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9 Commits

Author SHA1 Message Date
Nicolas Mowen
c84bfd3ace Improve deletion handling for classes 2025-11-10 06:28:47 -07:00
Nicolas Mowen
e0389382f8 Remove images when wizard is cancelled 2025-11-10 06:21:50 -07:00
Nicolas Mowen
8aad89a83a Improve flow handling for classification state 2025-11-10 06:21:44 -07:00
Nicolas Mowen
55dcbc6371 Adjust default rounded corners on larger screens 2025-11-10 05:57:30 -07:00
Nicolas Mowen
b8216d0536 Handle case where classification images are deleted 2025-11-10 05:51:09 -07:00
Josh Hawkins
c0f1fa1f61 fix race condition in detail stream context
navigating between tracked objects in Explore would sometimes prevent the object track from appearing
2025-11-10 06:50:32 -06:00
Nicolas Mowen
c3f242dc53 Catch OpenVINO runtime error 2025-11-10 05:31:04 -07:00
Nicolas Mowen
6ee5f246aa Import faster_whisper conditinally to avoid illegal instruction 2025-11-10 05:26:14 -07:00
Josh Hawkins
0314bdf84c Don't warn when event ids have expired for trigger sync 2025-11-09 20:20:24 -06:00
12 changed files with 61 additions and 171 deletions

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@ -177,12 +177,6 @@ class CameraConfig(FrigateBaseModel):
def ffmpeg_cmds(self) -> list[dict[str, list[str]]]:
return self._ffmpeg_cmds
def get_formatted_name(self) -> str:
"""Return the friendly name if set, otherwise return a formatted version of the camera name."""
if self.friendly_name:
return self.friendly_name
return self.name.replace("_", " ").title() if self.name else ""
def create_ffmpeg_cmds(self):
if "_ffmpeg_cmds" in self:
return

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@ -56,12 +56,6 @@ class ZoneConfig(BaseModel):
def contour(self) -> np.ndarray:
return self._contour
def get_formatted_name(self, zone_name: str) -> str:
"""Return the friendly name if set, otherwise return a formatted version of the zone name."""
if self.friendly_name:
return self.friendly_name
return zone_name.replace("_", " ").title()
@field_validator("objects", mode="before")
@classmethod
def validate_objects(cls, v):

View File

@ -16,7 +16,6 @@ from peewee import DoesNotExist
from frigate.comms.embeddings_updater import EmbeddingsRequestEnum
from frigate.comms.inter_process import InterProcessRequestor
from frigate.config import FrigateConfig
from frigate.config.camera import CameraConfig
from frigate.config.camera.review import GenAIReviewConfig, ImageSourceEnum
from frigate.const import CACHE_DIR, CLIPS_DIR, UPDATE_REVIEW_DESCRIPTION
from frigate.data_processing.types import PostProcessDataEnum
@ -31,7 +30,6 @@ from ..types import DataProcessorMetrics
logger = logging.getLogger(__name__)
RECORDING_BUFFER_EXTENSION_PERCENT = 0.10
MIN_RECORDING_DURATION = 10
class ReviewDescriptionProcessor(PostProcessorApi):
@ -132,17 +130,7 @@ class ReviewDescriptionProcessor(PostProcessorApi):
if image_source == ImageSourceEnum.recordings:
duration = final_data["end_time"] - final_data["start_time"]
buffer_extension = min(
10, max(2, duration * RECORDING_BUFFER_EXTENSION_PERCENT)
)
# Ensure minimum total duration for short review items
# This provides better context for brief events
total_duration = duration + (2 * buffer_extension)
if total_duration < MIN_RECORDING_DURATION:
# Expand buffer to reach minimum duration, still respecting max of 10s per side
additional_buffer_per_side = (MIN_RECORDING_DURATION - duration) / 2
buffer_extension = min(10, additional_buffer_per_side)
buffer_extension = duration * RECORDING_BUFFER_EXTENSION_PERCENT
thumbs = self.get_recording_frames(
camera,
@ -194,7 +182,7 @@ class ReviewDescriptionProcessor(PostProcessorApi):
self.requestor,
self.genai_client,
self.review_desc_speed,
camera_config,
camera,
final_data,
thumbs,
camera_config.review.genai,
@ -423,7 +411,7 @@ def run_analysis(
requestor: InterProcessRequestor,
genai_client: GenAIClient,
review_inference_speed: InferenceSpeed,
camera_config: CameraConfig,
camera: str,
final_data: dict[str, str],
thumbs: list[bytes],
genai_config: GenAIReviewConfig,
@ -431,19 +419,10 @@ def run_analysis(
attribute_labels: list[str],
) -> None:
start = datetime.datetime.now().timestamp()
# Format zone names using zone config friendly names if available
formatted_zones = []
for zone_name in final_data["data"]["zones"]:
if zone_name in camera_config.zones:
formatted_zones.append(
camera_config.zones[zone_name].get_formatted_name(zone_name)
)
analytics_data = {
"id": final_data["id"],
"camera": camera_config.get_formatted_name(),
"zones": formatted_zones,
"camera": camera,
"zones": final_data["data"]["zones"],
"start": datetime.datetime.fromtimestamp(final_data["start_time"]).strftime(
"%A, %I:%M %p"
),

