Function test_create_center_net_model has a Cognitive Complexity of 8 (exceeds 5 allowed). Consider refactoring.

Open

  def test_create_center_net_model(self, customize_head_params):
    """Test building a CenterNet model from proto txt."""
    proto_txt = """
      center_net {
        num_classes: 10

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Avoid deeply nested control flow statements.

Open

          if cat['name'] == class_label:
            category = cat
            break
        if not category:

Function result_dict_for_single_example has 6 arguments (exceeds 4 allowed). Consider refactoring.

Open

def result_dict_for_single_example(image,

Function _create_learning_rate has a Cognitive Complexity of 8 (exceeds 5 allowed). Consider refactoring.

Open

def _create_learning_rate(learning_rate_config, global_step=None):
  """Create optimizer learning rate based on config.

  Args:
    learning_rate_config: A LearningRate proto message.

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Function main has a Cognitive Complexity of 8 (exceeds 5 allowed). Consider refactoring.

Open

def main(_):
  pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
  with tf.gfile.GFile(FLAGS.pipeline_config_path, 'r') as f:
    text_format.Merge(f.read(), pipeline_config)
  text_format.Merge(FLAGS.config_override, pipeline_config)

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Function add_single_ground_truth_image_info has a Cognitive Complexity of 8 (exceeds 5 allowed). Consider refactoring.

Open

  def add_single_ground_truth_image_info(self,
                                         image_id,
                                         groundtruth_dict):
    """Adds groundtruth for a single image to be used for evaluation.

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Avoid deeply nested control flow statements.

Open

            for head_name in sorted_keys:
              if head_name == CLASS_PREDICTIONS_WITH_BACKGROUND:
                head_obj = self._class_prediction_head
              else:
                head_obj = self._other_heads[head_name]

Function _generate_sequence_examples has 6 arguments (exceeds 4 allowed). Consider refactoring.

Open

  def _generate_sequence_examples(self, annotation_file, excluded_file,

Avoid deeply nested control flow statements.

Open

          if int(visibility) > 0:
            num_valid_keypoints = num_valid_keypoints + 1
        export_dict['keypoints'] = coco_keypoints

Avoid deeply nested control flow statements.

Open

            for row in frame_annotations[(media_id, windowed_timestamp)]:
              if len(row) > 2 and int(row['action_label']) in label_map:
                boxes.append([float(row['ymin']), float(row['xmin']),
                              float(row['ymax']), float(row['xmax'])])
                labels.append(int(row['action_label']))

Function __init__ has 6 arguments (exceeds 4 allowed). Consider refactoring.

Open

  def __init__(self,

Avoid deeply nested control flow statements.

Open

            for head_name in sorted_keys:
              if head_name == BOX_ENCODINGS:
                head_obj = self._box_prediction_head
              elif head_name == CLASS_PREDICTIONS_WITH_BACKGROUND:
                head_obj = self._class_prediction_head

Function ExportDetectionsToCOCO has 6 arguments (exceeds 4 allowed). Consider refactoring.

Open

def ExportDetectionsToCOCO(image_ids,

Avoid deeply nested control flow statements.

Open

            if all_metrics_per_category:
              for metric_name, index in COCO_METRIC_NAMES_AND_INDEX:
                metric_key = '{} BySuperCategory/{}'.format(metric_name, key)
                super_category_ap[metric_key] += (
                    self.category_stats[index][category_index])

Avoid deeply nested control flow statements.

Open

            if (media_id, windowed_timestamp + frames_mv) in frame_excluded:
              frames_excluded_count += 1
          middle_frame_time += frames_mv

Function __init__ has 6 arguments (exceeds 4 allowed). Consider refactoring.

Open

  def __init__(self,

Function LoadAnnotations has a Cognitive Complexity of 8 (exceeds 5 allowed). Consider refactoring.

Open

  def LoadAnnotations(self, annotations):
    """Load annotations dictionary into COCO datastructure.

    See http://mscoco.org/dataset/#format for a description of the annotations
    format.  As above, this function replicates the default behavior of the API

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Avoid deeply nested control flow statements.

Open

            if (media_id, windowed_timestamp) in frame_excluded:
              end_time += 1
              windowed_timestamp += 1
              logging.info('Ignoring and skipping excluded frame.')
              continue

Avoid deeply nested control flow statements.

Open

            if len(row) > 2 and int(row['action_label']) in label_map:
              xmins.append(float(row['xmin']))
              xmaxs.append(float(row['xmax']))
              ymins.append(float(row['ymin']))
              ymaxs.append(float(row['ymax']))

Avoid deeply nested control flow statements.

Open

            if self._share_prediction_tower:
              box_tower_scope = 'PredictionTower'
            else:
              box_tower_scope = 'BoxPredictionTower'
            box_tower_feature = self._compute_base_tower(