convnetClassifier

What is it?

ConvnetClassifier is an openFrameworks application, part of the ml4a-ofx collection, which lets you train a classifier to recognise whatever objects, persons, postures, drawings and other visuals you show it through your webcam.

convnetClassifier gif

ConvnetClassifier has been used by Bjørn Karmann in his Objectifier project, which empowers people to train objects in their daily environment to respond to their unique behaviours.

OSC Output

By default the app outputs OSC to localhost, port 8000, adress “/classification”. This can be changed in ofApp.h.

Key inputs

As an alternative to using the GUI you can use the following key inputs:

Training instructions

  1. Make sure your camera sees your intended visuals for class 1. Click [record] to toggle recording of training examples.

  2. Set the Class Label slider to a different class and click [record] to record examples of a different class.

  3. Repeat this for class 3 or however many distinct things you intend to classify. Remember to change the classes by pressing the numeric keys accordingly.

  4. Click [train] to train the model.

  5. Show the webcam different visuals and see what class the model predicts.

The video below takes you through the steps of the training process.

Setup and training considerations

ConvnetClassifier is a very versatile application that can be used in a wide variety of setups. However, to optimise correct classification, some simple rules of thumbs are: