Tensor Flow to encode LFW set

To learn how to encode a simple image and a GIF

Import needed for Tensorflow



In [1]:

    
import numpy as np
import tensorflow as tf

Import needed for Jupiter:



In [2]:

    
%matplotlib notebook
import matplotlib
import matplotlib.pyplot as plt

from IPython.display import Image



In [3]:

    
size = 10

tf.reset_default_graph()

all_faces = tf.Variable(0,validate_shape=False, dtype=tf.float32, name='all_faces')
saver = tf.train.Saver()
sess =  tf.Session()



In [4]:

    
with sess.as_default():
    tf.initialize_all_variables().run()
    for var in tf.all_variables():
        print (var.name, var.eval().shape)
    print all_faces.eval()









    



(u'all_faces:0', ())
0.0



In [5]:

    
with sess.as_default():
    ckpt = tf.train.get_checkpoint_state("./tmp/")
    if ckpt and ckpt.model_checkpoint_path:
        print ckpt.model_checkpoint_path
        saver.restore(sess, ckpt.model_checkpoint_path)
        print("Model restored.")
    else:
        print ("Model not restored.")









    



./tmp/model.ckpt
Model restored.



In [6]:

    
with sess.as_default():
    for var in tf.all_variables():
        print (var.name, var.eval().shape)
    print all_faces.eval()









    



(u'all_faces:0', (10, 250, 250))
[[[ 0.14536607  0.15289439  0.14419065 ...,  0.92481071  0.95753837
    0.95830441]
  [ 0.14536607  0.15289439  0.14419065 ...,  0.90830153  0.95753837
    0.95830441]
  [ 0.14536607  0.15289439  0.14419065 ...,  0.89179236  0.94102919
    0.94179523]
  ..., 
  [ 0.44253123  0.45005956  0.44135582 ...,  1.15593922  1.17215765
    1.17292368]
  [ 0.47554958  0.46656874  0.457865   ...,  1.15593922  1.17215765
    1.17292368]
  [ 0.47554958  0.46656874  0.47437418 ...,  1.15593922  1.17215765
    1.17292368]]

 [[ 0.73969638  0.74722475  0.75503016 ...,  1.18895757  1.205176
    1.20594203]
  [ 0.73969638  0.74722475  0.75503016 ...,  1.18895757  1.205176
    1.20594203]
  [ 0.73969638  0.74722475  0.75503016 ...,  1.1724484   1.18866682
    1.18943286]
  ..., 
  [ 0.3930037   0.35100451  0.24324571 ..., -2.11287761 -2.12967753
   -2.14542055]
  [ 0.37649453  0.11987605  0.21022736 ..., -2.2119329  -2.22873259
   -2.3105123 ]
  [ 0.35998535  0.10336687  0.19371818 ..., -2.410043   -2.45986104
   -2.55814981]]

 [[ 0.73969638  0.74722475  0.75503016 ...,  1.18895757  1.205176
    1.20594203]
  [ 0.73969638  0.74722475  0.75503016 ...,  1.18895757  1.205176
    1.20594203]
  [ 0.73969638  0.74722475  0.75503016 ...,  1.18895757  1.205176
    1.20594203]
  ..., 
  [-1.24140465 -1.25038552 -1.24258006 ...,  1.04037499  0.97404754
    0.85924935]
  [-1.2083863  -1.21736717 -1.20956171 ...,  1.07339334  1.04008424
    0.99132276]
  [-1.2083863  -1.21736717 -1.20956171 ...,  1.07339334  1.12263012
    1.07386863]]

 ..., 
 [[-1.58809733 -1.56405985 -1.50672686 ..., -0.90770781 -0.39621404
   -0.14781035]
  [-1.62111568 -1.5970782  -1.55625439 ..., -1.30392802 -1.00705349
   -0.79166818]
  [-1.65413404 -1.63009655 -1.58927274 ..., -1.66712987 -1.43629205
   -1.27043426]
  ..., 
  [-2.71072149 -2.86828494 -3.00906181 ..., -1.60109317 -1.66742063
   -1.56759942]
  [-2.64468479 -2.67017484 -2.76142406 ..., -1.6506207  -1.63440228
   -1.53458107]
  [-2.49610209 -2.53810143 -2.62935066 ..., -1.53505647 -1.56836557
   -1.48505354]]

 [[-1.50555146 -1.49802315 -1.45719934 ..., -0.34639582 -0.34668651
   -0.32941127]
  [-1.43951476 -1.48151398 -1.49021769 ..., -0.362905   -0.34668651
   -0.34592047]
  [-1.30744135 -1.41547728 -1.49021769 ..., -0.39592335 -0.34668651
   -0.34592047]
  ..., 
  [ 0.54158628  0.53260541  0.54041088 ...,  1.13943005  1.07310259
    1.02434111]
  [ 0.54158628  0.53260541  0.54041088 ...,  1.1064117   1.05659342
    0.97481358]
  [ 0.54158628  0.53260541  0.54041088 ...,  1.1064117   1.02357507
    0.94179523]]

 [[ 0.73969638  0.74722475  0.75503016 ...,  1.18895757  1.205176
    1.20594203]
  [ 0.73969638  0.74722475  0.75503016 ...,  1.18895757  1.205176
    1.20594203]
  [ 0.73969638  0.74722475  0.75503016 ...,  1.18895757  1.205176
    1.20594203]
  ..., 
  [-2.54562974 -2.58762884 -2.62935066 ..., -0.47846922 -0.06603053
   -0.0487553 ]
  [-2.59515715 -2.62064719 -2.66236901 ..., -0.77563441 -0.34668651
   -0.13130118]
  [-2.59515715 -2.62064719 -2.66236901 ..., -1.07279956 -0.56130582
   -0.32941127]]]

A function to save a picture



In [7]:

    
#need to be called within a session
def write_png(tensor, name):
    casted_to_uint8 = tf.cast(tensor, tf.uint8)
    converted_to_png = tf.image.encode_png(casted_to_uint8)
    f = open(name, "wb+")
    f.write(converted_to_png.eval())
    f.close()

Create a test pictures

Encode the input (a number)

This example convert the number to a binary representation



In [8]:

    
# Init size
with sess.as_default():
    a_face = tf.gather(all_faces,[0])
    print a_face.eval().shape
    # remove channel dimension and add index dimension
    pict_face = tf.expand_dims(tf.squeeze(a_face, squeeze_dims=[0]),2)
    print pict_face.eval().shape
    write_png(pict_face, 'a_face.png')









    



(1, 250, 250)
(250, 250, 1)



In [9]:

    
Image("a_face.png")









    Out[9]:

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