File size: 1,344 Bytes
de60a6a
458da1c
 
5a86410
 
eb0bc41
77121d6
 
d0b2fc8
77121d6
 
 
 
 
 
ac0ec53
6af81aa
77121d6
458da1c
6af81aa
77121d6
d0b2fc8
 
 
5a86410
77121d6
5a86410
 
 
 
 
 
d0b2fc8
 
5a86410
41bada8
77121d6
41bada8
5a86410
77121d6
d0b2fc8
de60a6a
77121d6
d7b3827
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
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)

    # 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)

    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()