def setUp(self): # configure the root logger logger.config_root_logger() # get a logger for this session self.log = logging.getLogger(__name__) # create dataset train = numpy.array([[1, 2], [4, 5]]) valid = numpy.array([[2, 3], [5, 6], [8, 9]]) test = numpy.array([[3, 4], [6, 7], [1, 2], [9, 0]]) self.dataset = MemoryDataset(train_X=train, valid_X=valid, test_X=test)
class TestMemoryDataset(unittest.TestCase): def setUp(self): # configure the root logger logger.config_root_logger() # get a logger for this session self.log = logging.getLogger(__name__) # create dataset train = numpy.array([[1, 2], [4, 5]]) valid = numpy.array([[2, 3], [5, 6], [8, 9]]) test = numpy.array([[3, 4], [6, 7], [1, 2], [9, 0]]) self.dataset = MemoryDataset(train_X=train, valid_X=valid, test_X=test) def testSizes(self): assert self.dataset.getDataShape(dataset.TRAIN) == (2, 2) assert self.dataset.getDataShape(dataset.VALID) == (3, 2) assert self.dataset.getDataShape(dataset.TEST) == (4, 2) def tearDown(self): del self.dataset
from PIL import Image import numpy import matplotlib.pyplot as plt import glob from opendeep.data.dataset import MemoryDataset import theano.tensor as T imageFolderPath = 'eyes/' imagePath = glob.glob(imageFolderPath+'/*.JPG') im_array = numpy.array( [numpy.array(Image.open(imagePath[i]).convert('L'), 'f') for i in range(len(imagePath))] ) flatten_array = im_array.reshape((im_array.shape[0], -1)) #print flatten_array[190] #plt.imshow(flatten_array[5], cmap='Greys_r') #plt.show() data = MemoryDataset(train_X=flatten_array[1:180], test_X=flatten_array[180:191]) print data.getSubset(2)