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.
Trained Neural Network deployed on GestureAI-iOS, iOS 11 app using CoreML :
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 |
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 |  |
| 1 | Rectangle | 200 |  |
| 2 | Triangle | 200 |  |
| 3 | Cross | 200 |  |
| 4 | Other | 200 |
- 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)
$ virtualenv venv
$ source venv/bin/activate
$ git clone https://github.com/akimach/GestureAI.git
$ cd GestureAI
$ pip install -r requirements.txt
Try with Jupyter notebook!
- Loading datasets
- Tuning hyper-parameters with Grid Search
- Training RNN with Early-stopping