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- import numpy as np
- zone_folder = "zone"
- output_data_folder = 'data'
- threshold_map_folder = 'threshold_map'
- models_information_folder = 'models_info'
- saved_models_folder = 'saved_models'
- min_max_custom_folder = 'custom_norm'
- generated_folder = 'generated'
- pictures_output_folder = 'curves_pictures'
- csv_model_comparisons_filename = "models_comparisons.csv"
- seuil_expe_filename = 'seuilExpe'
- min_max_filename_extension = "_min_max_values"
- config_filename = "config"
- filename_ext = 'png'
- default_number_of_images = 1000
- models_names_list = ["svm_model","ensemble_model","ensemble_model_v2"]
- # define all scenes values
- scenes_folders = ['appartAopt', 'bureau1', 'cendrierIUT2', 'cuisine01', 'echecs', 'pnd', 'Sdb2', 'Sdb2_D', 'selles_envir']
- scenes_indices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I']
- maxwell_scenes_folders = ['appartAopt', 'cuisine01', 'Sdb2', 'Sdb2_D']
- maxwell_scenes_indices = ['A', 'D', 'G', 'H']
- normalization_choices = ['svd', 'svdn', 'svdne']
- zones_indices = np.arange(16)
- metric_choices_labels = ['lab', 'mscn', 'mscn_revisited', 'low_bits_2', 'low_bits_3', 'low_bits_4', 'low_bits_5', 'low_bits_6','low_bits_4_shifted_2']
- # noise information
- noise_labels = ['cauchy', 'gaussian', 'laplace', 'log_normal', 'mut_white', 'salt_pepper', 'white']
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