Defining a tf.data.Dataset

Now let’s look at how we can create a tf.data.Dataset using the data. We will first write a few helper functions. Namely, we’ll define:

• parse_image() to load and process an image from a filepath
• generate_tokenizer() to generate a tokenizer trained on the data passed to the function

First let’s discuss the parse_image() function. It takes three arguments:

• filepath – Location of the image
• resize_height – Height to resize the image to
• resize_width – Width to resize the image to

The function is defined as follows:

def parse_image(filepath, resize_height, resize_width):
    """ Reading an image from a given filepath """
    
    # Reading the image
    image = tf.io.read_file(filepath)
    # Decode the JPEG, make sure there are 3 channels in the output
    image = tf.io.decode_jpeg(image, channels=3)
    image = tf.image.convert_image_dtype...