text: '''
  I/O:
      Input: image to be inferenced
      Output: depth image
      Relation: out = model(in)
      
      path -> readimg -> image -> transform -> tensor
      tensor -> model
      model: get model from get_model() in train.py, load_param from .pth file
      model -> output tensor -> transpose to H x W x C -> imshow & save
  '''
  import argparse
  import cv2
  import matplotlib.pyplot as plt
  import torchvision.transforms as transforms
  import numpy as np
  from utils import load_param
  from model.model import get_model
  