Python object_detection.core.region_similarity_calculator.IouSimilarity() Examples

The following are 30 code examples of object_detection.core.region_similarity_calculator.IouSimilarity(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module object_detection.core.region_similarity_calculator , or try the search function .
Example #1
Source File: ssd_dataloader.py    From benchmarks with Apache License 2.0 6 votes vote down vote up
def __init__(self):
    similarity_calc = region_similarity_calculator.IouSimilarity()
    matcher = argmax_matcher.ArgMaxMatcher(
        matched_threshold=ssd_constants.MATCH_THRESHOLD,
        unmatched_threshold=ssd_constants.MATCH_THRESHOLD,
        negatives_lower_than_unmatched=True,
        force_match_for_each_row=True)

    box_coder = faster_rcnn_box_coder.FasterRcnnBoxCoder(
        scale_factors=ssd_constants.BOX_CODER_SCALES)

    self.default_boxes = DefaultBoxes()('ltrb')
    self.default_boxes = box_list.BoxList(
        tf.convert_to_tensor(self.default_boxes))
    self.assigner = target_assigner.TargetAssigner(
        similarity_calc, matcher, box_coder) 
Example #2
Source File: target_assigner_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 5 votes vote down vote up
def test_assign_agnostic(self):
    def graph_fn(anchor_means, anchor_stddevs, groundtruth_box_corners):
      similarity_calc = region_similarity_calculator.IouSimilarity()
      matcher = argmax_matcher.ArgMaxMatcher(matched_threshold=0.5,
                                             unmatched_threshold=0.5)
      box_coder = mean_stddev_box_coder.MeanStddevBoxCoder()
      target_assigner = targetassigner.TargetAssigner(
          similarity_calc, matcher, box_coder, unmatched_cls_target=None)
      anchors_boxlist = box_list.BoxList(anchor_means)
      anchors_boxlist.add_field('stddev', anchor_stddevs)
      groundtruth_boxlist = box_list.BoxList(groundtruth_box_corners)
      result = target_assigner.assign(anchors_boxlist, groundtruth_boxlist)
      (cls_targets, cls_weights, reg_targets, reg_weights, _) = result
      return (cls_targets, cls_weights, reg_targets, reg_weights)

    anchor_means = np.array([[0.0, 0.0, 0.5, 0.5],
                             [0.5, 0.5, 1.0, 0.8],
                             [0, 0.5, .5, 1.0]], dtype=np.float32)
    anchor_stddevs = np.array(3 * [4 * [.1]], dtype=np.float32)
    groundtruth_box_corners = np.array([[0.0, 0.0, 0.5, 0.5],
                                        [0.5, 0.5, 0.9, 0.9]],
                                       dtype=np.float32)
    exp_cls_targets = [[1], [1], [0]]
    exp_cls_weights = [1, 1, 1]
    exp_reg_targets = [[0, 0, 0, 0],
                       [0, 0, -1, 1],
                       [0, 0, 0, 0]]
    exp_reg_weights = [1, 1, 0]

    (cls_targets_out, cls_weights_out, reg_targets_out,
     reg_weights_out) = self.execute(graph_fn, [anchor_means, anchor_stddevs,
                                                groundtruth_box_corners])
    self.assertAllClose(cls_targets_out, exp_cls_targets)
    self.assertAllClose(cls_weights_out, exp_cls_weights)
    self.assertAllClose(reg_targets_out, exp_reg_targets)
    self.assertAllClose(reg_weights_out, exp_reg_weights)
    self.assertEquals(cls_targets_out.dtype, np.float32)
    self.assertEquals(cls_weights_out.dtype, np.float32)
    self.assertEquals(reg_targets_out.dtype, np.float32)
    self.assertEquals(reg_weights_out.dtype, np.float32) 
Example #3
Source File: region_similarity_calculator_builder.py    From Traffic-Rule-Violation-Detection-System with MIT License 5 votes vote down vote up
def build(region_similarity_calculator_config):
  """Builds region similarity calculator based on the configuration.

  Builds one of [IouSimilarity, IoaSimilarity, NegSqDistSimilarity] objects. See
  core/region_similarity_calculator.proto for details.

  Args:
    region_similarity_calculator_config: RegionSimilarityCalculator
      configuration proto.

  Returns:
    region_similarity_calculator: RegionSimilarityCalculator object.

