run clustering

app.py

@@ -35,7 +35,7 @@ def f1(voices, sent, indices):
     #tts_audio, tts_score, graph = scripts.runSQ.run(sent, voices, indices)
     tts_audio, tts_score, tts_fig_p, mid_fig_p, bad_fig_p, tts_fig_e, fig_mid_e, fig_bad_e = scripts.runSQ.run(sent, [voices], indices)
     score_report = f'Difference from TTS to real speech: {round(tts_score,2)}'
-    return (tts_audio, score_report, tts_fig_p, mid_fig_p, bad_fig_p)
+    return (tts_audio, score_report, tts_fig_p, mid_fig_p, bad_fig_p, tts_fig_e, fig_mid_e, fig_bad_e)
 
 
 def label_indices(sentence):
@@ -76,13 +76,28 @@ with bl:
     
     tts_output = gr.Audio(interactive=False)
     report_score = gr.Markdown('Difference from TTS to real speech:')
-    pl1 = gr.Plot()
-    with gr.Row():
-        pl2 = gr.Plot()
-        pl3 = gr.Plot()
+    
+    with gr.Tabs():
+        with gr.TabItem("Pitch"):
+    
+            pl1 = gr.Plot()
+            with gr.Row():
+                pl2 = gr.Plot()
+                pl3 = gr.Plot()
+                
+        with gr.TabItem("Energy"):
+    
+            pl4 = gr.Plot()
+            with gr.Row():
+                pl5 = gr.Plot()
+                pl6 = gr.Plot()
+        
+
+
+
 
     temp_sentmenu.input(label_indices,temp_sentmenu,marked_sentence)
-    temp_button.click(f1,[voiceselect,temp_sentmenu,spanselect],[tts_output,report_score,pl1,pl2,pl3])
+    temp_button.click(f1,[voiceselect,temp_sentmenu,spanselect],[tts_output,report_score,pl1,pl2,pl3,pl4,pl5,pl6])
     
     
 if __name__ == "__main__":