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