keep 5000 as anonymous user

docs/static/frigate-api.yaml

@@ -25,7 +25,7 @@ paths:
           description: Authentication Accepted (no response body, different headers depending on auth method)
           headers:
             remote-user:
-              description: Authenticated username or "anonymous" in proxy-only mode
+              description: Authenticated username or "viewer" in proxy-only mode
               schema:
                 type: string
             remote-role:

frigate/api/auth.py

@@ -167,7 +167,7 @@ def allow_any_authenticated():
     Allows:
     - Port 5000 internal requests (remote-user: "anonymous", remote-role: "admin")
     - Authenticated users with JWT tokens (remote-user: username)
-    - Unauthenticated requests when auth is disabled (remote-user: "anonymous")
+    - Unauthenticated requests when auth is disabled (remote-user: "viewer")
 
     Rejects:
     - Requests with no remote-user header (did not pass through /auth endpoint)
@@ -550,7 +550,7 @@ def resolve_role(
             "description": "Authentication Accepted (no response body)",
             "headers": {
                 "remote-user": {
-                    "description": 'Authenticated username or "anonymous" in proxy-only mode',
+                    "description": 'Authenticated username or "viewer" in proxy-only mode',
                     "schema": {"type": "string"},
                 },
                 "remote-role": {
@@ -592,12 +592,12 @@ def auth(request: Request):
     # if auth is disabled, just apply the proxy header map and return success
     if not auth_config.enabled:
         # pass the user header value from the upstream proxy if a mapping is specified
-        # or use anonymous if none are specified
+        # or use viewer if none are specified
         user_header = proxy_config.header_map.user
         success_response.headers["remote-user"] = (
-            request.headers.get(user_header, default="anonymous")
+            request.headers.get(user_header, default="viewer")
             if user_header
-            else "anonymous"
+            else "viewer"
         )
 
         # parse header and resolve a valid role
@@ -712,7 +712,7 @@ def auth(request: Request):
     description="Returns the current authenticated user's profile including username, role, and allowed cameras. This endpoint requires authentication and returns information about the user's permissions.",
 )
 def profile(request: Request):
-    username = request.headers.get("remote-user", "anonymous")
+    username = request.headers.get("remote-user", "viewer")
     role = request.headers.get("remote-role", "viewer")
 
     all_camera_names = set(request.app.frigate_config.cameras.keys())

frigate/comms/mqtt.py

@@ -225,7 +225,8 @@ class MqttClient(Communicator):
             "birdseye_mode",
             "review_alerts",
             "review_detections",
-            "genai",
+            "object_descriptions",
+            "review_descriptions",
         ]
 
         for name in self.config.cameras.keys():

frigate/const.py

@@ -77,6 +77,9 @@ FFMPEG_HWACCEL_RKMPP = "preset-rkmpp"
 FFMPEG_HWACCEL_AMF = "preset-amd-amf"
 FFMPEG_HVC1_ARGS = ["-tag:v", "hvc1"]
 
+# RKNN constants
+SUPPORTED_RK_SOCS = ["rk3562", "rk3566", "rk3568", "rk3576", "rk3588"]
+
 # Regex constants
 
 REGEX_CAMERA_NAME = r"^[a-zA-Z0-9_-]+$"

frigate/detectors/plugins/rknn.py

@@ -8,7 +8,7 @@ import cv2
 import numpy as np
 from pydantic import Field
 
-from frigate.const import MODEL_CACHE_DIR
+from frigate.const import MODEL_CACHE_DIR, SUPPORTED_RK_SOCS
 from frigate.detectors.detection_api import DetectionApi
 from frigate.detectors.detection_runners import RKNNModelRunner
 from frigate.detectors.detector_config import BaseDetectorConfig, ModelTypeEnum
@@ -19,8 +19,6 @@ logger = logging.getLogger(__name__)
 
 DETECTOR_KEY = "rknn"
 
-supported_socs = ["rk3562", "rk3566", "rk3568", "rk3576", "rk3588"]
-
 supported_models = {
     ModelTypeEnum.yologeneric: "^frigate-fp16-yolov9-[cemst]$",
     ModelTypeEnum.yolonas: "^deci-fp16-yolonas_[sml]$",
@@ -82,9 +80,9 @@ class Rknn(DetectionApi):
         except FileNotFoundError:
             raise Exception("Make sure to run docker in privileged mode.")
 
