Update app.py

app.py

@@ -132,27 +132,35 @@ def enroll_person(name: str, face_image: np.ndarray):
 
     faces = recognizer.get(face_image, max_num=1)
     if not faces:
-        return "No face detected! Please try a clearer photo."
+        return "No face detected! Try a clearer photo."
 
     emb = faces[0].normed_embedding
 
-    # Save to disk
-    embs = np.load(KNOWN_EMBS_PATH) if os.path.exists(KNOWN_EMBS_PATH) else np.empty((0, 512))
-    names = np.load(KNOWN_NAMES_PATH, allow_pickle=True).tolist() if os.path.exists(KNOWN_NAMES_PATH) else []
+    # Load existing data (or create new)
+    if not os.path.exists(KNOWN_EMBS_PATH):
+        all_embs = np.empty((0, 512))
+        all_names = []
+    else:
+        all_embs = np.load(KNOWN_EMBS_PATH)
+        all_names = np.load(KNOWN_NAMES_PATH, allow_pickle=True).tolist()
 
-    embs = np.vstack([embs, emb])
-    names.append(name)
+    # Append new person
+    all_embs = np.vstack([all_embs, emb])
+    all_names.append(name)
 
-    np.save(KNOWN_EMBS_PATH, embs)
-    np.save(KNOWN_NAMES_PATH, np.array(names))
+    # Save to disk
+    np.save(KNOWN_EMBS_PATH, all_embs)
+    np.save(KNOWN_NAMES_PATH, np.array(all_names))
 
-    # Rebuild index
-    dim = 512
-    index = faiss.IndexHNSWFlat(dim, 32)
-    index.add(embs.astype('float32'))
-    known_names = names
+    # ←←← THIS IS THE CRUCIAL PART ←←←
+    # Rebuild FAISS index immediately
+    index = faiss.IndexHNSWFlat(512, 32)
+    index.hnsw.efSearch = 16
+    index.add(all_embs.astype('float32'))
+    known_names = all_names
+    # ←←← END ←←←
 
-    return f"Successfully enrolled: {name}"
+    return f"Successfully enrolled: **{name}** → now instantly recognized!"
 
 # ==================== 4. GRADIO UI ====================
 with gr.Blocks(title="SecureFace ID – Privacy-First Recognition") as demo: