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import cv2
cv2
import numpy as np
np
 
def resizeAndPad(img, size, padColor=0):
  h, w = img.shape[:2]
sh, sw = size
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
scaled_img
 
v_img = cv2.imread('v.jpg') # vertical image
image scaled_v_img = resizeAndPad(v_img, (200,200), 127)
 h_img = cv2.imread('h.jpg') # horizontal image
image scaled_h_img = resizeAndPad(h_img, (200,200), 127)
 sq_img = cv2.imread('sq.jpg') # square image
image scaled_sq_img = resizeAndPad(sq_img, (200,200), 127)

import cv2
import numpy as np
 
np
def resizeAndPad(img, size, padColor=0):
h, w = img.shape[:2]
sh, sw = size
 
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
 
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)
 127)

import cv2
import numpy as np
np
 
def resizeAndPad(img, size, padColor=0):
h, w = img.shape[:2]
sh, sw = size
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)