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5 Commits

Author SHA1 Message Date
Eric W
1a09423831
Merge 317d1acfe1 into 088e1ad7ef 2026-04-28 17:34:17 -07:00
Nicolas Mowen
088e1ad7ef
Add ability to download case as zip (#23034)
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2026-04-28 19:11:41 -05:00
Josh Hawkins
011ad8eda7
Miscellaneous fixes (#23017)
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* add ui to camera config update topics enum

* add mqtt to camera config update enum

* ensure cleanup runs when an event end skips post-processing

* end any in-progress audio events when audio detection is disabled

we already end in-progress audio events when we disable a camera, but this mirrors that logic for specifically disabling audio detection

* Improve GenAI metadata

* fix invalid recording segment topic being misrouted to the valid handler

* Add confidence default to avoid unnecessary field causing issues

---------

Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
2026-04-28 08:54:09 -06:00
Nicolas Mowen
4171efcd79
Miscellaneous fixes (#23009)
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* Reduce max frames per second to 1

* Use pydantic but don't fail if some constraints are not met.

* Adjust limits

* Adjust limits

* Cleanup

* add unsaved changes icon/popover to individual settings section

* allow changing camera friendly_name from camera management pane

---------

Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>
2026-04-26 17:09:35 -05:00
Eric W
317d1acfe1 Fix motion activity endpoint returning invalid timestamps after pandas 3.0 upgrade
pandas 3.0 changed DatetimeIndex internal storage from datetime64[ns]
(nanoseconds) to datetime64[us] (microseconds). The motion activity
endpoint in review.py converted DatetimeIndex to epoch seconds using:

    df.index = df.index.astype(int) // (10**9)

This assumed nanosecond resolution, dividing by 10^9 to get seconds.
With microsecond resolution the division produces values ~1000x too
small (e.g. 1774785 instead of 1774785600), causing every entry to
have a start_time near zero. The frontend timeline could not match
these timestamps to the visible range, so motion indicator bars
disappeared entirely — despite the underlying recording data being
correct.

Replace the resolution-dependent integer division with pandas
Timedelta arithmetic:

    df.index = (df.index - _EPOCH) // _ONE_SECOND

This is resolution-independent (produces correct results on
datetime64[s], [ms], [us], and [ns]), ~148x faster than the
per-element .timestamp() alternative, produces native Python int
types that serialize cleanly to JSON, and is backwards-compatible
with older pandas versions.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-29 09:38:56 -04:00
16 changed files with 501 additions and 140 deletions

