b6db687ec336e896ea8d267c14679318f266a9a2,unet3d/model.py,,unet_model_3d,#,17

Before Change

    act = Activation("sigmoid")(final_convolution)
    model = Model(inputs=inputs, outputs=act)

    model.compile(optimizer=Adam(lr=initial_learning_rate), loss=dice_coef_loss,
                  metrics=[dice_coef] + [get_label_dice_coefficient_function(index) for index in range(n_labels)])

    return model

After Change

        else:
            metrics = label_wise_dice_metrics

    model.compile(optimizer=Adam(lr=initial_learning_rate), loss=dice_coef_loss, metrics=metrics)
    return model


def dice_coef(y_true, y_pred, smooth=1.):

Instances