custom_config.py 1.5 KB

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  1. from modules.config.attributes_config import *
  2. # store all variables from global config
  3. context_vars = vars()
  4. # folders
  5. ## min_max_custom_folder = 'custom_norm'
  6. ## correlation_indices_folder = 'corr_indices'
  7. generated_folder = 'generated'
  8. pictures_output_folder = 'curves_pictures'
  9. # variables
  10. ## models_names_list = ["svm_model","ensemble_model","ensemble_model_v2","deep_keras"]
  11. ## normalization_choices = ['svd', 'svdn', 'svdne']
  12. features_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', 'ica_diff', 'svd_trunc_diff', 'ipca_diff', 'svd_reconstruct', 'highest_sv_std_filters', 'lowest_sv_std_filters', 'highest_wave_sv_std_filters', 'lowest_wave_sv_std_filters', 'highest_sv_std_filters_full', 'lowest_sv_std_filters_full', 'highest_sv_entropy_std_filters', 'lowest_sv_entropy_std_filters']
  13. noise_labels = ['cauchy', 'gaussian', 'laplace', 'log_normal', 'mut_white', 'salt_pepper', 'white']
  14. error_data_choices = ['mae', 'mse', 'ssim', 'psnr']
  15. filename_ext = 'png'
  16. # parameters
  17. ## keras_epochs = 500
  18. ## keras_batch = 32
  19. ## val_dataset_size = 0.2
  20. default_number_of_images = 1000