View File

@ -5,13 +5,15 @@ import logging
import random
import string
import time
import zipfile
from collections import deque
from pathlib import Path
from typing import List, Optional
from typing import Iterator, List, Optional
import psutil
from fastapi import APIRouter, Depends, Query, Request
from fastapi.responses import JSONResponse
from pathvalidate import sanitize_filepath
from fastapi.responses import JSONResponse, StreamingResponse
from pathvalidate import sanitize_filename, sanitize_filepath
from peewee import DoesNotExist
from playhouse.shortcuts import model_to_dict
@ -361,6 +363,136 @@ def get_export_case(case_id: str):
)
_ZIP_STREAM_CHUNK_SIZE = 1024 * 1024 # 1 MiB
class _StreamingZipBuffer:
"""File-like sink for ZipFile that exposes written bytes via drain().
ZipFile writes synchronously into this buffer; the generator drains the
queue between writes so StreamingResponse can yield bytes without
materializing the whole archive in memory.
"""
def __init__(self) -> None:
self._queue: deque[bytes] = deque()
self._offset = 0
def write(self, data: bytes) -> int:
if data:
self._queue.append(bytes(data))
self._offset += len(data)
return len(data)
def tell(self) -> int:
return self._offset
def flush(self) -> None:
pass
def drain(self) -> Iterator[bytes]:
while self._queue:
yield self._queue.popleft()
def _unique_archive_name(export: Export, used: set[str]) -> str:
base = sanitize_filename(export.name) if export.name else None
if not base:
base = f"{export.camera}_{int(datetime.datetime.timestamp(export.date))}"
candidate = f"{base}.mp4"
counter = 1
while candidate in used:
candidate = f"{base}_{counter}.mp4"
counter += 1
used.add(candidate)
return candidate
def _stream_case_archive(exports: List[Export]) -> Iterator[bytes]:
"""Yield bytes of a zip archive built from the given exports' mp4 files."""
buffer = _StreamingZipBuffer()
used_names: set[str] = set()
# ZIP_STORED: mp4 is already compressed, recompressing wastes CPU for ~0% size win.
with zipfile.ZipFile(
buffer,
mode="w",
compression=zipfile.ZIP_STORED,
allowZip64=True,
) as archive:
for export in exports:
source = Path(export.video_path)
if not source.exists():
continue
arcname = _unique_archive_name(export, used_names)
with (
archive.open(arcname, mode="w", force_zip64=True) as entry,
source.open("rb") as src,
):
while True:
chunk = src.read(_ZIP_STREAM_CHUNK_SIZE)
if not chunk:
break
entry.write(chunk)
yield from buffer.drain()
yield from buffer.drain()
yield from buffer.drain()
@router.get(
"/cases/{case_id}/download",
dependencies=[Depends(allow_any_authenticated())],
summary="Download export case as zip",
description="Streams a zip archive containing every completed export's mp4 for the given case.",
)
def download_export_case(
case_id: str,
allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
):
try:
case = ExportCase.get(ExportCase.id == case_id)
except DoesNotExist:
return JSONResponse(
content={"success": False, "message": "Export case not found"},
status_code=404,
)
exports = list(
Export.select()
.where(
Export.export_case == case_id,
~Export.in_progress,
Export.camera << allowed_cameras,
)
.order_by(Export.date.asc())
)
if not exports:
return JSONResponse(
content={"success": False, "message": "No exports available to download."},
status_code=404,
)
archive_base = sanitize_filename(case.name) if case.name else ""
if not archive_base:
archive_base = case_id
return StreamingResponse(
_stream_case_archive(exports),
media_type="application/zip",
headers={
"Content-Disposition": f'attachment; filename="{archive_base}.zip"',
},
)
@router.patch(
"/cases/{case_id}",
response_model=GenericResponse,

View File

@ -40,6 +40,11 @@ from frigate.util.time import get_dst_transitions
logger = logging.getLogger(__name__)
# Pre-computed constants for resolution-independent datetime-to-epoch conversion
# (pandas 3.0+ stores datetime64 as microseconds, not nanoseconds)
_EPOCH = pd.Timestamp("1970-01-01")
_ONE_SECOND = pd.Timedelta("1s")
router = APIRouter(tags=[Tags.review])
@ -659,7 +664,7 @@ def motion_activity(
df.iloc[i : i + chunk, 0] = 0.0
# change types for output
df.index = df.index.astype(int) // (10**9)
df.index = (df.index - _EPOCH) // _ONE_SECOND
normalized = df.reset_index().to_dict("records")
return JSONResponse(content=normalized)

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@ -20,6 +20,7 @@ class CameraConfigUpdateEnum(str, Enum):
ffmpeg = "ffmpeg"
live = "live"
motion = "motion" # includes motion and motion masks
mqtt = "mqtt"
notifications = "notifications"
objects = "objects"
object_genai = "object_genai"
@ -33,6 +34,7 @@ class CameraConfigUpdateEnum(str, Enum):
lpr = "lpr"
snapshots = "snapshots"
timestamp_style = "timestamp_style"
ui = "ui"
zones = "zones"

View File

@ -40,7 +40,7 @@ logger = logging.getLogger(__name__)
RECORDING_BUFFER_EXTENSION_PERCENT = 0.10
MIN_RECORDING_DURATION = 10
MAX_IMAGE_TOKENS = 24000
MAX_FRAMES_PER_SECOND = 2
MAX_FRAMES_PER_SECOND = 1
class ReviewDescriptionProcessor(PostProcessorApi):

