new_contents: #!/usr/bin/env python3
  # -*- coding: utf-8 -*-
  import cv2
  import numpy as np
  import tensorflow as tf
  
  camera = cv2.VideoCapture(0)
  sess = tf.Session()
  while True:
      ret, frame = camera.read()
      #frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
      (height, width, channel) = frame.shape
      input = tf.to_float(tf.reshape(frame, [1, height, width, channel]))
      filter = tf.ones(shape=(3, 3, 3, 3), dtype=tf.float32)
      filter = filter* 0.0001
      conv_op = tf.nn.conv2d(input, filter, [1, 3, 3, 1], "SAME")
  
      # compute avg pool in a 2*2 matrix
      pool_op = tf.nn.avg_pool(conv_op, ksize=[1,2,2,1], strides=[1,1,1,1], padding = "SAME")
      pool = sess.run(pool_op)
      pooled= np.reshape(pool, pool.shape[1:])
      cv2.imshow('hello', pooled)
      if cv2.waitKey(1) == ord('q'):
          break
  
  camera.release()
  
subject: add a convolution and pool image read from camera