OpenCV 3 Computer Vision with Python Cookbook

How to do it...

For this recipe, we need the following steps to be executed:

1. Load an image and print its original size:

img = cv2.imread('../data/Lena.png')print('original image shape:', img.shape)

2. OpenCV offers several ways of using the cv2.resize function. We can set the target size (width, height) in pixels as the second parameter:

width, height = 128, 256resized_img = cv2.resize(img, (width, height))print('resized to 128x256 image shape:', resized_img.shape)

3. Resize by setting multipliers of the image's original width and height:

w_mult, h_mult = 0.25, 0.5resized_img = cv2.resize(img, (0, 0), resized_img, w_mult, h_mult)print('image shape:', resized_img.shape)

4. Resize using nearest-neighbor interpolation instead of the default one: ...