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Python PIL | Image.resize() method

Last Updated : 09 Aug, 2024
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PIL is the Python Imaging Library which provides the python interpreter with image editing capabilities. The Image module provides a class with the same name which is used to represent a PIL image. The module also provides a number of factory functions, including functions to load images from files, and to create new images.
Image.resize() Returns a resized copy of this image.
 

Syntax: Image.resize(size, resample=0) 
Parameters
size – The requested size in pixels, as a 2-tuple: (width, height). 
resample – An optional resampling filter. This can be one of PIL.Image.NEAREST (use nearest neighbour), PIL.Image.BILINEAR (linear interpolation), PIL.Image.BICUBIC (cubic spline interpolation), or PIL.Image.LANCZOS (a high-quality downsampling filter). If omitted, or if the image has mode “1” or “P”, it is set PIL.Image.NEAREST. Otherwise, the default filter is Resampling.BICUBIC. 
Returns type: An Image object.

Source
 


Image Used: 
 


 

Python3
 
# Importing Image class from PIL module 
from PIL import Image 

# Opens a image in RGB mode 
im = Image.open(r"C:\Users\System-Pc\Desktop\ybear.jpg") 

# Size of the image in pixels (size of original image) 
# (This is not mandatory) 
width, height = im.size 

# Setting the points for cropped image 
left = 4
top = height / 5
right = 154
bottom = 3 * height / 5

# Cropped image of above dimension 
# (It will not change original image) 
im1 = im.crop((left, top, right, bottom))
newsize = (300, 300)
im1 = im1.resize(newsize)
# Shows the image in image viewer 
im1.show() 

Output: 
 


Another example:Here we use the different newsize value.
 

Python3
# Importing Image class from PIL module 
from PIL import Image 

# Opens a image in RGB mode 
im = Image.open(r"C:\Users\System-Pc\Desktop\ybear.jpg") 

# Size of the image in pixels (size of original image) 
# (This is not mandatory) 
width, height = im.size 

# Setting the points for cropped image 
left = 6
top = height / 4
right = 174
bottom = 3 * height / 4

# Cropped image of above dimension 
# (It will not change original image) 
im1 = im.crop((left, top, right, bottom))
newsize = (200, 200)
im1 = im1.resize(newsize)
# Shows the image in image viewer 
im1.show() 

Output: 
 




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