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import gradio as gr
import matplotlib.pyplot as plt
import numpy as np
import os
import soundfile as sf
import requests
def download_file(url):
file_id = url.split('/')[-2]
download_url = f'https://docs.google.com/uc?export=download&id={file_id}'
response = requests.get(download_url, allow_redirects=True)
local_filename = url.split('/')[-1] + '.wav'
open(local_filename, 'wb').write(response.content)
return local_filename
def main():
with gr.Blocks() as app:
gr.Markdown(
"""
Audio Analyzer Software by Ilaria, Help me on Ko-Fi!\n
Special thanks to Alex Murkoff for helping me coding it!
Need help with AI? Join Join AI Hub!
"""
)
with gr.Row():
with gr.Column():
audio_input = gr.Audio(type='filepath')
create_spec_butt = gr.Button(value='Create Spectrogram And Get Info', variant='primary')
with gr.Column():
output_markdown = gr.Markdown(value="", visible=True)
image_output = gr.Image(type='filepath', interactive=False)
with gr.Accordion('Audio Downloader', open=False):
url_input = gr.Textbox(value='', label='Google Drive Audio URL')
download_butt = gr.Button(value='Download audio', variant='primary')
download_butt.click(fn=download_file, inputs=[url_input], outputs=[audio_input])
create_spec_butt.click(fn=create_spectrogram_and_get_info, inputs=[audio_input], outputs=[output_markdown, image_output])
download_butt.click(fn=download_file, inputs=[url_input], outputs=[audio_input])
create_spec_butt.click(fn=create_spectrogram_and_get_info, inputs=[audio_input], outputs=[output_markdown, image_output])
app.queue(max_size=1022).launch(share=True)
def create_spectrogram_and_get_info(audio_file):
plt.clf()
plt.figure(figsize=(15, 5))
audio_data, sample_rate = sf.read(audio_file)
if len(audio_data.shape) > 1:
audio_data = np.mean(audio_data, axis=1)
plt.specgram(audio_data, Fs=sample_rate / 1, NFFT=4096, sides='onesided',
cmap="inferno", scale_by_freq=True, scale='dB', mode='magnitude', window=np.hanning(4096))
plt.savefig('spectrogram.png')
audio_info = sf.info(audio_file)
bit_depth = {'PCM_16': 16, 'FLOAT': 32}.get(audio_info.subtype, 0)
minutes, seconds = divmod(audio_info.duration, 60)
seconds, milliseconds = divmod(seconds, 1)
milliseconds *= 1000
bitrate = audio_info.samplerate * audio_info.channels * bit_depth / 8 / 1024 / 1024
speed_in_kbps = audio_info.samplerate * bit_depth / 1000
filename_without_extension, _ = os.path.splitext(os.path.basename(audio_file))
info_table = f"""
| Information | Value |
| :---: | :---: |
| File Name | {filename_without_extension} |
| Duration | {int(minutes)} minutes - {int(seconds)} seconds - {int(milliseconds)} milliseconds |
| Bitrate | {speed_in_kbps} kbp/s |
| Audio Channels | {audio_info.channels} |
| Samples per second | {audio_info.samplerate} Hz |
| Bit per second | {audio_info.samplerate * audio_info.channels * bit_depth} bit/s |
"""
# Return the PNG file of the spectrogram and the info table
return info_table, 'spectrogram.png'
# Create the Gradio interface
main() |