Method build_full_info_json

mbench/__init__.py:256–319

Build the full information JSON file for evaluation Args: evaluation_path: Path containing dimension folders with motion files name: Name for the evaluation run dimension_list: List of dimensions to evaluate **kwargs: Addition

(self, evaluation_path: str, name: str, 
                           dimension_list: List[str], **kwargs)

        print(f'Successfully rendered {rendered_count} unique motions across all categories')

    def build_full_info_json(self, evaluation_path: str, name: str, 
                           dimension_list: List[str], **kwargs) -> str:
        """
        Build the full information JSON file for evaluation
        
        Args:
            evaluation_path: Path containing dimension folders with motion files
            name: Name for the evaluation run
            dimension_list: List of dimensions to evaluate
            **kwargs: Additional arguments
            
        Returns:
            Path to the created full info JSON file
        """
        cur_full_info_list = []
        mbench_dir = self._get_mbench_dir(evaluation_path)
        
        # Separate video-based, pose-quality (needs SMPLify .pt), and motion-quality (needs .npy) dimensions  
        video_dimension_list = ["Motion_Condition_Consistency", "Motion_Generalizability"]
        pose_quality_dimension_list = ["Pose_Quality", "Body_Penetration"]  # Need .pt with pose/vertices
        
        video_dimensions = [dim for dim in dimension_list if dim in video_dimension_list]
        pose_dimensions = [dim for dim in dimension_list if dim in pose_quality_dimension_list]
        motion_dimensions = [dim for dim in dimension_list if dim not in video_dimensions and dim not in pose_dimensions]
        
        full_info_list = load_json(self.full_info_dir)
        for prompt_dict in full_info_list:
            if prompt_dict["dimension"] in video_dimensions: 
                candidates = [
                    mbench_dir / f'{prompt_dict["id"]}.mp4',
                    self._find_source_video_path(evaluation_path, self.get_category(prompt_dict["dimension"]), prompt_dict["id"])
                ]
            elif prompt_dict["dimension"] in pose_dimensions:
                # For pose_quality dimensions, need .pt files with pose/vertices (from SMPLify)
                candidates = [
                    mbench_dir / f'{prompt_dict["id"]}.pt',   # SMPLify output with pose/vertices
                ]
            elif prompt_dict["dimension"] in motion_dimensions:
                # For motion_quality dimensions, check .npy first (raw joints), then .pt
                candidates = [
                    mbench_dir / f'{prompt_dict["id"]}.npy',  # Raw joints from organize script
                    mbench_dir / f'{prompt_dict["id"]}.pt',   # Processed from SMPLify
                ]
            else:
                candidates = []

            evaluation_file = None
            for candidate in candidates:
                if candidate and Path(candidate).exists():
                    evaluation_file = str(candidate)
                    break

            if evaluation_file is None:
                print(f'WARNING: No evaluation file found for ID {prompt_dict["id"]} and dimension {prompt_dict["dimension"]}')
                continue

            prompt_copy = prompt_dict.copy()
            prompt_copy["evaluation_file"] = evaluation_file