Function compute_dynamic_degree

mbench/motion_quality.py:406–446

Compute the dynamic degree of the motion based on the average velocity of the joints.

(full_info_path: str, device: str, **kwargs)

    }

def compute_dynamic_degree(full_info_path: str, device: str, **kwargs):
    """
    Compute the dynamic degree of the motion based on the average velocity of the joints.
    """
    prompt_dict_ls = load_dimension_info(full_info_path, dimension='Dynamic_Degree')
    
    dynamic_degree_list = []
    per_motion_metrics = []
    
    for prompt_dict in tqdm(prompt_dict_ls):
        evaluation_file = prompt_dict["evaluation_file"]
        pred_joints = load_joints(evaluation_file, device)

        
        # Global dynamic degree
        velocity = torch.norm(pred_joints[1:] - pred_joints[:-1], dim=2)  # Shape: (T-1, 24)
        global_dynamic = velocity.mean()
        
        # Local dynamic degree (remove global translation)
        local_joints = remove_global_translation(pred_joints)
        local_velocity = torch.norm(local_joints[1:] - local_joints[:-1], dim=2)  # Shape: (T-1, 24)
        local_dynamic = local_velocity.mean()
        
        # Combined dynamic degree
        combined_dynamic = global_dynamic + local_dynamic
        dynamic_value = combined_dynamic.item()
        dynamic_degree_list.append(dynamic_value)
        per_motion_metrics.append(
            {
                "id": prompt_dict.get("id"),
                "prompt": prompt_dict.get("prompt"),
                "value": dynamic_value,
                "evaluation_file": evaluation_file,
                "motion_duration": prompt_dict.get("motion_duration"),
            }
        )
    
    return {
        "aggregate": summarize_scores(dynamic_degree_list),
        "per_motion": per_motion_metrics,
    }