def test_bbox_batches(self):
batch_size, size = 2, (28, 28)
with self.test_session() as sess:
data_file_path = test_helper.get_test_metadata()
data_batches, bbox_batches = \
inputs.bbox_batches(data_file_path, batch_size, size, num_preprocess_threads=1, channels=3)
self.assertEqual(data_batches.get_shape(), (2, 28, 28, 3))
self.assertEqual(bbox_batches.get_shape(), (2, 4))
coord = tf.train.Coordinator()
threads = tf.train.start_queue_runners(sess=sess, coord=coord)
# bbox of 1.png: 246, 77, 173, 223, size of 1.png: 741 x 350
_, bb = sess.run([data_batches, bbox_batches])
self.assertAllClose(bb[0],
[246 / 741, 77 / 350, 173 / 741, 223 / 350])
coord.request_stop()
coord.join(threads)
sess.close()
def _test_bbox_batches(self,
target_bbox,
first_expected_bbox,
data_file_path=None):
data_file_path = test_helper.get_test_metadata(
) if data_file_path is None else data_file_path
batch_size, size = 2, (28, 28)
with self.test_session() as sess:
data_batches, bbox_batches = \
inputs.bbox_batches(data_file_path, batch_size, size, 5,
num_preprocess_threads=1, channels=3, target_bbox=target_bbox)
self.assertEqual(data_batches.get_shape(), (2, 28, 28, 3))
self.assertEqual(bbox_batches.get_shape(), (2, 4))
coord = tf.train.Coordinator()
threads = tf.train.start_queue_runners(sess=sess, coord=coord)
_, bb = sess.run([data_batches, bbox_batches])
self.assertAllClose(bb[0], first_expected_bbox)
coord.request_stop()
coord.join(threads)
sess.close()
def _setup_input(self):
config = self.config
with ops.name_scope(None, 'Input') as sc:
self.data_batches, self.label_batches = \
inputs.bbox_batches(config.data_file_path, config.batch_size, config.size, config.max_number_length,
channels=self.config.channels)