def __call__(self, model_output: List[ModelOutput]) -> List[SampledData]:
        """
        Transform model output into ground truth data through sampling

        Args:
          model_output (Dict[str, Any]): model output
        Returns:
          Dict[str, Any]: sampled data
        """
        for model_output_i in model_output:
            instances: Instances = model_output_i["instances"]
            # transform data in each field
            for _, sampler in self._samplers.items():
                if not instances.has(sampler.src) or sampler.dst is None:
                    continue
                if sampler.func is None:
                    instances.set(sampler.dst, instances.get(sampler.src))
                else:
                    instances.set(sampler.dst, sampler.func(instances))
            # delete model output data that was transformed
            for _, sampler in self._samplers.items():
                if sampler.src != sampler.dst and instances.has(sampler.src):
                    instances.remove(sampler.src)
            model_output_i["dataset"] = self.dataset_name
        return model_output

        Transform model output into ground truth data through sampling

        Args:
          model_output (Dict[str, Any]): model output
        Returns:
          Dict[str, Any]: sampled data
        
EVA-02/det/projects/DensePose/densepose/data/samplers/prediction_to_gt.py