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https://github.com/akimach/gestureai
RNN(Recurrent Nerural network) model which recognize hand-gestures drawing 5 figures.
https://github.com/akimach/gestureai
coreml dataset deep-learning deep-neural-networks demo ios keras keras-models keras-tensorflow machine-learning python python-2 recurrent-nerural-network rnn tensorflow
Last synced: 2 days ago
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RNN(Recurrent Nerural network) model which recognize hand-gestures drawing 5 figures.
- Host: GitHub
- URL: https://github.com/akimach/gestureai
- Owner: akimach
- License: mit
- Created: 2017-09-25T10:43:24.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2017-09-28T08:37:14.000Z (over 7 years ago)
- Last Synced: 2025-01-03T22:12:57.258Z (19 days ago)
- Topics: coreml, dataset, deep-learning, deep-neural-networks, demo, ios, keras, keras-models, keras-tensorflow, machine-learning, python, python-2, recurrent-nerural-network, rnn, tensorflow
- Language: Jupyter Notebook
- Homepage:
- Size: 4.89 MB
- Stars: 24
- Watchers: 2
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# GestureAI
[![MIT License](http://img.shields.io/badge/license-MIT-blue.svg?style=flat)](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](https://github.com/akimach/GestureAI-iOS) :
![demo](images/demo.gif)
## 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](https://github.com/akimach/GestureAI/blob/master/datasets/gesture-3axis-accel.tar.gz?raw=true)|`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](images/circle.jpg)|
|1|Rectangle|200|![Rectangle](images/rectangle.jpg)|
|2|Triangle|200|![Triangle](images/triangle.jpg)|
|3|Cross|200|![Cross](images/cross.jpg)|
|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](https://github.com/akimach/GestureAI/blob/master/LICENSE)
## Author
[Akimasa KIMURA](https://github.com/akimach)