| import gradio as gr |
| import matplotlib.pyplot as plt |
| import soundfile as sf |
| import numpy as np |
| import os |
|
|
| from assets.i18n.i18n import I18nAuto |
|
|
| i18n = I18nAuto() |
|
|
|
|
| def generate_spectrogram(audio_data, sample_rate, file_name): |
| plt.clf() |
|
|
| plt.specgram( |
| audio_data, |
| Fs=sample_rate / 1, |
| NFFT=4096, |
| sides="onesided", |
| cmap="Reds_r", |
| scale_by_freq=True, |
| scale="dB", |
| mode="magnitude", |
| window=np.hanning(4096), |
| ) |
|
|
| plt.title(file_name) |
| plt.savefig("spectrogram.png") |
|
|
|
|
| def get_audio_info(audio_file): |
| audio_data, sample_rate = sf.read(audio_file) |
|
|
| if len(audio_data.shape) > 1: |
| audio_data = np.mean(audio_data, axis=1) |
|
|
| generate_spectrogram(audio_data, sample_rate, os.path.basename(audio_file)) |
|
|
| 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 |
|
|
| speed_in_kbps = audio_info.samplerate * bit_depth / 1000 |
|
|
| info_table = f""" |
| - **File Name:** {os.path.basename(audio_file)} |
| - **Duration:** {int(minutes)} minutes, {int(seconds)} seconds, {int(milliseconds)} milliseconds |
| - **Bitrate:** {speed_in_kbps} kbp/s |
| - **Audio Channels:** {audio_info.channels} |
| - **Sampling rate:** {audio_info.samplerate} Hz |
| - **Bit per second:** {audio_info.samplerate * audio_info.channels * bit_depth} bit/s |
| """ |
|
|
| return info_table, "spectrogram.png" |
|
|
|
|
| def analyzer(): |
| with gr.Column(): |
| gr.Markdown( |
| "Tool inspired in the original [Ilaria-Audio-Analyzer](https://github.com/TheStingerX/Ilaria-Audio-Analyzer) code." |
| ) |
| audio_input = gr.Audio(type="filepath") |
| get_info_button = gr.Button( |
| value=i18n("Get information about the audio"), variant="primary" |
| ) |
| with gr.Column(): |
| with gr.Row(): |
| with gr.Column(): |
| gr.Markdown( |
| value=i18n("Information about the audio file"), |
| visible=True, |
| ) |
| output_markdown = gr.Markdown( |
| value=i18n("Waiting for information..."), visible=True |
| ) |
| image_output = gr.Image(type="filepath", interactive=False) |
|
|
| get_info_button.click( |
| fn=get_audio_info, |
| inputs=[audio_input], |
| outputs=[output_markdown, image_output], |
| ) |
|
|