  Raises:
    ValueError: On unknown region similarity calculator.
  """

  if not isinstance(
      region_similarity_calculator_config,
      region_similarity_calculator_pb2.RegionSimilarityCalculator):
    raise ValueError(
        'region_similarity_calculator_config not of type '
        'region_similarity_calculator_pb2.RegionsSimilarityCalculator')

  similarity_calculator = region_similarity_calculator_config.WhichOneof(
      'region_similarity')
  if similarity_calculator == 'iou_similarity':
    return region_similarity_calculator.IouSimilarity()
  if similarity_calculator == 'ioa_similarity':
    return region_similarity_calculator.IoaSimilarity()
  if similarity_calculator == 'neg_sq_dist_similarity':
    return region_similarity_calculator.NegSqDistSimilarity()

  raise ValueError('Unknown region similarity calculator.') 
Example #4
Source File: target_assigner_test.py    From vehicle_counting_tensorflow with MIT License 5 votes vote down vote up
def test_assign_agnostic(self):
    def graph_fn(anchor_means, groundtruth_box_corners):
      similarity_calc = region_similarity_calculator.IouSimilarity()
      matcher = argmax_matcher.ArgMaxMatcher(matched_threshold=0.5,
                                             unmatched_threshold=0.5)
      box_coder = mean_stddev_box_coder.MeanStddevBoxCoder(stddev=0.1)
      target_assigner = targetassigner.TargetAssigner(
          similarity_calc, matcher, box_coder)
      anchors_boxlist = box_list.BoxList(anchor_means)
      groundtruth_boxlist = box_list.BoxList(groundtruth_box_corners)
      result = target_assigner.assign(
          anchors_boxlist, groundtruth_boxlist, unmatched_class_label=None)
      (cls_targets, cls_weights, reg_targets, reg_weights, _) = result
      return (cls_targets, cls_weights, reg_targets, reg_weights)

    anchor_means = np.array([[0.0, 0.0, 0.5, 0.5],
                             [0.5, 0.5, 1.0, 0.8],
                             [0, 0.5, .5, 1.0]], dtype=np.float32)
    groundtruth_box_corners = np.array([[0.0, 0.0, 0.5, 0.5],
                                        [0.5, 0.5, 0.9, 0.9]],
                                       dtype=np.float32)
    exp_cls_targets = [[1], [1], [0]]
    exp_cls_weights = [[1], [1], [1]]
    exp_reg_targets = [[0, 0, 0, 0],
                       [0, 0, -1, 1],
                       [0, 0, 0, 0]]
    exp_reg_weights = [1, 1, 0]

    (cls_targets_out,
     cls_weights_out, reg_targets_out, reg_weights_out) = self.execute(
         graph_fn, [anchor_means, groundtruth_box_corners])
    self.assertAllClose(cls_targets_out, exp_cls_targets)
    self.assertAllClose(cls_weights_out, exp_cls_weights)
    self.assertAllClose(reg_targets_out, exp_reg_targets)
    self.assertAllClose(reg_weights_out, exp_reg_weights)
    self.assertEquals(cls_targets_out.dtype, np.float32)
    self.assertEquals(cls_weights_out.dtype, np.float32)
    self.assertEquals(reg_targets_out.dtype, np.float32)
    self.assertEquals(reg_weights_out.dtype, np.float32) 
Example #5
Source File: region_similarity_calculator_builder_test.py    From DOTA_models with Apache License 2.0 5 votes vote down vote up
def testBuildIouSimilarityCalculator(self):
    similarity_calc_text_proto = """
      iou_similarity {
      }
    """
    similarity_calc_proto = sim_calc_pb2.RegionSimilarityCalculator()
    text_format.Merge(similarity_calc_text_proto, similarity_calc_proto)
    similarity_calc = region_similarity_calculator_builder.build(
        similarity_calc_proto)
    self.assertTrue(isinstance(similarity_calc,
                               region_similarity_calculator.IouSimilarity)) 
Example #6
Source File: region_similarity_calculator_builder.py    From DOTA_models with Apache License 2.0 5 votes vote down vote up
def build(region_similarity_calculator_config):
  """Builds region similarity calculator based on the configuration.

  Builds one of [IouSimilarity, IoaSimilarity, NegSqDistSimilarity] objects. See
  core/region_similarity_calculator.proto for details.

  Args:
    region_similarity_calculator_config: RegionSimilarityCalculator
      configuration proto.

  Returns:
    region_similarity_calculator: RegionSimilarityCalculator object.