View File

@ -51,7 +51,8 @@ class GenAIClient:
def get_concern_prompt() -> str:
if concerns:
concern_list = "\n - ".join(concerns)
return f"""- `other_concerns` (list of strings): Include a list of any of the following concerns that are occurring:
return f"""
- `other_concerns` (list of strings): Include a list of any of the following concerns that are occurring:
- {concern_list}"""
else:
return ""
@ -69,7 +70,7 @@ class GenAIClient:
return "\n- (No objects detected)"
context_prompt = f"""
Your task is to analyze the sequence of images ({len(thumbnails)} total) taken in chronological order from the perspective of the {review_data["camera"]} security camera.
Your task is to analyze the sequence of images ({len(thumbnails)} total) taken in chronological order from the perspective of the {review_data["camera"].replace("_", " ")} security camera.
## Normal Activity Patterns for This Property
@ -109,7 +110,7 @@ Your response MUST be a flat JSON object with:
- Frame 1 = earliest, Frame {len(thumbnails)} = latest
- Activity started at {review_data["start"]} and lasted {review_data["duration"]} seconds
- Zones involved: {", ".join(review_data["zones"]) if review_data["zones"] else "None"}
- Zones involved: {", ".join(z.replace("_", " ").title() for z in review_data["zones"]) or "None"}
## Objects in Scene

View File

@ -28,7 +28,6 @@ import {
CustomClassificationModelConfig,
FrigateConfig,
} from "@/types/frigateConfig";
import { ClassificationDatasetResponse } from "@/types/classification";
import { getTranslatedLabel } from "@/utils/i18n";
import { zodResolver } from "@hookform/resolvers/zod";
import axios from "axios";
@ -141,19 +140,16 @@ export default function ClassificationModelEditDialog({
});
// Fetch dataset to get current classes for state models
const { data: dataset } = useSWR<ClassificationDatasetResponse>(
isStateModel ? `classification/${model.name}/dataset` : null,
{
revalidateOnFocus: false,
},
);
const { data: dataset } = useSWR<{
[id: string]: string[];
}>(isStateModel ? `classification/${model.name}/dataset` : null, {
revalidateOnFocus: false,
});
// Update form with classes from dataset when loaded
useEffect(() => {
if (isStateModel && dataset?.categories) {
const classes = Object.keys(dataset.categories).filter(
(key) => key !== "none",
);
if (isStateModel && dataset) {
const classes = Object.keys(dataset).filter((key) => key !== "none");
if (classes.length > 0) {
(form as ReturnType<typeof useForm<StateFormData>>).setValue(
"classes",

