CBSE 10 AI (Artificial Intelleigence) | 21. OpenCV by Abraham | Learn Smarter
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21. OpenCV

21. OpenCV

OpenCV is a powerful and widely used open-source library designed for image and video processing, integral to computer vision applications. The chapter covers how to install OpenCV in Python, manage images, and utilize various image processing techniques. It also delves into face detection and real-time video capture, highlighting applications in several fields such as healthcare and automotive.

17 sections

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  1. 21

    OpenCV is a powerful, open-source library for computer vision applications,...

  2. 21.1
    What Is Opencv?

    OpenCV is an open-source library that provides tools for image processing,...

  3. 21.2
    Installing Opencv In Python

    This section covers the installation process to set up OpenCV for Python.

  4. 21.3
    Working With Images

    This section introduces how to read and display images using OpenCV, as well...

  5. 21.3.1
    Reading An Image

    This section covers the basics of reading an image using OpenCV, including...

  6. 21.3.2
    Image As A Matrix

    This section introduces the concept of images being represented as matrices,...

  7. 21.4
    Image Processing With Opencv

    This section covers basic image processing techniques using OpenCV,...

  8. 21.4.1
    Converting To Grayscale

    This section explains how to convert color images to grayscale using...

  9. 21.4.2
    Resizing An Image

    This section covers how to resize images using OpenCV, an essential...

  10. 21.4.3
    Blurring An Image

    This section covers the method of blurring an image using OpenCV's...

  11. 21.4.4
    Drawing On Images

    This section covers how to draw basic shapes, such as rectangles and...

  12. 21.5
    Face Detection Using Opencv

    This section introduces face detection using OpenCV and its Haar Cascade...

  13. 21.5.1
    Load Haar Cascade Classifier

    This section describes how to load a pre-trained Haar Cascade Classifier in...

  14. 21.5.2
    Detect Faces In An Image

    The section covers the process of detecting faces in images using the OpenCV...

  15. 21.5.3
    Display Detected Faces

    This section explains how to display detected faces in an image using OpenCV.

  16. 21.6
    Using Webcam With Opencv

    This section discusses how to capture live video from a webcam using OpenCV,...

  17. 21.7
    Applications Of Opencv

    OpenCV has diverse applications across various fields, including healthcare,...

What we have learnt

  • OpenCV is crucial for computer vision tasks.
  • Images can be manipulated through different techniques using OpenCV.
  • Real-time video processing and face detection are implemented through OpenCV.

Key Concepts

-- OpenCV
An open-source library that provides tools for image processing and computer vision.
-- Image Processing
Techniques including reading, displaying, and modifying images using libraries like OpenCV.
-- Haar Cascades
A machine learning object detection method used for detecting objects for which it has been trained, such as faces.
-- Realtime Video Capture
The ability to capture and process video feed from a camera in live time using OpenCV.

Additional Learning Materials

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