  Raises:
    ValueError: On unknown region similarity calculator.
  """

  if not isinstance(
      region_similarity_calculator_config,
      region_similarity_calculator_pb2.RegionSimilarityCalculator):
    raise ValueError(
        'region_similarity_calculator_config not of type '
        'region_similarity_calculator_pb2.RegionsSimilarityCalculator')

  similarity_calculator = region_similarity_calculator_config.WhichOneof(
      'region_similarity')
  if similarity_calculator == 'iou_similarity':
    return region_similarity_calculator.IouSimilarity()
  if similarity_calculator == 'ioa_similarity':
    return region_similarity_calculator.IoaSimilarity()
  if similarity_calculator == 'neg_sq_dist_similarity':
    return region_similarity_calculator.NegSqDistSimilarity()

  raise ValueError('Unknown region similarity calculator.') 
Example #7
Source File: region_similarity_calculator_builder_test.py    From Traffic-Rule-Violation-Detection-System with MIT License 5 votes vote down vote up
def testBuildIouSimilarityCalculator(self):
    similarity_calc_text_proto = """
      iou_similarity {
      }
    """
    similarity_calc_proto = sim_calc_pb2.RegionSimilarityCalculator()
    text_format.Merge(similarity_calc_text_proto, similarity_calc_proto)
    similarity_calc = region_similarity_calculator_builder.build(
        similarity_calc_proto)
    self.assertTrue(isinstance(similarity_calc,
                               region_similarity_calculator.IouSimilarity)) 
Example #8
Source File: region_similarity_calculator_builder.py    From object_detector_app with MIT License 5 votes vote down vote up
def build(region_similarity_calculator_config):
  """Builds region similarity calculator based on the configuration.

  Builds one of [IouSimilarity, IoaSimilarity, NegSqDistSimilarity] objects. See
  core/region_similarity_calculator.proto for details.

  Args:
    region_similarity_calculator_config: RegionSimilarityCalculator
      configuration proto.

  Returns:
    region_similarity_calculator: RegionSimilarityCalculator object.

  Raises:
    ValueError: On unknown region similarity calculator.
  """

  if not isinstance(
      region_similarity_calculator_config,
      region_similarity_calculator_pb2.RegionSimilarityCalculator):
    raise ValueError(
        'region_similarity_calculator_config not of type '
        'region_similarity_calculator_pb2.RegionsSimilarityCalculator')

  similarity_calculator = region_similarity_calculator_config.WhichOneof(
      'region_similarity')
  if similarity_calculator == 'iou_similarity':
    return region_similarity_calculator.IouSimilarity()
  if similarity_calculator == 'ioa_similarity':
    return region_similarity_calculator.IoaSimilarity()
  if similarity_calculator == 'neg_sq_dist_similarity':
    return region_similarity_calculator.NegSqDistSimilarity()

  raise ValueError('Unknown region similarity calculator.') 
Example #9
Source File: region_similarity_calculator_builder_test.py    From object_detector_app with MIT License 5 votes vote down vote up
def testBuildIouSimilarityCalculator(self):
    similarity_calc_text_proto = """
      iou_similarity {
      }
    """
    similarity_calc_proto = sim_calc_pb2.RegionSimilarityCalculator()
    text_format.Merge(similarity_calc_text_proto, similarity_calc_proto)
    similarity_calc = region_similarity_calculator_builder.build(
        similarity_calc_proto)
    self.assertTrue(isinstance(similarity_calc,
                               region_similarity_calculator.IouSimilarity)) 
Example #10
Source File: region_similarity_calculator_test.py    From Traffic-Rule-Violation-Detection-System with MIT License 5 votes vote down vote up
def test_get_correct_pairwise_similarity_based_on_iou(self):
    corners1 = tf.constant([[4.0, 3.0, 7.0, 5.0], [5.0, 6.0, 10.0, 7.0]])
    corners2 = tf.constant([[3.0, 4.0, 6.0, 8.0], [14.0, 14.0, 15.0, 15.0],
                            [0.0, 0.0, 20.0, 20.0]])
    exp_output = [[2.0 / 16.0, 0, 6.0 / 400.0], [1.0 / 16.0, 0.0, 5.0 / 400.0]]
    boxes1 = box_list.BoxList(corners1)
    boxes2 = box_list.BoxList(corners2)
    iou_similarity_calculator = region_similarity_calculator.IouSimilarity()
    iou_similarity = iou_similarity_calculator.compare(boxes1, boxes2)
    with self.test_session() as sess:
      iou_output = sess.run(iou_similarity)
      self.assertAllClose(iou_output, exp_output) 
Example #11
Source File: target_assigner_test.py    From vehicle_counting_tensorflow with MIT License 5 votes vote down vote up
def _get_target_assigner(self):
    similarity_calc = region_similarity_calculator.IouSimilarity()
    matcher = argmax_matcher.ArgMaxMatcher(matched_threshold=0.5,
                                           unmatched_threshold=0.5)
    box_coder = mean_stddev_box_coder.MeanStddevBoxCoder(stddev=0.1)
    return targetassigner.TargetAssigner(similarity_calc, matcher, box_coder) 
Example #12
Source File: region_similarity_calculator_test.py    From object_detector_app with MIT License 5 votes vote down vote up
def test_get_correct_pairwise_similarity_based_on_iou(self):
    corners1 = tf.constant([[4.0, 3.0, 7.0, 5.0], [5.0, 6.0, 10.0, 7.0]])
    corners2 = tf.constant([[3.0, 4.0, 6.0, 8.0], [14.0, 14.0, 15.0, 15.0],
                            [0.0, 0.0, 20.0, 20.0]])
    exp_output = [[2.0 / 16.0, 0, 6.0 / 400.0], [1.0 / 16.0, 0.0, 5.0 / 400.0]]
    boxes1 = box_list.BoxList(corners1)
    boxes2 = box_list.BoxList(corners2)
    iou_similarity_calculator = region_similarity_calculator.IouSimilarity()
    iou_similarity = iou_similarity_calculator.compare(boxes1, boxes2)
    with self.test_session() as sess:
      iou_output = sess.run(iou_similarity)
      self.assertAllClose(iou_output, exp_output) 
Example #13
Source File: region_similarity_calculator_builder.py    From vehicle_counting_tensorflow with MIT License 5 votes vote down vote up
def build(region_similarity_calculator_config):
  """Builds region similarity calculator based on the configuration.

