Computer Vision Projects with OpenCV and Python 3: Six end-to-end projects built using machine learning with OpenCV, Python, and TensorFlow

Matthew Rever

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商品描述

Gain a working knowledge of advanced machine learning and explore Python's powerful tools for extracting data from images and videos

Key Features

  • Implement image classification and object detection using machine learning and deep learning
  • Perform image classification, object detection, image segmentation, and other Computer Vision tasks
  • Crisp content with a practical approach to solving real-world problems in Computer Vision

Book Description

Python is the ideal programming language for rapidly prototyping and developing production-grade codes for image processing and Computer Vision with its robust syntax and wealth of powerful libraries. This book will help you design and develop production-grade Computer Vision projects tackling real-world problems.

With the help of this book, you will learn how to set up Anaconda and Python for the major OSes with cutting-edge third-party libraries for Computer Vision. You'll learn state-of-the-art techniques for classifying images, finding and identifying human postures, and detecting faces within videos. You will use powerful machine learning tools such as OpenCV, Dlib, and TensorFlow to build exciting projects such as classifying handwritten digits, detecting facial features,and much more. The book also covers some advanced projects, such as reading text from license plates from real-world images using Google's Tesseract software, and tracking human body poses using DeeperCut within TensorFlow.

By the end of this book, you will have the expertise required to build your own Computer Vision projects using Python and its associated libraries.

What you will learn

  • Install and run major Computer Vision packages within Python
  • Apply powerful support vector machines for simple digit classification
  • Understand deep learning with TensorFlow
  • Build a deep learning classifier for general images
  • Use LSTMs for automated image captioning
  • Read text from real-world images
  • Extract human pose data from images

Who this book is for

Python programmers and machine learning developers who wish to build exciting Computer Vision projects using the power of machine learning and OpenCV will find this book useful. The only prerequisite for this book is that you should have a sound knowledge of Python programming.

Table of Contents

  1. Download & install Anaconda for your platform and Introduction to Tool Setup
  2. Image Captioning with TensorFlow
  3. Reading license plates with Tesseract & OpenCV
  4. Human pose estimation with TensorFlow
  5. Handwritten digit recognition with scikit-learn & TensorFlow
  6. Facial feature tracking and classification with dlib
  7. Deep learning image classification with TensorFlow

商品描述(中文翻譯)

獲得對高級機器學習的實際知識,並探索Python在從圖像和視頻中提取數據方面的強大工具

主要特點:
- 使用機器學習和深度學習實現圖像分類和物體檢測
- 執行圖像分類、物體檢測、圖像分割和其他計算機視覺任務
- 以實用的方法解決計算機視覺中的實際問題

書籍描述:
Python是用於快速原型設計和開發生產級圖像處理和計算機視覺代碼的理想編程語言,憑藉其強大的語法和豐富的強大庫。本書將幫助您設計和開發生產級計算機視覺項目,解決現實世界的問題。

通過本書的幫助,您將學習如何使用先進的第三方庫在主要操作系統上設置Anaconda和Python,進行計算機視覺。您將學習最先進的技術,用於分類圖像、尋找和識別人體姿勢以及在視頻中檢測人臉。您將使用強大的機器學習工具,如OpenCV、Dlib和TensorFlow,構建令人興奮的項目,例如分類手寫數字、檢測面部特徵等等。本書還涵蓋了一些高級項目,例如使用Google的Tesseract軟件從現實世界圖像中讀取車牌上的文本,以及在TensorFlow中使用DeeperCut跟踪人體姿勢。

通過閱讀本書,您將具備使用Python及其相關庫構建自己的計算機視覺項目所需的專業知識。

您將學到什麼:
- 在Python中安裝和運行主要的計算機視覺包
- 使用強大的支持向量機進行簡單數字分類
- 了解TensorFlow中的深度學習
- 構建用於一般圖像的深度學習分類器
- 使用LSTMs進行自動圖像標題生成
- 從現實世界圖像中讀取文本
- 從圖像中提取人體姿勢數據

本書適合對象:
希望利用機器學習和OpenCV的強大功能來構建令人興奮的計算機視覺項目的Python程序員和機器學習開發人員將會發現本書非常有用。閱讀本書的唯一先決條件是您應該對Python編程有扎實的知識。

目錄:
1. 下載和安裝適用於您的平台的Anaconda和工具設置介紹
2. 使用TensorFlow進行圖像標題生成
3. 使用Tesseract和OpenCV讀取車牌
4. 使用TensorFlow進行人體姿勢估計
5. 使用scikit-learn和TensorFlow進行手寫數字識別
6. 使用dlib進行面部特徵跟踪和分類
7. 使用TensorFlow進行深度學習圖像分類