# type(train_images): <class 'list'>
# len(train_images): 60000
#
# type(train_images[ i ]): <class 'numpy.ndarray'>
# train_images[ i ].dtype: uint8
# train_images[ i ].min(): 0
# train_images[ i ].max(): 255
# train_images[ i ].shape: (HEIGHT, WIDTH)
#
# type(train_labels): <class 'list'>
# len(train_labels): 60000
#
# type(train_labels[ i ]): <class 'int'>
# train_labels[ i ]: 0...9
print('Reading Train 60000.cdb ...')
train_images, train_labels = read_hoda_cdb('./DigitDB/Train 60000.cdb')
# type(test_images): <class 'list'>
# len(test_images): 20000
#
# type(test_images[ i ]): <class 'numpy.ndarray'>
# test_images[ i ].dtype: uint8
# test_images[ i ].min(): 0
# test_images[ i ].max(): 255
# test_images[ i ].shape: (HEIGHT, WIDTH)
#
# type(test_labels): <class 'list'>
# len(test_labels): 20000
#
# type(test_labels[ i ]): <class 'int'>
from HodaDatasetReader import read_hoda_dataset, read_hoda_cdb
from matplotlib import pyplot as plt
print('Reading Train 60000.cdb ...')
train_images, train_labels = read_hoda_cdb('./DigitDB/Train 60000.cdb')
print('Reading Test 20000.cdb ...')
test_images, test_labels = read_hoda_cdb('./DigitDB/Test 20000.cdb')
plt.imshow(train_images[0], cmap='gray')
plt.title("Plot for %s (train data)" % train_labels[0])
plt.show()
plt.imshow(test_images[1], cmap='gray')
plt.title("Plot for %s (test data)" % test_labels[0])
plt.show()