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Intelligent Projects Using Python

You're reading from   Intelligent Projects Using Python 9 real-world AI projects leveraging machine learning and deep learning with TensorFlow and Keras

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781788996921
Length 342 pages
Edition 1st Edition
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Author (1):
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Santanu Pattanayak Santanu Pattanayak
Author Profile Icon Santanu Pattanayak
Santanu Pattanayak
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Table of Contents (12) Chapters Close

Preface 1. Foundations of Artificial Intelligence Based Systems FREE CHAPTER 2. Transfer Learning 3. Neural Machine Translation 4. Style Transfer in Fashion Industry using GANs 5. Video Captioning Application 6. The Intelligent Recommender System 7. Mobile App for Movie Review Sentiment Analysis 8. Conversational AI Chatbots for Customer Service 9. Autonomous Self-Driving Car Through Reinforcement Learning 10. CAPTCHA from a Deep-Learning Perspective 11. Other Books You May Enjoy

Freezing the model to a protobuf format

The saved, trained model, in the form of the model.pbtxt and model_ckpt files, cannot be used by the Android app directly. We need to convert it to an optimized protobuf format (a .pb extension file), which can be integrated with the Android app. The file size of the optimized protobuf format will be much smaller than the combined size of the model.pbtxt and model_ckpt files.

The following code(freeze_code.py) will create the optimized protobuf model from the model.pbtxt and the model_ckpt files:

# -*- coding: utf-8 -*-

import sys
import tensorflow as tf
from tensorflow.python.tools import freeze_graph
from tensorflow.python.tools import optimize_for_inference_lib
import fire
from elapsedtimer import ElapsedTimer

#path = '/home/santanu/Downloads/Mobile_App/'
#MODEL_NAME = 'model'

def model_freeze(path,MODEL_NAME='model&apos...
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