vrm_system = VRMSimulationModel(assembly_type, assembly_kccs,
assembly_kpis, part_name, part_type,
voxel_dim, voxel_channels, point_dim,
aritifical_noise)
deploy_model = BayesDeployModel()
#Generate Paths
train_path = '../trained_models/' + part_type
model_path = train_path + '/model' + '/Bayes_trained_model_0'
logs_path = train_path + '/logs'
deploy_path = train_path + '/deploy/'
plots_path = train_path + '/plots/'
#Voxel Mapping File
get_data = GetTrainData()
print('Importing and Preprocessing Cloud-of-Point Data')
dataset = []
dataset.append(get_data.data_import(file_names_x, data_folder))
dataset.append(get_data.data_import(file_names_y, data_folder))
dataset.append(get_data.data_import(file_names_z, data_folder))
point_index = get_data.load_mapping_index(mapping_index)
#Make an Object of the Measurement System Class
measurement_system = HexagonWlsScanner(data_type, application,
system_noise, part_type,
data_format)
#Make an Object of the Assembly System Class
assembly_system = PartType(assembly_type, assembly_kccs, assembly_kpis,
part_name, part_type, voxel_dim, voxel_channels,
logs_path = train_path + '/logs'
pathlib.Path(logs_path).mkdir(parents=True, exist_ok=True)
plots_path = train_path + '/plots'
pathlib.Path(plots_path).mkdir(parents=True, exist_ok=True)
# In[7]:
#Objects of Measurement System, Assembly System, Get Inference Data
print('Initializing the Assembly System and Measurement System....')
measurement_system = HexagonWlsScanner(data_type, application, system_noise,
part_type, data_format)
vrm_system = VRMSimulationModel(assembly_type, assembly_kccs, assembly_kpis,
part_name, part_type, voxel_dim,
voxel_channels, point_dim, aritifical_noise)
get_data = GetTrainData()
kcc_sublist = cftrain.encode_decode_params['kcc_sublist']
output_heads = cftrain.encode_decode_params['output_heads']
encode_decode_multi_output_construct = config.encode_decode_multi_output_construct
if (output_heads == len(encode_decode_multi_output_construct)):
print("Valid Output Stages and heads")
else:
print("Inconsistent model setting")
print("KCC sub-listing: ", kcc_sublist)
#Check for KCC sub-listing
if (kcc_sublist != 0):
output_dimension = len(kcc_sublist)
pathlib.Path(plots_path).mkdir(parents=True, exist_ok=True)
deployment_path = train_path + '/deploy'
pathlib.Path(deployment_path).mkdir(parents=True, exist_ok=True)
#Objects of Measurement System, Assembly System, Get Inference Data
print('Initializing the Assembly System and Measurement System....')
measurement_system = HexagonWlsScanner(data_type, application,
system_noise, part_type,
data_format)
vrm_system = VRMSimulationModel(assembly_type, assembly_kccs,
assembly_kpis, part_name, part_type,
voxel_dim, voxel_channels, point_dim,
aritifical_noise)
get_data = GetTrainData()
#print(input_conv_data.shape,kcc_subset_dump.shape)
print('Building Unet Model')
kcc_sublist = cftrain.encode_decode_params['kcc_sublist']
print("KCC sub-listing: ", kcc_sublist)
#Check for KCC sub-listing
if (kcc_sublist != 0):
output_dimension = len(kcc_sublist)
else:
output_dimension = assembly_kccs
print("Process Parameter Dimension: ", output_dimension)
pathlib.Path(plots_path).mkdir(parents=True, exist_ok=True)
deployment_path = train_path + '/deploy'
pathlib.Path(deployment_path).mkdir(parents=True, exist_ok=True)
#Objects of Measurement System, Assembly System, Get Inference Data
print('Initializing the Assembly System and Measurement System....')
measurement_system = HexagonWlsScanner(data_type, application,
system_noise, part_type,
data_format)
vrm_system = VRMSimulationModel(assembly_type, assembly_kccs,
assembly_kpis, part_name, part_type,
voxel_dim, voxel_channels, point_dim,
aritifical_noise)
get_data = GetTrainData()
#print(input_conv_data.shape,kcc_subset_dump.shape)
print('Building 3D CNN model')
output_dimension = assembly_kccs
dl_model = Multi_Head_DLModel(model_type, assembly_stages,
output_dimension, categorical_kccs)
model = dl_model.multi_head_standard_cnn_model_3d(voxel_dim,
voxel_channels)
print('Importing data')
point_index = get_data.load_mapping_index(mapping_index)
kcc_dataset = get_data.data_import(kcc_files, kcc_folder)
kmc_path = train_path + '/kmc'
pathlib.Path(kmc_path).mkdir(parents=True, exist_ok=True)
kmc_plot_path = kmc_path + '/plots'
pathlib.Path(kmc_plot_path).mkdir(parents=True, exist_ok=True)
print('Initializing the Assembly System and Measurement System....')
