Fixes (#18338)

* improve spacing of face selection in mobile drawer

* fix spacing

* sort face names alphabetically

* Improve face selection dialog

* Use a state to track when face image loads

The naturalWidth and naturalHeight will always be 0 until the image loads. So we use onLoad and a state to track loading and then calculate the area after it has loaded

* Verify that a camera only tracks objects that are possible to track

* Fix test

* genai docs tweak

* Disable openvino model cache

* Clenaup

* Sanitize floats for estimated speed and angle

Users can configure speed zones in such a way that velocity estimates from Norfair cause a value of inf to be stored as an estimated speed. FastAPI doesn't serialize inf as a float, so trying to return this value would result in an API error. Sanitizing the value before storing should correct this.

---------

Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>

docs/docs/configuration/genai.md

@@ -167,7 +167,7 @@ Analyze the sequence of images containing the {label}. Focus on the likely inten
 
 :::tip
 
-Prompts can use variable replacements like `{label}`, `{sub_label}`, and `{camera}` to substitute information from the tracked object as part of the prompt.
+Prompts can use variable replacements `{label}`, `{sub_label}`, and `{camera}` to substitute information from the tracked object as part of the prompt.
 
 :::
 

frigate/config/config.py

@@ -299,6 +299,22 @@ def verify_motion_and_detect(camera_config: CameraConfig) -> ValueError | None:
         )
 
 
+def verify_objects_track(
+    camera_config: CameraConfig, enabled_objects: list[str]
+) -> None:
+    """Verify that a user has not specified an object to track that is not in the labelmap."""
+    valid_objects = [
+        obj for obj in camera_config.objects.track if obj in enabled_objects
+    ]
+
+    if len(valid_objects) != len(camera_config.objects.track):
+        invalid_objects = set(camera_config.objects.track) - set(valid_objects)
+        logger.warning(
+            f"{camera_config.name} is configured to track {list(invalid_objects)} objects, which are not supported by the current model."
+        )
+        camera_config.objects.track = valid_objects
+
+
 def verify_lpr_and_face(
     frigate_config: FrigateConfig, camera_config: CameraConfig
 ) -> ValueError | None:
@@ -471,6 +487,37 @@ class FrigateConfig(FrigateBaseModel):
             exclude_unset=True,
         )
 
+        for key, detector in self.detectors.items():
+            adapter = TypeAdapter(DetectorConfig)
+            model_dict = (
+                detector
+                if isinstance(detector, dict)
+                else detector.model_dump(warnings="none")
+            )
+            detector_config: BaseDetectorConfig = adapter.validate_python(model_dict)
+
+            # users should not set model themselves
+            if detector_config.model:
+                detector_config.model = None
+
+            model_config = self.model.model_dump(exclude_unset=True, warnings="none")
+
+            if detector_config.model_path:
+                model_config["path"] = detector_config.model_path
+
+            if "path" not in model_config:
+                if detector_config.type == "cpu":
+                    model_config["path"] = "/cpu_model.tflite"
+                elif detector_config.type == "edgetpu":
+                    model_config["path"] = "/edgetpu_model.tflite"
+
+            model = ModelConfig.model_validate(model_config)
+            model.check_and_load_plus_model(self.plus_api, detector_config.type)
+            model.compute_model_hash()
+            labelmap_objects = model.merged_labelmap.values()
+            detector_config.model = model
+            self.detectors[key] = detector_config
+
         for name, camera in self.cameras.items():
             modified_global_config = global_config.copy()
 
@@ -644,6 +691,7 @@ class FrigateConfig(FrigateBaseModel):
             verify_required_zones_exist(camera_config)
             verify_autotrack_zones(camera_config)
             verify_motion_and_detect(camera_config)
+            verify_objects_track(camera_config, labelmap_objects)
             verify_lpr_and_face(self, camera_config)
 
         self.objects.parse_all_objects(self.cameras)
@@ -655,36 +703,6 @@ class FrigateConfig(FrigateBaseModel):
                 "Frigate+ is configured but clean snapshots are not enabled, submissions to Frigate+ will not be possible./"
             )
 
