def _create_test_tfrecord(self, num_samples):
tfexample_utils.dump_to_tfrecord(self._test_tfrecord_file, [
tf.train.Example.FromString(
tfexample_utils.create_classification_example(image_height=256,
image_width=256))
for _ in range(num_samples)
])
def setUp(self):
super(TrainTest, self).setUp()
self._model_dir = os.path.join(self.get_temp_dir(), 'model_dir')
tf.io.gfile.makedirs(self._model_dir)
data_dir = os.path.join(self.get_temp_dir(), 'data')
tf.io.gfile.makedirs(data_dir)
self._data_path = os.path.join(data_dir, 'data.tfrecord')
examples = [make_yt8m_example() for _ in range(8)]
tfexample_utils.dump_to_tfrecord(self._data_path, tf_examples=examples)
def setUp(self):
super().setUp()
data_dir = os.path.join(self.get_temp_dir(), 'data')
tf.io.gfile.makedirs(data_dir)
self._data_path = os.path.join(data_dir, 'data.tfrecord')
# pylint: disable=g-complex-comprehension
examples = [
tfexample_utils.create_3d_image_test_example(
image_height=32, image_width=32, image_volume=32, image_channel=2)
for _ in range(20)
]
# pylint: enable=g-complex-comprehension
tfexample_utils.dump_to_tfrecord(self._data_path, tf_examples=examples)
def setUp(self):
super(VideoClassificationTaskTest, self).setUp()
data_dir = os.path.join(self.get_temp_dir(), 'data')
tf.io.gfile.makedirs(data_dir)
self._data_path = os.path.join(data_dir, 'data.tfrecord')
# pylint: disable=g-complex-comprehension
examples = [
tfexample_utils.make_video_test_example(image_shape=(36, 36, 3),
audio_shape=(20, 128),
label=random.randint(
0, 100))
for _ in range(2)
]
# pylint: enable=g-complex-comprehension
tfexample_utils.dump_to_tfrecord(self._data_path, tf_examples=examples)
def test_scan_and_generator_annotation_file(self):
num_samples = 10
example = tfexample_utils.create_detection_test_example(
image_height=512,
image_width=512,
image_channel=3,
num_instances=10)
tf_examples = [example] * num_samples
data_file = os.path.join(self.create_tempdir(), 'test.tfrecord')
tfexample_utils.dump_to_tfrecord(record_file=data_file,
tf_examples=tf_examples)
annotation_file = os.path.join(self.create_tempdir(),
'annotation.json')
coco_utils.scan_and_generator_annotation_file(
file_pattern=data_file,
file_type='tfrecord',
num_samples=num_samples,
include_mask=True,
annotation_file=annotation_file)
self.assertTrue(
tf.io.gfile.exists(annotation_file),
msg='Annotation file {annotation_file} does not exists.')
def _create_test_tfrecord(self, tfrecord_file, example, num_samples):
examples = [example] * num_samples
tfexample_utils.dump_to_tfrecord(record_file=tfrecord_file,
tf_examples=examples)
