Update app.py

app.py

@@ -82,47 +82,49 @@ with about_tab:
     """)
 
 with app_tab:
-    enable = st.checkbox("Enable camera")
-    picture = st.camera_input("Take a picture", disabled=not enable)
-
-    if picture is not None:
-        with st.spinner("Analyzing face..."):
-            image_pil = Image.open(picture)
-            matches, image_bgr = prod_function(app, image_paths, image_pil)
-
-            if not matches:
-                st.warning("No face detected in the captured image.")
-            else:
-                # st.write("Similarity Scores:", prediction_scores)
-                for match in matches:
-                    x1, y1, x2, y2 = match['bbox']
-                    name = match['name']
-                    color = (0, 255, 0) if name != "Unknown" else (0, 0, 255)
-                    cv2.rectangle(image_bgr, (x1, y1), (x2, y2), color, 2)
-                    cv2.putText(image_bgr, name, (x1, y2 + 20), cv2.FONT_HERSHEY_SIMPLEX, 0.8, color, 2)
+    col1, col2 = st.columns(2)
+    with col1:
+        enable = st.checkbox("Enable camera")
+        picture = st.camera_input("Take a picture", disabled=not enable)
+    with col2:
+        if picture is not None:
+            with st.spinner("Analyzing face..."):
+                image_pil = Image.open(picture)
+                matches, image_bgr = prod_function(app, image_paths, image_pil)
     
-                    if name != "Unknown":
-                    # recognized = False
-                    # for score, idx in matches:
-                    #     if matched_score >= 0.6:
-                    #         matched_name = os.path.basename(image_paths[match_idx]).split('.')[0]
-                    #         st.success(f"✅ Welcome: {matched_name}")
-                    #         recognizes=True
-                        
-                        # Send attendance via POST
-                        url = "https://nielit-attendance.glitch.me/adds"
-                        data = {'rno': 15, 'sname': matched_name, 'sclass': 7}
-                        try:
-                            response = requests.post(url, data=data)
-                            if response.status_code == 200:
-                                st.success(f"Attendance marked successfully for {matched_name}.")
-                            else:
-                                st.warning(f"Failed to update attendance for {matched_name}.")
-                        except Exception as e:
-                            st.error(f"Request failed: {e}")
-                    else:
-                        st.warning("❌ Face match not found or too low confidence.")
-                
-            # Convert back to RGB for display
-            image_rgb = cv2.cvtColor(image_bgr, cv2.COLOR_BGR2RGB)
-            st.image(image_rgb, caption="Detected Faces", use_column_width=True)
+                if not matches:
+                    st.warning("No face detected in the captured image.")
+                else:
+                    # st.write("Similarity Scores:", prediction_scores)
+                    for match in matches:
+                        x1, y1, x2, y2 = match['bbox']
+                        name = match['name']
+                        color = (0, 255, 0) if name != "Unknown" else (0, 0, 255)
+                        cv2.rectangle(image_bgr, (x1, y1), (x2, y2), color, 2)
+                        cv2.putText(image_bgr, name, (x1, y2 + 20), cv2.FONT_HERSHEY_SIMPLEX, 0.8, color, 2)
+        
+                        if name != "Unknown":
+                        # recognized = False
+                        # for score, idx in matches:
+                        #     if matched_score >= 0.6:
+                        #         matched_name = os.path.basename(image_paths[match_idx]).split('.')[0]
+                        #         st.success(f"✅ Welcome: {matched_name}")
+                        #         recognizes=True
+                            
+                            # Send attendance via POST
+                            url = "https://nielit-attendance.glitch.me/adds"
+                            data = {'rno': 15, 'sname': matched_name, 'sclass': 7}
+                            try:
+                                response = requests.post(url, data=data)
+                                if response.status_code == 200:
+                                    st.success(f"Attendance marked successfully for {matched_name}.")
+                                else:
+                                    st.warning(f"Failed to update attendance for {matched_name}.")
+                            except Exception as e:
+                                st.error(f"Request failed: {e}")
+                        else:
+                            st.warning("❌ Face match not found or too low confidence.")
+                    
+                # Convert back to RGB for display
+                image_rgb = cv2.cvtColor(image_bgr, cv2.COLOR_BGR2RGB)
+                st.image(image_rgb, caption="Detected Faces", use_container_width=True)