OpenCV-Python

:dart: Learning Objectives

By the end of this lesson, you will be able to:

• Install and import OpenCV-Python in your projects
• Read and display images using OpenCV
• Capture and show video from files or webcam
• Understand basic computer vision concepts

:information_source: OpenCV-Python is a Python library that helps you solve computer vision problems. It combines the power of OpenCV (Open Source Computer Vision) with Python's simplicity.

:books: Background

• OpenCV started at Intel in 1999 by Gary Bradsky. The first release came out in 2000.
• Many programming languages can use OpenCV: Python, C++, Java, JavaScript, and more!
• OpenCV-Python combines OpenCV's powerful C++ API with Python's easy syntax.
• You can use OpenCV-Python for:
  • Image processing - Edit and enhance photos
  • Object detection - Find things in pictures
  • Face recognition - Identify people in images
  • Video analysis - Process video streams

:bulb: Want to explore more? Visit the OpenCV-Python Documentation for advanced tutorials!

:emoji:️ What We'll Learn

We'll explore three main topics with hands-on examples:

1. Installing and importing OpenCV-Python - Set up your environment
2. Reading and showing images - Work with pictures
3. Capturing and showing video/webcam - Process video streams

:computer: Install and Import OpenCV-Python

First, let's set up our environment! We'll use VSCode for learning OpenCV-Python. (Set up VSCode for Python following the guidelines here)

Installing the Library

Since OpenCV-Python is a library, you need to install it using pip:

• For Windows:
  bash

  py -m pip install opencv-contrib-python
  

• For macOS:
  bash

  pip3 install opencv-python
  

Installing NumPy

NumPy helps OpenCV work with arrays and matrices. Install it too:

• For Windows:
  bash

  py -m pip install numpy
  

• For macOS:
  bash

  pip3 install numpy
  

Importing the Libraries

After installation, import both libraries in your Python code:

python

import numpy as np
import cv2 as cv

note We use short names (np for NumPy and cv for OpenCV) to make our code cleaner!

:emoji:️ Read and Show an Image

Let's learn how to work with images! OpenCV provides three main functions:

1. cv.imread(image) - Reads an image from a file
2. cv.imshow(window_name, image_readed) - Shows the image in a window
3. cv.waitKey(0) - Keeps the window open (0 means wait forever)

Example: Display an Image

Here's how to read and show an image called "image.jpg":

# read image
img = cv.imread("image.jpg")
# show image
cv.imshow("Image", img)
# showing the image forever
cv.waitKey(0)

:bulb: The window will stay open until you press any key. This gives you time to look at your image!

:movie_camera: Read and Show Video/Webcam

Understanding Video

A video is like a flipbook - it's made of many pictures (called frames) shown quickly one after another!

:information_source: Frames Per Second (FPS) tells us how many pictures show in one second:

• Less than 24 FPS: Video looks choppy
• 24-30 FPS: Smooth for movies
• 60+ FPS: Super smooth for games

The image below shows how different FPS values affect video quality:

Working with Video

OpenCV handles video by processing it frame by frame. Here are the key functions:

1. Capture video source:
   • cv.VideoCapture("video.mp4") - Opens a video file
   • cv.VideoCapture(0) - Opens your webcam (0 = default camera)
2. Process frames in a loop:
   • ret, frame = video.read() - Gets the next frame
   • cv.imshow(window_name, frame) - Shows the frame
   • cv.waitKey(milliseconds) - Controls playback speed
3. Clean up when done:
   • video.release() - Stops capturing
   • cv.destroyAllWindows() - Closes all windows

Example: Play a Video File

Here's how to play a video file called "video.mp4":

python

# capture video
video = cv.VideoCapture("video.mp4")
# Show video frame by frame in a while loop
while True:
    # capture frame-by-frame
    ret, frame = video.read()
    # show video frame-by-frame every 25 millisecond
    cv.imshow('frame', frame)
    cv.waitKey(25)
# Release everything if job is finished
video.release()
cv.destroyAllWindows()

Stopping Video Playback

We need to stop the video in two situations:

1. Video ends - No more frames to show
2. User wants to quit - Press a key to stop

Example: Video with Stop Controls

This example shows how to stop when the video ends or when you press 'Q':

python

# capture video
video = cv.VideoCapture("video.mp4")
while True:
    # capture frame-by-frame
    ret, frame = video.read()
    # Quit when no more frame
    if not ret:
        print("Video Ended")
        break
    # show video frame-by-frame
    cv.imshow('frame', frame)
    # stop when Q is pressed
    if cv.waitKey(25) == ord("q"):
         break
# Release everything if job is finished
video.release()
cv.destroyAllWindows()

note Remember: ord("q") converts the letter 'q' into a number that the computer understands!

:emoji: Summary

In this lesson, you learned:

• :white_check_mark: How to install OpenCV-Python and NumPy
• :white_check_mark: How to read and display images
• :white_check_mark: How to capture and play videos
• :white_check_mark: How to control video playback with keyboard input

OpenCV-Python opens the door to computer vision projects. You can now work with images and videos in your Python programs!

:emoji: Video Tutorial

Watch this video to see OpenCV-Python in action:

:emoji: AI Prompts

Use AI to explore OpenCV further! Try these prompts:

Getting Started:

• "Show me how to use basic OpenCV functions like imread(), imshow(), and waitKey()."
• "What are the common OpenCV data structures and how do I work with them?"
• "Explain the difference between BGR and RGB color spaces in OpenCV."

Going Deeper:

• "How can I resize an image using OpenCV?"
• "Show me how to convert a color image to grayscale."
• "How do I save a processed image to a file?"

:dart: Practice Activities

Try these hands-on exercises to master OpenCV-Python:

1. Image Explorer: Create a program that:

   • Loads an image from your computer
   • Displays it in a window
   • Shows the image dimensions when you press 'd'
   • Closes when you press 'q'

2. Webcam Fun: Build a simple webcam app that:

   • Shows your webcam feed
   • Takes a screenshot when you press 's'
   • Stops when you press 'q'

3. Video Player: Make a basic video player that:

   • Plays a video file
   • Pauses when you press spacebar
   • Shows the current frame number

:bulb: Tip Start with the first exercise and work your way up. Each one builds on what you learned before!