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()