audiostruct.py 文件源码

def getdata(self):
    # Structure for the array of songs
    song_data = []
    genre_data = []

    # Read files from the folders
    for x,_ in self.genres.items():
      for root, subdirs, files in os.walk(self.file_path + x):
        for file in files:
          # Read the audio file
            file_name = self.file_path + x + "/" + file
            print(file_name)
            signal, sr = librosa.load(file_name)

            # Calculate the melspectrogram of the audio and use log scale
            melspec = librosa.feature.melspectrogram(signal[:self.song_samples],
              sr = sr, n_fft = self.n_fft, hop_length = self.hop_length).T[:1280,]

            # Append the result to the data structure
            song_data.append(melspec)
            genre_data.append(self.genres[x])
    return np.array(song_data), keras.utils.to_categorical(genre_data, len(self.genres))