""" TODO COMPLETE evaluate precomputed output files """ from baseline import parameter import os from APRI.compute_metrics import compute_metrics from APRI.utils import plot_results # %% PARAMS preset = 'particle' params = parameter.get_params(preset) gt_folder = os.path.join(params['dataset_dir'], 'metadata_dev') # path to annotations this_file_path = os.path.dirname(os.path.abspath(__file__)) result_folder_path = os.path.join(this_file_path, params['results_dir'], preset) # %% PLOT # Achtung! will plot *all* metadata result files # res_files = [f for f in os.listdir(result_folder_path) if f != '.DS_Store'] res_files = ['fold1_room1_mix007_ov1.csv', 'fold2_room1_mix007_ov1.csv', 'fold3_room1_mix007_ov1.csv', # 'fold4_room1_mix007_ov1.csv', # 'fold5_room1_mix007_ov1.csv', # 'fold6_room1_mix007_ov1.csv',
''' import os, datetime from baseline import parameter from APRI.training_batch_data_augmentation import * from APRI.training_batch_generate_audio_features import * from APRI.get_dataframes import * from APRI.localization_detection import * import pickle import soundfile as sf from APRI.utils import plot_metadata, get_class_name_dict, get_mono_audio_from_event, Event from baseline.cls_feature_class import create_folder import time # Import general parametes params = parameter.get_params() dataset_dir = os.path.join(params['dataset_dir']) # Parameters mode = 'new' # new or modify pipeline = 'Datasets_2020-06-05_22-15' #if mode is 'modify' #original_event_dataset='oracle_mono_testing' extra_events = False data_augmentation = True audio_parameters_real = True audio_parameters_aug = True audio_parameters_extra = False creating_dataframe_real = True creating_dataframe_aug = True creating_dataframe_extra = False