|
| | icp.cloud_dimension = ref.getEuclideanDim() |
| |
| string | icp.complete_file_name = f"{output_base_directory + test_base}_{output_base_file}_complete_transfo.txt" |
| |
| string | icp.config_file = "../data/default.yaml" |
| |
| | icp.data = DP(DP.load('../data/car_cloud401.csv')) |
| |
| | icp.data_out = DP(initialized_data) |
| |
| | icp.DP = PM.DataPoints |
| |
| | icp.icp = PM.ICP() |
| |
| string | icp.icp_file_name = f"{output_base_directory + test_base}_{output_base_file}_icp.transfo.txt" |
| |
| string | icp.init_file_name = f"{output_base_directory + test_base}_{output_base_file}_init_transfo.txt" |
| |
| string | icp.init_rotation = "1,0,0;0,1,0;0,0,1" if is_3D else "1,0;0,1" |
| |
| | icp.init_transfo = np.matmul(translation, rotation) |
| |
| string | icp.init_translation = "0,0,0" if is_3D else "0,0" |
| |
| | icp.initialized_data = rigid_trans.compute(data, init_transfo) |
| |
| bool | icp.is_3D = True |
| |
| bool | icp.is_transfo_saved = False |
| |
| bool | icp.is_verbose = True |
| |
| string | icp.output_base_directory = "tests/icp/" |
| |
| string | icp.output_base_file = "test" |
| |
| | icp.PM = pm.PointMatcher |
| |
| | icp.ref = DP(DP.load('../data/car_cloud400.csv')) |
| |
| | icp.rigid_trans = PM.get().TransformationRegistrar.create("RigidTransformation") |
| |
| | icp.rotation = parse_rotation(init_rotation, cloud_dimension) |
| |
| | icp.T = icp(initialized_data, ref) |
| |
| string | icp.test_base = "3D" |
| |
| | icp.translation = parse_translation(init_translation, cloud_dimension) |
| |