diff --git a/frigate/embeddings/maintainer.py b/frigate/embeddings/maintainer.py
index 13c5a26c5..d3df385cc 100644
--- a/frigate/embeddings/maintainer.py
+++ b/frigate/embeddings/maintainer.py
@@ -105,7 +105,7 @@ class EmbeddingMaintainer(threading.Thread):
         # Lazily create the classifier.
         if "face_detector" not in self.__dict__:
             self.__dict__["face_detector"] = cv2.FaceDetectorYN.create(
-                "/config/model_cache/facenet/facedet.onnx",
+                "/config/model_cache/facedet/facedet.onnx",
                 config="",
                 input_size=(320, 320),
                 score_threshold=0.8,
diff --git a/frigate/util/model.py b/frigate/util/model.py
index cc4ccb0d0..b3e310225 100644
--- a/frigate/util/model.py
+++ b/frigate/util/model.py
@@ -163,7 +163,7 @@ class FaceClassificationModel:
         self.config = config
         self.db = db
         self.landmark_detector = cv2.face.createFacemarkLBF()
-        self.landmark_detector.loadModel("/config/model_cache/facenet/landmarkdet.yaml")
+        self.landmark_detector.loadModel("/config/model_cache/facedet/landmarkdet.yaml")
         self.recognizer: cv2.face.LBPHFaceRecognizer = (
             cv2.face.LBPHFaceRecognizer_create(
                 radius=2, threshold=(1 - config.threshold) * 1000