def graph_fn():
candidates = box_list.BoxList(
tf.constant([[0.1, 0.1, 0.4, 0.4]], tf.float32))
pool = box_list.BoxList(tf.constant([[0.6, 0.6, 0.8, 0.8]], tf.float32))
pool.add_field('scores', tf.constant([0.2]))
averaged_boxes = box_list_ops.box_voting(candidates, pool)
return averaged_boxes.get()
def test_box_voting_fails_with_negative_scores(self):
candidates = box_list.BoxList(
tf.constant([[0.1, 0.1, 0.4, 0.4]], tf.float32))
pool = box_list.BoxList(tf.constant([[0.1, 0.1, 0.4, 0.4]], tf.float32))
pool.add_field('scores', tf.constant([-0.2]))
averaged_boxes = box_list_ops.box_voting(candidates, pool)
with self.test_session() as sess:
with self.assertRaisesOpError('Scores must be non negative'):
sess.run([averaged_boxes.get()])
def test_box_voting_fails_with_negative_scores(self):
candidates = box_list.BoxList(
tf.constant([[0.1, 0.1, 0.4, 0.4]], tf.float32))
pool = box_list.BoxList(tf.constant([[0.1, 0.1, 0.4, 0.4]], tf.float32))
pool.add_field('scores', tf.constant([-0.2]))
averaged_boxes = box_list_ops.box_voting(candidates, pool)
with self.test_session() as sess:
with self.assertRaisesOpError('Scores must be non negative'):
sess.run([averaged_boxes.get()])
def graph_fn():
candidates = box_list.BoxList(
tf.constant([[0.1, 0.1, 0.4, 0.4], [0.6, 0.6, 0.8, 0.8]], tf.float32))
candidates.add_field('ExtraField', tf.constant([1, 2]))
pool = box_list.BoxList(
tf.constant([[0.1, 0.1, 0.4, 0.4], [0.1, 0.1, 0.5, 0.5],
[0.6, 0.6, 0.8, 0.8]], tf.float32))
pool.add_field('scores', tf.constant([0.75, 0.25, 0.3]))
averaged_boxes = box_list_ops.box_voting(candidates, pool)
return (averaged_boxes.get(), averaged_boxes.get_field('scores'),
averaged_boxes.get_field('ExtraField'))
def test_box_voting_fails_when_unmatched(self):
candidates = box_list.BoxList(
tf.constant([[0.1, 0.1, 0.4, 0.4]], tf.float32))
pool = box_list.BoxList(tf.constant([[0.6, 0.6, 0.8, 0.8]], tf.float32))
pool.add_field('scores', tf.constant([0.2]))
averaged_boxes = box_list_ops.box_voting(candidates, pool)
with self.test_session() as sess:
with self.assertRaisesOpError('Each box in selected_boxes must match '
'with at least one box in pool_boxes.'):
sess.run([averaged_boxes.get()])
def test_box_voting_fails_when_unmatched(self):
candidates = box_list.BoxList(
tf.constant([[0.1, 0.1, 0.4, 0.4]], tf.float32))
pool = box_list.BoxList(tf.constant([[0.6, 0.6, 0.8, 0.8]], tf.float32))
pool.add_field('scores', tf.constant([0.2]))
averaged_boxes = box_list_ops.box_voting(candidates, pool)
with self.test_session() as sess:
with self.assertRaisesOpError('Each box in selected_boxes must match '
'with at least one box in pool_boxes.'):
sess.run([averaged_boxes.get()])
def test_box_voting(self):
candidates = box_list.BoxList(
tf.constant([[0.1, 0.1, 0.4, 0.4], [0.6, 0.6, 0.8, 0.8]], tf.float32))
candidates.add_field('ExtraField', tf.constant([1, 2]))
pool = box_list.BoxList(
tf.constant([[0.1, 0.1, 0.4, 0.4], [0.1, 0.1, 0.5, 0.5],
[0.6, 0.6, 0.8, 0.8]], tf.float32))
pool.add_field('scores', tf.constant([0.75, 0.25, 0.3]))
averaged_boxes = box_list_ops.box_voting(candidates, pool)
expected_boxes = [[0.1, 0.1, 0.425, 0.425], [0.6, 0.6, 0.8, 0.8]]
expected_scores = [0.5, 0.3]
with self.test_session() as sess:
boxes_out, scores_out, extra_field_out = sess.run(
[averaged_boxes.get(), averaged_boxes.get_field('scores'),
averaged_boxes.get_field('ExtraField')])
self.assertAllClose(expected_boxes, boxes_out)
self.assertAllClose(expected_scores, scores_out)
self.assertAllEqual(extra_field_out, [1, 2])
def test_box_voting(self):
candidates = box_list.BoxList(
tf.constant([[0.1, 0.1, 0.4, 0.4], [0.6, 0.6, 0.8, 0.8]], tf.float32))
candidates.add_field('ExtraField', tf.constant([1, 2]))
pool = box_list.BoxList(
tf.constant([[0.1, 0.1, 0.4, 0.4], [0.1, 0.1, 0.5, 0.5],
[0.6, 0.6, 0.8, 0.8]], tf.float32))
pool.add_field('scores', tf.constant([0.75, 0.25, 0.3]))
averaged_boxes = box_list_ops.box_voting(candidates, pool)
expected_boxes = [[0.1, 0.1, 0.425, 0.425], [0.6, 0.6, 0.8, 0.8]]
expected_scores = [0.5, 0.3]
with self.test_session() as sess:
boxes_out, scores_out, extra_field_out = sess.run(
[averaged_boxes.get(), averaged_boxes.get_field('scores'),
averaged_boxes.get_field('ExtraField')])
self.assertAllClose(expected_boxes, boxes_out)
self.assertAllClose(expected_scores, scores_out)
self.assertAllEqual(extra_field_out, [1, 2])
