Mastering OpenCV 4 with Python

Deep learning REST API using Keras Applications

In the previous subsection, we have seen how to work with the applications module of the Keras deep learning library, providing both deep learning model definitions and pre-trained weights for a number of popular architectures.

In this subsection, we are going to see how to create a deep learning REST API based on one of these pre-trained architectures.

The Keras deep learning REST API is a single file named keras_server.py. The code for this script can be seen next:

# Import required packages:from keras.applications import nasnet, NASNetMobilefrom keras.preprocessing.image import img_to_arrayfrom keras.applications import imagenet_utilsfrom PIL import Imageimport numpy as npimport flaskimport ...