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 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
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)
