Conventions used

There are a number of text conventions used throughout this book.

Code in text: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: “Using image_generator, we’ll pick and display a random batch of 10 images directly from the directory they are stored in.”

A block of code is set as follows:

iterator = (image_generator
           .flow_from_directory(directory=data_directory, 
                                 batch_size=10))
for batch, _ in iterator:
plt.figure(figsize=(5, 5))
for index, image in enumerate(batch, start=1):
ax = plt.subplot(5, 5, index)
plt.imshow(image)
plt.axis(‘off’)
plt.show()
break

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

[default]
exten => s,1,Dial(Zap/1|30)
exten => s,2,Voicemail(u100)
exten => s,102,Voicemail(b100)
exten => i,1,Voicemail(s0)

Any command-line input or output is written as follows:

$ pip install tensorflow-hub Pillow
$ pip install tensorflow-datasets tqdm

Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: “Select System info from the Administration panel.”

Tips or important notes

We’ll use the modified version of the Stanford Cars dataset we just worked on in future recipes in this chapter.