Python Opencv Imresize

Opencv is an open-source computer vision library which consists of various image and video analysis functions. One of the most widely used functions in OpenCV is "imresize" which is used to resize the given image.

Installation

To use opencv in Python, you'll need to install it first. There are various methods to install opencv for Python, but here is the most common way via pip:

pip install opencv-python

Syntax

The function imresize takes two arguments: the input image and the desired output size. The output size can be specified in different formats, such as a tuple of (width, height) or a scaling factor as a single float value.

resized_image = cv2.resize(input_image, output_size[, interpolation])

The third argument interpolation is optional which specifies the method that should be used during resizing. The default interpolation method is cv2.INTER_LINEAR which uses linear interpolation.

Examples

Resize by scaling factor

Here is a code snippet that shows how to resize an image by a scaling factor of 0.5 using OpenCV.

import cv2

input_image = cv2.imread('input_image.jpg')
scale_percent = 0.5

# calculate the new dimensions
width = int(input_image.shape[1] * scale_percent)
height = int(input_image.shape[0] * scale_percent)
output_size = (width, height)

# resize image
resized_image = cv2.resize(input_image, output_size)

cv2.imshow('Input Image', input_image)
cv2.imshow('Resized Image', resized_image)
cv2.waitKey(0)
cv2.destroyAllWindows()

Resize by width and height

Here is a code snippet that shows how to resize an image to a specific width and height using OpenCV.

import cv2

input_image = cv2.imread('input_image.jpg')
output_size = (500, 400)  # (width, height)

# resize image
resized_image = cv2.resize(input_image, output_size)

cv2.imshow('Input Image', input_image)
cv2.imshow('Resized Image', resized_image)
cv2.waitKey(0)
cv2.destroyAllWindows()

Resize with interpolation

Here is a code snippet that shows how to resize an image with different interpolation methods using OpenCV.

import cv2

input_image = cv2.imread('input_image.jpg')
output_size = (500, 400)  # (width, height)

# resize image with different interpolation methods
interpolation_methods = [cv2.INTER_NEAREST, cv2.INTER_LINEAR, cv2.INTER_AREA,
                         cv2.INTER_CUBIC, cv2.INTER_LANCZOS4]
for method in interpolation_methods:
    resized_image = cv2.resize(input_image, output_size, interpolation=method)
    cv2.imshow(f'Resized Image ({method})', resized_image)

cv2.imshow('Input Image', input_image)
cv2.waitKey(0)
cv2.destroyAllWindows()

In the above code, we have used various interpolation methods such as cv2.INTER_NEAREST, cv2.INTER_LINEAR, cv2.INTER_AREA, cv2.INTER_CUBIC, and cv2.INTER_LANCZOS4 to resize the input image.