  Builds one of [IouSimilarity, IoaSimilarity, NegSqDistSimilarity] objects. See
  core/region_similarity_calculator.proto for details.

  Args:
    region_similarity_calculator_config: RegionSimilarityCalculator
      configuration proto.

  Returns:
    region_similarity_calculator: RegionSimilarityCalculator object.

  Raises:
    ValueError: On unknown region similarity calculator.
  """

  if not isinstance(
      region_similarity_calculator_config,
      region_similarity_calculator_pb2.RegionSimilarityCalculator):
    raise ValueError(
        'region_similarity_calculator_config not of type '
        'region_similarity_calculator_pb2.RegionsSimilarityCalculator')

  similarity_calculator = region_similarity_calculator_config.WhichOneof(
      'region_similarity')
  if similarity_calculator == 'iou_similarity':
    return region_similarity_calculator.IouSimilarity()
  if similarity_calculator == 'ioa_similarity':
    return region_similarity_calculator.IoaSimilarity()
  if similarity_calculator == 'neg_sq_dist_similarity':
    return region_similarity_calculator.NegSqDistSimilarity()
  if similarity_calculator == 'thresholded_iou_similarity':
    return region_similarity_calculator.ThresholdedIouSimilarity(
        region_similarity_calculator_config.thresholded_iou_similarity.threshold
    )

  raise ValueError('Unknown region similarity calculator.') 
Example #14
Source File: target_assigner_test.py    From Person-Detection-and-Tracking with MIT License 5 votes vote down vote up
def _get_multi_class_target_assigner(self, num_classes):
    similarity_calc = region_similarity_calculator.IouSimilarity()
    matcher = argmax_matcher.ArgMaxMatcher(matched_threshold=0.5,
                                           unmatched_threshold=0.5)
    box_coder = mean_stddev_box_coder.MeanStddevBoxCoder(stddev=0.1)
    unmatched_cls_target = tf.constant([1] + num_classes * [0], tf.float32)
    return targetassigner.TargetAssigner(
        similarity_calc, matcher, box_coder,
        unmatched_cls_target=unmatched_cls_target) 
Example #15
Source File: target_assigner_test.py    From Traffic-Rule-Violation-Detection-System with MIT License 5 votes vote down vote up
def test_assign_agnostic(self):
    def graph_fn(anchor_means, anchor_stddevs, groundtruth_box_corners):
      similarity_calc = region_similarity_calculator.IouSimilarity()
      matcher = argmax_matcher.ArgMaxMatcher(matched_threshold=0.5,
                                             unmatched_threshold=0.5)
      box_coder = mean_stddev_box_coder.MeanStddevBoxCoder()
      target_assigner = targetassigner.TargetAssigner(
          similarity_calc, matcher, box_coder, unmatched_cls_target=None)
      anchors_boxlist = box_list.BoxList(anchor_means)
      anchors_boxlist.add_field('stddev', anchor_stddevs)
      groundtruth_boxlist = box_list.BoxList(groundtruth_box_corners)
      result = target_assigner.assign(anchors_boxlist, groundtruth_boxlist)
      (cls_targets, cls_weights, reg_targets, reg_weights, _) = result
      return (cls_targets, cls_weights, reg_targets, reg_weights)

