text: from __future__ import division
  
  import torch
  import cv2
  
  try:
      from util import count_parameters as count
      from util import convert2cpu as cpu
  except ImportError:
      from yolo.util import count_parameters as count
      from yolo.util import convert2cpu as cpu
  from PIL import Image, ImageDraw
  
  
  def letterbox_image(img, img_size=(1088, 608), color=(127.5, 127.5, 127.5)):  
      # resize a rectangular image to a padded rectangular 
      height=img_size[1]
      width=img_size[0]
      shape = img.shape[:2]  # shape = [height, width]
      ratio = min(float(height)/shape[0], float(width)/shape[1])
      new_shape = (round(shape[1] * ratio), round(shape[0] * ratio)) # new_shape = [width, height]
      dw = (width - new_shape[0]) / 2  # width padding
      dh = (height - new_shape[1]) / 2  # height padding
      top, bottom = round(dh - 0.1), round(dh + 0.1)
      left, right = round(dw - 0.1), round(dw + 0.1)
      img = cv2.resize(img, new_shape, interpolation=cv2.INTER_AREA)  # resized, no border
      img = cv2.copyMakeBorder(img, top, bottom, left, right, cv2.BORDER_CONSTANT, value=color)  # padded rectangular
      return img
  
  
  def prep_image(img, img_size=(1088, 608)):
      """
      Prepare image for inputting to the neural network.
  
      Returns a Variable
      """
  
      orig_im = cv2.imread(img)
      dim = orig_im.shape[1], orig_im.shape[0]
      img = (letterbox_image(orig_im, img_size))
      img_ = img[:, :, ::-1].transpose((2, 0, 1)).copy()
      img_ = torch.from_numpy(img_).float().div(255.0).unsqueeze(0)
      return img_, orig_im, dim
  
  
  def prep_frame(img, img_size=(1088, 608)):
      """
      Prepare image for inputting to the neural network.
  
      Returns a Variable
      """
  
      orig_im = img
      dim = orig_im.shape[1], orig_im.shape[0]
      img = (letterbox_image(orig_im, img_size))
      img_ = img[:, :, ::-1].transpose((2, 0, 1)).copy()
      img_ = torch.from_numpy(img_).float().div(255.0).unsqueeze(0)
      return img_, orig_im, dim
  
  