Image Resizing using OpenCV | Python (original) (raw)
Last Updated : 30 Oct, 2025
OpenCV provides the cv2.resize() function, which allows you to resize images efficiently. By selecting different interpolation methods, you can control the balance between image quality and resizing speed.
Syntax:
cv2.resize(src, dsize[, dst[, fx[, fy[, interpolation]]]])
**Parameters:
- **src: Source/input image.
- **dsize: Desired size (width, height). Order is width first, then height.
- **dst(Optional): Output image, rarely used explicitly.
- **fx(optional): Scale factor along the horizontal axis.
- **fy(optional): Scale factor along the vertical axis.
- **interpolation(optional): Interpolation method to use.
**Return Value: Returns a resized image as a NumPy array, which can be displayed, saved, or further processed.
**Note: Use either **dsize or **fx/fy for scaling, **dsize: when you know exact width & height and fx/fy: when you want to scale by a factor. Do not set both together (unless dsize=None)
Interpolation Methods
Interpolation is the method used to decide pixel colors when an image is resized. Below are some methods:
| Method | When to Use | Description |
|---|---|---|
| cv2.INTER_AREA | Shrinking | Minimizes distortion while downscaling. |
| cv2.INTER_LINEAR | General resizing | Balances speed and quality |
| cv2.INTER_CUBIC | Enlarging | Higher quality for upscaling |
| cv2.INTER_NEAREST | Fast resizing | Quick but lower quality |
Example: Resizing images using OpenCV
Python `
import cv2
import matplotlib.pyplot as plt
image = cv2.imread("grapes.jpg")
small = cv2.resize(image, None, fx=0.1, fy=0.1, interpolation=cv2.INTER_AREA)
large = cv2.resize(image, (1050, 1610), interpolation=cv2.INTER_CUBIC) medium = cv2.resize(image, (780, 540), interpolation=cv2.INTER_LINEAR)
titles = ["Original", "10% (INTER_AREA)", "1050x1610 (INTER_CUBIC)", "780x540 (INTER_LINEAR)"] images = [image, small, large, medium]
plt.figure(figsize=(10, 8))
for i in range(4):
plt.subplot(2, 2, i + 1)
plt.imshow(cv2.cvtColor(images[i], cv2.COLOR_BGR2RGB)) # Convert BGR → RGB
plt.title(titles[i])
plt.axis("off")
plt.tight_layout() plt.show()
`
**Output
Output representing different way to resize image
**Explanation:
- **cv2.imread(): Loads the image in BGR format.
- cv2.resize(): Resizes the image using either scale factors (fx, fy) or exact dimensions (dsize). INTER_AREA: Downscaling, INTER_CUBIC:** Upscaling (smooth results) and **INTER_LINEAR: General resizing
- **cv2.cvtColor(): Converts image from BGR to RGB for correct Matplotlib display.
- **plt.subplot(): Arranges multiple images in a 2×2 grid.
- **plt.title(): Adds a title for each image.
- **plt.axis("off"): Hides axis lines and labels.
- **plt.tight_layout(): Adjusts spacing between images.