377989c11903f69f042fee717ce6be66bd6eb43a,niftynet/layer/loss_segmentation.py,,sensitivity_specificity_loss,#Any#Any#Any#Any#,182

Before Change

        // raise NotImplementedError
        tf.logging.warning("Weight map specified but not used.")

    ground_truth = tf.to_int64(ground_truth)
    n_voxels = ground_truth.shape[0].value
    n_classes = prediction.shape[1].value
    ids = tf.constant(np.arange(n_voxels), dtype=tf.int64)
    ids = tf.stack([ids, ground_truth], axis=1)

    one_hot = tf.SparseTensor(indices=ids,
                              values=tf.ones([n_voxels], dtype=tf.float32),
                              dense_shape=[n_voxels, n_classes])
    one_hot = tf.sparse_tensor_to_dense(one_hot)
    // value of unity everywhere except for the previous "hot" locations
    one_cold = 1 - one_hot

After Change

        // raise NotImplementedError
        tf.logging.warning("Weight map specified but not used.")

    prediction = tf.cast(prediction, tf.float32)
    one_hot = labels_to_one_hot(ground_truth, tf.shape(prediction))

    one_hot = tf.sparse_tensor_to_dense(one_hot)
    // value of unity everywhere except for the previous "hot" locations

Instances