SciPy provides basic image manipulation functions. These include functions to read images from disk into numpy arrays, to write numpy arrays to disk as images, and to resize images.
In the following code, only one image is used. It is tinted, resized, and saved. Both original and resulting images are shown below:
import numpy as np //scipy is numpy-dependent from scipy.misc import imread, imsave, imresize //image resizing functions # Read an JPEG image into a numpy array img = imread('assets/cat.jpg') print img.dtype, img.shape # Prints "uint8 (400, 248, 3)" # We can tint the image by scaling each of the color channels # by a different scalar constant. The image has shape (400, 248, 3); # we multiply it by the array [1, 0.95, 0.9] of shape (3,); # numpy broadcasting means that this leaves the red channel unchanged, # and multiplies the green and blue channels by 0.95 and 0.9 # respectively. img_tinted = img * [1, 0.95, 0.9] # Resize the tinted image to be 300 by 300 pixels. img_tinted = imresize(img_tinted, (300, 300)) # Write the tinted image back to disk imsave('assets/cat_tinted.jpg', img_tinted)