docker/main/install_s6_overlay.sh

@@ -2,7 +2,7 @@
 
 set -euxo pipefail
 
-s6_version="3.2.1.0"
+s6_version="3.1.5.0"
 
 if [[ "${TARGETARCH}" == "amd64" ]]; then
     s6_arch="x86_64"

docs/docs/configuration/face_recognition.md

@@ -65,8 +65,6 @@ Fine-tune face recognition with these optional parameters at the global level of
   - Default: `0.8`.
 - `recognition_threshold`: Recognition confidence score required to add the face to the object as a sub label.
   - Default: `0.9`.
-- `min_faces`: Min face attempts for the sub label to be applied to the person object.
-  - Default: `1`
 - `save_attempts`: Number of images of recognized faces to save for training.
   - Default: `100`.
 - `blur_confidence_filter`: Enables a filter that calculates how blurry the face is and adjusts the confidence based on this.

docs/docs/configuration/reference.md

@@ -559,8 +559,6 @@ face_recognition:
   recognition_threshold: 0.9
   # Optional: Min area of detected face box to consider running face recognition (default: shown below)
   min_area: 500
-  # Optional: Min face attempts for the sub label to be applied to the person object (default: shown below)
-  min_faces: 1
   # Optional: Number of images of recognized faces to save for training (default: shown below)
   save_attempts: 100
   # Optional: Apply a blur quality filter to adjust confidence based on the blur level of the image (default: shown below)

frigate/config/classification.py

@@ -80,12 +80,6 @@ class FaceRecognitionConfig(FrigateBaseModel):
     min_area: int = Field(
         default=750, title="Min area of face box to consider running face recognition."
     )
-    min_faces: int = Field(
-        default=1,
-        gt=0,
-        le=6,
-        title="Min face attempts for the sub label to be applied to the person object.",
-    )
     save_attempts: int = Field(
         default=100, ge=0, title="Number of face attempts to save in the train tab."
     )

frigate/data_processing/real_time/face.py

@@ -302,9 +302,6 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
             self.person_face_history[id]
         )
 
-        if len(self.person_face_history[id]) < self.face_config.min_faces:
-            weighted_sub_label = "unknown"
-
         self.requestor.send_data(
             "tracked_object_update",
             json.dumps(