fcd690b14b04c11e7f25b9d473db056c4b7947b3,official/vision/keras_cv/ops/iou_similarity.py,,iou,#Any#Any#,59

Before Change

  intersections = intersection(box1, box2)
  areas1 = area(box1)
  areas2 = area(box2)
  unions = (
      tf.expand_dims(areas1, 1) + tf.expand_dims(areas2, 0) - intersections)
  return tf.where(
      tf.equal(intersections, 0.0), tf.zeros_like(intersections),
      tf.truediv(intersections, unions))

After Change

  Returns:
    a Tensor with shape [N, M] representing pairwise iou scores.
  
  with tf.name_scope("IOU"):
    intersections = intersection(gt_boxes, boxes)
    gt_boxes_areas = area(gt_boxes)
    boxes_areas = area(boxes)
    boxes_rank = len(boxes_areas.shape)
    boxes_axis = 1 if (boxes_rank == 2) else 0
    gt_boxes_areas = tf.expand_dims(gt_boxes_areas, -1)
    boxes_areas = tf.expand_dims(boxes_areas, boxes_axis)
    unions = gt_boxes_areas + boxes_areas
    unions = unions - intersections
    return tf.where(
        tf.equal(intersections, 0.0), tf.zeros_like(intersections),
        tf.truediv(intersections, unions))


class IouSimilarity():
  Class to compute similarity based on Intersection over Union (IOU) metric.

  

Instances