trained model from GazeML to Keras, Like you did in this repo? I currently trained a model from GazeML, but I would like to test in your code.
Could you guide me how to achieve this?
Thank you.

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    πŸ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. πŸ“ŠπŸ“ˆπŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❀️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.