-        for key, detector in self.detectors.items():
-            adapter = TypeAdapter(DetectorConfig)
-            model_dict = (
-                detector
-                if isinstance(detector, dict)
-                else detector.model_dump(warnings="none")
-            )
-            detector_config: BaseDetectorConfig = adapter.validate_python(model_dict)
-
-            # users should not set model themselves
-            if detector_config.model:
-                detector_config.model = None
-
-            model_config = self.model.model_dump(exclude_unset=True, warnings="none")
-
-            if detector_config.model_path:
-                model_config["path"] = detector_config.model_path
-
-            if "path" not in model_config:
-                if detector_config.type == "cpu":
-                    model_config["path"] = "/cpu_model.tflite"
-                elif detector_config.type == "edgetpu":
-                    model_config["path"] = "/edgetpu_model.tflite"
-
-            model = ModelConfig.model_validate(model_config)
-            model.check_and_load_plus_model(self.plus_api, detector_config.type)
-            model.compute_model_hash()
-            detector_config.model = model
-            self.detectors[key] = detector_config
-
         return self
 
     @field_validator("cameras")

frigate/detectors/plugins/openvino.py

@@ -3,11 +3,9 @@ import os
 
 import numpy as np
 import openvino as ov
-import openvino.properties as props
 from pydantic import Field
 from typing_extensions import Literal
 
-from frigate.const import MODEL_CACHE_DIR
 from frigate.detectors.detection_api import DetectionApi
 from frigate.detectors.detector_config import BaseDetectorConfig, ModelTypeEnum
 from frigate.util.model import (
@@ -49,10 +47,6 @@ class OvDetector(DetectionApi):
             logger.error(f"OpenVino model file {detector_config.model.path} not found.")
             raise FileNotFoundError
 
-        os.makedirs(os.path.join(MODEL_CACHE_DIR, "openvino"), exist_ok=True)
-        self.ov_core.set_property(
-            {props.cache_dir: os.path.join(MODEL_CACHE_DIR, "openvino")}
-        )
         self.interpreter = self.ov_core.compile_model(
             model=detector_config.model.path, device_name=detector_config.device
         )

frigate/test/test_config.py

@@ -39,7 +39,7 @@ class TestConfig(unittest.TestCase):
             "description": "Fine tuned model",
             "trainDate": "2023-04-28T23:22:01.262Z",
             "type": "ssd",
-            "supportedDetectors": ["edgetpu"],
+            "supportedDetectors": ["cpu", "edgetpu"],
             "width": 320,
             "height": 320,
             "inputShape": "nhwc",

frigate/track/tracked_object.py

@@ -18,6 +18,7 @@ from frigate.config import (
 )
 from frigate.const import CLIPS_DIR, THUMB_DIR
 from frigate.review.types import SeverityEnum
+from frigate.util.builtin import sanitize_float
 from frigate.util.image import (
     area,
     calculate_region,
@@ -202,6 +203,11 @@ class TrackedObject:
                             )
                         )
 
+                        # users can configure speed zones incorrectly, so sanitize speed_magnitude
+                        # and velocity_angle in case the values come back as inf or NaN
+                        speed_magnitude = sanitize_float(speed_magnitude)
+                        self.velocity_angle = sanitize_float(self.velocity_angle)
+
                         if self.ui_config.unit_system == "metric":
                             self.current_estimated_speed = (
                                 speed_magnitude * 3.6

frigate/util/builtin.py

@@ -4,6 +4,7 @@ import ast
 import copy
 import datetime
 import logging
+import math
 import multiprocessing as mp
 import queue
 import re
@@ -399,3 +400,10 @@ def serialize(
 def deserialize(bytes_data: bytes) -> list[float]:
     """Deserializes a compact "raw bytes" format into a list of floats"""
     return list(struct.unpack("%sf" % (len(bytes_data) // 4), bytes_data))
+
+
+def sanitize_float(value):
+    """Replace NaN or inf with 0.0."""
+    if isinstance(value, (int, float)) and not math.isfinite(value):
+        return 0.0
+    return value