    anchor_means = np.array([[0.0, 0.0, 0.5, 0.5],
                             [0.5, 0.5, 1.0, 0.8],
                             [0, 0.5, .5, 1.0]], dtype=np.float32)
    anchor_stddevs = np.array(3 * [4 * [.1]], dtype=np.float32)
    groundtruth_box_corners = np.array([[0.0, 0.0, 0.5, 0.5],
                                        [0.5, 0.5, 0.9, 0.9]],
                                       dtype=np.float32)
    exp_cls_targets = [[1], [1], [0]]
    exp_cls_weights = [1, 1, 1]
    exp_reg_targets = [[0, 0, 0, 0],
                       [0, 0, -1, 1],
                       [0, 0, 0, 0]]
    exp_reg_weights = [1, 1, 0]

    (cls_targets_out, cls_weights_out, reg_targets_out,
     reg_weights_out) = self.execute(graph_fn, [anchor_means, anchor_stddevs,
                                                groundtruth_box_corners])
    self.assertAllClose(cls_targets_out, exp_cls_targets)
    self.assertAllClose(cls_weights_out, exp_cls_weights)
    self.assertAllClose(reg_targets_out, exp_reg_targets)
    self.assertAllClose(reg_weights_out, exp_reg_weights)
    self.assertEquals(cls_targets_out.dtype, np.float32)
    self.assertEquals(cls_weights_out.dtype, np.float32)
    self.assertEquals(reg_targets_out.dtype, np.float32)
    self.assertEquals(reg_weights_out.dtype, np.float32) 
Example #16
Source File: region_similarity_calculator_builder_test.py    From vehicle_counting_tensorflow with MIT License 5 votes vote down vote up
def testBuildIouSimilarityCalculator(self):
    similarity_calc_text_proto = """
      iou_similarity {
      }
    """
    similarity_calc_proto = sim_calc_pb2.RegionSimilarityCalculator()
    text_format.Merge(similarity_calc_text_proto, similarity_calc_proto)
    similarity_calc = region_similarity_calculator_builder.build(
        similarity_calc_proto)
    self.assertTrue(isinstance(similarity_calc,
                               region_similarity_calculator.IouSimilarity)) 
Example #17
Source File: target_assigner_test.py    From Person-Detection-and-Tracking with MIT License 5 votes vote down vote up
def _get_agnostic_target_assigner(self):
    similarity_calc = region_similarity_calculator.IouSimilarity()
    matcher = argmax_matcher.ArgMaxMatcher(matched_threshold=0.5,
                                           unmatched_threshold=0.5)
    box_coder = mean_stddev_box_coder.MeanStddevBoxCoder(stddev=0.1)
    return targetassigner.TargetAssigner(
        similarity_calc, matcher, box_coder,
        unmatched_cls_target=None) 
Example #18
Source File: region_similarity_calculator_builder_test.py    From yolo_v2 with Apache License 2.0 5 votes vote down vote up
def testBuildIouSimilarityCalculator(self):
    similarity_calc_text_proto = """
      iou_similarity {
      }
    """
    similarity_calc_proto = sim_calc_pb2.RegionSimilarityCalculator()
    text_format.Merge(similarity_calc_text_proto, similarity_calc_proto)
    similarity_calc = region_similarity_calculator_builder.build(
        similarity_calc_proto)
    self.assertTrue(isinstance(similarity_calc,
                               region_similarity_calculator.IouSimilarity)) 
Example #19
Source File: region_similarity_calculator_builder.py    From yolo_v2 with Apache License 2.0 5 votes vote down vote up
def build(region_similarity_calculator_config):
  """Builds region similarity calculator based on the configuration.

  Builds one of [IouSimilarity, IoaSimilarity, NegSqDistSimilarity] objects. See
  core/region_similarity_calculator.proto for details.

  Args:
    region_similarity_calculator_config: RegionSimilarityCalculator
      configuration proto.

  Returns:
    region_similarity_calculator: RegionSimilarityCalculator object.

