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RNN(Recurrent Nerural network) model which recognize hand-gestures drawing 5 figures.

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GestureAI

MIT License

GestureAI is a RNN(Recurrent Nerural network) model which recognize hand-gestures drawing 5 figures(Circl, Rectangle, Triangle, Cross and the other). This dataset of hand-motion drawing 5 figures is sequences of 3-axis accelerations captured by iPhone. Example to implement RNN in Keras gets 90.8% accuracy by Cross-validation.

Demo

Trained Neural Network deployed on GestureAI-iOS, iOS 11 app using CoreML :

demo

Get the Dataset

You can use direct links to download the dataset.

Name Examples Size Link MD5 Checksum
gesture-3axis-accel.tar.gz 1,000 338 KBytes Download 37664771fd60e930033fb24387fb1601

Labels

The dataset consists of 1,000 3-axis acceleration sequences of 5 gesture classes, which are defined by motions drawing 5 figures. We don't set a specific rule about stroke order for drawing a figure by hand.

Label Description Examples Figure
0 Circle 200 Circle
1 Rectangle 200 Rectangle
2 Triangle 200 Triangle
3 Cross 200 Cross
4 Other 200

Requirement

  • Python (2.7+)
  • numpy (1.12.1+)
  • protobuf (3.1.0+)
  • Keras (1.2.2)
  • TensorFlow (1.2.1)
  • Scikit-learn (0.15+)
  • coremltools (0.6.3)

Install

$ virtualenv venv
$ source venv/bin/activate
$ git clone https://github.com/akimach/GestureAI.git
$ cd GestureAI
$ pip install -r requirements.txt

Examples

Try with Jupyter notebook!

  • Loading datasets
  • Tuning hyper-parameters with Grid Search
  • Training RNN with Early-stopping

Licence

MIT

Author

Akimasa KIMURA