OpenCV & Python: Resize Images Too Large to Display

Introduction
Step-by-Step Guide
Code Example
Additional Notes
Summary
Conclusion
References

Introduction

This guide demonstrates how to resize images for display using the OpenCV library in Python. We'll cover resizing images to fixed dimensions and creating resizable display windows.

Step-by-Step Guide

To resize an image for display using OpenCV in Python:

import cv2

img = cv2.imread('large_image.jpg')

resized_img = cv2.resize(img, (800, 600)) 

cv2.imshow('Resized Image', resized_img)
cv2.waitKey(0)
cv2.destroyAllWindows()

This code snippet reads an image named 'large_image.jpg' and resizes it to a width of 800 pixels and a height of 600 pixels. The resized image is then displayed in a window titled 'Resized Image'.

To create a resizable window for displaying images:

cv2.namedWindow('Image', cv2.WINDOW_NORMAL)
cv2.imshow('Image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

This code creates a window titled 'Image' that can be resized by the user. The image will scale to fit the window size.

Code Example

This Python code uses OpenCV to load an image named 'large_image.jpg', resize it to 800x600 pixels, and display both the resized and original images in separate windows. The resized image is shown in a fixed-size window, while the original image is displayed in a resizable window. The code waits for a key press before closing the windows.

import cv2

# Load the image
img = cv2.imread('large_image.jpg')

# Resize the image to a specific width and height
resized_img = cv2.resize(img, (800, 600))

# Display the resized image in a window
cv2.imshow('Resized Image', resized_img)
cv2.waitKey(0)
cv2.destroyAllWindows()

# Display the image in a resizable window
cv2.namedWindow('Image', cv2.WINDOW_NORMAL)
cv2.imshow('Image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

Explanation:

Import OpenCV: import cv2 imports the OpenCV library.
Load the image: img = cv2.imread('large_image.jpg') loads the image named 'large_image.jpg' into the img variable.
Resize the image: resized_img = cv2.resize(img, (800, 600)) resizes the image to a width of 800 pixels and a height of 600 pixels.
Display the resized image:
- cv2.imshow('Resized Image', resized_img) displays the resized image in a window titled 'Resized Image'.
- cv2.waitKey(0) waits for a key press.
- cv2.destroyAllWindows() closes all OpenCV windows.
Create a resizable window:
- cv2.namedWindow('Image', cv2.WINDOW_NORMAL) creates a resizable window titled 'Image'.
- cv2.imshow('Image', img) displays the original image in the resizable window.
- cv2.waitKey(0) and cv2.destroyAllWindows() work the same way as before.

Note:

Replace 'large_image.jpg' with the actual name of your image file.
The cv2.waitKey(0) function waits indefinitely for a key press. You can replace 0 with a specific number of milliseconds to wait for a limited time.
When you resize the window, the image will automatically scale to fit the new window size.

Additional Notes

Resizing Images:

Aspect Ratio: When resizing, it's important to maintain the aspect ratio of the original image to avoid distortion. You can calculate the appropriate new dimensions based on the desired width or height, or use the fx and fy parameters in cv2.resize() to scale by a factor.
Interpolation Methods: OpenCV provides different interpolation methods for resizing, each with its own trade-offs in terms of speed and quality. Common methods include cv2.INTER_AREA (good for shrinking), cv2.INTER_CUBIC (good for enlarging), and cv2.INTER_LINEAR (a balance between the two).
Resizing for Processing: Resizing images can be useful for tasks beyond display, such as reducing computational cost for image processing algorithms.

Displaying Images:

Window Size: If the image is too large for the screen, the window might extend beyond the visible area. Using cv2.WINDOW_NORMAL allows resizing the window, but you can also use cv2.resizeWindow() to set a specific window size programmatically.
Alternative Libraries: While OpenCV is powerful, other libraries like Matplotlib (plt.imshow()) offer more convenient options for displaying images, especially when working with plots and figures.
Image Formats: OpenCV supports various image formats. Ensure the image file you're loading is in a compatible format (e.g., JPG, PNG).

General Tips:

Error Handling: Incorporate error handling (e.g., using try-except blocks) to gracefully handle cases where the image file is not found or cannot be loaded.
Documentation: Refer to the official OpenCV documentation for detailed information on functions and parameters: https://docs.opencv.org/
Experimentation: Don't hesitate to experiment with different resizing options, interpolation methods, and window settings to find what works best for your specific needs.

Summary

Feature	Description	Code
Resize Image	Resizes an image to a specific width and height.	`cv2.resize(img, (800, 600))`
Display Image	Displays an image in a window.	`cv2.imshow('Resized Image', resized_img)`
Create Resizable Window	Creates a window that can be resized by the user.	`cv2.namedWindow('Image', cv2.WINDOW_NORMAL)`

Conclusion

This guide explained how to resize images for display using OpenCV in Python, covering resizing to fixed dimensions and creating resizable display windows. You learned how to load an image, resize it using cv2.resize(), and display it in a window with cv2.imshow(). You also saw how to create a resizable window using cv2.namedWindow(). Remember to consult the OpenCV documentation for more advanced resizing options and interpolation methods. By mastering these techniques, you can effectively manage image display and optimize your computer vision applications.

References

How to deal with large images - Python - OpenCV | Hi, for example, I have a very large image that weighs 3 GB opened on RAM I want to do some operations that create a copy of the image like a color conversion and threshold So I have this… import numpy as np import cv2 # Load a color image in BGR OriginalImage = cv2.imread('LargeImage.png') # 3GB Size # Convert BGR to HSV HSVCopy = cv2.cvtColor(OriginalImage , cv2.COLOR_BGR2HSV) # + 3GB Size #Image Threshold ret,TRCopy= cv2.threshold( cv2.split(HSVCopy )[1],127,255,cv2.THRESH_BINARY)...
python - image is too big for OpenCV imshow window, how do I ... | Nov 23, 2022 ... Before imshow , call namedWindow() with the WINDOW_NORMAL flag. That makes it resizable and scales the image to the size of the window.
Tools for stitching large datasets - Usage & Issues - Image.sc Forum | Hi all, We’re currently facing our limits with stitching large 3D datasets (~1TB) and after some investigation, I was curious to hear about what tools other members of the forum use for this. I started making a list of what I tested and got so far, any input is welcome ! 🙂 Grid/Collection stitching Pros : In Fiji Experience with it Works very nicely for smaller datasets Cons : Exporting as H5/XML is very slow (4 days and not even one channel was saved so no results to show…...
python - OpenCV imshow window too large - blurred image - Stack ... | Jan 11, 2019 ... The image window clearly is too large after the resize. How can I easily resize the window to the correct size such that the displayed image doesn't get ...
read and display image of large size - OpenCV Q&A Forum | Mar 19, 2019 ... I have images of size 1.1 - 1.5 G that need to be loaded and processed, then displayed. When I load the image, I get the following error ...
python - How can i modify cv2.selectROI image display to normal ... | Dec 24, 2018 ... cv2.selectROI display my image but it's too big for the screen and i can't navigate on the image because it's automatically starting the crop procedure.
window too big, can't resize or maximize - Ask Ubuntu | Oct 12, 2011 ... When a window is bigger than the resolution of the monitor do the following: Press and HOLD ALT (On Ubuntu 18.04+ Hold SUPER ) and then ...
Docker image size is becoming huge after DOCKER COMMIT ... | I’m started using a docker with basic docker image Linux - x86-64 ( latest ). I have pulled this image with the command docker pull ubuntu I run this docker using the command docker run -it ea4c82dcd15a /bin/bash where “ea4c82dcd15a” is the IMAGE ID for the image. This allows me to run the image successfully and work with it. But after doing some work in the container and storing some of my small work data into the container, committing the docker makes the docker image size too huge as...
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