nginx: don't gzip png, gif, jpeg or jpg (#17400)

* Simplify normalization

* Fix confidence check

docker/main/rootfs/usr/local/nginx/conf/nginx.conf

@@ -30,7 +30,7 @@ http {
 
     gzip on;
     gzip_comp_level 6;
-    gzip_types text/plain text/css application/json application/x-javascript application/javascript text/javascript image/svg+xml image/x-icon image/bmp image/png image/gif image/jpeg image/jpg;
+    gzip_types text/plain text/css application/json application/x-javascript application/javascript text/javascript image/svg+xml image/x-icon image/bmp;
     gzip_proxied no-cache no-store private expired auth;
     gzip_vary on;
 

frigate/data_processing/common/face/model.py

@@ -10,7 +10,7 @@ from scipy import stats
 
 from frigate.config import FrigateConfig
 from frigate.const import MODEL_CACHE_DIR
-from frigate.embeddings.onnx.facenet import ArcfaceEmbedding
+from frigate.embeddings.onnx.face_embedding import ArcfaceEmbedding
 
 logger = logging.getLogger(__name__)
 
@@ -329,7 +329,7 @@ class ArcFaceRecognizer(FaceRecognizer):
             cosine_similarity = dot_product / (magnitude_A * magnitude_B)
             confidence = self.similarity_to_confidence(cosine_similarity)
 
-            if cosine_similarity > score:
+            if confidence > score:
                 score = confidence
                 label = name
 

frigate/embeddings/onnx/face_embedding.py

@@ -90,8 +90,7 @@ class ArcfaceEmbedding(BaseEmbedding):
         frame[y_center : y_center + og_h, x_center : x_center + og_w] = og
 
         # run arcface normalization
-        normalized_image = frame.astype(np.float32) / 255.0
+        frame = (frame / 127.5) - 1.0
-        frame = (normalized_image - 0.5) / 0.5
 
         frame = np.transpose(frame, (2, 0, 1))
         frame = np.expand_dims(frame, axis=0)

web/public/locales/en/views/settings.json

@@ -11,9 +11,9 @@
     "frigatePlus": "Frigate+ Settings - Frigate"
   },
   "menu": {
-    "uiSettings": "UI Settings",
+    "ui": "UI",
-    "classificationSettings": "Classification Settings",
+    "classification": "Classification",
-    "cameraSettings": "Camera Settings",
+    "cameras": "Camera Settings",
     "masksAndZones": "Masks / Zones",
     "motionTuner": "Motion Tuner",
     "debug": "Debug",

web/public/locales/zh-CN/views/settings.json

@@ -11,9 +11,9 @@
     "frigatePlus": "Frigate+ 设置 - Frigate"
   },
   "menu": {
-    "uiSettings": "界面设置",
+    "ui": "界面设置",
-    "classificationSettings": "分类设置",
+    "classification": "分类设置",
-    "cameraSettings": "摄像头设置",
+    "cameras": "摄像头设置",
     "masksAndZones": "遮罩/ 区域",
     "motionTuner": "运动调整器",
     "debug": "调试",
@@ -109,16 +109,16 @@
       "desc": "人脸识别功能允许为人物分配名称，当识别到他们的面孔时，Frigate 会将人物的名字作为子标签进行分配。这些信息会显示在界面、过滤器以及通知中。",
       "readTheDocumentation": "阅读文档（英文）",
       "modelSize": {
-          "label": "模型大小",
+        "label": "模型大小",
-          "desc": "用于人脸识别的模型尺寸。",
+        "desc": "用于人脸识别的模型尺寸。",
-          "small": {
+        "small": {
-              "title": "小模型",
+          "title": "小模型",
-              "desc": "使用<em>小模型</em>将采用OpenCV的局部二值模式直方图(LBPH)算法，可在大多数CPU上高效运行。"
+          "desc": "使用<em>小模型</em>将采用OpenCV的局部二值模式直方图(LBPH)算法，可在大多数CPU上高效运行。"
-          },
+        },
-          "large": {
+        "large": {
-              "title": "大模型",
+          "title": "大模型",
-              "desc": "使用<em>大模型</em>将采用ArcFace人脸嵌入模型，若适用将自动在GPU上运行。"
+          "desc": "使用<em>大模型</em>将采用ArcFace人脸嵌入模型，若适用将自动在GPU上运行。"
-          }
+        }
       }
     },
     "licensePlateRecognition": {
@@ -565,8 +565,8 @@
       "modelSelect": "您可以在Frigate+上选择可用的模型。请注意，只能选择与当前探测器配置兼容的模型。"
     },
     "toast": {
-        "success": "Frigate+ 设置已保存。请重启 Frigate 以应用更改。",
+      "success": "Frigate+ 设置已保存。请重启 Frigate 以应用更改。",
-        "error": "配置更改保存失败：{{errorMessage}}"
+      "error": "配置更改保存失败：{{errorMessage}}"
     }
   }
 }