Image Resizing
Scaling operations increase or reduce the size of an image.
- The
cv2.resize()function is used to resize an python image in OpenCV. It takes the following arguments:
cv2.resize(src, dsize,interpolation)
Here,
src :The image to be resized.
dsize :The desired width and height of the resized image.
interpolation:The interpolation method to be used.
- When the python image is resized, the interpolation method defines how the new pixels are computed. There are several interpolation techniques, each of which has its own quality vs. speed trade-offs.
- It is important to note that resizing an image can reduce its quality. This is because the new pixels are calculated by interpolating between the existing pixels, and this can introduce some blurring.
# Import the necessary libraries
import cv2
import numpy as np
import matplotlib.pyplot as plt
# Load the image
image = cv2.imread('Ganeshji.webp')
# Convert BGR image to RGB
image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
# Define the scale factor
# Increase the size by 3 times
scale_factor_1 = 3.0
# Decrease the size by 3 times
scale_factor_2 = 1/3.0
# Get the original image dimensions
height, width = image_rgb.shape[:2]
# Calculate the new image dimensions
new_height = int(height * scale_factor_1)
new_width = int(width * scale_factor_1)
# Resize the image
zoomed_image = cv2.resize(src =image_rgb,
dsize=(new_width, new_height),
interpolation=cv2.INTER_CUBIC)
# Calculate the new image dimensions
new_height1 = int(height * scale_factor_2)
new_width1 = int(width * scale_factor_2)
# Scaled image
scaled_image = cv2.resize(src= image_rgb,
dsize =(new_width1, new_height1),
interpolation=cv2.INTER_AREA)
# Create subplots
fig, axs = plt.subplots(1, 3, figsize=(10, 4))
# Plot the original image
axs[0].imshow(image_rgb)
axs[0].set_title('Original Image Shape:'+str(image_rgb.shape))
# Plot the Zoomed Image
axs[1].imshow(zoomed_image)
axs[1].set_title('Zoomed Image Shape:'+str(zoomed_image.shape))
# Plot the Scaled Image
axs[2].imshow(scaled_image)
axs[2].set_title('Scaled Image Shape:'+str(scaled_image.shape))
# Remove ticks from the subplots
for ax in axs:
ax.set_xticks([])
ax.set_yticks([])
# Display the subplots
plt.tight_layout()
plt.show()
Output: