detnet.py 文件源码

def refine_boxes(boxes, num_iters, step, sigma):
  assert num_iters > 1

  def iteration(prev, i):
    state_prev, _ = prev
    features = state_prev / sigma
    dists = tf.nn.relu(nnutil.pairwise_distance(features))
    weights = tf.exp(-dists)
    confidence = tf.reduce_sum(weights, [1], True)
    weights = weights / confidence
    state_up = tf.matmul(weights, state_prev)
    return (1.0 - step) * state_prev + step * state_up, confidence

  states = tf.scan(iteration,
                   tf.range(0, num_iters),
                   initializer=(boxes, boxes[:,0:1]))
  return states[0][-1], states[1][-1]