def METHOD_NAME(self, annotation, prediction):
    for annotation_, prediction_ in zip(annotation, prediction):
        height, width, _ = self.image_size
        x_start, y_start = 0, 0
        resized_box = annotation_.metadata.get('rect')
        x_start, y_start, x_max, y_max = resized_box
        width = x_max - x_start
        height = y_max - y_start
        center, scale = self._xywh2cs(x_start, y_start, width, height)
        pred, _ = self._keypoints_from_heatmaps(np.array(prediction_.heatmap), [center], [scale])
        detLms_x = []
        detLms_y = []
        for pr in pred[0]:
            detLms_x.append(pr[0])
            detLms_y.append(pr[1])
        prediction_.x_values = detLms_x
        prediction_.y_values = detLms_y
    return annotation, prediction