Catch OSError for deleting classification image

docs/docs/configuration/custom_classification/object_classification.md

@@ -35,6 +35,12 @@ For object classification:
   - Ideal when multiple attributes can coexist independently.
   - Example: Detecting if a `person` in a construction yard is wearing a helmet or not.
 
+:::note
+
+A tracked object can only have a single sub label. If you are using Face Recognition and you configure an object classification model for `person` using the sub label type, your sub label may not be assigned correctly as it depends on which enrichment completes its analysis first. Consider using the `attribute` type instead.
+
+:::
+
 ## Assignment Requirements
 
 Sub labels and attributes are only assigned when both conditions are met:

docs/docs/configuration/object_detectors.md

@@ -147,11 +147,11 @@ detectors:
 ### EdgeTPU Supported Models
 
 | Model                   | Notes                                       |
-| ------------------------------------- | ------------------------------------------- |
-| [MobileNet v2](#ssdlite-mobilenet-v2) | Default model                               |
-| [YOLOv9](#yolo-v9)                    | More accurate but slower than default model |
+| ----------------------- | ------------------------------------------- |
+| [Mobiledet](#mobiledet) | Default model                               |
+| [YOLOv9](#yolov9)       | More accurate but slower than default model |
 
-#### SSDLite MobileNet v2
+#### Mobiledet
 
 A TensorFlow Lite model is provided in the container at `/edgetpu_model.tflite` and is used by this detector type by default. To provide your own model, bind mount the file into the container and provide the path with `model.path`.
 

frigate/data_processing/real_time/custom_classification.py

@@ -654,5 +654,5 @@ def write_classification_attempt(
 
         if len(files) > max_files:
             os.unlink(os.path.join(folder, files[-1]))
-    except FileNotFoundError:
+    except (FileNotFoundError, OSError):
         pass