web/src/components/overlay/FaceSelectionDialog.tsx

@@ -53,7 +53,13 @@ export default function FaceSelectionDialog({
   const Selector = isDesktop ? DropdownMenu : Drawer;
   const SelectorTrigger = isDesktop ? DropdownMenuTrigger : DrawerTrigger;
   const SelectorContent = isDesktop ? DropdownMenuContent : DrawerContent;
-  const SelectorItem = isDesktop ? DropdownMenuItem : DrawerClose;
+  const SelectorItem = isDesktop
+    ? DropdownMenuItem
+    : (props: React.HTMLAttributes<HTMLDivElement>) => (
+        <DrawerClose asChild>
+          <div {...props} className={cn(props.className, "my-2")} />
+        </DrawerClose>
+      );
 
   return (
     <div className={className ?? ""}>
@@ -72,10 +78,7 @@ export default function FaceSelectionDialog({
             <TooltipTrigger asChild={isChildButton}>{children}</TooltipTrigger>
           </SelectorTrigger>
           <SelectorContent
-            className={cn(
-              "max-h-[75dvh] overflow-hidden",
-              isMobile && "mx-1 gap-2 rounded-t-2xl px-4",
-            )}
+            className={cn("", isMobile && "mx-1 gap-2 rounded-t-2xl px-4")}
           >
             {isMobile && (
               <DrawerHeader className="sr-only">
@@ -86,8 +89,8 @@ export default function FaceSelectionDialog({
             <DropdownMenuLabel>{t("trainFaceAs")}</DropdownMenuLabel>
             <div
               className={cn(
-                "flex flex-col",
-                isMobile && "gap-2 overflow-y-auto pb-4",
+                "flex max-h-[40dvh] flex-col overflow-y-auto",
+                isMobile && "gap-2 pb-4",
               )}
             >
               <SelectorItem
@@ -97,7 +100,7 @@ export default function FaceSelectionDialog({
                 <LuPlus />
                 {t("createFaceLibrary.new")}
               </SelectorItem>
-              {faceNames.map((faceName) => (
+              {faceNames.sort().map((faceName) => (
                 <SelectorItem
                   key={faceName}
                   className="flex cursor-pointer gap-2 smart-capitalize"

web/src/pages/FaceLibrary.tsx

@@ -876,6 +876,7 @@ function FaceAttempt({
   onRefresh,
 }: FaceAttemptProps) {
   const { t } = useTranslation(["views/faceLibrary"]);
+  const [imageLoaded, setImageLoaded] = useState(false);
 
   const scoreStatus = useMemo(() => {
     if (data.score >= recognitionConfig.recognition_threshold) {
@@ -896,14 +897,12 @@ function FaceAttempt({
   });
 
   const imageArea = useMemo(() => {
-    if (!imgRef.current) {
+    if (imgRef.current == null || !imageLoaded) {
       return undefined;
     }
 
     return imgRef.current.naturalWidth * imgRef.current.naturalHeight;
-    // only refresh when severity changes
-    // eslint-disable-next-line react-hooks/exhaustive-deps
-  }, [imgRef.current]);
+  }, [imageLoaded]);
 
   // api calls
 
@@ -966,9 +965,10 @@ function FaceAttempt({
             : "outline-transparent duration-500",
         )}
       >
-        <div className="relative w-full select-none overflow-hidden rounded-lg *:text-card-foreground">
+        <div className="relative w-full select-none overflow-hidden rounded-lg">
           <img
             ref={imgRef}
+            onLoad={() => setImageLoaded(true)}
             className={cn("size-44", isMobile && "w-full")}
             src={`${baseUrl}clips/faces/train/${data.filename}`}
             onClick={(e) => {