Chapter 8: Tips and Tricks of the Trade

Activity 21: Classifying Images using InceptionV3

Solution:

1. Create functions to get images and labels. Here PATH variable contains the path to the training dataset.

   from PIL import Image
   def get_input(file):
       return Image.open(PATH+file)
   def get_output(file):
       class_label = file.split('.')[0]
       if class_label == 'dog': label_vector = [1,0]
       elif class_label == 'cat': label_vector = [0,1]
       return label_vector

2. Set SIZE and CHANNELS. SIZE is the dimension of the square image input. CHANNELS is the number of channels in the training data images. There are 3 channels in a RGB image.

   SIZE = 200
   CHANNELS = 3

3. Create a function to preprocess and augment images:

   def preprocess_input(image):
       
       # Data preprocessing
       image = image...