In [78]:

    

import scipy.io as sio
from PIL import Image
import random
import matplotlib.pyplot as plt


    

In [79]:

    

train_data = sio.loadmat('../data/CroppedDigits/train_32x32.mat')


    

In [80]:

    

imgs = []
labels = []
for i in range(10):
    idx = random.randint(0,1000)
    imgs.append(train_data['X'][:,:,:,idx])
    labels.append(train_data['y'][idx])


    

In [81]:

    

print train_data['y'][0]


    

    




[1]

In [82]:

    

_,ax = plt.subplots(1,len(imgs),figsize=(15,15))
for i in range(len(a)):
    ax[i].imshow(imgs[i])
print [labels[i] for i in range(len(imgs))]


    

    




[array([2], dtype=uint8), array([5], dtype=uint8), array([7], dtype=uint8), array([2], dtype=uint8), array([5], dtype=uint8), array([3], dtype=uint8), array([4], dtype=uint8), array([1], dtype=uint8), array([6], dtype=uint8), array([3], dtype=uint8)]






    

In [ ]: