def __call__(self, instances: Instances) -> DensePoseList:
        """
        Convert DensePose predictions (an instance of `DensePoseChartPredictorOutput`)
        into DensePose annotations data (an instance of `DensePoseList`)
        """
        boxes_xyxy_abs = instances.pred_boxes.tensor.clone().cpu()
        boxes_xywh_abs = BoxMode.convert(boxes_xyxy_abs, BoxMode.XYXY_ABS, BoxMode.XYWH_ABS)
        dp_datas = []
        for i in range(len(boxes_xywh_abs)):
            annotation_i = self._sample(instances[i], make_int_box(boxes_xywh_abs[i]))
            annotation_i[DensePoseDataRelative.S_KEY] = self._resample_mask(  # pyre-ignore[6]
                instances[i].pred_densepose
            )
            dp_datas.append(DensePoseDataRelative(annotation_i))
        # create densepose annotations on CPU
        dp_list = DensePoseList(dp_datas, boxes_xyxy_abs, instances.image_size)
        return dp_list

        Convert DensePose predictions (an instance of `DensePoseChartPredictorOutput`)
        into DensePose annotations data (an instance of `DensePoseList`)
        
EVA-02/det/projects/DensePose/densepose/data/samplers/densepose_base.py