Python机器视觉OpenCV视频教程Learn Python Computer Vision with OpenCV by Kiran A. Bendigeri

您将使用 OpenCV 和 Python 学习计算机视觉。

OpenCV（开源计算机视觉库）是一个主要针对实时计算机视觉的编程函数库。最初由 Intel 开发，后来得到 Willow Garage 和 Itseez（后来被 Intel 收购）的支持。该库是跨平台的，可在开源 Apache 2 许可下免费使用。从 2011 年开始，OpenCV 具有用于实时操作的 GPU 加速功能。

OpenCV 是 Python 编程的中级水平，但在本课程中，我从 Python 编程的基础开始，即使您是编程新手，也可以学习本课程并开始构建应用程序。

我涵盖了 Python、Numpy、Matplotlib、OpenCV 和 3 个应用程序的基础知识。

1) Python – 数据类型、列表、元组、字典、集合、类、函数

2) Numpy – 数组及其使用

3) Matplotlib – 图表

4) 使用 OpenCV 的图像处理 – 平移、旋转、缩放、灰度缩放、色彩空间、图像金字塔、亮度和对比度、裁剪、算术运算、卷积、模糊、锐化、阈值、膨胀和侵蚀、边缘检测、轮廓、形状匹配、绘制图像，寻找角落。

5) 项目:-

A) 实时视频草图 – 在这里，我们正在拍摄一个小视频剪辑并将视频转换为草图。我们将使用先前学习的灰度、边缘检测等概念

B) 物体检测 – 从视频中检测物体。使用 Haar 级联。

C) 人脸检测 – 检测图像中的人脸。

您可以使用本课程开发成熟的图像处理应用程序。有了这些知识，您还可以为安全系统开发应用程序、对对象进行分类、将旧书转换为图像、使其可读等。

MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 35 lectures (2h 55m) | Size: 1.31 GB
Course includes Python, Numpy, Matplotlib and OpenCV. Image processing and object detection from videos and images

What you’ll learn:
Computer Vision using OpenCV
Image Processing – Translation, Rotation, Scaling, Brightness, Arithmetic Operations, Convolutions, Blurring, Sharpening and many more
Object Detection using Haar Cascade

Requirements
Be able to operate the computer.
High School Math.

Description
You are going to learn Computer vision using OpenCV and Python.

OpenCV (Open Source Computer Vision Library) is a library of programming functions mainly aimed at real-time computer vision. Originally developed by Intel, it was later supported by Willow Garage then Itseez (which was later acquired by Intel). The library is cross-platform and free for use under the open-source Apache 2 License. Starting with 2011, OpenCV features GPU acceleration for real-time operations.

OpenCV is something which is of intermediate level in Python programming, But in this course as I start from basics of Python programming, even if you are a novice in programming you can take this course and start building applications.

I am covering the basics of Python, Numpy, Matplotlib, OpenCV and 3 Applications.

1) Python – Data types, Lists, Tuples, Dictionary, Sets, Class, Function

2) Numpy – Arrays and its use

3) Matplotlib – Charts

4) Image Processing using OpenCV – Translation, Rotation, Scaling, Greyscaling, Color Spaces, Image Pyramids, Brightness and Contrast, Cropping, Arithmetic Operations, Convolutions, Blurring, Sharpening, Threshold, Dilation and Erosion, Edge Detection, Contour, Shape Matching, Drawing Images, Finding Corners.

5) Projects :-

A) Live Video Sketch – Here we are taking a small video clip and covert the video into sketch. We are going to use previously learnt concept of greyscaling, edge detection etc

B) Object Detection – Detecting Objects from video. Using Haar cascade.

C) Face Detection – Detecting Face in an image.

You can develop full fledged Image processing application using this course. Also with this knowledge you can develop applications for security systems, classifying objects, converting old books to images, make it readable and so on.

Who this course is for
Everyone who want to build some interesting Computer Vision Applications.
Anyone who want to learn a new thing in Python Programming.
Students, Professinals, Hobbyists.