Computer Vision Projects with OpenCV and Python 3: Six end-to-end projects built using machine learning with OpenCV, Python, and TensorFlow
暫譯: 使用 OpenCV 和 Python 3 的電腦視覺專案:六個基於機器學習的端到端專案,使用 OpenCV、Python 和 TensorFlow 構建

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)

獲得進階機器學習的實作知識,並探索 Python 強大的工具以從影像和影片中提取數據

主要特點
- 使用機器學習和深度學習實現影像分類和物體偵測
- 執行影像分類、物體偵測、影像分割及其他計算機視覺任務
- 內容清晰,實用的方法解決計算機視覺中的現實問題

書籍描述
Python 是快速原型設計和開發生產級影像處理及計算機視覺代碼的理想程式語言,擁有強大的語法和豐富的強大庫。本書將幫助您設計和開發針對現實問題的生產級計算機視覺專案。

藉由本書的幫助,您將學會如何為主要作業系統設置 Anaconda 和 Python,並使用尖端的第三方庫進行計算機視覺。您將學習最先進的技術來分類影像、尋找和識別人體姿勢,以及在影片中偵測人臉。您將使用強大的機器學習工具,如 OpenCV、Dlib 和 TensorFlow,來構建令人興奮的專案,例如分類手寫數字、偵測面部特徵等。本書還涵蓋一些進階專案,例如使用 Google 的 Tesseract 軟體從現實影像中讀取車牌文字,以及在 TensorFlow 中使用 DeeperCut 追蹤人體姿勢。

在本書結束時,您將具備使用 Python 及其相關庫構建自己的計算機視覺專案所需的專業知識。

您將學到的內容
- 在 Python 中安裝和運行主要的計算機視覺套件
- 應用強大的支持向量機進行簡單的數字分類
- 理解使用 TensorFlow 的深度學習
- 為一般影像構建深度學習分類器
- 使用 LSTM 進行自動影像標題生成
- 從現實影像中讀取文字
- 從影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 的力量構建令人興奮的計算機視覺專案的 Python 程式設計師和機器學習開發者將會發現本書非常有用。本書的唯一前提是您應該具備良好的 Python 程式設計知識。

目錄
1. 下載並安裝適合您平台的 Anaconda 及工具設置介紹
2. 使用 TensorFlow 進行影像標題生成
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 進行面部特徵追蹤和分類
7. 使用 TensorFlow 進行深度學習影像分類