blakeblackshear.frigate/web/src/hooks/use-stats.ts
GuoQing Liu c8e22a3653
Fix some page i18n wrong (#17682)
* fix: some pages can't translation object label.

* revert: revert wrong label fix

* feat: add openai base_url setting

* fix: fix classification modelSize i18n error

* revert: revert openai base_url setting

* fix: fix enrichments pages i18n keys wrong

* fix: fix mobile bottom bar reindexing embeddings i18n wrong

* feat: add more system stats i18n keys

* fix: fix review filter objects i18n

* chore: remove frigate+ label i18n
2025-04-19 09:02:15 -05:00

129 lines
3.7 KiB
TypeScript

import { FrigateConfig } from "@/types/frigateConfig";
import {
CameraDetectThreshold,
CameraFfmpegThreshold,
InferenceThreshold,
} from "@/types/graph";
import { FrigateStats, PotentialProblem } from "@/types/stats";
import { useMemo } from "react";
import useSWR from "swr";
import useDeepMemo from "./use-deep-memo";
import { capitalizeFirstLetter } from "@/utils/stringUtil";
import { useFrigateStats } from "@/api/ws";
import { useTranslation } from "react-i18next";
export default function useStats(stats: FrigateStats | undefined) {
const { t } = useTranslation(["views/system"]);
const { data: config } = useSWR<FrigateConfig>("config");
const memoizedStats = useDeepMemo(stats);
const potentialProblems = useMemo<PotentialProblem[]>(() => {
const problems: PotentialProblem[] = [];
if (!memoizedStats) {
return problems;
}
// if frigate has just started
// don't look for issues
if (memoizedStats.service.uptime < 120) {
return problems;
}
// check detectors for high inference speeds
Object.entries(memoizedStats["detectors"]).forEach(([key, det]) => {
if (det["inference_speed"] > InferenceThreshold.error) {
problems.push({
text: t("stats.detectIsVerySlow", {
detect: capitalizeFirstLetter(key),
speed: det["inference_speed"],
}),
color: "text-danger",
relevantLink: "/system#general",
});
} else if (det["inference_speed"] > InferenceThreshold.warning) {
problems.push({
text: t("stats.detectIsSlow", {
detect: capitalizeFirstLetter(key),
speed: det["inference_speed"],
}),
color: "text-orange-400",
relevantLink: "/system#general",
});
}
});
// check for offline cameras
Object.entries(memoizedStats["cameras"]).forEach(([name, cam]) => {
if (!config) {
return;
}
if (config.cameras[name].enabled && cam["camera_fps"] == 0) {
problems.push({
text: t("stats.cameraIsOffline", {
camera: capitalizeFirstLetter(name.replaceAll("_", " ")),
}),
color: "text-danger",
relevantLink: "logs",
});
}
});
// check camera cpu usages
Object.entries(memoizedStats["cameras"]).forEach(([name, cam]) => {
const ffmpegAvg = parseFloat(
memoizedStats["cpu_usages"][cam["ffmpeg_pid"]]?.cpu_average,
);
const detectAvg = parseFloat(
memoizedStats["cpu_usages"][cam["pid"]]?.cpu_average,
);
if (!isNaN(ffmpegAvg) && ffmpegAvg >= CameraFfmpegThreshold.error) {
problems.push({
text: t("stats.ffmpegHighCpuUsage", {
camera: capitalizeFirstLetter(name.replaceAll("_", " ")),
ffmpegAvg,
}),
color: "text-danger",
relevantLink: "/system#cameras",
});
}
if (!isNaN(detectAvg) && detectAvg >= CameraDetectThreshold.error) {
problems.push({
text: t("stats.detectHighCpuUsage", {
camera: capitalizeFirstLetter(name.replaceAll("_", " ")),
detectAvg,
}),
color: "text-danger",
relevantLink: "/system#cameras",
});
}
});
return problems;
}, [config, memoizedStats, t]);
return { potentialProblems };
}
export function useAutoFrigateStats() {
const { data: initialStats } = useSWR<FrigateStats>("stats", {
revalidateOnFocus: false,
});
const latestStats = useFrigateStats();
const stats = useMemo(() => {
if (latestStats) {
return latestStats;
}
return initialStats;
}, [initialStats, latestStats]);
return stats;
}