View File

@ -1,25 +1,48 @@
from pydantic import BaseModel, ConfigDict, Field
from typing import Annotated
from pydantic import BaseModel, ConfigDict, Field, StringConstraints
ObservationItem = Annotated[str, StringConstraints(min_length=20, max_length=160)]
class ReviewMetadata(BaseModel):
model_config = ConfigDict(extra="ignore", protected_namespaces=())
observations: list[str] = Field(
default_factory=list,
description="Chronological list of significant observations from the frames, written before the scene narrative is composed.",
observations: list[ObservationItem] = Field(
...,
min_length=3,
max_length=15,
description=(
"Enumerate the significant observations across all frames, in "
"chronological order, BEFORE composing the scene narrative. "
"Include the very start of the activity — for example, a vehicle "
"entering the frame or pulling into the driveway — even if it "
"lasts only a few frames and the rest of the clip is dominated "
"by a longer activity. Include each arrival, departure, motion "
"event, object handled, and notable change in position or state. "
"Each item is a single concrete fact written as a complete "
"sentence. Do not summarize, interpret, or assign meaning here — "
"that belongs in the scene field."
),
)
title: str = Field(
description="A short title characterizing what took place and where, under 10 words."
max_length=80,
description="Under 10 words. Name the apparent purpose or outcome of the activity together with the location involved. Do not narrate or list the sequence of actions step by step.",
)
scene: str = Field(
description="A chronological narrative of what happens from start to finish.",
min_length=150,
max_length=600,
description="A chronological narrative of what happens from start to finish, drawing directly from the items in observations.",
)
shortSummary: str = Field(
description="A brief 2-sentence summary of the scene, suitable for notifications."
min_length=70,
max_length=120,
description="A brief 2-sentence summary of the scene, suitable for notifications.",
)
confidence: float = Field(
ge=0.0,
description="Confidence in the analysis, from 0 to 1.",
le=1.0,
description="Confidence in the analysis as a decimal between 0.0 and 1.0, where 0.0 means no confidence and 1.0 means complete confidence. Express ONLY as a decimal.",
)
potential_threat_level: int = Field(
ge=0,

View File

@ -517,10 +517,16 @@ class EmbeddingMaintainer(threading.Thread):
try:
event: Event = Event.get(Event.id == event_id)
except DoesNotExist:
for processor in self.post_processors:
if isinstance(processor, ObjectDescriptionProcessor):
processor.cleanup_event(event_id)
continue
# Skip the event if not an object
if event.data.get("type") != "object":
for processor in self.post_processors:
if isinstance(processor, ObjectDescriptionProcessor):
processor.cleanup_event(event_id)
continue
# Extract valid thumbnail

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@ -205,6 +205,7 @@ class AudioEventMaintainer(threading.Thread):
self.transcription_thread.start()
self.was_enabled = camera.enabled
self.was_audio_enabled = camera.audio.enabled
def detect_audio(self, audio: np.ndarray) -> None:
if not self.camera_config.audio.enabled or self.stop_event.is_set():
@ -363,6 +364,17 @@ class AudioEventMaintainer(threading.Thread):
time.sleep(0.1)
continue
audio_enabled = self.camera_config.audio.enabled
if audio_enabled != self.was_audio_enabled:
if not audio_enabled:
self.logger.debug(
f"Disabling audio detections for {self.camera_config.name}, ending events"
)
self.requestor.send_data(
EXPIRE_AUDIO_ACTIVITY, self.camera_config.name
)
self.was_audio_enabled = audio_enabled
self.read_audio()
if self.audio_listener:

