Siamese Network

new_triplet_loss.py

def triplet_loss(y_true, y_pred, alpha = ALPHA):
    """
    Implementation of the triplet loss function

    Arguments:
    y_true -- true labels, required when you define a loss in Keras, you don't need it in this function.
    y_pred -- python list containing three objects:
            anchor -- the encodings for the anchor data
            positive -- the encodings for the positive data (similar to anchor)
            negative -- the encodings for the negative data (different from anchor)

    Returns:
    loss -- real number, value of the loss

    """

    anchor = y_pred[:,0:3]
    positive = y_pred[:,3:6]
    negative = y_pred[:,6:9]

    # distance between the anchor and the positive
    pos_dist = K.sum(K.square(anchor-positive),axis=1)

    # distance between the anchor and the negative
    neg_dist = K.sum(K.square(anchor-negative),axis=1)

    # compute loss
    basic_loss = pos_dist-neg_dist+alpha
    loss = K.maximum(basic_loss,0.0)
 
    return loss