fix normalization

frigate/api/event.py

@@ -479,42 +479,75 @@ def events_search(request: Request, params: EventsSearchQueryParams = Depends())
     else:
         event_ids = []
 
-    thumb_results = []
-    desc_results = []
+    thumb_ids = {}
+    desc_ids = {}
 
     if search_type == "similarity":
         try:
             search_event: Event = Event.get(Event.id == event_id)
         except DoesNotExist:
             return JSONResponse(
-                content=(
-                    {
-                        "success": False,
-                        "message": "Event not found",
-                    }
-                ),
+                content={
+                    "success": False,
+                    "message": "Event not found",
+                },
                 status_code=404,
             )
-        thumb_results = context.embeddings.search_thumbnail(search_event, limit)
+
+        # Get thumbnail results for the specific event
+        thumb_result = context.embeddings.search_thumbnail(
+            search_event, event_ids, limit
+        )
+
+        thumb_ids = dict(
+            zip(
+                [result[0] for result in thumb_result],
+                context.thumb_stats.normalize([result[1] for result in thumb_result]),
+            )
+        )
     else:
         search_types = search_type.split(",")
 
         if "thumbnail" in search_types:
-            thumb_results = context.embeddings.search_thumbnail(query, limit)
-            logger.info(f"thumb results: {thumb_results}")
+            thumb_result = context.embeddings.search_thumbnail(query, event_ids, limit)
+
+            thumb_ids = dict(
+                zip(
+                    [result[0] for result in thumb_result],
+                    context.thumb_stats.normalize(
+                        [result[1] for result in thumb_result]
+                    ),
+                )
+            )
 
         if "description" in search_types:
-            desc_results = context.embeddings.search_description(query, limit)
+            desc_result = context.embeddings.search_description(query, event_ids, limit)
+
+            desc_ids = dict(
+                zip(
+                    [result[0] for result in desc_result],
+                    context.desc_stats.normalize([result[1] for result in desc_result]),
+                )
+            )
 
     results = {}
-    for result in thumb_results + desc_results:
-        event_id, distance = result[0], result[1]
-        if event_id in event_ids or not event_ids:
-            if event_id not in results or distance < results[event_id]["distance"]:
-                results[event_id] = {
-                    "distance": distance,
-                    "source": "thumbnail" if result in thumb_results else "description",
-                }
+    for event_id in thumb_ids.keys() | desc_ids.keys():
+        thumb_distance = thumb_ids.get(event_id)
+        desc_distance = desc_ids.get(event_id)
+
+        # Select the minimum distance from the available results
+        if thumb_distance is not None and (
+            desc_distance is None or thumb_distance < desc_distance
+        ):
+            results[event_id] = {
+                "distance": thumb_distance,
+                "source": "thumbnail",
+            }
+        elif desc_distance is not None:
+            results[event_id] = {
+                "distance": desc_distance,
+                "source": "description",
+            }
 
     if not results:
         return JSONResponse(content=[])