{"id":12964,"date":"2023-05-09T10:00:00","date_gmt":"2023-05-09T01:00:00","guid":{"rendered":"https:\/\/www.gigas-jp.com\/appnews\/?p=12964"},"modified":"2023-05-08T20:51:35","modified_gmt":"2023-05-08T11:51:35","slug":"rotating-and-cropping-the-images-in-python-using-opencv","status":"publish","type":"post","link":"https:\/\/www.gigas-jp.com\/appnews\/archives\/12964","title":{"rendered":"Rotating and cropping the images in Python using opencv"},"content":{"rendered":"\n

Today, I would like to share how to rotate and crop the images in Python using opencv.<\/p>\n\n\n\n

Rotating and cropping are common image processing techniques used to manipulate digital images. Python OpenCV is a powerful library for image processing that provides numerous tools for image manipulation. In this tutorial, we will learn how to rotate and crop images using Python OpenCV.<\/p>\n\n\n\n

1. Installing OpenCV<\/p>\n\n\n\n

First, we need to install OpenCV in our system. If you haven’t installed OpenCV yet, you can install it using pip:<\/p>\n\n\n\n

pip install opencv-python<\/code><\/p>\n\n\n\n

2. Loading an Image<\/p>\n\n\n\n

After installing OpenCV, we can load an image using the imread() function. The imread() function takes the image file path as an argument and returns an array representing the image.<\/p>\n\n\n\n

import cv2<\/code><\/p>\n\n\n\n

# Load image<\/code><\/p>\n\n\n\n

image = cv2.imread('path\/to\/image.jpg')<\/code><\/p>\n\n\n\n

3. Rotating an Image<\/p>\n\n\n\n

Rotating an image involves changing the orientation of the image. We can use the cv2.rotate() function to rotate an image. The cv2.rotate() function takes three arguments: the image, the rotation type, and the angle of rotation.<\/p>\n\n\n\n

# Rotate image<\/code><\/p>\n\n\n\n

rotated_image = cv2.rotate(image, cv2.cv2.ROTATE_90_CLOCKWISE)<\/code><\/p>\n\n\n\n

In the above example, we have rotated the image 90 degrees clockwise.<\/p>\n\n\n\n

4. Cropping an Image<\/p>\n\n\n\n

Cropping an image involves selecting a portion of the image and discarding the rest. We can use array slicing to crop an image. The array slicing notation is [start_row:end_row, start_column:end_column].<\/p>\n\n\n\n

# Crop image<\/p>\n\n\n\n

cropped_image = image[start_row:end_row, start_column:end_column]<\/code><\/p>\n\n\n\n

In the above example, we have cropped the image from start_row to end_row and start_column to end_column.<\/p>\n\n\n\n

5. Displaying Images<\/p>\n\n\n\n

After rotating or cropping an image, we can display the images using the cv2.imshow() function. The cv2.imshow() function takes two arguments: the name of the window and the image.<\/p>\n\n\n\n

# Display images<\/p>\n\n\n\n

cv2.imshow('Original Image', image)<\/code><\/p>\n\n\n\n

cv2.imshow('Rotated Image', rotated_image)<\/code><\/p>\n\n\n\n

cv2.imshow('Cropped Image', cropped_image)<\/code><\/p>\n\n\n\n

# Wait for a key press and close all windows<\/code><\/p>\n\n\n\n

cv2.waitKey(0)<\/code><\/p>\n\n\n\n

cv2.destroyAllWindows()<\/code><\/p>\n\n\n\n

6. Saving an Image<\/p>\n\n\n\n

We can save the rotated or cropped image using the cv2.imwrite() function. The cv2.imwrite() function takes two arguments: the name of the file and the image.<\/p>\n\n\n\n

# Save image<\/p>\n\n\n\n

cv2.imwrite('path\/to\/saved\/image.jpg', rotated_image)<\/code><\/p>\n\n\n\n

In the above example, we have saved the rotated image to a file named ‘saved_image.jpg’ in the specified path.<\/p>\n\n\n\n

Conclusion<\/p>\n\n\n\n

In this tutorial, we have learned how to rotate and crop images using Python OpenCV. We have also learned how to display and save images. These are just a few of the many image processing techniques that can be performed using OpenCV. With OpenCV, we can perform a wide range of image processing tasks, from simple operations like cropping and rotating to more complex operations like edge detection and object recognition.<\/p>\n\n\n\n

This is all for now. Hope you enjoy that.<\/p>\n\n\n\n

By Asahi<\/p>\n

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