# load config parameters used in 'audio_representation.py',
config_json = config_file.DATA_FOLDER + config[
'audio_representation_folder'] + 'config.json'
with open(config_json, "r") as f:
params = json.load(f)
config['audio_rep'] = params
# set patch parameters
config['xInput'] = config['n_frames']
config['yInput'] = config['audio_rep']['n_mels']
# load audio representation paths
file_index = config_file.DATA_FOLDER + config[
'audio_representation_folder'] + 'index.tsv'
[audio_repr_paths,
id2audio_repr_path] = shared.load_id2audioReprPath(file_index)
# load training ground truth
file_ground_truth_train = config_file.DATA_FOLDER + config['gt_train']
[all_ids_train, id2gt_train] = shared.load_id2gt(file_ground_truth_train)
[_, id2label_train] = shared.load_id2label(file_ground_truth_train)
label2ids_train = shared.load_label2ids(id2label_train)
# load test ground truth
file_ground_truth_test = config_file.DATA_FOLDER + config['gt_test']
[all_ids_test, id2gt_test] = shared.load_id2gt(file_ground_truth_test)
[_, id2label_test] = shared.load_id2label(file_ground_truth_test)
label2ids_test = shared.load_label2ids(id2label_test)
# set output according to the experimental setup
classes_vector = list(range(config['num_classes_dataset']))
# which experiment we want to evaluate?
parser = argparse.ArgumentParser()
parser.add_argument('experiment',
help='Id of the configuration dictionary')
args = parser.parse_args()
experiment = args.experiment
experiment_folder = config_file.DATA_FOLDER + 'experiments/' + str(
experiment) + '/'
config = json.load(open(experiment_folder + 'config.json'))
print('Experiment: ' + str(experiment))
print('\n' + str(config))
# load all audio representation paths
[audio_repr_paths,
id2audio_repr_path] = shared.load_id2audioReprPath(FILE_INDEX)
# load ground truth
FILE_GROUND_TRUTH_TEST = config_file.DATA_FOLDER + 'index/' + DATASET + '/gt_' + DATASET + '_fold' + str(
config['fold']) + '_test.tsv'
[ids, id2gt] = shared.load_id2gt(FILE_GROUND_TRUTH_TEST)
[_, id2label] = shared.load_id2label(FILE_GROUND_TRUTH_TEST)
print(FILE_GROUND_TRUTH_TEST)
# pescador: define (finite, batched & parallel) streamer
pack = [config, 'overlap_sampling', 1]
streams = [
pescador.Streamer(transfer_train.data_gen, id, id2audio_repr_path[id],
id2gt[id], pack) for id in ids
]
mux_stream = pescador.ChainMux(streams, mode='exhaustive')