更新时间：2021-07-02 14:21:33
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Title Page
Copyright and Credits
Computer Vision Projects with OpenCV and Python 3
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Preface
Who this book is for
What this book covers
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Conventions used
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Setting Up an Anaconda Environment
Introducing and installing Python and Anaconda
Installing Anaconda
Installing additional libraries
Installing OpenCV
Installing dlib
Installing Tesseract
Installing TensorFlow
Exploring Jupyter Notebook
Summary
Image Captioning with TensorFlow
Technical requirements
Introduction to image captioning
Difference between image classification and image captioning
Recurrent neural networks with long short-term memory
Google Brain im2txt captioning model
Running the captioning code on Jupyter
Analyzing the result captions
Running the captioning code on Jupyter for multiple images
Retraining the captioning model
Reading License Plates with OpenCV
Identifying the license plate
Plate utility functions
The gray_thresh_img function and morphological functions
Kernels
The matching character function
The k-nearest neighbors digit classifier
Finding plate characters
Finding matches and groups of characters
Finding and reading license plates with OpenCV
Result analysis
Human Pose Estimation with TensorFlow
Pose estimation using DeeperCut and ArtTrack
Single-person pose detection
Multi-person pose detection
Retraining the human pose estimation model
Handwritten Digit Recognition with scikit-learn and TensorFlow
Acquiring and processing MNIST digit data
Creating and training a support vector machine
Applying the support vector machine to new data
Introducing TensorFlow with digit classification
Evaluating the results
Facial Feature Tracking and Classification with dlib
Introducing dlib
Facial landmarks
Finding 68 facial landmarks in images
Faces in videos
Facial recognition
Deep Learning Image Classification with TensorFlow
An introduction to TensorFlow
Using Inception for image classification
Retraining with our own images
Speeding up computation with your GPU
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