Update app.py

app.py

@@ -1,6 +1,4 @@
 import gradio as gr
-import matplotlib.pyplot as plt
-import numpy as np
 import os
 import soundfile as sf
 
@@ -10,52 +8,28 @@ def main():
         gr.Markdown(
             """
             # <div align="center"> diablofx Audio Interval Cutter (BETA) </div>
-            Want to [support](https://ko-fi.com/diablofx) me? or [join AI HUB](https://discord.gg/aihub) for more help\n
+            Want to [support](https://ko-fi.com/diablofx) me? Or [join AI HUB](https://discord.gg/aihub) for more Help!\n
             """
         )
-    
         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')
+                create_info_butt = gr.Button(value='Get Audio 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])
+        create_info_butt.click(fn=get_audio_info, inputs=[audio_input], outputs=[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)
-
-    # Create the spectrogram
-    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))
-
-    # Save the spectrogram to a PNG file
-    plt.savefig('spectrogram.png')
-
+def get_audio_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
+    # Convert duration to minutes and seconds
     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
@@ -66,16 +40,13 @@ def create_spectrogram_and_get_info(audio_file):
     | Information | Value |
     | :---: | :---: |
     | File Name | {os.path.basename(audio_file)} |
-    | Duration | {int(minutes)} minutes - {int(seconds)} seconds - {int(milliseconds)} milliseconds |
+    | Duration | {int(minutes)} minutes - {int(seconds)} seconds |
     | 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'
+    return info_table
 
 # Create the Gradio interface
 main()