import time import copy import open3d as o3d from tools import metrics def icp_reg_and_eval(source, target, method, max_correspondence_distance, init_transformation, gt_transformation): """ Perform registration and evaluation for a given ICP-based method. Args: source (open3d.geometry.PointCloud): The source point cloud. target (open3d.geometry.PointCloud): The target point cloud. method (str): The registration method ('p2point', 'p2plane', 'robust', 'gicp', 'fgr'). max_correspondence_distance (float): The maximum correspondence distance. init_transformation (np.ndarray): The initial transformation matrix. gt_transformation (np.ndarray): The ground truth transformation matrix. Returns: result (np.ndarray): The evaluation results (rmse, rotation_error, translation_error, computation_time). """ if method == 'p2point': start_time = time.time() result = o3d.pipelines.registration.registration_icp( source, target, max_correspondence_distance, init_transformation, o3d.pipelines.registration.TransformationEstimationPointToPoint()) end_time = time.time() computation_time = end_time - start_time elif method == 'p2plane': source.estimate_normals(search_param=o3d.geometry.KDTreeSearchParamHybrid(radius=0.1, max_nn=30)) target.estimate_normals(search_param=o3d.geometry.KDTreeSearchParamHybrid(radius=0.1, max_nn=30)) start_time = time.time() result = o3d.pipelines.registration.registration_icp( source, target, max_correspondence_distance, init_transformation, o3d.pipelines.registration.TransformationEstimationPointToPlane()) end_time = time.time() computation_time = end_time - start_time elif method == 'robust': loss = o3d.pipelines.registration.TukeyLoss(k=0.5) start_time = time.time() result = o3d.pipelines.registration.registration_icp( source, target, max_correspondence_distance, init_transformation, o3d.pipelines.registration.TransformationEstimationPointToPlane(loss)) end_time = time.time() computation_time = end_time - start_time elif method == 'gicp': # Define convergence criteria criteria = o3d.pipelines.registration.ICPConvergenceCriteria( relative_fitness=1e-6, relative_rmse=1e-6, max_iteration=50) #default: relative_fitness=1e-6, relative_rmse=1e-6, max_iteration=30 estimation_method = o3d.pipelines.registration.TransformationEstimationForGeneralizedICP(epsilon=0.001) start_time = time.time() result = o3d.pipelines.registration.registration_generalized_icp( source, target, max_correspondence_distance, init_transformation,estimation_method, criteria) end_time = time.time() computation_time = end_time - start_time else: raise ValueError(f"Unknown method: {method}") # Apply transformation pc_result = copy.deepcopy(source).transform(result.transformation) # Evaluation evaluation_results = metrics.all_evaluations(source, target, pc_result, computation_time, gt_transformation, result, corres= None) return pc_result, evaluation_results