Update app.py

app.py

@@ -4,16 +4,44 @@ import numpy as np
 import os
 import soundfile as sf
 
-def create_spectrogram_and_get_info(audio_file):
+def main():
+    # Gradio Interface
+    with gr.Blocks() as app:
+        gr.Markdown(
+            """
+            # <div align="center"> Ilaria Audio Analyzer 💖 (BETA) </div>
+            Audio Analyzer Software by Ilaria, Help me on [Ko-Fi](https://ko-fi.com/ilariaowo)\n
+            Special thanks to [Alex Murkoff](https://github.com/alexlnkp) for helping me coding it!
+    
+            Need help with AI? [Join AI Hub!](https://discord.gg/aihub)
+            """
+        )
+    
+        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)
+    
+        create_spec_butt.click(fn=create_spectrogram_and_get_info, inputs=[audio_input], outputs=[output_markdown, image_output])
+        audio_input.change(fn=lambda: ({"value": "", "__type__": "update"},
+                                       {"value": "", "__type__": "update"}),
+                           inputs=[], outputs=[image_output, output_markdown])
+        
+        app.queue(max_size=1022).launch(share=True)
 
+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
+    # Convert to mono if it's not mono
+    if len(audio_data.shape) > 1:
+        audio_data = np.mean(audio_data, axis=1)
 
     # Create the spectrogram
     plt.specgram(audio_data, Fs=sample_rate / 1, NFFT=4096, sides='onesided',
@@ -24,23 +52,38 @@ def create_spectrogram_and_get_info(audio_file):
 
     # Get the audio file info
     audio_info = sf.info(audio_file)
-
+    
     bit_depth = {'PCM_16': 16, 'FLOAT': 32}.get(audio_info.subtype, 0)
     
+    # Convert duration to minutes, seconds, and milliseconds
+    minutes, seconds = divmod(audio_info.duration, 60)
+    seconds, milliseconds = divmod(seconds, 1)
+    milliseconds *= 1000  # convert from seconds to milliseconds
+    
+    # Convert bitrate to mb/s
+    bitrate = audio_info.samplerate * audio_info.channels * bit_depth / 8 / 1024 / 1024
+    
+    # Calculate speed in kbps
+    speed_in_kbps = audio_info.samplerate * bit_depth / 1000
+    
     # 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]} |
+    <center>
+    
+    | Information | Value |
+    | :---: | :---: |
+    | 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} |
+    | Samples per second | {audio_info.samplerate} Hz |
+    | Bit per second | {audio_info.samplerate * audio_info.channels * bit_depth} bit/s |
+    
+    </center>
     """
-
+    
     # Return the PNG file of the spectrogram and the info table
-    return info_table, 'spectrogram.png'
+    return {"value": info_table, "__type__": "update"}, '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()
+main()