new_contents: #!/usr/bin/env python3
  # -*- coding: utf-8 -*-
  
  import numpy as np
  import tensorflow as tf
  import cv2
  img = cv2.imread('/home/liu/data/x.bmp')
  print(img.shape)
  (height, width, channel) = img.shape
  input = tf.to_float(tf.reshape(img, [1, height, width, channel]))
  filter = tf.ones(shape=(3, 3, 3, 3), dtype=tf.float32)
  filter = filter* 0.1
  c = tf.nn.conv2d(input, filter, [1, 3, 3, 1], "SAME")
  sess = tf.Session()
  conv =  sess.run(c)
  print(conv.shape)
  p = tf.nn.avg_pool(c, ksize=[1,2,2,1], strides=[1,1,1,1], padding = "SAME")
  pool = sess.run(p)
  print(pool.shape)
  
  newimg = np.reshape(pool, pool.shape[1:])
  cv2.imwrite("y.bmp", newimg)
  
subject: add convolution on real image