-        if soc not in supported_socs:
+        if soc not in SUPPORTED_RK_SOCS:
             raise Exception(
-                f"Your SoC is not supported. Your SoC is: {soc}. Currently these SoCs are supported: {supported_socs}."
+                f"Your SoC is not supported. Your SoC is: {soc}. Currently these SoCs are supported: {SUPPORTED_RK_SOCS}."
             )
 
         return soc

frigate/util/rknn_converter.py

@@ -8,6 +8,7 @@ import time
 from pathlib import Path
 from typing import Optional
 
+from frigate.const import SUPPORTED_RK_SOCS
 from frigate.util.file import FileLock
 
 logger = logging.getLogger(__name__)
@@ -68,9 +69,20 @@ def is_rknn_compatible(model_path: str, model_type: str | None = None) -> bool:
         True if the model is RKNN-compatible, False otherwise
     """
     soc = get_soc_type()
+
     if soc is None:
         return False
 
+    # Check if the SoC is actually a supported RK device
+    # This prevents false positives on non-RK devices (e.g., macOS Docker)
+    # where /proc/device-tree/compatible might exist but contain non-RK content
+    if soc not in SUPPORTED_RK_SOCS:
+        logger.debug(
+            f"SoC '{soc}' is not a supported RK device for RKNN conversion. "
+            f"Supported SoCs: {SUPPORTED_RK_SOCS}"
+        )
+        return False
+
     if not model_type:
         model_type = get_rknn_model_type(model_path)
 

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

@@ -139,6 +139,7 @@
         "nameOnlyNumbers": "Model name cannot contain only numbers",
         "classRequired": "At least 1 class is required",
         "classesUnique": "Class names must be unique",
+        "noneNotAllowed": "The class 'none' is not allowed",
         "stateRequiresTwoClasses": "State models require at least 2 classes",
         "objectLabelRequired": "Please select an object label",
         "objectTypeRequired": "Please select a classification type"

web/src/components/card/ClassificationCard.tsx

@@ -40,6 +40,7 @@ type ClassificationCardProps = {
   data: ClassificationItemData;
   threshold?: ClassificationThreshold;
   selected: boolean;
+  clickable: boolean;
   i18nLibrary: string;
   showArea?: boolean;
   count?: number;
@@ -56,6 +57,7 @@ export const ClassificationCard = forwardRef<
     data,
     threshold,
     selected,
+    clickable,
     i18nLibrary,
     showArea = true,
     count,
@@ -101,11 +103,12 @@ export const ClassificationCard = forwardRef<
     <div
       ref={ref}
       className={cn(
-        "relative flex size-full cursor-pointer flex-col overflow-hidden rounded-lg outline outline-[3px]",
+        "relative flex size-full flex-col overflow-hidden rounded-lg outline outline-[3px]",
         className,
         selected
           ? "shadow-selected outline-selected"
           : "outline-transparent duration-500",
+        clickable && "cursor-pointer",
       )}
       onClick={(e) => {
         const isMeta = e.metaKey || e.ctrlKey;
@@ -289,6 +292,7 @@ export function GroupedClassificationCard({
         data={bestItem}
         threshold={threshold}
         selected={selectedItems.includes(bestItem.filename)}
+        clickable={true}
         i18nLibrary={i18nLibrary}
         count={group.length}
         onClick={(_, meta) => {
@@ -413,6 +417,7 @@ export function GroupedClassificationCard({
                     data={data}
                     threshold={threshold}
                     selected={false}
+                    clickable={false}
                     i18nLibrary={i18nLibrary}
                     onClick={() => {}}
                   >

web/src/components/classification/wizard/Step1NameAndDefine.tsx

@@ -94,7 +94,14 @@ export default function Step1NameAndDefine({
       objectLabel: z.string().optional(),
       objectType: z.enum(["sub_label", "attribute"]).optional(),
       classes: z
-        .array(z.string())
+        .array(
+          z
+            .string()
+            .refine(
+              (val) => val.trim().toLowerCase() !== "none",
+              t("wizard.step1.errors.noneNotAllowed"),
+            ),
+        )
         .min(1, t("wizard.step1.errors.classRequired"))
         .refine(
           (classes) => {
@@ -467,6 +474,7 @@ export default function Step1NameAndDefine({
                           )}
                         </div>
                       </FormControl>
+                      <FormMessage />
                     </FormItem>
                   )}
                 />

web/src/pages/FaceLibrary.tsx

@@ -1026,6 +1026,7 @@ function FaceGrid({
               filepath: `clips/faces/${pageToggle}/${image}`,
             }}
             selected={selectedFaces.includes(image)}
+            clickable={selectedFaces.length > 0}
             i18nLibrary="views/faceLibrary"
             onClick={(data, meta) => onClickFaces([data.filename], meta)}
           >

web/src/views/classification/ModelTrainingView.tsx

@@ -804,6 +804,7 @@ function DatasetGrid({
               name: "",
             }}
             showArea={false}
+            clickable={selectedImages.length > 0}
             selected={selectedImages.includes(image)}
             i18nLibrary="views/classificationModel"
             onClick={(data, _) => onClickImages([data.filename], true)}
@@ -962,6 +963,7 @@ function StateTrainGrid({
             data={data}
             threshold={threshold}
             selected={selectedImages.includes(data.filename)}
+            clickable={selectedImages.length > 0}
             i18nLibrary="views/classificationModel"
             showArea={false}
             onClick={(data, meta) => onClickImages([data.filename], meta)}