fix app

app.py

@@ -14,9 +14,6 @@ import gradio as gr
 from annoy import AnnoyIndex
 from deepface import DeepFace
 
-import lancedb
-db = lancedb.connect("../../.lancedb")
-tbl = db.open_table("face")
 
 index = AnnoyIndex(512, "euclidean")
 index.load(f"face.db")
@@ -56,6 +53,7 @@ def image_search_performers(image, threshold=20.0, results=3):
     t = time.time()
     faces = DeepFace.represent(img_path = image_array, detector_backend='retinaface', model_name='Facenet512', normalization="Facenet2018")
     # faces = DeepFace.represent(img_path = image_array, detector_backend='yolov8', model_name='Facenet512', normalization="Facenet2018")
+    # faces = DeepFace.represent(img_path = image_array, detector_backend='mtcnn', model_name='Facenet512', normalization="Facenet2018")
     print(f"Time to find faces: {time.time() - t}")
     for face in faces:
         embedding = face['embedding']
@@ -100,11 +98,12 @@ def search_performer(vector, threshold=20.0, results=3):
     threshold = threshold or 20.0
     results = results or 3
     
-    db_results = tbl.search(vector).limit(50).to_list()
-
+    ids, distances = index.get_nns_by_vector(
+        vector, 50, search_k=100000, include_distances=True
+    )
     persons = {}
-    for result in db_results:
-        id = result['performer_id']
+    for p, distance in zip(ids, distances):
+        id = ANNOY_INDEX[p]
         if id in persons:
             persons[id]["hits"] += 1
             persons[id]["distance"] -= 0.5
@@ -113,8 +112,8 @@ def search_performer(vector, threshold=20.0, results=3):
 
         persons[id] = {
             "id": id,
-            "distance": round(result['_distance'], 2),
-            "confidence": normalize_confidence_from_distance(result['_distance'], threshold),
+            "distance": round(distance, 2),
+            "confidence": normalize_confidence_from_distance(distance, threshold),
             "hits": 1,
         }
 
@@ -122,6 +121,7 @@ def search_performer(vector, threshold=20.0, results=3):
             persons[id].update(PERFORMER_DB.get(id))
 
     persons = sorted(persons.values(), key=lambda x: x["distance"])
+    # persons = [p for p in persons if p["distance"] < threshold]
     return persons[:results]