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TensorFlow 2.0 Computer Vision Cookbook

You're reading from   TensorFlow 2.0 Computer Vision Cookbook Implement machine learning solutions to overcome various computer vision challenges

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Product type Paperback
Published in Feb 2021
Publisher Packt
ISBN-13 9781838829131
Length 542 pages
Edition 1st Edition
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Author (1):
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Jesús Martínez Jesús Martínez
Author Profile Icon Jesús Martínez
Jesús Martínez
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Table of Contents (14) Chapters Close

Preface 1. Chapter 1: Getting Started with TensorFlow 2.x for Computer Vision 2. Chapter 2: Performing Image Classification FREE CHAPTER 3. Chapter 3: Harnessing the Power of Pre-Trained Networks with Transfer Learning 4. Chapter 4: Enhancing and Styling Images with DeepDream, Neural Style Transfer, and Image Super-Resolution 5. Chapter 5: Reducing Noise with Autoencoders 6. Chapter 6: Generative Models and Adversarial Attacks 7. Chapter 7: Captioning Images with CNNs and RNNs 8. Chapter 8: Fine-Grained Understanding of Images through Segmentation 9. Chapter 9: Localizing Elements in Images with Object Detection 10. Chapter 10: Applying the Power of Deep Learning to Videos 11. Chapter 11: Streamlining Network Implementation with AutoML 12. Chapter 12: Boosting Performance 13. Other Books You May Enjoy

Detecting emotions in real time

At its most basic form, a video is just a series of images. By leveraging this seemingly simple or trivial fact, we can adapt what we know about image classification to create very interesting video processing pipelines powered by deep learning.

In this recipe, we'll build an algorithm to detect emotions in real time (webcam streaming) or from video files. Pretty interesting, right?

Let's begin.

Getting ready

First, we must install several external libraries, such as OpenCV and imutils. Execute the following command to install them:

$> pip install opencv-contrib-python imutils

To train an emotion classifier network, we'll use the dataset from the Kaggle competition Challenges in Representation Learning: Facial Expression Recognition Challenge, which is available here: https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge/data. You must sign in or sign up in order to...

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