# 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()