Update app.py

app.py

@@ -169,12 +169,20 @@ def recognize_faces(video_frame):
 
 # --- GRADIO INTERFACE (ENHANCED WITH BLOCKS) ---
 
-def recognize_and_return(frame: np.ndarray):
-    annotated_frame, names = recognize_faces(frame)
+def recognize_and_return(frame: np.ndarray, recognition_enabled: bool):
+    if not recognition_enabled:
+        return frame, "Recognition Paused"
+    
+    result = recognize_faces(frame)
+    if result is None:
+        return frame, "No faces detected"
+
+    annotated_frame, names = result
     name_str = ", ".join(names) if names else "No known faces"
     return annotated_frame, name_str
 
 with gr.Blocks(css=".gr-button {background-color: #2c3e50; color: white;}") as demo:
+    recognition_enabled = gr.State(True)  # Shared state
     gr.Markdown("# 🧠 Advanced Real-Time Facial Recognition")
     gr.Markdown(
         """
@@ -193,14 +201,16 @@ with gr.Blocks(css=".gr-button {background-color: #2c3e50; color: white;}") as d
             video_output = gr.Image(label="🧾 Annotated Output Frame")
             names_output = gr.Textbox(label="👤 Recognition Log", interactive=False)
 
-    video_input.stream(fn=recognize_and_return, inputs=video_input, outputs=[video_output, names_output])
+    with gr.Row():
+        toggle = gr.Checkbox(value=True, label="Enable Recognition")
+        clear_btn = gr.Button("🧹 Clear Output")
 
-    clear_button = gr.Button("🧹 Clear Output")
+    video_input.stream(fn=recognize_and_return, 
+                       inputs=[video_input, recognition_enabled], 
+                       outputs=[video_output, names_output])
 
-    def clear_outputs():
-        return None, ""
-    
-    clear_button.click(fn=clear_outputs, outputs=[video_output, names_output])
+    toggle.change(lambda v: v, inputs=toggle, outputs=recognition_enabled)
+    clear_btn.click(lambda: (None, ""), outputs=[video_output, names_output])
 
     gr.Markdown("---")
     gr.Markdown(