View File

@ -2,6 +2,7 @@
import datetime
import importlib
import json
import logging
import os
import re
@ -9,6 +10,7 @@ from typing import Any, Callable, Optional
import numpy as np
from playhouse.shortcuts import model_to_dict
from pydantic import ValidationError
from frigate.config import CameraConfig, GenAIConfig, GenAIProviderEnum
from frigate.const import CLIPS_DIR
@ -151,50 +153,6 @@ Each line represents a detection state, not necessarily unique individuals. The
if "other_concerns" in schema.get("required", []):
schema["required"].remove("other_concerns")
# Length hints injected into the schema as suggestions to the model
# (enforced by grammar-based providers like llama.cpp) but kept off the
# Pydantic model so a non-compliant response does not fail validation.
length_hints = {
"scene": {"minLength": 120, "maxLength": 600},
"shortSummary": {"minLength": 70, "maxLength": 100},
}
for field, hints in length_hints.items():
prop = schema.get("properties", {}).get(field)
if prop is not None:
prop.update(hints)
# observations is a chain-of-thought-by-schema field: forcing the model
# to enumerate concrete facts before writing scene/title surfaces details
# the narrative would otherwise gloss past (e.g. brief vehicle arrivals
# overshadowed by a longer activity). The minItems floor scales with
# event duration so longer clips get more observations.
observations_prop = schema.get("properties", {}).get("observations")
if observations_prop is not None:
duration_seconds = float(review_data.get("duration") or 0)
min_observations = max(3, round(duration_seconds / 5))
max_observations = min_observations + 8
observations_prop["description"] = (
"Enumerate the significant observations across all frames, in "
"chronological order, BEFORE composing the scene narrative. "
"Include the very start of the activity — for example, a "
"vehicle entering the frame or pulling into the driveway — "
"even if it lasts only a few frames and the rest of the clip "
"is dominated by a longer activity. Include each arrival, "
"departure, motion event, object handled, and notable change "
"in position or state. Each item is a single concrete fact "
"written as a complete sentence (e.g., 'A blue sedan turns "
"from the street into the driveway', 'Nick exits the driver "
"side carrying a plant pot'). Do not summarize, interpret, or "
"assign meaning here — that belongs in the scene field."
)
observations_prop["minItems"] = min_observations
observations_prop["maxItems"] = max_observations
observations_prop["items"] = {"type": "string", "minLength": 20}
required = schema.setdefault("required", [])
if "observations" not in required:
required.append("observations")
# OpenAI strict mode requires additionalProperties: false on all objects
schema["additionalProperties"] = False
@ -225,7 +183,36 @@ Each line represents a detection state, not necessarily unique individuals. The
try:
metadata = ReviewMetadata.model_validate_json(clean_json)
except ValidationError as ve:
# Constraint violations (length, item count, ranges) are logged
# at debug and the response is kept anyway — a slightly
# off-spec answer is still usable, and dropping the whole
# response loses the narrative content the model produced.
for err in ve.errors():
loc = ".".join(str(p) for p in err["loc"]) or "<root>"
logger.debug(
"Review metadata soft validation: %s%s (input: %r)",
loc,
err["msg"],
err.get("input"),
)
try:
raw = json.loads(clean_json)
except json.JSONDecodeError as je:
logger.error("Failed to parse review description JSON: %s", je)
return None
# observations and confidence are required on the model; fill an empty default
# if the response omitted it so attribute access stays safe.
raw.setdefault("observations", [])
raw.setdefault("confidence", 0.0)
metadata = ReviewMetadata.model_construct(**raw)
except Exception as e:
logger.error(
f"Failed to parse review description as the response did not match expected format. {e}"
)
return None
try:
# Normalize confidence if model returned a percentage (e.g. 85 instead of 0.85)
if metadata.confidence > 1.0:
metadata.confidence = min(metadata.confidence / 100.0, 1.0)
@ -238,10 +225,7 @@ Each line represents a detection state, not necessarily unique individuals. The
metadata.time = review_data["start"]
return metadata
except Exception as e:
# rarely LLMs can fail to follow directions on output format
logger.warning(
f"Failed to parse review description as the response did not match expected format. {e}"
)
logger.error(f"Failed to post-process review metadata: {e}")
return None
else:
logger.debug(

View File

@ -317,16 +317,16 @@ class CameraWatchdog(threading.Thread):
if camera != self.config.name:
continue
if topic.endswith(RecordingsDataTypeEnum.valid.value):
self.logger.debug(
f"Latest valid recording segment time on {camera}: {segment_time}"
)
self.latest_valid_segment_time = segment_time
elif topic.endswith(RecordingsDataTypeEnum.invalid.value):
if topic.endswith(RecordingsDataTypeEnum.invalid.value):
self.logger.warning(
f"Invalid recording segment detected for {camera} at {segment_time}"
)
self.latest_invalid_segment_time = segment_time
elif topic.endswith(RecordingsDataTypeEnum.valid.value):
self.logger.debug(
f"Latest valid recording segment time on {camera}: {segment_time}"
)
self.latest_valid_segment_time = segment_time
elif topic.endswith(RecordingsDataTypeEnum.latest.value):
if segment_time is not None:
self.latest_cache_segment_time = segment_time

