test mp3

test_mp3.py

@@ -0,0 +1,51 @@
+
+# https://tfhub.dev/google/lite-model/yamnet/classification/tflite/1
+
+import tensorflow as tf
+import tensorflow_hub as hub
+import numpy as np
+import csv
+
+# import matplotlib.pyplot as plt
+# from IPython.display import Audio
+from scipy.io import wavfile
+import scipy
+
+# import soundfile as sf
+# import audio2numpy as a2n
+import os
+
+import gradio as gr
+
+# import audio2numpy
+# import numpy as np
+
+from pydub import AudioSegment
+from matplotlib import pyplot as plt
+
+
+# https://stackoverflow.com/questions/16634128/how-to-extract-the-raw-data-from-a-mp3-file-using-python
+# This will open and read the audio file with pydub.  Replace the file path with
+# your own file.
+audio_file = AudioSegment.from_file('miaow_16k.mp3')
+
+# Set up a list for us to dump PCM samples into, and create a 'data' variable
+# so we don't need to type audio_file._data again
+data = audio_file._data
+pcm16_signed_integers = []
+
+# This loop decodes the bytestring into PCM samples.
+# The bytestring is a stream of little-endian encoded signed integers.
+# This basically just cuts each two-byte sample out of the bytestring, converts
+# it to an integer, and appends it to the list of samples.
+for sample_index in range(len(data) // 2):
+    sample = int.from_bytes(data[sample_index * 2:sample_index * 2 + 2], 'little', signed=True)
+    pcm16_signed_integers.append(sample / 255)
+
+wav_data = np.array([x for x in pcm16_signed_integers])
+sample_rate = 16000
+if debug: print(f'pcm16_signed_integers: {len(pcm16_signed_integers)}')
+
+# Now plot the samples!
+plt.plot(pcm16_signed_integers)
+plt.show()