View File

@ -6,7 +6,6 @@ import { LivePlayerMode, LiveStreamMetadata } from "@/types/live";
export default function useCameraLiveMode(
cameras: CameraConfig[],
windowVisible: boolean,
activeStreams?: { [cameraName: string]: string },
) {
const { data: config } = useSWR<FrigateConfig>("config");
@ -21,20 +20,16 @@ export default function useCameraLiveMode(
);
if (isRestreamed) {
if (activeStreams && activeStreams[camera.name]) {
streamNames.add(activeStreams[camera.name]);
} else {
Object.values(camera.live.streams).forEach((streamName) => {
streamNames.add(streamName);
});
}
Object.values(camera.live.streams).forEach((streamName) => {
streamNames.add(streamName);
});
}
});
return streamNames.size > 0
? Array.from(streamNames).sort().join(",")
: null;
}, [cameras, config, activeStreams]);
}, [cameras, config]);
const streamsFetcher = useCallback(async (key: string) => {
const streamNames = key.split(",");
@ -73,9 +68,7 @@ export default function useCameraLiveMode(
[key: string]: LiveStreamMetadata;
}>(restreamedStreamsKey, streamsFetcher, {
revalidateOnFocus: false,
revalidateOnReconnect: false,
revalidateIfStale: false,
dedupingInterval: 60000,
dedupingInterval: 10000,
});
const [preferredLiveModes, setPreferredLiveModes] = useState<{

View File

@ -20,17 +20,3 @@ export type ClassificationThreshold = {
recognition: number;
unknown: number;
};
export type ClassificationDatasetResponse = {
categories: {
[id: string]: string[];
};
training_metadata: {
has_trained: boolean;
last_training_date: string | null;
last_training_image_count: number;
current_image_count: number;
new_images_count: number;
dataset_changed: boolean;
} | null;
};

View File

@ -11,7 +11,6 @@ import {
CustomClassificationModelConfig,
FrigateConfig,
} from "@/types/frigateConfig";
import { ClassificationDatasetResponse } from "@/types/classification";
import { useCallback, useEffect, useMemo, useState } from "react";
import { useTranslation } from "react-i18next";
import { FaFolderPlus } from "react-icons/fa";
@ -210,10 +209,9 @@ type ModelCardProps = {
function ModelCard({ config, onClick, onUpdate, onDelete }: ModelCardProps) {
const { t } = useTranslation(["views/classificationModel"]);
const { data: dataset } = useSWR<ClassificationDatasetResponse>(
`classification/${config.name}/dataset`,
{ revalidateOnFocus: false },
);
const { data: dataset } = useSWR<{
[id: string]: string[];
}>(`classification/${config.name}/dataset`, { revalidateOnFocus: false });
const [deleteDialogOpen, setDeleteDialogOpen] = useState(false);
const [editDialogOpen, setEditDialogOpen] = useState(false);
@ -262,25 +260,20 @@ function ModelCard({ config, onClick, onUpdate, onDelete }: ModelCardProps) {
}, []);
const coverImage = useMemo(() => {
if (!dataset || !dataset.categories) {
return undefined;
}
const keys = Object.keys(dataset.categories).filter((key) => key != "none");
if (keys.length === 0) {
if (!dataset) {
return undefined;
}
const keys = Object.keys(dataset).filter((key) => key != "none");
const selectedKey = keys[0];
const images = dataset.categories[selectedKey];
if (!images || images.length === 0) {
if (!dataset[selectedKey]) {
return undefined;
}
return {
name: selectedKey,
img: images[0],
img: dataset[selectedKey][0],
};
}, [dataset]);
@ -324,19 +317,11 @@ function ModelCard({ config, onClick, onUpdate, onDelete }: ModelCardProps) {
)}
onClick={onClick}
>
{coverImage ? (
<>
<img
className="size-full"
src={`${baseUrl}clips/${config.name}/dataset/${coverImage.name}/${coverImage.img}`}
/>
<ImageShadowOverlay lowerClassName="h-[30%] z-0" />
</>
) : (
<div className="flex size-full items-center justify-center bg-background_alt">
<MdModelTraining className="size-16 text-muted-foreground" />
</div>
)}
<img
className="size-full"
src={`${baseUrl}clips/${config.name}/dataset/${coverImage?.name}/${coverImage?.img}`}
/>
<ImageShadowOverlay lowerClassName="h-[30%] z-0" />
<div className="absolute bottom-2 left-3 text-lg text-white smart-capitalize">
{config.name}
</div>

