import numpy as np
import matplotlib.pyplot as plt
try:
    from scipy import misc
except ImportError:
    !pip install scipy
    from scipy import misc

#train
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
try:
    from scipy import misc
except ImportError:
    !pip install scipy
    from scipy import misc

training_size = 265
img_size = 400*400
training_data = np.empty(shape=(training_size,img_size ))

import glob
i = 0
for filename in glob.glob('D:/TensorPalms/Train/*.jpg'):
    image = misc.imread(filename)
    print(image.shape)
    training_data[i] = image.reshape(-1)
    #training_data[i] = image

    i+=1


#label


a= [0,0,0,0,0,
    1,1,1,1,1,
    2,2,2,2,2,
    3,3,3,3,3,
    4,4,4,4,4,
    5,5,5,5,5,
    6,6,6,6,6,
    7,7,7,7,7,
    8,8,8,8,8,
    9,9,9,9,9,
    10,10,10,10,10,
    11,11,11,11,11,
    12,12,12,12,12,
    13,13,13,13,13,
    14,14,14,14,14,
    15,15,15,15,15,
    16,16,16,16,16,
    17,17,17,17,17,
    18,18,18,18,18,
    19,19,19,19,19,
    20,20,20,20,20,
    21,21,21,21,21,
    22,22,22,22,22,
    23,23,23,23,23,
    24,24,24,24,24,
    25,25,25,25,25,
    26,26,26,26,26,
    27,27,27,27,27,
    28,28,28,28,28,
    29,29,29,29,29,
    30,30,30,30,30,
    31,31,31,31,31,
    32,32,32,32,32,
    33,33,33,33,33,
    34,34,34,34,34,
    35,35,35,35,35,
    36,36,36,36,36,
    37,37,37,37,37,
    38,38,38,38,38,
    39,39,39,39,39,
    40,40,40,40,40,
    41,41,41,41,41,
    42,42,42,42,42,
    43,43,43,43,43,
    44,44,44,44,44,
    45,45,45,45,45,
    46,46,46,46,46,
    47,47,47,47,47,
    48,48,48,48,48,
    49,49,49,49,49,
    50,50,50,50,50,
    51,51,51,51,51,
    52,52,52,52,52,]



b = tf.one_hot(a,53)
sess = tf.Session()
sess.run(b)

print(b.shape)

from sklearn.preprocessing import OneHotEncoder
training_label = OneHotEncoder(sparse=False).fit_transform(np.asarray(a).reshape(-1, 1))
print(training_label)