ASL interpretation
Based on features get from LeapMotion sendor, using SDK toolit, this project uses Sckit-learn library to interpret American Signal Languages symbols.
Three models were been analyzed:
- ANN (Artificial neural netwod)
- KNN
- SVM
- Nearest Centroid
Features and training
The set of features used to train the set of models were (get from LeapMotion sensor SDK):
- RTP
- RTT
- RTJ
To get trained model:
- Run script:
python train.py --classifierType ANNto get Confusion Matrix from SVM, for example.
The list of available models can be visualized with:
python train.py --helpRunning trained model
All the trained models are in the directory data/.
To run the ANN trained model, type:
python app.py- Read the document: Letter_Leap.pdf to get more information
In case of you want the real time application, please send me a message!
