Rock Paper Scissor with MediaPipe & TensorFlow

The author of this repo is HawkieOne, one of the student developers of Arthron. Project Arthron is a health and gaming research project with the goal of preventing hand injuries for gamers with the help of Augmented Reality.

This specific Git repository was made for one of the development streams held for the project's community. In this repo you can learn how to detect the three gestures: rock, paper and scissor, with the use of MediaPipe and TensorFlow. The underlying tech used in this repository comes from the following Git Repo: https://github.com/asus4/tf-lite-unity-sample .

Useful links

• Official TFlite Models
• MediaPipe

TensorFlow Lite for Unity Samples

Porting of "TensorFlow Lite Examples" to Unity. and some utilities for Unity.

Tested on

• iOS / Android / macOS / Windows
• Unity 2019.4.24f1
• TensorFlow 2.4.0

Samples

Only the Hand Tracking sample was used during the dev stream but feel free to test the another ones out too.

• TensorFlow
  • MNIST
  • SSD Object Detection
  • DeepLab
  • PoseNet
  • Style Transfer
  • Text Classification
  • Bert Question and Answer
  • Super Resolution
• MediaPipe
  • Hand Tracking
  • Blaze Face
  • Face Mesh
  • Blaze Pose (Upper body)
• MLKit
  • Blaze Pose (Full body)
• Meet Segmentation

Install TensorFlow Lite for Unity

• Clone this repository with examples
  • Requires installing Git-LFS
• The TFLite core library is available on:
  • OpenUPM
    Run openupm add com.github.asus4.tflite from the command line.
  • Or add git URL from the Package Maneger UI: https://github.com/asus4/tf-lite-unity-sample.git?path=/Packages/com.github.asus4.tflite

Build TensorFlow Lite libraries

Pre-built libraries are included. If you want to build the latest TFLite,

1. Clone TensorFlow library
2. Run ./configure in the TensorFlow library
3. Run ./build_tflite.py (Python3) to build for each platform

# Update iOS, Andoid and macOS
./build_tflte.py --tfpath ../tensorflow -ios -android -macos

# Build with XNNPACK
./build_tflte.py --tfpath ../tensorflow -macos -xnnpack

• To build macOS Metal Delegate on TensorFlow v2.3.0 or later, You need to apply following changes the issue

Show Case

Hand Tracking

License

Samples folder Assets/Samples/* is licensed under MIT

MIT License

Copyright (c) 2021 Koki Ibukuro

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

Other Licenses

• TensorFlow: Apache License 2.0
• MediaPipe: Apache License 2.0
  • Some MediaPipe C# codes are based on terryky/tflite_gles_app

Notes

This git repositry was made with the purpose of increasing the interest for the Arthron project. The project wants to help pain and hardship for gamers or persons that use computers a lot. With this we need all the help we can get. We need feedback on what we do, we need people who tell their friends that we exist and we need people to follow your discord!

• Discord Server for Arthron