(anchors, bboxes)
return ious, indices
Compute iou of two batch of boxes. Box format '[y_min, x_min, y_max, x_max]'.
  Args:
    anchors: know shape
    bboxes: dynamic shape
  Return:
    ious: 2-D with shape '[num_bboxes, num_anchors]'
    indices: [num_bboxes, 1]
Compute iou of two batch of boxes. Box format '[y_min, x_min, y_max, x_max]'.
  Args:
    anchors: know shape
    bboxes: dynamic shape
  Return:
    ious: 2-D with shape '[num_bboxes, num_anchors]'
    indices: [num_bboxes, 1]
Compute iou of two batch of boxes . Box format [ y_min x_min y_max x_max ] . Args : anchors : know shape bboxes : dynamic shape Return : ious : 2 - D with shape [ num_bboxes num_anchors ] indices : [ num_bboxes 1 ]
def batch_iou_(anchors, bboxes):
  """ Compute iou of two batch of boxes. Box format '[y_min, x_min, y_max, x_max]'.
  Args:
    anchors: know shape
    bboxes: dynamic shape
  Return:
    ious: 2-D with shape '[num_bboxes, num_anchors]'
    indices: [num_bboxes, 1]
  """
  num_anchors = anchors.get_shape().as_list()[0]
  ious_list = []
  for i in range(num_anchors):
    anchor = anchors[i]
    _ious = batch_iou(bboxes, anchor)
    ious_list.append(_ious)
  ious = tf.stack(ious_list, axis=0)
  ious = tf.transpose(ious)

  indices = tf.arg_max(ious, dimension=1)

  return ious, indices
def batch_iou_ ( anchors , bboxes ) : num_anchors = anchors . get_shape ( ) . as_list ( ) [ 0 ] ious_list = [ ] for i in range ( num_anchors ) : anchor = anchors [ i ] _ious = batch_iou ( bboxes , anchor ) ious_list . append ( _ious ) ious = tf . stack ( ious_list , axis = 0 ) ious = tf . transpose ( ious ) indices = tf . arg_max ( ious , dimension = 1 ) return ious , indices