Deploying a deep neural network with Keras

In this exercise, we will generate an instance of the previously described Inception model, provided by the Keras application library. First of all, we will import all the required libraries, including the Keras model handling, the image preprocessing library, the gradient descent used to optimize the variables, and several Inception utilities. Additionally, we will use OpenCV libraries to adjust the new input images, and the common NumPy and matplotlib libraries:

from keras.models import Model
from keras.preprocessing import image
from keras.optimizers import SGD
from keras.applications.inception_v3 import InceptionV3, decode_predictions, preprocess_input

import matplotlib.pyplot as plt
import numpy as np
import cv2

Using TensorFlow backend.

Keras makes it really simple to load a model. You just have to invoke a new instance of the...