Repository for a browser based tensorflow model to classify hand gestures.
We make use of trasfer learning and of MobileNet, a set of light and efficient CNNs designed specifically for mobile and embedded computer vision applications. MobileNets are based on a streamlined architecture that uses depth-wise separable convolutions to build light weight deep neural networks.
Simply, go to the webpage. It might be required to allow the browser to access your webcam. Hence, you build a little dataset (50/60 images per class should be enough).
You put your hand in front of the camera, indicating for instance 2.
Click on the two button would add the image and the corresponding label to the dataset.
Once you are happy with the examples you have added, train your network. A browser alert would notify when training is done, allowing you starting the predictions.
Again, you put your hand in front of the camera, miming the gesture of three, and you should visualise the message I see three.