Optimal way to resize an image with OpenCV Python

Question

I want to resize an image based on a percentage and keep it as close to the original with minimal noise and distortion. The resize could be up or down as in I could scale to 5% the size of the original image or 500% (or any other value these are given as example)

This is what i tried and i'd need absolute minimal changes in the resized image since i'll be using it in comparison with other images

def resizing(main,percentage): main = cv2.imread(main) height = main.shape[ 0] * percentage width = crop.shape[ 1] * percentage dim = (width,height) final_im = cv2.resize(main, dim, interpolation = cv2.INTER_AREA) cv2.imwrite("C:\\Users\\me\\nature.jpg", final_im)

check opencv docs 'docs.opencv.org/3.4/d4/d1f/tutorial_pyramids.html' — kavko
– kavko, Commented Jul 3, 2019 at 4:00

Chris · Accepted Answer · 2019-07-02 18:18:17Z

You can use this syntax of cv2.resize:

 cv2.resize(image,None,fx=int or float,fy=int or float)

fx depends on width

fy depends on height

You can put the second argument None or (0,0)

Example:

 img = cv2.resize(oriimg,None,fx=0.5,fy=0.5)

Note:

0.5 means 50% of image to be scaling

nathancy · Accepted Answer · 2019-07-02 20:01:09Z

I think you're trying to resize and maintain aspect ratio. Here's a function to upscale or downscale an image based on percentage

Original image example

Resized image to 0.5 (50%)

Resized image to 1.3 (130%)

import cv2 # Resizes a image and maintains aspect ratio def maintain_aspect_ratio_resize(image, width=None, height=None, inter=cv2.INTER_AREA): # Grab the image size and initialize dimensions dim = None (h, w) = image.shape[:2] # Return original image if no need to resize if width is None and height is None: return image # We are resizing height if width is none if width is None: # Calculate the ratio of the height and construct the dimensions r = height / float(h) dim = (int(w * r), height) # We are resizing width if height is none else: # Calculate the ratio of the width and construct the dimensions r = width / float(w) dim = (width, int(h * r)) # Return the resized image return cv2.resize(image, dim, interpolation=inter) if __name__ == '__main__': image = cv2.imread('1.png') cv2.imshow('image', image) resize_ratio = 1.2 resized = maintain_aspect_ratio_resize(image, width=int(image.shape[1] * resize_ratio)) cv2.imshow('resized', resized) cv2.imwrite('resized.png', resized) cv2.waitKey(0)

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