Update app.py

app.py

@@ -76,27 +76,36 @@ def process_video(input_path):
     plt.pie(sizes, labels=labels, autopct='%1.1f%%', colors=sns.color_palette('pastel'))
     plt.title("Emotion Distribution")
     plt.savefig("emotion_distribution.jpg")
-    plt.close()
-
-    return "output_video.mp4", "emotion_distribution.jpg", major_emotion
+    
+    return "output_video.mp4", plt, major_emotion
 
 # Gradio Web Interface
-gr.Interface(
-    fn=process_video,
-    inputs=gr.File(type="filepath"),
-    outputs=[
-        gr.File(label="Processed Video"),
-        gr.File(label="Emotion Distribution Chart"),
-        gr.Textbox(label="Major Emotion Detected")
-    ],
-    title="Emotion Detection from Video",
-    description="Upload a video, and the AI will detect emotions in each frame, providing a processed video, an emotion distribution chart, and the major detected emotion.",
-    css="""
-    .gradio-container { max-width: 800px !important; margin: auto; }
-    .gradio-container h1 { font-size: 22px; }
+with gr.Blocks(css="""
+    .gradio-container { max-width: 750px !important; margin: auto; background-color: #f8f9fa; padding: 20px; border-radius: 15px; }
+    .gradio-container h1 { font-size: 22px; text-align: center; color: #333; }
+    .gradio-container .gr-button { background-color: #007bff; color: white; border-radius: 10px; padding: 8px 15px; }
+    .gradio-container .gr-textbox { font-size: 16px; font-weight: bold; color: #007bff; }
+    .gradio-container .gr-file { border-radius: 10px; padding: 5px; }
     @media screen and (max-width: 768px) {
         .gradio-container { width: 100%; padding: 10px; }
         .gradio-container h1 { font-size: 18px; }
     }
-    """
-).launch()
+""") as demo:
+    gr.Markdown("# 🎭 Emotion Analysis from Video 🎥")
+    gr.Markdown("Upload a video, and the AI will detect emotions in each frame, providing a processed video, an emotion distribution chart, and the major detected emotion.")
+
+    with gr.Row():
+        video_input = gr.File(label="📤 Upload Video (MP4, MOV, AVI)")
+    
+    with gr.Row():
+        process_button = gr.Button("🚀 Analyze")
+
+    with gr.Row():
+        video_output = gr.File(label="📥 Processed Video")
+        emotion_chart = gr.Plot(label="📊 Emotion Distribution Chart")
+    
+    major_emotion_output = gr.Textbox(label="🔥 Major Emotion Detected", interactive=False)
+
+    process_button.click(fn=process_video, inputs=video_input, outputs=[video_output, emotion_chart, major_emotion_output])
+
+demo.launch()