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Image Reading with OpenCV

OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning library widely used in:

  • Image processing\
  • Video processing\
  • Machine vision\
  • Artificial intelligence

This document explains both the concepts and a practical Python example for reading images using OpenCV.

1. Implementation Principle​

OpenCV provides simple APIs for image input/output:

  • cv2.imread() --- reads an image file from disk\
  • cv2.imshow() --- displays the image in a window

The basic workflow is:

  1. Load the image from a file path\
  2. Check whether the image is loaded successfully\
  3. Display the image\
  4. Wait for user input and close the window

2. Implementation Effect​

Navigate to the OpenCV working directory:

cd ~/opencv

Run the image reading script:

python3 01.image_read.py
note

Select the image display window and press q to exit the program.

Image Display Result

3. Python Example Code​

import cv2

def read_image(file_path):
    image = cv2.imread(file_path)

    if image is None:
        print("Error: Unable to open image file.")
    else:
        cv2.imshow('Image Preview', image)
        cv2.waitKey(0)
        cv2.destroyAllWindows()

read_image('/home/jetson/opencv/images/hemihex_logo.png')

4. Code Explanation​

  • cv2.imread(file_path)
    Loads the image from disk. Returns None if the file cannot be read.

  • cv2.imshow()
    Opens a window and displays the image.

  • cv2.waitKey(0)
    Waits indefinitely for a key press.

  • cv2.destroyAllWindows()
    Closes all OpenCV windows.

Maintained by HemiHex for computer vision and OpenCV learning workflows.