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import librosa
import numpy as np
import os
import glob
audio_folder = 'images/audio'
file_paths = glob.glob(os.path.join(audio_folder, '*.wav'))
results = []
for file_path in file_paths:
y, sr = librosa.load(file_path)
S = librosa.feature.melspectrogram(y=y, sr=44100, n_mels=256)
log_S = librosa.power_to_db(S, ref=np.max)
vector = log_S.mean(axis=0)
results.append([os.path.basename(file_path), vector])
# Convert the 'results' list to a dictionary
results_dict = {item[0]: item[1] for item in results}
np.save('vec.npy', results_dict)
print("Results saved to 'vec.npy'")
import json
with open('vectors.jsonl', 'w') as fout:
for filename, vec in results_dict.items():
entry = {'filename': filename, 'audio_vector': vec.tolist()}
line = json.dumps(entry) + '\n'
fout.write(line)
print("Vectors saved to 'vectors.jsonl'") |