new_contents: import os
  import cv2
  import tensorflow as tf
  import numpy as np
  import pgnet
  
  image_path = "/data/PASCAL_2012_cropped/2010_003078.jpg"
  image = cv2.imread(image_path)
  images_ = tf.placeholder(tf.float32, [None, image.shape[0], image.shape[1], 3])
  model = pgnet.get(images_)
  
  #kernels = tf.get_variable("kernels", [3, 3, 3, 3],
  #                         initializer=tf.random_normal_initializer())
  init = tf.initialize_all_variables()
  
  with tf.Session() as sess:
      sess.run(init)
      out = sess.run(
          model,
          feed_dict={
              images_: tf.reshape(
                  tf.cast(image, tf.float32).eval(),
                  [-1, image.shape[0], image.shape[1], image.shape[2]]).eval()
          })
  
      print(model)
      print(out)
  
      #cv2.imshow("impadded", cv2.normalize(padded[0], padded[0], alpha=0, beta=2**24, norm_type=cv2.NORM_MINMAX))
      cv2.imshow("imp", tf.cast(out[0], tf.uint8).eval())
  
      #always rememer to cast to tf.uint8 if you want to display the result with opencv
      #cv2.imshow("original", tf.cast(reshaped_input[0], tf.uint8).eval())
  
      cv2.waitKey(0)
  
subject: Add test.py