  Raises:
    ValueError: On unknown region similarity calculator.
  """

  if not isinstance(
      region_similarity_calculator_config,
      region_similarity_calculator_pb2.RegionSimilarityCalculator):
    raise ValueError(
        'region_similarity_calculator_config not of type '
        'region_similarity_calculator_pb2.RegionsSimilarityCalculator')

  similarity_calculator = region_similarity_calculator_config.WhichOneof(
      'region_similarity')
  if similarity_calculator == 'iou_similarity':
    return region_similarity_calculator.IouSimilarity()
  if similarity_calculator == 'ioa_similarity':
    return region_similarity_calculator.IoaSimilarity()
  if similarity_calculator == 'neg_sq_dist_similarity':
    return region_similarity_calculator.NegSqDistSimilarity()

  raise ValueError('Unknown region similarity calculator.') 
Example #20
Source File: region_similarity_calculator_test.py    From yolo_v2 with Apache License 2.0 5 votes vote down vote up
def test_get_correct_pairwise_similarity_based_on_iou(self):
    corners1 = tf.constant([[4.0, 3.0, 7.0, 5.0], [5.0, 6.0, 10.0, 7.0]])
    corners2 = tf.constant([[3.0, 4.0, 6.0, 8.0], [14.0, 14.0, 15.0, 15.0],
                            [0.0, 0.0, 20.0, 20.0]])
    exp_output = [[2.0 / 16.0, 0, 6.0 / 400.0], [1.0 / 16.0, 0.0, 5.0 / 400.0]]
    boxes1 = box_list.BoxList(corners1)
    boxes2 = box_list.BoxList(corners2)
    iou_similarity_calculator = region_similarity_calculator.IouSimilarity()
    iou_similarity = iou_similarity_calculator.compare(boxes1, boxes2)
    with self.test_session() as sess:
      iou_output = sess.run(iou_similarity)
      self.assertAllClose(iou_output, exp_output) 
Example #21
Source File: target_assigner_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 5 votes vote down vote up
def _get_agnostic_target_assigner(self):
    similarity_calc = region_similarity_calculator.IouSimilarity()
    matcher = argmax_matcher.ArgMaxMatcher(matched_threshold=0.5,
                                           unmatched_threshold=0.5)
    box_coder = mean_stddev_box_coder.MeanStddevBoxCoder()
    return targetassigner.TargetAssigner(
        similarity_calc, matcher, box_coder,
        unmatched_cls_target=None) 
Example #22
Source File: target_assigner_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 5 votes vote down vote up
def _get_multi_dimensional_target_assigner(self, target_dimensions):
    similarity_calc = region_similarity_calculator.IouSimilarity()
    matcher = argmax_matcher.ArgMaxMatcher(matched_threshold=0.5,
                                           unmatched_threshold=0.5)
    box_coder = mean_stddev_box_coder.MeanStddevBoxCoder()
    unmatched_cls_target = tf.constant(np.zeros(target_dimensions),
                                       tf.float32)
    return targetassigner.TargetAssigner(
        similarity_calc, matcher, box_coder,
        unmatched_cls_target=unmatched_cls_target) 
Example #23
Source File: region_similarity_calculator_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 5 votes vote down vote up
def test_get_correct_pairwise_similarity_based_on_iou(self):
    corners1 = tf.constant([[4.0, 3.0, 7.0, 5.0], [5.0, 6.0, 10.0, 7.0]])
    corners2 = tf.constant([[3.0, 4.0, 6.0, 8.0], [14.0, 14.0, 15.0, 15.0],
                            [0.0, 0.0, 20.0, 20.0]])
    exp_output = [[2.0 / 16.0, 0, 6.0 / 400.0], [1.0 / 16.0, 0.0, 5.0 / 400.0]]
    boxes1 = box_list.BoxList(corners1)
    boxes2 = box_list.BoxList(corners2)
    iou_similarity_calculator = region_similarity_calculator.IouSimilarity()
    iou_similarity = iou_similarity_calculator.compare(boxes1, boxes2)
    with self.test_session() as sess:
      iou_output = sess.run(iou_similarity)
      self.assertAllClose(iou_output, exp_output) 
Example #24
Source File: region_similarity_calculator_builder.py    From ros_people_object_detection_tensorflow with Apache License 2.0 5 votes vote down vote up
def build(region_similarity_calculator_config):
  """Builds region similarity calculator based on the configuration.

  Builds one of [IouSimilarity, IoaSimilarity, NegSqDistSimilarity] objects. See
  core/region_similarity_calculator.proto for details.

  Args:
    region_similarity_calculator_config: RegionSimilarityCalculator
      configuration proto.

  Returns:
    region_similarity_calculator: RegionSimilarityCalculator object.

