app.py

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):

    # Clear figure in case it has data in it
    plt.clf()
    
    # Read the audio data from the file
    audio_data, sample_rate = sf.read(audio_file)

    # Flatten the audio data if it's not mono
    audio_data = audio_data.flatten() if len(audio_data.shape) > 1 else audio_data

    # Create the spectrogram
    plt.specgram(audio_data, Fs=sample_rate / 1, NFFT=4096, sides='onesided',
                 cmap="Reds_r", scale_by_freq=True, scale='dB', mode='magnitude')

    # Save the spectrogram to a PNG file
    plt.savefig('spectrogram.png')

    # Get the audio file info
    audio_info = sf.info(audio_file)

    bit_depth = {'PCM_16': 16, 'FLOAT': 32}.get(audio_info.subtype, 0)
    
    # 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 * bit_depth} bit/s |
    | Estensione | {os.path.splitext(audio_file)[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="filepath"), outputs=["markdown", "image"])
iface.launch()