Machine Learning for OpenCV 4 - Second Edition

Getting acquainted with Keras

The core data structure of Keras is a model, which is similar to OpenCV's classifier object, except it focuses on neural networks only. The simplest type of model is the sequential model, which arranges the different layers of the neural network in a linear stack, just like we did for the MLP in OpenCV:

In [1]: from keras.models import Sequential...     model = Sequential()Out[1]: Using TensorFlow backend.

Then, different layers can be added to the model one by one. In Keras, layers do not just contain neurons, they also perform a function. Some core layer types include the following:

• Dense: This is a densely connected layer. This is exactly what we used when we designed our MLP: a layer of neurons that is connected ...