Refactor face library page (#17424)

* Section faces by event id

* Make score keeping more robust

* layout improvements

* Cleanup dialog

* Fix clicking behavior

* Add view in explore option

* math.round

* Don't require events

* Cleanup

* Remove selection

* Don't require

* Change dialog size with snapshot

* Use filename as key

* fix key

* Rework layout for mobile

* Handle mobile landscape

* Fix train issue

* Match logic

* Move deletion logic

* Fix reprocessing

* Support creating a new face

* Translations

* Do sorting in frontend

* Adjust unknown

* Cleanup

* Set max limit to faces to recognize

* Fix sorting

* Fix

frigate/api/classification.py

@@ -41,13 +41,9 @@ def get_faces():
 
         face_dict[name] = []
 
-        for file in sorted(
-            filter(
-                lambda f: (f.lower().endswith((".webp", ".png", ".jpg", ".jpeg"))),
-                os.listdir(face_dir),
-            ),
-            key=lambda f: os.path.getctime(os.path.join(face_dir, f)),
-            reverse=True,
+        for file in filter(
+            lambda f: (f.lower().endswith((".webp", ".png", ".jpg", ".jpeg"))),
+            os.listdir(face_dir),
         ):
             face_dict[name].append(file)
 
@@ -125,10 +121,13 @@ def train_face(request: Request, name: str, body: dict = None):
     sanitized_name = sanitize_filename(name)
     rand_id = "".join(random.choices(string.ascii_lowercase + string.digits, k=6))
     new_name = f"{sanitized_name}-{rand_id}.webp"
-    new_file = os.path.join(FACE_DIR, f"{sanitized_name}/{new_name}")
+    new_file_folder = os.path.join(FACE_DIR, f"{sanitized_name}")
+
+    if not os.path.exists(new_file_folder):
+        os.mkdir(new_file_folder)
 
     if training_file_name:
-        shutil.move(training_file, new_file)
+        shutil.move(training_file, os.path.join(new_file_folder, new_name))
     else:
         try:
             event: Event = Event.get(Event.id == event_id)
@@ -155,7 +154,7 @@ def train_face(request: Request, name: str, body: dict = None):
         x2 = x1 + int(face_box[2] * detect_config.width) - 4
         y2 = y1 + int(face_box[3] * detect_config.height) - 4
         face = snapshot[y1:y2, x1:x2]
-        cv2.imwrite(new_file, face)
+        cv2.imwrite(os.path.join(new_file_folder, new_name), face)
 
     context: EmbeddingsContext = request.app.embeddings
     context.clear_face_classifier()