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)