In [1]:

    

import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
from PIL import Image
%matplotlib inline


    

In [37]:

    

X = tf.placeholder(dtype=tf.float32, shape=[None, 784])
Y = tf.placeholder(dtype=tf.float32, shape=[None, 10])


    

In [38]:

    

W1 = tf.Variable(tf.random_normal(shape=[784, 256], stddev=0.01), name="w1val")
L1 = tf.nn.relu(tf.matmul(X, W1))


    

In [39]:

    

W2 = tf.Variable(tf.random_normal(shape=[256, 256], stddev=0.01), name="w2val")
L2 = tf.nn.relu(tf.matmul(L1, W2))


    

In [40]:

    

W3 = tf.Variable(tf.random_normal([256, 10], stddev=0.01), name="w3val")
model = tf.matmul(L2, W3)


    

In [41]:

    

# param_list = [W1, W2, W3]
saver = tf.train.Saver({"w1val":W1, "w2val":W2, "w3val":W3})


    

In [47]:

    

im = Image.open("./temp.png")


    

In [48]:

    

im


    

    
Out[48]:

In [49]:

    

img2 = im.resize((28,28))
b = img2.tobytes("raw","A")
ll = [i/255 for i in b ]


    

In [50]:

    

len(ll)


    

    
Out[50]:





784

In [51]:

    

ll = np.array(ll)
ll.shape


    

    
Out[51]:





(784,)

In [53]:

    

with tf.Session() as sess:
#     sess.run(tf.global_variables_initializer())  #변수를 초기화 해서 세팅이되면 파일에서 restore시 에러발생함
    saver.restore(sess, "./chkp_save2/mnist")
    predict = sess.run([model], feed_dict={X:ll})
    print(predict)
    predict = np.array(predict)
    print("shape:", predict.shape)
    print("result : ",np.argmax(predict[0], axis=1))


    

    




INFO:tensorflow:Restoring parameters from ./chkp_save2/mnist
[array([[-5.16816425, -6.6451149 , -4.69532156, -8.01078415, -0.78692555,
         6.74659967, -1.33783627, -5.33159351, -3.24365306, -2.43115902]], dtype=float32)]
shape: (1, 1, 10)
result :  [5]

In [54]:

    

img2


    

    
Out[54]:

In [55]:

    

im


    

    
Out[55]:

In [57]:

    

im.width


    

    
Out[57]:





250

In [58]:

    

im.height


    

    
Out[58]:





250

In [59]:

    

newImg = Image.frombytes(data=im.tobytes('raw','RGBA'),size=(250,250), mode='RGBA')


    

In [60]:

    

newImg


    

    
Out[60]:

In [62]:

    

help(im.tostring)


    

    




Help on method tostring in module PIL.Image:

tostring(*args, **kw) method of PIL.PngImagePlugin.PngImageFile instance

In [72]:

    

with open('./temp.png','rb') as f:
    str = f.read()
#     print(str)
    li = [i for i in str]
    print(len(li))


    

    




3279

In [80]:

    

250 * 250 * 4


    

    
Out[80]:





250000

In [74]:

    

data=im.tobytes('raw','RGBA')


    

In [77]:

    

len([i for i in data])


    

    
Out[77]:





250000

In [78]:

    

len(data)


    

    
Out[78]:





250000

In [91]:

    

np.array([i for i in data])[:10]


    

    
Out[91]:





array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0])

In [102]:

    

hex_list = [hex(i) for i in data]


    

In [103]:

    

len(hex_list)


    

    
Out[103]:





250000

In [104]:

    

hex_list[1]


    

    
Out[104]:





'0x0'

In [106]:

    

ba = bytearray(h.decode("hex") for h in hex_list)


    

    




---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-106-16d1e1d59552> in <module>()
----> 1 ba = bytearray(h.decode("hex") for h in hex_list)

<ipython-input-106-16d1e1d59552> in <genexpr>(.0)
----> 1 ba = bytearray(h.decode("hex") for h in hex_list)

AttributeError: 'str' object has no attribute 'decode'

In [115]:

    

br = bytearray([i for i in data])


    

In [123]:

    

type(data)


    

    
Out[123]:





bytes

In [124]:

    

import array


    

In [127]:

    

by_str = array.array('B', [17, 24, 121, 1, 12, 222, 34, 76]).tostring()


    

In [128]:

    

len(by_str)


    

    
Out[128]:





8

In [129]:

    

bt_str = array.array('B', [i for i in data]).tostring()


    

In [131]:

    

len(bt_str)


    

    
Out[131]:





250000

In [132]:

    

newImg3 = Image.frombytes(data=bt_str,size=(250,250), mode='RGBA')


    

In [133]:

    

newImg3


    

    
Out[133]:

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