  Raises:
    ValueError: On unknown region similarity calculator.
  """

  if not isinstance(
      region_similarity_calculator_config,
      region_similarity_calculator_pb2.RegionSimilarityCalculator):
    raise ValueError(
        'region_similarity_calculator_config not of type '
        'region_similarity_calculator_pb2.RegionsSimilarityCalculator')

  similarity_calculator = region_similarity_calculator_config.WhichOneof(
      'region_similarity')
  if similarity_calculator == 'iou_similarity':
    return region_similarity_calculator.IouSimilarity()
  if similarity_calculator == 'ioa_similarity':
    return region_similarity_calculator.IoaSimilarity()
  if similarity_calculator == 'neg_sq_dist_similarity':
    return region_similarity_calculator.NegSqDistSimilarity()

  raise ValueError('Unknown region similarity calculator.') 
Example #25
Source File: region_similarity_calculator_builder_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 5 votes vote down vote up
def testBuildIouSimilarityCalculator(self):
    similarity_calc_text_proto = """
      iou_similarity {
      }
    """
    similarity_calc_proto = sim_calc_pb2.RegionSimilarityCalculator()
    text_format.Merge(similarity_calc_text_proto, similarity_calc_proto)
    similarity_calc = region_similarity_calculator_builder.build(
        similarity_calc_proto)
    self.assertTrue(isinstance(similarity_calc,
                               region_similarity_calculator.IouSimilarity)) 
Example #26
Source File: region_similarity_calculator_test.py    From HereIsWally with MIT License 5 votes vote down vote up
def test_get_correct_pairwise_similarity_based_on_iou(self):
    corners1 = tf.constant([[4.0, 3.0, 7.0, 5.0], [5.0, 6.0, 10.0, 7.0]])
    corners2 = tf.constant([[3.0, 4.0, 6.0, 8.0], [14.0, 14.0, 15.0, 15.0],
                            [0.0, 0.0, 20.0, 20.0]])
    exp_output = [[2.0 / 16.0, 0, 6.0 / 400.0], [1.0 / 16.0, 0.0, 5.0 / 400.0]]
    boxes1 = box_list.BoxList(corners1)
    boxes2 = box_list.BoxList(corners2)
    iou_similarity_calculator = region_similarity_calculator.IouSimilarity()
    iou_similarity = iou_similarity_calculator.compare(boxes1, boxes2)
    with self.test_session() as sess:
      iou_output = sess.run(iou_similarity)
      self.assertAllClose(iou_output, exp_output) 
Example #27
Source File: target_assigner_test.py    From Person-Detection-and-Tracking with MIT License 5 votes vote down vote up
def test_assign_agnostic(self):
    def graph_fn(anchor_means, groundtruth_box_corners):
      similarity_calc = region_similarity_calculator.IouSimilarity()
      matcher = argmax_matcher.ArgMaxMatcher(matched_threshold=0.5,
                                             unmatched_threshold=0.5)
      box_coder = mean_stddev_box_coder.MeanStddevBoxCoder(stddev=0.1)
      target_assigner = targetassigner.TargetAssigner(
          similarity_calc, matcher, box_coder, unmatched_cls_target=None)
      anchors_boxlist = box_list.BoxList(anchor_means)
      groundtruth_boxlist = box_list.BoxList(groundtruth_box_corners)
      result = target_assigner.assign(anchors_boxlist, groundtruth_boxlist)
      (cls_targets, cls_weights, reg_targets, reg_weights, _) = result
      return (cls_targets, cls_weights, reg_targets, reg_weights)

    anchor_means = np.array([[0.0, 0.0, 0.5, 0.5],
                             [0.5, 0.5, 1.0, 0.8],
                             [0, 0.5, .5, 1.0]], dtype=np.float32)
    groundtruth_box_corners = np.array([[0.0, 0.0, 0.5, 0.5],
                                        [0.5, 0.5, 0.9, 0.9]],
                                       dtype=np.float32)
    exp_cls_targets = [[1], [1], [0]]
    exp_cls_weights = [1, 1, 1]
    exp_reg_targets = [[0, 0, 0, 0],
                       [0, 0, -1, 1],
                       [0, 0, 0, 0]]
    exp_reg_weights = [1, 1, 0]

