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- import numpy as np
- zone_folder = "zone"
- output_data_folder = 'data'
- dataset_path = 'fichiersSVD_light'
- threshold_map_folder = 'threshold_map'
- models_information_folder = 'models_info'
- saved_models_folder = 'saved_models'
- min_max_custom_folder = 'custom_norm'
- learned_zones_folder = 'learned_zones'
- correlation_indices_folder = 'corr_indices'
- csv_model_comparisons_filename = "models_comparisons.csv"
- seuil_expe_filename = 'seuilExpe'
- min_max_filename_extension = "_min_max_values"
- config_filename = "config"
- models_names_list = ["svm_model","ensemble_model","ensemble_model_v2","deep_keras"]
- # define all scenes values
- renderer_choices = ['all', 'maxwell', 'igloo', 'cycle']
- scenes_names = ['Appart1opt02', 'Bureau1', 'Cendrier', 'Cuisine01', 'EchecsBas', 'PNDVuePlongeante', 'SdbCentre', 'SdbDroite', 'Selles']
- scenes_indices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I']
- maxwell_scenes_names = ['Appart1opt02', 'Cuisine01', 'SdbCentre', 'SdbDroite']
- maxwell_scenes_indices = ['A', 'D', 'G', 'H']
- igloo_scenes_names = ['Bureau1', 'PNDVuePlongeante']
- igloo_scenes_indices = ['B', 'F']
- cycle_scenes_names = ['EchecBas', 'Selles']
- cycle_scenes_indices = ['E', 'I']
- normalization_choices = ['svd', 'svdn', 'svdne']
- zones_indices = np.arange(16)
- metric_choices_labels = ['lab', 'mscn', 'low_bits_2', 'low_bits_3', 'low_bits_4', 'low_bits_5', 'low_bits_6','low_bits_4_shifted_2', 'sub_blocks_stats', 'sub_blocks_area', 'sub_blocks_stats_reduced', 'sub_blocks_area_normed', 'mscn_var_4', 'mscn_var_16', 'mscn_var_64', 'mscn_var_16_max', 'mscn_var_64_max']
- keras_epochs = 500
- keras_batch = 32
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