fix formatting due to new version of ruff

frigate/api/classification.py

@@ -73,7 +73,7 @@ def get_faces():
         face_dict[name] = []
 
         for file in filter(
-            lambda f: (f.lower().endswith((".webp", ".png", ".jpg", ".jpeg"))),
+            lambda f: f.lower().endswith((".webp", ".png", ".jpg", ".jpeg")),
             os.listdir(face_dir),
         ):
             face_dict[name].append(file)
@@ -582,7 +582,7 @@ def get_classification_dataset(name: str):
         dataset_dict[category_name] = []
 
         for file in filter(
-            lambda f: (f.lower().endswith((".webp", ".png", ".jpg", ".jpeg"))),
+            lambda f: f.lower().endswith((".webp", ".png", ".jpg", ".jpeg")),
             os.listdir(category_dir),
         ):
             dataset_dict[category_name].append(file)
@@ -693,7 +693,7 @@ def get_classification_images(name: str):
         status_code=200,
         content=list(
             filter(
-                lambda f: (f.lower().endswith((".webp", ".png", ".jpg", ".jpeg"))),
+                lambda f: f.lower().endswith((".webp", ".png", ".jpg", ".jpeg")),
                 os.listdir(train_dir),
             )
         ),

frigate/data_processing/real_time/custom_classification.py

@@ -695,7 +695,7 @@ def write_classification_attempt(
     # delete oldest face image if maximum is reached
     try:
         files = sorted(
-            filter(lambda f: (f.endswith(".webp")), os.listdir(folder)),
+            filter(lambda f: f.endswith(".webp"), os.listdir(folder)),
             key=lambda f: os.path.getctime(os.path.join(folder, f)),
             reverse=True,
         )

frigate/data_processing/real_time/face.py

@@ -539,7 +539,7 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
             cv2.imwrite(file, frame)
 
             files = sorted(
-                filter(lambda f: (f.endswith(".webp")), os.listdir(folder)),
+                filter(lambda f: f.endswith(".webp"), os.listdir(folder)),
                 key=lambda f: os.path.getctime(os.path.join(folder, f)),
                 reverse=True,
             )

frigate/log.py

@@ -26,15 +26,16 @@ LOG_HANDLER.setFormatter(
 
 # filter out norfair warning
 LOG_HANDLER.addFilter(
-    lambda record: not record.getMessage().startswith(
-        "You are using a scalar distance function"
+    lambda record: (
+        not record.getMessage().startswith("You are using a scalar distance function")
     )
 )
 
 # filter out tflite logging
 LOG_HANDLER.addFilter(
-    lambda record: "Created TensorFlow Lite XNNPACK delegate for CPU."
-    not in record.getMessage()
+    lambda record: (
+        "Created TensorFlow Lite XNNPACK delegate for CPU." not in record.getMessage()
+    )
 )
 
 

frigate/record/maintainer.py

@@ -208,8 +208,10 @@ class RecordingMaintainer(threading.Thread):
             processed_segment_count = len(
                 list(
                     filter(
-                        lambda r: r["start_time"].timestamp()
-                        < most_recently_processed_frame_time,
+                        lambda r: (
+                            r["start_time"].timestamp()
+                            < most_recently_processed_frame_time
+                        ),
                         grouped_recordings[camera],
                     )
                 )