nerve_net.py 文件源码

def loss_image(prediction, mask):
  """Calc loss for predition on image of mask.
  Args.
    inputs: prediction image 
    mask: true image 

  Return:
    error: loss value
  """
  print(prediction.get_shape())
  print(mask.get_shape())
  #mask = tf.flatten(mask)
  #prediction = tf.flatten(prediction)
  intersection = tf.reduce_sum(prediction * mask)
  loss = -(2. * intersection + 1.) / (tf.reduce_sum(mask) + tf.reduce_sum(prediction) + 1.)
  tf.scalar_summary('loss', loss)
  return loss