Revision history [back]

For future reference: Fixed the first part of the question with this function:

import cv2
import numpy as np

def resizeAndPad(img, size, padColor=0):

    h, w = img.shape[:2]
    sh, sw = size

    # interpolation method
    if h > sh or w > sw: # shrinking image
    interp = cv2.INTER_AREA
    else: # stretching image
    interp = cv2.INTER_CUBIC

    # aspect ratio of image
    aspect = w/h  # if on Python 2, you might need to cast as a float: float(w)/h

    # compute scaling and pad sizing
    if aspect > 1: # horizontal image
    new_w = sw
    new_h = np.round(new_w/aspect).astype(int)
    pad_vert = (sh-new_h)/2
    pad_top, pad_bot = np.floor(pad_vert).astype(int), np.ceil(pad_vert).astype(int)
    pad_left, pad_right = 0, 0
    elif aspect < 1: # vertical image
    new_h = sh
    new_w = np.round(new_h*aspect).astype(int)
    pad_horz = (sw-new_w)/2
    pad_left, pad_right = np.floor(pad_horz).astype(int), np.ceil(pad_horz).astype(int)
    pad_top, pad_bot = 0, 0
    else: # square image
    new_h, new_w = sh, sw
    pad_left, pad_right, pad_top, pad_bot = 0, 0, 0, 0

    # set pad color
    if len(img.shape) is 3 and not isinstance(padColor, (list, tuple, np.ndarray)): # color image but only one color provided
    padColor = [padColor]*3

    # scale and pad
    scaled_img = cv2.resize(img, (new_w, new_h), interpolation=interp)
    scaled_img = cv2.copyMakeBorder(scaled_img, pad_top, pad_bot, pad_left, pad_right, borderType=cv2.BORDER_CONSTANT, value=padColor)

    return scaled_img

v_img = cv2.imread('v.jpg') # vertical image
scaled_v_img = resizeAndPad(v_img, (200,200), 127)

h_img = cv2.imread('h.jpg') # horizontal image
scaled_h_img = resizeAndPad(h_img, (200,200), 127)

sq_img = cv2.imread('sq.jpg') # square image
scaled_sq_img = resizeAndPad(sq_img, (200,200), 127)

Source

Don't know if you can make the output image a fixed size even after manually resizing the window though.

For future reference: reference:

Fixed the first part of the question with this function:

import cv2
import numpy as np

def resizeAndPad(img, size, padColor=0):

    h, w = img.shape[:2]
    sh, sw = size

    # interpolation method
    if h > sh or w > sw: # shrinking image
    interp = cv2.INTER_AREA
    else: # stretching image
    interp = cv2.INTER_CUBIC

    # aspect ratio of image
    aspect = w/h  # if on Python 2, you might need to cast as a float: float(w)/h

    # compute scaling and pad sizing
    if aspect > 1: # horizontal image
    new_w = sw
    new_h = np.round(new_w/aspect).astype(int)
    pad_vert = (sh-new_h)/2
    pad_top, pad_bot = np.floor(pad_vert).astype(int), np.ceil(pad_vert).astype(int)
    pad_left, pad_right = 0, 0
    elif aspect < 1: # vertical image
    new_h = sh
    new_w = np.round(new_h*aspect).astype(int)
    pad_horz = (sw-new_w)/2
    pad_left, pad_right = np.floor(pad_horz).astype(int), np.ceil(pad_horz).astype(int)
    pad_top, pad_bot = 0, 0
    else: # square image
    new_h, new_w = sh, sw
    pad_left, pad_right, pad_top, pad_bot = 0, 0, 0, 0

    # set pad color
    if len(img.shape) is 3 and not isinstance(padColor, (list, tuple, np.ndarray)): # color image but only one color provided
    padColor = [padColor]*3

    # scale and pad
    scaled_img = cv2.resize(img, (new_w, new_h), interpolation=interp)
    scaled_img = cv2.copyMakeBorder(scaled_img, pad_top, pad_bot, pad_left, pad_right, borderType=cv2.BORDER_CONSTANT, value=padColor)

    return scaled_img

v_img = cv2.imread('v.jpg') # vertical image
scaled_v_img = resizeAndPad(v_img, (200,200), 127)

h_img = cv2.imread('h.jpg') # horizontal image
scaled_h_img = resizeAndPad(h_img, (200,200), 127)

sq_img = cv2.imread('sq.jpg') # square image
scaled_sq_img = resizeAndPad(sq_img, (200,200), 127)

Source

Don't know if you can make the output image a fixed size even after manually resizing the window though.