loss.py

class weighted_categorical_crossentropy:
    def __init__(self, weights):
        self.weights = weights
        self.__name__ = 'wcentroid_loss'

    def __call__(self, y_true, y_pred):
        class0 = K.ones_like(y_pred)[:, :, :, 0] * self.weights[0]
        class1 = K.ones_like(y_pred)[:, :, :, 0] * self.weights[1]
        x = K.tf.where(y_true[:, :, :, 0] > 0, class0, class1)
        result = x * K.categorical_crossentropy(y_pred, y_true)
        return result