Update app.py

app.py

@@ -48,8 +48,7 @@ def plotly_plot_audio(audio_path):
         p = px.bar(data, x='Emotion', y='Probability', color="Probability")
         return (
             p,
-            f"🗣️ Transcription:\n{text}",
-            f"## 🏆 Dominant Emotion: {data['Emotion'].values[np.argmax(np.array(data['Probability']))]}"
+            f"## ✔️ Dominant Emotion: {data['Emotion'].values[np.argmax(np.array(data['Probability']))]}"
         )
 
     except Exception as e:
@@ -71,8 +70,8 @@ def plotly_plot_audio(audio_path):
         p = px.bar(data, x='Emotion', y='Probability', color="Probability")
         return (
             p,
-            f"🗣️ Transcription:\n{text}",
-            f"## 🏆 Dominant Emotion: {data['Emotion'].values[np.argmax(np.array(data['Probability']))]}"
+            f"🎤 Transcription:\n{text}",
+            f"## ✔️ Dominant Emotion: {data['Emotion'].values[np.argmax(np.array(data['Probability']))]}"
         )
 
     except Exception as e:
@@ -86,14 +85,14 @@ def plotly_plot_audio(audio_path):
         )
     
 def create_demo_text():
-    with gr.Blocks(theme=gr.themes.Soft(), title="Emotion Detection") as demo:
+    with gr.Blocks(theme='Nymbo/rounded-gradient', css=".gradio-container {background-color: #F0F8FF}", title="Emotion Detection") as demo:
         gr.Markdown("# Text-based bilingual emotion recognition")
 
         with gr.Row():
             text_input = gr.Textbox(label="Write Text")
 
         with gr.Row():
-            top_emotion = gr.Markdown("## 🏆 Dominant Emotion: Waiting for input ...",
+            top_emotion = gr.Markdown("## ✔️ Dominant Emotion: Waiting for input ...",
                                       elem_classes="dominant-emotion")
 
         with gr.Row():
@@ -103,8 +102,8 @@ def create_demo_text():
     return demo
 
 def create_demo_audio():
-    with gr.Blocks(theme=gr.themes.Soft(), title="Emotion Detection") as demo:
-        gr.Markdown("# Text-based bilingual emotion recognition")
+    with gr.Blocks(theme='Nymbo/rounded-gradient', css=".gradio-container {background-color: #F0F8FF}", title="Emotion Detection") as demo:
+        gr.Markdown("# Text-based bilingual emotion recognition with audio transcription")
 
         with gr.Row():
             audio_input = gr.Audio(
@@ -115,7 +114,7 @@ def create_demo_audio():
                 interactive=True
             )
         with gr.Row():
-            top_emotion = gr.Markdown("## 🏆 Dominant Emotion: Waiting for input ...",
+            top_emotion = gr.Markdown("## ✔️ Dominant Emotion: Waiting for input ...",
                                       elem_classes="dominant-emotion")
 
         with gr.Row():