Update app.py

app.py

@@ -4,44 +4,16 @@ import numpy as np
 import os
 import soundfile as sf
 
-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)
 
-    # Convert to mono if it's not mono
-    if len(audio_data.shape) > 1:
-        audio_data = np.mean(audio_data, axis=1)
+    # Flatten the audio data if it's not mono
+    audio_data = audio_data.flatten() if len(audio_data.shape) > 1 else audio_data
 
     # Create the spectrogram
     plt.specgram(audio_data, Fs=sample_rate / 1, NFFT=4096, sides='onesided',
@@ -52,38 +24,23 @@ 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"""
-    <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>
+    | 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 {"value": info_table, "__type__": "update"}, 'spectrogram.png'
+    return info_table, 'spectrogram.png'
 
 # Create the Gradio interface
-main()
+iface = gr.Interface(fn=create_spectrogram_and_get_info, inputs=gr.Audio(type="filepath"), outputs=["markdown", "image"])
+iface.launch()