View File

@ -457,7 +457,13 @@
"enableDesc": "Temporarily disable an enabled camera until Frigate restarts. Disabling a camera completely stops Frigate's processing of this camera's streams. Detection, recording, and debugging will be unavailable.<br /> <em>Note: This does not disable go2rtc restreams.</em>",
"disableLabel": "Disabled cameras",
"disableDesc": "Enable a camera that is currently not visible in the UI and disabled in the configuration. A restart of Frigate is required after enabling.",
"enableSuccess": "Enabled {{cameraName}} in configuration. Restart Frigate to apply the changes."
"enableSuccess": "Enabled {{cameraName}} in configuration. Restart Frigate to apply the changes.",
"friendlyName": {
"edit": "Edit camera display name",
"title": "Edit Display Name",
"description": "Set the friendly name shown for this camera throughout the Frigate UI. Leave blank to use the camera ID.",
"rename": "Rename"
}
},
"cameraConfig": {
"add": "Add Camera",

View File

@ -65,10 +65,14 @@ import {
globalCameraDefaultSections,
buildOverrides,
buildConfigDataForPath,
flattenOverrides,
getBaseCameraSectionValue,
sanitizeSectionData as sharedSanitizeSectionData,
requiresRestartForOverrides as sharedRequiresRestartForOverrides,
} from "@/utils/configUtil";
import SaveAllPreviewPopover, {
type SaveAllPreviewItem,
} from "@/components/overlay/detail/SaveAllPreviewPopover";
import RestartDialog from "@/components/overlay/dialog/RestartDialog";
import { useRestart } from "@/api/ws";
import type {
@ -913,6 +917,34 @@ export function ConfigSection({
);
}, [sectionConfig?.renderers, sectionPath, cameraName, setPendingData]);
// Build a flat list of pending field changes for this section only.
// Mirrors the global Save All preview but scoped to the current section so
// users can inspect what will be saved without leaving the section.
const sectionPreviewItems = useMemo<SaveAllPreviewItem[]>(() => {
if (!hasChanges) return [];
if (!effectiveOverrides || typeof effectiveOverrides !== "object") {
return [];
}
const flattened = flattenOverrides(effectiveOverrides as JsonValue);
return flattened.map(({ path, value }) => ({
scope: effectiveLevel,
cameraName,
profileName: profileName
? (profileFriendlyName ?? profileName)
: undefined,
fieldPath: path ? `${sectionPath}.${path}` : sectionPath,
value,
}));
}, [
hasChanges,
effectiveOverrides,
effectiveLevel,
cameraName,
profileName,
profileFriendlyName,
sectionPath,
]);
if (!modifiedSchema) {
return null;
}
@ -1018,6 +1050,12 @@ export function ConfigSection({
defaultValue: "You have unsaved changes",
})}
</span>
<SaveAllPreviewPopover
items={sectionPreviewItems}
className="h-7 w-7"
align="start"
side="top"
/>
</div>
)}
<div className="flex w-full flex-col gap-2 sm:flex-row sm:items-center md:w-auto">

View File

@ -1,3 +1,4 @@
import ActivityIndicator from "@/components/indicators/activity-indicator";
import TextEntry from "@/components/input/TextEntry";
import { Button } from "@/components/ui/button";
import {
@ -19,7 +20,9 @@ type TextEntryDialogProps = {
setOpen: (open: boolean) => void;
onSave: (text: string) => void;
defaultValue?: string;
placeholder?: string;
allowEmpty?: boolean;
isSaving?: boolean;
regexPattern?: RegExp;
regexErrorMessage?: string;
forbiddenPattern?: RegExp;
@ -33,7 +36,9 @@ export default function TextEntryDialog({
setOpen,
onSave,
defaultValue = "",
placeholder,
allowEmpty = false,
isSaving = false,
regexPattern,
regexErrorMessage,
forbiddenPattern,
@ -50,6 +55,7 @@ export default function TextEntryDialog({
</DialogHeader>
<TextEntry
defaultValue={defaultValue}
placeholder={placeholder}
allowEmpty={allowEmpty}
onSave={onSave}
regexPattern={regexPattern}
@ -58,11 +64,22 @@ export default function TextEntryDialog({
forbiddenErrorMessage={forbiddenErrorMessage}
>
<DialogFooter className={cn("pt-4", isMobile && "gap-2")}>
<Button type="button" onClick={() => setOpen(false)}>
<Button
type="button"
disabled={isSaving}
onClick={() => setOpen(false)}
>
{t("button.cancel")}
</Button>
<Button variant="select" type="submit">
{t("button.save")}
<Button variant="select" type="submit" disabled={isSaving}>
{isSaving ? (
<div className="flex flex-row items-center gap-2">
<ActivityIndicator className="size-4" />
<span>{t("button.saving")}</span>
</div>
) : (
t("button.save")
)}
</Button>
</DialogFooter>
</TextEntry>

