OpenCV: Computer Vision Projects with Python

Joseph Howse, Prateek Joshi, Michael Beyeler

相關主題

商品描述

Get savvy with OpenCV and actualize cool computer vision applications

About This Book

  • Use OpenCV's Python bindings to capture video, manipulate images, and track objects
  • Learn about the different functions of OpenCV and their actual implementations.
  • Develop a series of intermediate to advanced projects using OpenCV and Python

Who This Book Is For

This learning path is for someone who has a working knowledge of Python and wants to try out OpenCV. This Learning Path will take you from a beginner to an expert in computer vision applications using OpenCV. OpenCV's application are humongous and this Learning Path is the best resource to get yourself acquainted thoroughly with OpenCV.

What You Will Learn

  • Install OpenCV and related software such as Python, NumPy, SciPy, OpenNI, and SensorKinect - all on Windows, Mac or Ubuntu
  • Apply "curves" and other color transformations to simulate the look of old photos, movies, or video games
  • Apply geometric transformations to images, perform image filtering, and convert an image into a cartoon-like image
  • Recognize hand gestures in real time and perform hand-shape analysis based on the output of a Microsoft Kinect sensor
  • Reconstruct a 3D real-world scene from 2D camera motion and common camera reprojection techniques
  • Detect and recognize street signs using a cascade classifier and support vector machines (SVMs)
  • Identify emotional expressions in human faces using convolutional neural networks (CNNs) and SVMs
  • Strengthen your OpenCV2 skills and learn how to use new OpenCV3 features

In Detail

OpenCV is a state-of-art computer vision library that allows a great variety of image and video processing operations. OpenCV for Python enables us to run computer vision algorithms in real time. This learning path proposes to teach the following topics. First, we will learn how to get started with OpenCV and OpenCV3's Python API, and develop a computer vision application that tracks body parts. Then, we will build amazing intermediate-level computer vision applications such as making an object disappear from an image, identifying different shapes, reconstructing a 3D map from images , and building an augmented reality application, Finally, we'll move to more advanced projects such as hand gesture recognition, tracking visually salient objects, as well as recognizing traffic signs and emotions on faces using support vector machines and multi-layer perceptrons respectively.

This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products:

  • OpenCV Computer Vision with Python by Joseph Howse
  • OpenCV with Python By Example by Prateek Joshi
  • OpenCV with Python Blueprints by Michael Beyeler

Style and approach

This course aims to create a smooth learning path that will teach you how to get started with will learn how to get started with OpenCV and OpenCV 3's Python API, and develop superb computer vision applications. Through this comprehensive course, you'll learn to create computer vision applications from scratch to finish and more!.

商品描述(中文翻譯)

精通 OpenCV,實現酷炫的電腦視覺應用程式

關於本書
- 使用 OpenCV 的 Python 綁定來捕捉視頻、操作圖像和追蹤物體
- 了解 OpenCV 的不同功能及其實際實現
- 使用 OpenCV 和 Python 開發一系列中級到高級的項目

本書適合對 Python 有一定了解並想嘗試 OpenCV 的人。這條學習路徑將帶您從初學者變成使用 OpenCV 的電腦視覺應用專家。OpenCV 的應用非常廣泛,這條學習路徑是您全面瞭解 OpenCV 的最佳資源。

您將學到什麼
- 在 Windows、Mac 或 Ubuntu 上安裝 OpenCV 及相關軟體,如 Python、NumPy、SciPy、OpenNI 和 SensorKinect
- 應用「曲線」和其他色彩轉換來模擬舊照片、電影或視頻遊戲的外觀
- 對圖像應用幾何變換,執行圖像過濾,並將圖像轉換為卡通風格的圖像
- 實時識別手勢並根據 Microsoft Kinect 感應器的輸出進行手形分析
- 從 2D 相機運動和常見的相機重投影技術中重建 3D 真實世界場景
- 使用級聯分類器和支持向量機(SVM)檢測和識別交通標誌
- 使用卷積神經網絡(CNN)和支持向量機(SVM)識別人臉上的情緒表達
- 加強您的 OpenCV2 技能,並學習如何使用新的 OpenCV3 功能

詳細內容
OpenCV 是一個先進的電腦視覺庫,可以進行各種圖像和視頻處理操作。OpenCV for Python 讓我們能夠實時運行電腦視覺算法。本學習路徑旨在教授以下主題。首先,我們將學習如何開始使用 OpenCV 和 OpenCV3 的 Python API,並開發一個追蹤身體部位的電腦視覺應用程式。然後,我們將建立令人驚嘆的中級電腦視覺應用程式,例如從圖像中消失物體、識別不同形狀、從圖像重建 3D 地圖以及建立擴增實境應用程式。最後,我們將進行更高級的項目,如手勢識別、追蹤視覺突出的物體,以及使用支持向量機和多層感知器分別識別交通標誌和人臉上的情緒。

本學習路徑結合了 Packt 提供的最佳內容,以一個完整的、精選的套裝方式呈現。它包括以下 Packt 產品的內容:
- 《OpenCV Computer Vision with Python》(作者:Joseph Howse)
- 《OpenCV with Python By Example》(作者:Prateek Joshi)
- 《OpenCV with Python Blueprints》(作者:Michael Beyeler)

風格和方法
本課程旨在創建一條平滑的學習路徑,教您如何開始使用 OpenCV 和 OpenCV 3 的 Python API,並開發出優秀的電腦視覺應用程式。通過這個全面的課程,您將學會從頭開始創建電腦視覺應用程式等技能。