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@ -59,11 +59,7 @@ import { useNavigate } from "react-router-dom";
import { IoMdArrowRoundBack } from "react-icons/io";
import TrainFilterDialog from "@/components/overlay/dialog/TrainFilterDialog";
import useApiFilter from "@/hooks/use-api-filter";
import {
ClassificationDatasetResponse,
ClassificationItemData,
TrainFilter,
} from "@/types/classification";
import { ClassificationItemData, TrainFilter } from "@/types/classification";
import {
ClassificationCard,
GroupedClassificationCard,
@ -122,10 +118,17 @@ export default function ModelTrainingView({ model }: ModelTrainingViewProps) {
const { data: trainImages, mutate: refreshTrain } = useSWR<string[]>(
`classification/${model.name}/train`,
);
const { data: datasetResponse, mutate: refreshDataset } =
useSWR<ClassificationDatasetResponse>(
`classification/${model.name}/dataset`,
);
const { data: datasetResponse, mutate: refreshDataset } = useSWR<{
categories: { [id: string]: string[] };
training_metadata: {
has_trained: boolean;
last_training_date: string | null;
last_training_image_count: number;
current_image_count: number;
new_images_count: number;
dataset_changed: boolean;
} | null;
}>(`classification/${model.name}/dataset`);
const dataset = datasetResponse?.categories || {};
const trainingMetadata = datasetResponse?.training_metadata;

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@ -86,6 +86,14 @@ export default function DraggableGridLayout({
// preferred live modes per camera
const {
preferredLiveModes,
setPreferredLiveModes,
resetPreferredLiveMode,
isRestreamedStates,
supportsAudioOutputStates,
} = useCameraLiveMode(cameras, windowVisible);
const [globalAutoLive] = usePersistence("autoLiveView", true);
const [displayCameraNames] = usePersistence("displayCameraNames", false);
@ -98,33 +106,6 @@ export default function DraggableGridLayout({
}
}, [allGroupsStreamingSettings, cameraGroup]);
const activeStreams = useMemo(() => {
const streams: { [cameraName: string]: string } = {};
cameras.forEach((camera) => {
const availableStreams = camera.live.streams || {};
const streamNameFromSettings =
currentGroupStreamingSettings?.[camera.name]?.streamName || "";
const streamExists =
streamNameFromSettings &&
Object.values(availableStreams).includes(streamNameFromSettings);
const streamName = streamExists
? streamNameFromSettings
: Object.values(availableStreams)[0] || "";
streams[camera.name] = streamName;
});
return streams;
}, [cameras, currentGroupStreamingSettings]);
const {
preferredLiveModes,
setPreferredLiveModes,
resetPreferredLiveMode,
isRestreamedStates,
supportsAudioOutputStates,
} = useCameraLiveMode(cameras, windowVisible, activeStreams);
// grid layout
const ResponsiveGridLayout = useMemo(() => WidthProvider(Responsive), []);

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@ -162,9 +162,6 @@ export default function LiveCameraView({
isRestreamed ? `go2rtc/streams/${streamName}` : null,
{
revalidateOnFocus: false,
revalidateOnReconnect: false,
revalidateIfStale: false,
dedupingInterval: 60000,
},
);

View File

@ -202,6 +202,14 @@ export default function LiveDashboardView({
};
}, []);
const {
preferredLiveModes,
setPreferredLiveModes,
resetPreferredLiveMode,
isRestreamedStates,
supportsAudioOutputStates,
} = useCameraLiveMode(cameras, windowVisible);
const [globalAutoLive] = usePersistence("autoLiveView", true);
const [displayCameraNames] = usePersistence("displayCameraNames", false);
@ -231,33 +239,6 @@ export default function LiveDashboardView({
[visibleCameraObserver.current],
);
const activeStreams = useMemo(() => {
const streams: { [cameraName: string]: string } = {};
cameras.forEach((camera) => {
const availableStreams = camera.live.streams || {};
const streamNameFromSettings =
currentGroupStreamingSettings?.[camera.name]?.streamName || "";
const streamExists =
streamNameFromSettings &&
Object.values(availableStreams).includes(streamNameFromSettings);
const streamName = streamExists
? streamNameFromSettings
: Object.values(availableStreams)[0] || "";
streams[camera.name] = streamName;
});
return streams;
}, [cameras, currentGroupStreamingSettings]);
const {
preferredLiveModes,
setPreferredLiveModes,
resetPreferredLiveMode,
isRestreamedStates,
supportsAudioOutputStates,
} = useCameraLiveMode(cameras, windowVisible, activeStreams);
const birdseyeConfig = useMemo(() => config?.birdseye, [config]);
const handleError = useCallback(