osvos.py 文件源码

def class_balanced_cross_entropy_loss_theoretical(output, label):
    """Theoretical version of the class balanced cross entropy loss to train the network (Produces unstable results)
    Args:
    output: Output of the network
    label: Ground truth label
    Returns:
    Tensor that evaluates the loss
    """
    output = tf.nn.sigmoid(output)

    labels_pos = tf.cast(tf.greater(label, 0), tf.float32)
    labels_neg = tf.cast(tf.less(label, 1), tf.float32)

    num_labels_pos = tf.reduce_sum(labels_pos)
    num_labels_neg = tf.reduce_sum(labels_neg)
    num_total = num_labels_pos + num_labels_neg

    loss_pos = tf.reduce_sum(tf.multiply(labels_pos, tf.log(output + 0.00001)))
    loss_neg = tf.reduce_sum(tf.multiply(labels_neg, tf.log(1 - output + 0.00001)))

    final_loss = -num_labels_neg / num_total * loss_pos - num_labels_pos / num_total * loss_neg

    return final_loss