|
| | icp_advance_api.cloud_dimension = ref.getEuclideanDim() |
| |
| string | icp_advance_api.complete_file_name = f"{output_base_directory + test_base}_{output_base_file}_complete_transfo.txt" |
| |
| string | icp_advance_api.config_file = "../data/default.yaml" |
| |
| | icp_advance_api.data = DP.load('../data/car_cloud401.csv') |
| |
| | icp_advance_api.data_out = DP(initialized_data) |
| |
| | icp_advance_api.dim = matched_points.reading.getEuclideanDim() |
| |
| | icp_advance_api.dist = np.linalg.norm(matched_read - matched_ref, axis=0) |
| |
| | icp_advance_api.DP = PM.DataPoints |
| |
| | icp_advance_api.haussdorff_dist = max(max_dist1, max_dist2) |
| |
| | icp_advance_api.haussdorff_quantile_dist = max(max_dist_robust1, max_dist_robust2) |
| |
| | icp_advance_api.icp = PM.ICP() |
| |
| string | icp_advance_api.icp_file_name = f"{output_base_directory + test_base}_{output_base_file}_icp.transfo.txt" |
| |
| string | icp_advance_api.init_file_name = f"{output_base_directory + test_base}_{output_base_file}_init_transfo.txt" |
| |
| string | icp_advance_api.init_rotation = "1,0,0;0,1,0;0,0,1" if is_3D else "1,0;0,1" |
| |
| | icp_advance_api.init_transfo = np.matmul(translation, rotation) |
| |
| string | icp_advance_api.init_translation = "0,0,0" if is_3D else "0,0" |
| |
| | icp_advance_api.initialized_data = rigid_trans.compute(data, init_transfo) |
| |
| bool | icp_advance_api.is_3D = True |
| |
| bool | icp_advance_api.is_transfo_saved = False |
| |
| bool | icp_advance_api.is_verbose = True |
| |
| | icp_advance_api.match_ratio = icp.errorMinimizer.getWeightedPointUsedRatio() |
| |
| | icp_advance_api.matched_points = PM.ErrorMinimizer.ErrorElements(data_out, ref, outlier_weights, matches) |
| |
| | icp_advance_api.matched_read = matched_points.reading.features[:dim] |
| |
| | icp_advance_api.matched_ref = matched_points.reference.features[:dim] |
| |
| | icp_advance_api.matcher_Hausdorff = PM.get().MatcherRegistrar.create("KDTreeMatcher", params) |
| |
| | icp_advance_api.matches = matcher_Hausdorff.findClosests(data_out) |
| |
| | icp_advance_api.max_dist1 = matches.getDistsQuantile(1.0) |
| |
| | icp_advance_api.max_dist2 = matches.getDistsQuantile(1.0) |
| |
| | icp_advance_api.max_dist_robust1 = matches.getDistsQuantile(0.85) |
| |
| | icp_advance_api.max_dist_robust2 = matches.getDistsQuantile(0.85) |
| |
| | icp_advance_api.mean_dist = dist.sum() / nb_matched_points |
| |
| | icp_advance_api.nb_matched_points = matched_points.reading.getNbPoints() |
| |
| | icp_advance_api.outlier_weights = icp.outlierFilters.compute(data_out, ref, matches) |
| |
| string | icp_advance_api.output_base_directory = "tests/icp_advance_api/" |
| |
| string | icp_advance_api.output_base_file = "test" |
| |
| | icp_advance_api.Parameters = pms.Parametrizable.Parameters |
| |
| | icp_advance_api.params = Parameters() |
| |
| | icp_advance_api.PM = pm.PointMatcher |
| |
| | icp_advance_api.ref = DP.load('../data/car_cloud400.csv') |
| |
| | icp_advance_api.rigid_trans = PM.get().TransformationRegistrar.create("RigidTransformation") |
| |
| | icp_advance_api.rotation = parse_rotation(init_rotation, cloud_dimension) |
| |
| | icp_advance_api.T = icp(initialized_data, ref) |
| |
| string | icp_advance_api.test_base = "3D" |
| |
| | icp_advance_api.translation = parse_translation(init_translation, cloud_dimension) |
| |