class TestClfDataset(absltest.TestCase):
def setUp(self):
self.tempdir = tempfile.mkdtemp()
_test_create_clf_records(self.tempdir)
configs = DatasetConfigs()
configs.batch_size_train = 1
configs.batch_size_val = 1
self._dataset = Dataset(self.tempdir, configs)
def tearDown(self):
rmtree(self.tempdir)
def test_train_fn(self):
ds = self._dataset.train_fn('train', False)
batch = next(iter(ds))
self.assertEqual(batch['image'].shape, [1, 2670, 2870, 3])
self.assertEqual(batch['label_test1'], 1)
def test_train_fn_shuffle(self):
ds = self._dataset.train_fn('train', True)
batch = next(iter(ds))
self.assertEqual(batch['image'].shape, [1, 2670, 2870, 3])
self.assertEqual(batch['label_test1'], 1)
def test_val_fn(self):
ds = self._dataset.train_fn('val', False)
batch = next(iter(ds))
self.assertEqual(batch['image'].shape, [1, 2670, 2870, 3])
self.assertEqual(batch['label_test1'], 1)
def test_padded_shapes(self):
exp = {
'image': [None] * 3,
'label_test1': [],
'label_test2': [],
'label_test3': [],
'label_test4': []
}
self.assertEqual(self._dataset.padded_shapes, exp)
def test_dataset_configs_prop(self):
configs = self._dataset.dataset_configs
self.assertEqual(configs.batch_size_train, 1)
self.assertEqual(configs.batch_size_val, 1)
configs.batch_size_train = 16
configs.batch_size_val = 16
self._dataset.dataset_configs = configs
configs = self._dataset.dataset_configs
self.assertEqual(configs.batch_size_train, 16)
self.assertEqual(configs.batch_size_val, 16)
class TestSegDataset(absltest.TestCase):
def setUp(self):
self.tempdir = tempfile.mkdtemp()
_test_create_seg_records(self.tempdir)
configs = DatasetConfigs()
configs.batch_size_train = 1
configs.batch_size_val = 1
self._dataset = Dataset(self.tempdir, configs)
def tearDown(self):
rmtree(self.tempdir)
def test_train_fn(self):
ds = self._dataset.train_fn('train', False)
batch = next(iter(ds))
self.assertEqual(batch['image'].shape, [1, 281, 500, 3])
self.assertEqual(batch['label'].shape, [1, 281, 500, 3])
class TestTextJsonDataset(absltest.TestCase):
def setUp(self):
self.tempdir = tempfile.mkdtemp()
_test_create_textjson_records(self.tempdir)
configs = DatasetConfigs()
configs.batch_size_train = 3
self._dataset = Dataset(self.tempdir, configs)
def tearDown(self):
rmtree(self.tempdir)
def test_train_fn(self):
ds = self._dataset.train_fn('train', False)
batch = next(iter(ds))
self.assertEqual(batch['text'].shape, [3])
self.assertEqual(batch['polarity'].shape, [3])
np.array_equal(batch['polarity'].numpy(), [1, 2, 0])
self.assertEqual(list(batch['text'].numpy()), [
b'this is label file', b'this is json file', b'this is text file'
])
class TestDetDataset(absltest.TestCase):
def setUp(self):
self.tempdir = tempfile.mkdtemp()
_test_create_det_records(self.tempdir)
configs = DatasetConfigs()
configs.batch_size_train = 1
configs.batch_size_val = 1
self._dataset = Dataset(self.tempdir, configs)
def tearDown(self):
rmtree(self.tempdir)
def test_train_fn(self):
ds = self._dataset.train_fn('train', False)
batch = next(iter(ds))
self.assertEqual(batch['image'].shape, [1, 281, 500, 3])
np.array_equal(batch['xmin'].numpy(),
np.array([0.208, 0.266, 0.39, 0.052], dtype=np.float32))
np.array_equal(
batch['pose'],
np.asarray([[b'frontal', b'left', b'rear', b'rear']],
dtype=np.str))