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load_parameters.py
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load_parameters.py
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Apr 19 11:57:01 2019
@author: dcase
"""
import numpy as np
import os
def load_pars():
parameter_dict={}
parameter_dict['fine_labels'] = ['1-1_small-sounding-engine', '1-2_medium-sounding-engine',
'1-3_large-sounding-engine', '1-X_engine-of-uncertain-size',
'2-1_rock-drill', '2-2_jackhammer', '2-3_hoe-ram', '2-4_pile-driver',
'2-X_other-unknown-impact-machinery', '3-1_non-machinery-impact',
'4-1_chainsaw', '4-2_small-medium-rotating-saw', '4-3_large-rotating-saw',
'4-X_other-unknown-powered-saw', '5-1_car-horn', '5-2_car-alarm',
'5-3_siren', '5-4_reverse-beeper', '5-X_other-unknown-alert-signal',
'6-1_stationary-music', '6-2_mobile-music', '6-3_ice-cream-truck',
'6-X_music-from-uncertain-source', '7-1_person-or-small-group-talking',
'7-2_person-or-small-group-shouting', '7-3_large-crowd',
'7-4_amplified-speech', '7-X_other-unknown-human-voice',
'8-1_dog-barking-whining']
parameter_dict['coarse_labels'] = ['1_engine', '2_machinery-impact', '3_non-machinery-impact',
'4_powered-saw', '5_alert-signal', '6_music', '7_human-voice', '8_dog']
parameter_dict['net_type'] = 'CNN' # choice = ['CNN','CNN9','CNN_gated']
parameter_dict['feature_type'] = 'log_mel' # choice = ['log_mel','STFT',HPSS_h']
parameter_dict['label_level'] = 'coarse'
parameter_dict['learning_rate'] = 0.001
parameter_dict['kernel_size'] = 3
parameter_dict['layer_depth'] = [64,128,256,512] # [ , , , , ]
parameter_dict['max_ckpt'] = 20
parameter_dict['n_epoch'] = 45
parameter_dict['batch_size'] = 32
parameter_dict['snapshot'] = 3
parameter_dict['model_path'] = '~/'
parameter_dict['train_audio_path'] = '~/audio/train'
parameter_dict['val_audio_path'] = '~/audio/validate'
parameter_dict['train_data_path'] = '~/train_data/'+parameter_dict['feature_type']
parameter_dict['val_data_path'] = '~/val_data/'+parameter_dict['feature_type']
parameter_dict['train_label_csv_path'] = '~/train_'+parameter_dict['label_level']+'_labels_1.csv'
parameter_dict['val_label_csv_path'] = '~/val'+parameter_dict['label_level']+'_labels_1.csv'
parameter_dict['submission_path'] = os.path.join(parameter_dict['model_path'],'pre_0.csv')
parameter_dict['annotation_path'] = '~/annotations.csv'
parameter_dict['yaml_path'] = '~/dcase-ust-taxonomy.yaml'
if not os.path.exists(parameter_dict['model_path']):
os.makedirs(parameter_dict['model_path'])
np.save(os.path.join(parameter_dict['model_path'],'parameter_dict.npy'),parameter_dict)
return parameter_dict