Update app.py

app.py

@@ -6,41 +6,52 @@ import tempfile
 import os
 
 def create_waveform_video(image, audio_path):
-    # Save uploaded image temporarily
-    image_path = tempfile.mktemp(suffix=".png")
-    video_path = tempfile.mktemp(suffix=".mp4")
-    waveform_path = tempfile.mktemp(suffix=".png")
-    
-    image.save(image_path)
-    
-    # Load audio
-    audio_clip = AudioFileClip(audio_path)
-    
-    # Generate waveform as an image
-    waveform = audio_clip.to_soundarray(fps=22050).mean(axis=1)  # Convert stereo to mono
-    waveform = np.interp(waveform, (waveform.min(), waveform.max()), (-1, 1))  # Normalize
-
-    # Plot waveform using matplotlib
-    plt.figure(figsize=(10, 2))
-    plt.plot(waveform, color="blue")
-    plt.axis("off")
-    plt.savefig(waveform_path, bbox_inches="tight", pad_inches=0)
-    plt.close()
-
-    # Load image and create a video clip of the same duration as the audio
-    img_clip = ImageClip(image_path).set_duration(audio_clip.duration).resize(height=720)
-    waveform_clip = ImageClip(waveform_path).set_duration(audio_clip.duration).resize(width=img_clip.w)
-    waveform_clip = waveform_clip.set_position(("center", img_clip.h - waveform_clip.h - 20))
-
-    # Combine image, waveform overlay, and audio into one video
-    final_clip = CompositeVideoClip([img_clip, waveform_clip.set_opacity(0.7)]).set_audio(audio_clip)
-    final_clip.write_videofile(video_path, codec="libx264", fps=24)
-    
-    # Cleanup temporary files
-    os.remove(image_path)
-    os.remove(waveform_path)
-    
-    return video_path
+    # Check if audio file was uploaded
+    if audio_path is None:
+        return "Error: No audio file provided."
+
+    try:
+        # Save uploaded image temporarily
+        image_path = tempfile.mktemp(suffix=".png")
+        video_path = tempfile.mktemp(suffix=".mp4")
+        waveform_path = tempfile.mktemp(suffix=".png")
+
+        image.save(image_path)
+
+        # Load audio
+        audio_clip = AudioFileClip(audio_path)
+
+        # Generate waveform as an image
+        waveform = audio_clip.to_soundarray(fps=22050)  # Convert audio to waveform array
+        if waveform.ndim > 1:
+            waveform = waveform.mean(axis=1)  # Convert stereo to mono
+
+        waveform = np.interp(waveform, (waveform.min(), waveform.max()), (-1, 1))  # Normalize
+
+        # Plot waveform using matplotlib
+        plt.figure(figsize=(10, 2))
+        plt.plot(waveform, color="blue")
+        plt.axis("off")
+        plt.savefig(waveform_path, bbox_inches="tight", pad_inches=0)
+        plt.close()
+
+        # Load image and create a video clip of the same duration as the audio
+        img_clip = ImageClip(image_path).set_duration(audio_clip.duration).resize(height=720)
+        waveform_clip = ImageClip(waveform_path).set_duration(audio_clip.duration).resize(width=img_clip.w)
+        waveform_clip = waveform_clip.set_position(("center", img_clip.h - waveform_clip.h - 20))
+
+        # Combine image, waveform overlay, and audio into one video
+        final_clip = CompositeVideoClip([img_clip, waveform_clip.set_opacity(0.7)]).set_audio(audio_clip)
+        final_clip.write_videofile(video_path, codec="libx264", fps=24)
+
+        # Cleanup temporary files
+        os.remove(image_path)
+        os.remove(waveform_path)
+
+        return video_path
+
+    except Exception as e:
+        return f"An error occurred: {str(e)}"
 
 iface = gr.Interface(
     fn=create_waveform_video,