Welcome to the Python OpenCV tutorial! OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. It is designed for computational photography, real-time 3D reconstruction, augmented reality, and much more.

Overview

OpenCV is widely used in various fields such as robotics, computer vision, and image processing. In this tutorial, we will cover the basics of OpenCV in Python.

Prerequisites

Before starting this tutorial, make sure you have the following prerequisites:

  • Python installed on your system
  • An IDE or text editor (e.g., Visual Studio Code, PyCharm)
  • OpenCV library installed (pip install opencv-python)

Installation

To install OpenCV in Python, open your terminal or command prompt and run the following command:

pip install opencv-python

Basic Concepts

OpenCV provides a wide range of functionalities. Here are some of the basic concepts you need to know:

  • Image Processing: OpenCV allows you to process images and videos.
  • Object Detection: You can detect objects in images and videos using OpenCV.
  • Face Recognition: OpenCV provides various algorithms for face recognition.
  • Feature Detection: Detect features in images using OpenCV.

Sample Code

Here is a simple example of how to load and display an image using OpenCV:

import cv2

# Load an image
image = cv2.imread('path/to/image.jpg')

# Display the image
cv2.imshow('Image', image)

# Wait for a key press
cv2.waitKey(0)

# Close all OpenCV windows
cv2.destroyAllWindows()

Further Reading

For more information, check out the following resources:

Image Processing