custom_config.py 1.5 KB

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  1. from modules.config.cnn_config import *
  2. import os
  3. # store all variables from cnn config
  4. context_vars = vars()
  5. # Custom config used for redefined config variables if necessary
  6. # folders
  7. output_data_folder = 'data'
  8. output_data_generated = os.path.join(output_data_folder, 'generated')
  9. output_datasets = os.path.join(output_data_folder, 'datasets')
  10. output_zones_learned = os.path.join(output_data_folder, 'learned_zones')
  11. ## noisy_folder = 'noisy'
  12. ## not_noisy_folder = 'notNoisy'
  13. backup_model_folder = 'models_backup'
  14. # file or extensions
  15. perf_prediction_model_path = 'predictions_models_results.csv'
  16. ## post_image_name_separator = '___'
  17. # variables
  18. perf_train_header_file = "model_name;global_train_size;global_test_size;filtered_train_size;filtered_test_size;f1_train;f1_test;recall_train;recall_test;presicion_train;precision_test;acc_train;acc_test;roc_auc_train;roc_auc_test;\n"
  19. perf_prediction_header_file = "data;data_size;model_name;accucary;f1;recall;precision;roc;\n"
  20. features_choices_labels = ['static', 'svd_reconstruction', 'fast_ica_reconstruction', 'ipca_reconstruction', 'min_diff_filter', 'sobel_based_filter','nl_mean_noise_mask']
  21. # parameters
  22. sub_image_size = (200, 200)
  23. keras_epochs = 30
  24. ## keras_batch = 32
  25. ## val_dataset_size = 0.2
  26. keras_img_size = (200, 200)