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import gradio as gr | |
import matplotlib.pyplot as plt | |
import numpy as np | |
import os | |
import soundfile as sf | |
def create_spectrogram_and_get_info(audio_file): | |
# Read the audio data from the file | |
audio_data, sample_rate = sf.read(audio_file.name) | |
# Flatten the audio data if it's not mono | |
if len(audio_data.shape) > 1: | |
audio_data = audio_data.flatten() | |
# Create the spectrogram | |
plt.specgram(audio_data, Fs=sample_rate) | |
# Save the spectrogram to a PNG file | |
plt.savefig('spectrogram.png') | |
# Get the audio file info | |
audio_info = sf.info(audio_file.name) | |
# Create a table with the audio file info | |
info_table = f""" | |
| Informazione | Valore | | |
| --- | --- | | |
| Durata | {audio_info.duration} secondi | | |
| Campioni al secondo | {audio_info.samplerate} Hz | | |
| Canali | {audio_info.channels} | | |
| Bitrate | {audio_info.samplerate * audio_info.channels * audio_info.subtype.itemsize * 8} bit/s | | |
| Estensione | {os.path.splitext(audio_file.name)[1]} | | |
""" | |
# Return the PNG file of the spectrogram and the info table | |
return info_table, 'spectrogram.png' | |
# Create the Gradio interface | |
iface = gr.Interface(fn=create_spectrogram_and_get_info, inputs=gr.Audio(type="numpy"), outputs=["markdown", "image"]) | |
iface.launch() | |