January 2019
Intermediate to advanced
322 pages
7h 29m
English
The first implementation of object recognition we are going to do is in Python and involves the Keras framework. To train and evaluate the model, we are going to use a public dataset called CIFAR-10 (http://www.cs.toronto.edu/~kriz/cifar.html). It consists of 60,000 (50,000 for training and 10,000 for testing) small (32 x 32 pixels) color images divided into 10 classes (airplane, automobile, bird, cat, deer, dog, frog, horse, ship, and truck). These 10 classes are mutually exclusive. The CIFAR-10 dataset (163 MB) is freely downloadable from http://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz.
The prerequisites for this implementation are Python 2.7.x, Keras, TensorFlow (it is used as the Keras backend), NumPy, and ...