Python matcher.Match方法代码示例

# 需要导入模块: from object_detection.core import matcher [as 别名]
# 或者: from object_detection.core.matcher import Match [as 别名]
def test_get_correct_counts(self):
    match_results = tf.constant([3, 1, -1, 0, -1, 5, -2])
    match = matcher.Match(match_results)
    exp_num_matched_columns = 4
    exp_num_unmatched_columns = 2
    exp_num_ignored_columns = 1
    num_matched_columns = match.num_matched_columns()
    num_unmatched_columns = match.num_unmatched_columns()
    num_ignored_columns = match.num_ignored_columns()
    self.assertEquals(num_matched_columns.dtype, tf.int32)
    self.assertEquals(num_unmatched_columns.dtype, tf.int32)
    self.assertEquals(num_ignored_columns.dtype, tf.int32)
    with self.test_session() as sess:
      (num_matched_columns_out, num_unmatched_columns_out,
       num_ignored_columns_out) = sess.run(
           [num_matched_columns, num_unmatched_columns, num_ignored_columns])
      self.assertAllEqual(num_matched_columns_out, exp_num_matched_columns)
      self.assertAllEqual(num_unmatched_columns_out, exp_num_unmatched_columns)
      self.assertAllEqual(num_ignored_columns_out, exp_num_ignored_columns) 

# 需要导入模块: from object_detection.core import matcher [as 别名]
# 或者: from object_detection.core.matcher import Match [as 别名]
def test_get_correct_matched_columnIndices(self):
    match_results = tf.constant([3, 1, -1, 0, -1, 5, -2])
    match = matcher.Match(match_results)
    expected_column_indices = [0, 1, 3, 5]
    matched_column_indices = match.matched_column_indices()
    self.assertEquals(matched_column_indices.dtype, tf.int32)
    with self.test_session() as sess:
      matched_column_indices = sess.run(matched_column_indices)
      self.assertAllEqual(matched_column_indices, expected_column_indices) 

# 需要导入模块: from object_detection.core import matcher [as 别名]
# 或者: from object_detection.core.matcher import Match [as 别名]
def testGetCorrectUnmatchedColumnIndices(self):
    match_results = tf.constant([3, 1, -1, 0, -1, 5, -2])
    match = matcher.Match(match_results)
    expected_column_indices = [2, 4]
    unmatched_column_indices = match.unmatched_column_indices()
    self.assertEquals(unmatched_column_indices.dtype, tf.int32)
    with self.test_session() as sess:
      unmatched_column_indices = sess.run(unmatched_column_indices)
      self.assertAllEqual(unmatched_column_indices, expected_column_indices) 

# 需要导入模块: from object_detection.core import matcher [as 别名]
# 或者: from object_detection.core.matcher import Match [as 别名]
def test_get_correct_ignored_column_indices(self):
    match_results = tf.constant([3, 1, -1, 0, -1, 5, -2])
    match = matcher.Match(match_results)
    expected_column_indices = [6]
    ignored_column_indices = match.ignored_column_indices()
    self.assertEquals(ignored_column_indices.dtype, tf.int32)
    with self.test_session() as sess:
      ignored_column_indices = sess.run(ignored_column_indices)
      self.assertAllEqual(ignored_column_indices, expected_column_indices) 

# 需要导入模块: from object_detection.core import matcher [as 别名]
# 或者: from object_detection.core.matcher import Match [as 别名]
def test_get_correct_matched_column_indicator(self):
    match_results = tf.constant([3, 1, -1, 0, -1, 5, -2])
    match = matcher.Match(match_results)
    expected_column_indicator = [True, True, False, True, False, True, False]
    matched_column_indicator = match.matched_column_indicator()
    self.assertEquals(matched_column_indicator.dtype, tf.bool)
    with self.test_session() as sess:
      matched_column_indicator = sess.run(matched_column_indicator)
      self.assertAllEqual(matched_column_indicator, expected_column_indicator) 

