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

 ############################################ train
training_size = 300
img_size = 20*20*3

#class Struct:
#    "A structure that can have any fields defined."
 #   def __init__(self, **entries): self.__dict__.update(entries)
#training_images=[];
#training_labels=[];
#training_data= Struct(training_set=training_images, labels=training_labels)
training_images = np.empty(shape=(training_size,20,20,3))
import glob
i = 0
for filename in glob.glob('D:/Minutia/PrincipleWrinkleMinutia/*.jpg'):
    image = misc.imread(filename)
    training_images[i] = image
    i+=1
print(training_images[0].shape)

a= [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
    1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,
    2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2]
training_labels = tf.one_hot(a,3)
sess = tf.Session()
sess.run(training_labels)
#############Converting to the numpy array

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