def __call__(self, output, center, scale):
        """
        Args:
            output (numpy.ndarray): numpy.ndarray([batch_size, num_joints, 3]), keypoints coords
            scale (numpy.ndarray): The scale factor
        Returns:
            preds: numpy.ndarray([batch_size, num_joints, 3]), keypoints coords
        """

        preds = output.numpy().copy()

        # Transform back
        for i in range(output.shape[0]):  # batch_size
            preds[i][:, 0] = preds[i][:, 0] * scale[i][0]
            preds[i][:, 1] = preds[i][:, 1] * scale[i][1]

        return preds

        Args:
            output (numpy.ndarray): numpy.ndarray([batch_size, num_joints, 3]), keypoints coords
            scale (numpy.ndarray): The scale factor
        Returns:
            preds: numpy.ndarray([batch_size, num_joints, 3]), keypoints coords
        
ppdet/modeling/architectures/keypoint_hrnet.py