plotly

app.py

@@ -1,32 +1,42 @@
 import gradio as gr
 import numpy as np
-import matplotlib.pyplot as plt
+import plotly.graph_objects as go
 import librosa
-import librosa.display
 
 def plot_stft(audio_file):
-    # Load audio file
+    # Load the audio file
     y, sr = librosa.load(audio_file)
     
-    # Compute the Short-Time Fourier Transform (STFT)
+    # Compute the STFT
     D = librosa.stft(y)
     S_db = librosa.amplitude_to_db(np.abs(D), ref=np.max)
     
-    # Plot the STFT
-    plt.figure(figsize=(10, 6))
-    librosa.display.specshow(S_db, sr=sr, x_axis='time', y_axis='log')
-    plt.colorbar(format='%+2.0f dB')
-    plt.title('STFT (Short-Time Fourier Transform)')
+    # Generate time and frequency axes
+    times = librosa.times_like(S_db)
+    freqs = librosa.fft_frequencies(sr=sr)
     
-    # Save the plot as an image
-    plt.savefig('stft_plot.png')
-    plt.close()
+    # Create Plotly figure
+    fig = go.Figure(data=go.Heatmap(
+        z=S_db,
+        x=times,
+        y=freqs,
+        colorscale='Viridis'
+    ))
     
-    return 'stft_plot.png'
+    # Update layout for better visualization
+    fig.update_layout(
+        title="STFT (Short-Time Fourier Transform)",
+        xaxis_title="Time (s)",
+        yaxis_title="Frequency (Hz)",
+        yaxis_type="log"
+    )
+    
+    # Return the HTML representation of the plot
+    return fig.to_html()
 
 # Gradio interface
 demo = gr.Interface(fn=plot_stft, 
                     inputs=gr.Audio(type="filepath"), 
-                    outputs="image")
+                    outputs="html")
 
 demo.launch()

requirements.txt

@@ -1,2 +1,2 @@
-matplotlib
+plotly
 librosa