measurement_system = HexagonWlsScanner(data_type, application,
system_noise, part_type,
data_format)
vrm_system = VRMSimulationModel(assembly_type, assembly_kccs,
assembly_kpis, part_name, part_type,
voxel_dim, voxel_channels, point_dim,
aritifical_noise)
get_data = GetTrainData()
print('Importing and preprocessing Cloud-of-Point Data')
dataset = []
dataset.append((get_data.data_import(file_names_x,
data_folder)).iloc[:, 0:point_dim])
dataset.append((get_data.data_import(file_names_y,
data_folder)).iloc[:, 0:point_dim])
dataset.append((get_data.data_import(file_names_z,
data_folder)).iloc[:, 0:point_dim])
kcc_dataset = get_data.data_import(kcc_files, kcc_folder)
point_index = get_data.load_mapping_index(mapping_index)
point_data = pd.concat([dataset[0], dataset[1], dataset[2]],
axis=1,
system_noise = config.assembly_system['system_noise']
aritifical_noise = config.assembly_system['aritifical_noise']
data_folder = config.assembly_system['data_folder']
kcc_folder = config.assembly_system['kcc_folder']
kcc_files = config.assembly_system['test_kcc_files']
print('Initializing the Assembly System and Measurement System....')
measurement_system = HexagonWlsScanner(data_type, application,
system_noise, part_type,
data_format)
vrm_system = VRMSimulationModel(assembly_type, assembly_kccs,
assembly_kpis, part_name, part_type,
voxel_dim, voxel_channels, point_dim,
aritifical_noise)
deploy_model = DeployModel()
get_data = GetTrainData()
#Generate Paths
train_path = '../trained_models/' + part_type
model_path = train_path + '/model' + '/trained_model_0.h5'
logs_path = train_path + '/logs'
deploy_path = train_path + '/deploy/'
#Import all static resources
#import Model
inference_model = deploy_model.get_model(model_path)
point_index = get_data.load_mapping_index(mapping_index)
cop_file_name = vc.voxel_parameters['nominal_cop_filename']
file_path = '../resources/nominal_cop_files/' + cop_file_name
#Read cop from csv file
nominal_cop = vrm_system.get_nominal_cop(file_path)
pathlib.Path(logs_path).mkdir(parents=True, exist_ok=True)
plots_path=train_path+'/plots'
pathlib.Path(plots_path).mkdir(parents=True, exist_ok=True)
deployment_path=train_path+'/deploy'
pathlib.Path(deployment_path).mkdir(parents=True, exist_ok=True)
print('Initializing....')
measurement_system=HexagonWlsScanner(data_type,application,system_noise,part_type,data_format)
print('Measurement system initialized')
vrm_system=VRMSimulationModel(assembly_type,assembly_kccs,assembly_kpis,part_name,part_type,voxel_dim,voxel_channels,point_dim,aritifical_noise)
print('Assembly and simulation system initialized')
get_data=GetTrainData();
metrics_eval=MetricsEval();
point_index=get_data.load_mapping_index(mapping_index)
print('Support systems initialized')
kcc_struct=kcc_config.kcc_struct
sampling_config=sampling_config.sampling_config
adaptive_sampling=AdaptiveSampling(sampling_config['sample_dim'],sampling_config['sample_type'],sampling_config['adaptive_sample_dim'],sampling_config['adaptive_runs'])
output_dimension=assembly_kccs
eval_metrics_type= ["Mean Absolute Error","Mean Squared Error","Root Mean Squared Error","R Squared"]
deployment_path = train_path + '/deploy'
pathlib.Path(deployment_path).mkdir(parents=True, exist_ok=True)
print('Initializing....')
measurement_system = HexagonWlsScanner(data_type, application,
system_noise, part_type,
data_format)
print('Measurement system initialized')
vrm_system = VRMSimulationModel(assembly_type, assembly_kccs,
assembly_kpis, part_name, part_type,
voxel_dim, voxel_channels, point_dim,
aritifical_noise)
print('Assembly and simulation system initialized')
get_data = GetTrainData()
metrics_eval = MetricsEval()
point_index = get_data.load_mapping_index(mapping_index)
print('Support systems initialized')
kcc_struct = kcc_config.kcc_struct
sampling_config = sampling_config.sampling_config
adaptive_sampling = AdaptiveSampling(
sampling_config['sample_dim'], sampling_config['sample_type'],
sampling_config['adaptive_sample_dim'],
sampling_config['adaptive_runs'])
output_dimension = assembly_kccs
