Update app.py

app.py

@@ -35,7 +35,7 @@ def prod_function(app, prod_path, webcam_img_pil):
     
     webcam_faces = app.get(cv2_webcam)
     if not webcam_faces:
-        return []
+        return [], cv2_webcam
     
     results = []
     for webcam_face in webcam_faces:
@@ -55,9 +55,17 @@ def prod_function(app, prod_path, webcam_img_pil):
         similarity_scores = torch.stack(similarity_scores)
         best_match_idx = torch.argmax(similarity_scores)
         best_score = similarity_scores[best_match_idx].item()
-        results.append((best_score, best_match_idx))
+        
+        # Get coordinates
+        x1, y1, x2, y2 = [int(i) for i in webcam_face.bbox]
+        if best_score >= 0.6:
+            name = os.path.basename(prod_path[best_match_idx]).split('.')[0]
+        else:
+            name = "Unknown"
+        results.append({'bbox': (x1, y1, x2, y2), 'name': name})
+        
     
-    return results
+    return results, cv2_webcam
 
 # Streamlit tabs
 about_tab, app_tab = st.tabs(["About the app", "Face Recognition"])
@@ -86,12 +94,20 @@ with app_tab:
                 st.warning("No face detected in the captured image.")
             else:
                 # st.write("Similarity Scores:", prediction_scores)
-                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
+                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"