def test_format_2_converter(self):
filename = os.path.join(self.tempdir, 'svhn_format_2.hdf5')
parser = argparse.ArgumentParser()
subparsers = parser.add_subparsers()
subparser = subparsers.add_parser('svhn')
svhn.fill_subparser(subparser)
subparser.set_defaults(directory=self.tempdir, output_file=filename)
args = parser.parse_args(['svhn', '2'])
args_dict = vars(args)
func = args_dict.pop('func')
func(**args_dict)
h5file = h5py.File(filename, mode='r')
assert_equal(
h5file['features'][...],
numpy.vstack([self.f2_train_features_mock.transpose(3, 2, 0, 1),
self.f2_test_features_mock.transpose(3, 2, 0, 1),
self.f2_extra_features_mock.transpose(3, 2, 0, 1)]))
assert_equal(
h5file['targets'][...],
numpy.vstack([self.f2_train_targets_mock,
self.f2_test_targets_mock,
self.f2_extra_targets_mock]))
assert_equal(str(h5file['features'].dtype), 'uint8')
assert_equal(str(h5file['targets'].dtype), 'uint8')
assert_equal(tuple(dim.label for dim in h5file['features'].dims),
('batch', 'channel', 'height', 'width'))
assert_equal(tuple(dim.label for dim in h5file['targets'].dims),
('batch', 'index'))
def test_format_2_converter(self):
parser = argparse.ArgumentParser()
subparsers = parser.add_subparsers()
subparser = subparsers.add_parser('svhn')
svhn.fill_subparser(subparser)
subparser.set_defaults(
directory=self.tempdir, output_directory=self.tempdir,
output_filename='svhn_format_2.hdf5')
args = parser.parse_args(['svhn', '2'])
args_dict = vars(args)
func = args_dict.pop('func')
filename, = func(**args_dict)
h5file = h5py.File(filename, mode='r')
assert_equal(
h5file['features'][...],
numpy.vstack([self.f2_train_features_mock.transpose(3, 2, 0, 1),
self.f2_test_features_mock.transpose(3, 2, 0, 1),
self.f2_extra_features_mock.transpose(3, 2, 0, 1)]))
assert_equal(
h5file['targets'][...],
numpy.vstack([self.f2_train_targets_mock,
self.f2_test_targets_mock,
self.f2_extra_targets_mock]))
assert_equal(str(h5file['features'].dtype), 'uint8')
assert_equal(str(h5file['targets'].dtype), 'uint8')
assert_equal(tuple(dim.label for dim in h5file['features'].dims),
('batch', 'channel', 'height', 'width'))
assert_equal(tuple(dim.label for dim in h5file['targets'].dims),
('batch', 'index'))
def test_format_1_converter(self):
filename = os.path.join(self.tempdir, 'svhn_format_1.hdf5')
parser = argparse.ArgumentParser()
subparsers = parser.add_subparsers()
subparser = subparsers.add_parser('svhn')
svhn.fill_subparser(subparser)
subparser.set_defaults(directory=self.tempdir, output_file=filename)
args = parser.parse_args(['svhn', '1'])
args_dict = vars(args)
func = args_dict.pop('func')
func(**args_dict)
h5file = h5py.File(filename, mode='r')
expected_features = sum((self.f1_mock[split]['image']
for split in ('train', 'test', 'extra')), [])
for val, truth in zip(h5file['features'][...], expected_features):
assert_equal(val, truth.transpose(2, 0, 1).flatten())
expected_labels = sum((self.f1_mock[split]['label']
for split in ('train', 'test', 'extra')), [])
for val, truth in zip(h5file['bbox_labels'][...], expected_labels):
truth[truth == 10] = 0
assert_equal(val, truth)
expected_lefts = sum((self.f1_mock[split]['left']
for split in ('train', 'test', 'extra')), [])
for val, truth in zip(h5file['bbox_lefts'][...], expected_lefts):
assert_equal(val, truth)
def test_format_1_converter(self):
parser = argparse.ArgumentParser()
subparsers = parser.add_subparsers()
subparser = subparsers.add_parser('svhn')
svhn.fill_subparser(subparser)
subparser.set_defaults(
directory=self.tempdir, output_directory=self.tempdir,
output_filename='svhn_format_1.hdf5')
args = parser.parse_args(['svhn', '1'])
args_dict = vars(args)
func = args_dict.pop('func')
filename, = func(**args_dict)
h5file = h5py.File(filename, mode='r')
expected_features = sum((self.f1_mock[split]['image']
for split in ('train', 'test', 'extra')), [])
for val, truth in zip(h5file['features'][...], expected_features):
assert_equal(val, truth.transpose(2, 0, 1).flatten())
expected_labels = sum((self.f1_mock[split]['label']
for split in ('train', 'test', 'extra')), [])
for val, truth in zip(h5file['bbox_labels'][...], expected_labels):
truth[truth == 10] = 0
assert_equal(val, truth)
expected_lefts = sum((self.f1_mock[split]['left']
for split in ('train', 'test', 'extra')), [])
for val, truth in zip(h5file['bbox_lefts'][...], expected_lefts):
assert_equal(val, truth)
