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Python Deep Learning Cookbook

You're reading from  Python Deep Learning Cookbook

Product type Book
Published in Oct 2017
Publisher Packt
ISBN-13 9781787125193
Pages 330 pages
Edition 1st Edition
Languages
Author (1):
Indra den Bakker Indra den Bakker
Profile icon Indra den Bakker
Toc

Table of Contents (21) Chapters close

Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Programming Environments, GPU Computing, Cloud Solutions, and Deep Learning Frameworks 2. Feed-Forward Neural Networks 3. Convolutional Neural Networks 4. Recurrent Neural Networks 5. Reinforcement Learning 6. Generative Adversarial Networks 7. Computer Vision 8. Natural Language Processing 9. Speech Recognition and Video Analysis 10. Time Series and Structured Data 11. Game Playing Agents and Robotics 12. Hyperparameter Selection, Tuning, and Neural Network Learning 13. Network Internals 14. Pretrained Models

Finding facial key points


One of the applications that is most commonly used in computer vision is detecting faces in images. This provides many solutions in different industries. The first step is to detect facial keypoints in an image (or frame). These facial keypoints, also known as facial landmarks, have proven to be unique and accurate for locating the faces in an image and the direction the face is pointing. More computer vision techniques and machine learning techniques are still often used, such as HOG + Linear SVM. In the following recipe, we will show you how to use deep learning to do this. Specifically, we will a CNN for detecting keypoints. Afterward, we will show you how to use keypoints for head pose estimation, face morphing, and tracking with OpenCV.

How to do it...

  1. We start with importing all necessary libraries and setting the seed, as follows:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

from sklearn.model_selection import train_test_split...
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