    (cls_targets_out,
     cls_weights_out, reg_targets_out, reg_weights_out) = self.execute(
         graph_fn, [anchor_means, groundtruth_box_corners])
    self.assertAllClose(cls_targets_out, exp_cls_targets)
    self.assertAllClose(cls_weights_out, exp_cls_weights)
    self.assertAllClose(reg_targets_out, exp_reg_targets)
    self.assertAllClose(reg_weights_out, exp_reg_weights)
    self.assertEquals(cls_targets_out.dtype, np.float32)
    self.assertEquals(cls_weights_out.dtype, np.float32)
    self.assertEquals(reg_targets_out.dtype, np.float32)
    self.assertEquals(reg_weights_out.dtype, np.float32) 
Example #28
Source File: target_assigner_test.py    From Person-Detection-and-Tracking with MIT License 5 votes vote down vote up
def test_assign_class_agnostic_with_ignored_matches(self):
    # Note: test is very similar to above. The third box matched with an IOU
    # of 0.35, which is between the matched and unmatched threshold. This means
    # That like above the expected classification targets are [1, 1, 0].
    # Unlike above, the third target is ignored and therefore expected
    # classification weights are [1, 1, 0].
    def graph_fn(anchor_means, groundtruth_box_corners):
      similarity_calc = region_similarity_calculator.IouSimilarity()
      matcher = argmax_matcher.ArgMaxMatcher(matched_threshold=0.5,
                                             unmatched_threshold=0.3)
      box_coder = mean_stddev_box_coder.MeanStddevBoxCoder(stddev=0.1)
      target_assigner = targetassigner.TargetAssigner(
          similarity_calc, matcher, box_coder, unmatched_cls_target=None)
      anchors_boxlist = box_list.BoxList(anchor_means)
      groundtruth_boxlist = box_list.BoxList(groundtruth_box_corners)
      result = target_assigner.assign(anchors_boxlist, groundtruth_boxlist)
      (cls_targets, cls_weights, reg_targets, reg_weights, _) = result
      return (cls_targets, cls_weights, reg_targets, reg_weights)

    anchor_means = np.array([[0.0, 0.0, 0.5, 0.5],
                             [0.5, 0.5, 1.0, 0.8],
                             [0.0, 0.5, .9, 1.0]], dtype=np.float32)
    groundtruth_box_corners = np.array([[0.0, 0.0, 0.5, 0.5],
                                        [0.5, 0.5, 0.9, 0.9]], dtype=np.float32)
    exp_cls_targets = [[1], [1], [0]]
    exp_cls_weights = [1, 1, 0]
    exp_reg_targets = [[0, 0, 0, 0],
                       [0, 0, -1, 1],
                       [0, 0, 0, 0]]
    exp_reg_weights = [1, 1, 0]
    (cls_targets_out,
     cls_weights_out, reg_targets_out, reg_weights_out) = self.execute(
         graph_fn, [anchor_means, groundtruth_box_corners])
    self.assertAllClose(cls_targets_out, exp_cls_targets)
    self.assertAllClose(cls_weights_out, exp_cls_weights)
    self.assertAllClose(reg_targets_out, exp_reg_targets)
    self.assertAllClose(reg_weights_out, exp_reg_weights)
    self.assertEquals(cls_targets_out.dtype, np.float32)
    self.assertEquals(cls_weights_out.dtype, np.float32)
    self.assertEquals(reg_targets_out.dtype, np.float32)
    self.assertEquals(reg_weights_out.dtype, np.float32) 
Example #29
Source File: region_similarity_calculator_builder_test.py    From HereIsWally with MIT License 5 votes vote down vote up
def testBuildIouSimilarityCalculator(self):
    similarity_calc_text_proto = """
      iou_similarity {
      }
    """
    similarity_calc_proto = sim_calc_pb2.RegionSimilarityCalculator()
    text_format.Merge(similarity_calc_text_proto, similarity_calc_proto)
    similarity_calc = region_similarity_calculator_builder.build(
        similarity_calc_proto)
    self.assertTrue(isinstance(similarity_calc,
                               region_similarity_calculator.IouSimilarity)) 
Example #30
Source File: region_similarity_calculator_builder.py    From HereIsWally with MIT License 5 votes vote down vote up
def build(region_similarity_calculator_config):
  """Builds region similarity calculator based on the configuration.

  Builds one of [IouSimilarity, IoaSimilarity, NegSqDistSimilarity] objects. See
  core/region_similarity_calculator.proto for details.

  Args:
    region_similarity_calculator_config: RegionSimilarityCalculator
      configuration proto.

  Returns:
    region_similarity_calculator: RegionSimilarityCalculator object.

  Raises:
    ValueError: On unknown region similarity calculator.
  """

  if not isinstance(
      region_similarity_calculator_config,
      region_similarity_calculator_pb2.RegionSimilarityCalculator):
    raise ValueError(
        'region_similarity_calculator_config not of type '
        'region_similarity_calculator_pb2.RegionsSimilarityCalculator')

  similarity_calculator = region_similarity_calculator_config.WhichOneof(
      'region_similarity')
  if similarity_calculator == 'iou_similarity':
    return region_similarity_calculator.IouSimilarity()
  if similarity_calculator == 'ioa_similarity':
    return region_similarity_calculator.IoaSimilarity()
  if similarity_calculator == 'neg_sq_dist_similarity':
    return region_similarity_calculator.NegSqDistSimilarity()

  raise ValueError('Unknown region similarity calculator.')