face_point_with_decay.py 文件源码

def loss(bbox_widths, preds, points, batch_size=100):
  """loss function based on paper, returns a tensor of batch_size.
  """
  diff = tf.squared_difference(preds, points)
  dist = []
  for i in range(5):
    dist.append(tf.reshape(tf.reduce_sum(diff[:,2*i:2*i+2], 1), [batch_size, 1]))
  dist = tf.reduce_sum(tf.sqrt(tf.concat(1, dist)), 1)
  error = tf.div(dist, bbox_widths)
  return error