# 需要导入模块: from object_detection.core import matcher [as 别名]
# 或者: from object_detection.core.matcher import Match [as 别名]
def test_get_correct_unmatched_column_indicator(self):
    match_results = tf.constant([3, 1, -1, 0, -1, 5, -2])
    match = matcher.Match(match_results)
    expected_column_indicator = [False, False, True, False, True, False, False]
    unmatched_column_indicator = match.unmatched_column_indicator()
    self.assertEquals(unmatched_column_indicator.dtype, tf.bool)
    with self.test_session() as sess:
      unmatched_column_indicator = sess.run(unmatched_column_indicator)
      self.assertAllEqual(unmatched_column_indicator, expected_column_indicator) 

# 需要导入模块: from object_detection.core import matcher [as 别名]
# 或者: from object_detection.core.matcher import Match [as 别名]
def test_get_correct_ignored_column_indicator(self):
    match_results = tf.constant([3, 1, -1, 0, -1, 5, -2])
    match = matcher.Match(match_results)
    expected_column_indicator = [False, False, False, False, False, False, True]
    ignored_column_indicator = match.ignored_column_indicator()
    self.assertEquals(ignored_column_indicator.dtype, tf.bool)
    with self.test_session() as sess:
      ignored_column_indicator = sess.run(ignored_column_indicator)
      self.assertAllEqual(ignored_column_indicator, expected_column_indicator) 

# 需要导入模块: from object_detection.core import matcher [as 别名]
# 或者: from object_detection.core.matcher import Match [as 别名]
def test_get_correct_unmatched_ignored_column_indices(self):
    match_results = tf.constant([3, 1, -1, 0, -1, 5, -2])
    match = matcher.Match(match_results)
    expected_column_indices = [2, 4, 6]
    unmatched_ignored_column_indices = (match.
                                        unmatched_or_ignored_column_indices())
    self.assertEquals(unmatched_ignored_column_indices.dtype, tf.int32)
    with self.test_session() as sess:
      unmatched_ignored_column_indices = sess.run(
          unmatched_ignored_column_indices)
      self.assertAllEqual(unmatched_ignored_column_indices,
                          expected_column_indices) 

# 需要导入模块: from object_detection.core import matcher [as 别名]
# 或者: from object_detection.core.matcher import Match [as 别名]
def test_scalar_gather_based_on_match(self):
    match_results = tf.constant([3, 1, -1, 0, -1, 5, -2])
    input_tensor = tf.constant([0, 1, 2, 3, 4, 5, 6, 7], dtype=tf.float32)
    expected_gathered_tensor = [3, 1, 100, 0, 100, 5, 200]
    match = matcher.Match(match_results)
    gathered_tensor = match.gather_based_on_match(input_tensor,
                                                  unmatched_value=100.,
                                                  ignored_value=200.)
    self.assertEquals(gathered_tensor.dtype, tf.float32)
    with self.test_session():
      gathered_tensor_out = gathered_tensor.eval()
    self.assertAllEqual(expected_gathered_tensor, gathered_tensor_out) 

# 需要导入模块: from object_detection.core import matcher [as 别名]
# 或者: from object_detection.core.matcher import Match [as 别名]
def test_multidimensional_gather_based_on_match(self):
    match_results = tf.constant([1, -1, -2])
    input_tensor = tf.constant([[0, 0.5, 0, 0.5], [0, 0, 0.5, 0.5]],
                               dtype=tf.float32)
    expected_gathered_tensor = [[0, 0, 0.5, 0.5], [0, 0, 0, 0], [0, 0, 0, 0]]
    match = matcher.Match(match_results)
    gathered_tensor = match.gather_based_on_match(input_tensor,
                                                  unmatched_value=tf.zeros(4),
                                                  ignored_value=tf.zeros(4))
    self.assertEquals(gathered_tensor.dtype, tf.float32)
    with self.test_session():
      gathered_tensor_out = gathered_tensor.eval()
    self.assertAllEqual(expected_gathered_tensor, gathered_tensor_out)