def __init__()

in 3_predict/visualization_utils.py [0:0]

• 16 lines of code
• 1 McCabe index (conditional complexity)

  def __init__(self,
               category_index,
               max_examples_to_draw=5,
               max_boxes_to_draw=20,
               min_score_thresh=0.2,
               use_normalized_coordinates=True,
               summary_name_prefix='evaluation_image',
               keypoint_edges=None):
    """Creates an EvalMetricOpsVisualization.

    Args:
      category_index: A category index (dictionary) produced from a labelmap.
      max_examples_to_draw: The maximum number of example summaries to produce.
      max_boxes_to_draw: The maximum number of boxes to draw for detections.
      min_score_thresh: The minimum score threshold for showing detections.
      use_normalized_coordinates: Whether to assume boxes and keypoints are in
        normalized coordinates (as opposed to absolute coordinates).
        Default is True.
      summary_name_prefix: A string prefix for each image summary.
      keypoint_edges: A list of tuples with keypoint indices that specify which
        keypoints should be connected by an edge, e.g. [(0, 1), (2, 4)] draws
        edges from keypoint 0 to 1 and from keypoint 2 to 4.
    """

    self._category_index = category_index
    self._max_examples_to_draw = max_examples_to_draw
    self._max_boxes_to_draw = max_boxes_to_draw
    self._min_score_thresh = min_score_thresh
    self._use_normalized_coordinates = use_normalized_coordinates
    self._summary_name_prefix = summary_name_prefix
    self._keypoint_edges = keypoint_edges
    self._images = []