View File

@ -57,6 +57,7 @@ import { useTranslation } from "react-i18next";
import { IoMdArrowRoundBack } from "react-icons/io";
import {
LuDownload,
LuFolderPlus,
LuFolderX,
LuPencil,
@ -777,54 +778,76 @@ function Exports() {
filters={["cameras"]}
onUpdateFilter={setExportFilter}
/>
{isAdmin && (
<div className="flex items-center gap-1 md:gap-2">
<div className="flex items-center gap-1 md:gap-2">
{(exportsByCase[selectedCase.id]?.length ?? 0) > 0 && (
<Button
asChild
className="flex items-center gap-2 p-2"
size="sm"
aria-label={t("toolbar.addExport")}
onClick={() => setCaseForAddExport(selectedCase)}
aria-label={t("button.download", { ns: "common" })}
>
<LuPlus className="text-secondary-foreground" />
{!isMobile && (
<div className="text-primary">
{t("toolbar.addExport")}
</div>
)}
<a
download
href={`${baseUrl}api/cases/${selectedCase.id}/download`}
>
<LuDownload className="text-secondary-foreground" />
{!isMobile && (
<div className="text-primary">
{t("button.download", { ns: "common" })}
</div>
)}
</a>
</Button>
<Button
className="flex items-center gap-2 p-2"
size="sm"
aria-label={t("toolbar.editCase")}
onClick={() =>
setCaseDialog({
mode: "edit",
exportCase: selectedCase,
})
}
>
<LuPencil className="text-secondary-foreground" />
{!isMobile && (
<div className="text-primary">
{t("toolbar.editCase")}
</div>
)}
</Button>
<Button
className="flex items-center gap-2 p-2"
size="sm"
aria-label={t("toolbar.deleteCase")}
onClick={() => setCaseToDelete(selectedCase)}
>
<LuTrash2 className="text-secondary-foreground" />
{!isMobile && (
<div className="text-primary">
{t("toolbar.deleteCase")}
</div>
)}
</Button>
</div>
)}
)}
{isAdmin && (
<>
<Button
className="flex items-center gap-2 p-2"
size="sm"
aria-label={t("toolbar.addExport")}
onClick={() => setCaseForAddExport(selectedCase)}
>
<LuPlus className="text-secondary-foreground" />
{!isMobile && (
<div className="text-primary">
{t("toolbar.addExport")}
</div>
)}
</Button>
<Button
className="flex items-center gap-2 p-2"
size="sm"
aria-label={t("toolbar.editCase")}
onClick={() =>
setCaseDialog({
mode: "edit",
exportCase: selectedCase,
})
}
>
<LuPencil className="text-secondary-foreground" />
{!isMobile && (
<div className="text-primary">
{t("toolbar.editCase")}
</div>
)}
</Button>
<Button
className="flex items-center gap-2 p-2"
size="sm"
aria-label={t("toolbar.deleteCase")}
onClick={() => setCaseToDelete(selectedCase)}
>
<LuTrash2 className="text-secondary-foreground" />
{!isMobile && (
<div className="text-primary">
{t("toolbar.deleteCase")}
</div>
)}
</Button>
</>
)}
</div>
</div>
)}
</>

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@ -28,11 +28,7 @@ import useOptimisticState from "@/hooks/use-optimistic-state";
import { isMobile } from "react-device-detect";
import { FaVideo } from "react-icons/fa";
import { CameraConfig, FrigateConfig } from "@/types/frigateConfig";
import type {
ConfigSectionData,
JsonObject,
JsonValue,
} from "@/types/configForm";
import type { ConfigSectionData, JsonObject } from "@/types/configForm";
import useSWR from "swr";
import FilterSwitch from "@/components/filter/FilterSwitch";
import { ZoneMaskFilterButton } from "@/components/filter/ZoneMaskFilter";
@ -93,6 +89,7 @@ import { mutate } from "swr";
import { RJSFSchema } from "@rjsf/utils";
import {
buildConfigDataForPath,
flattenOverrides,
parseProfileFromSectionPath,
prepareSectionSavePayload,
PROFILE_ELIGIBLE_SECTIONS,
@ -190,25 +187,6 @@ const parsePendingDataKey = (pendingDataKey: string) => {
};
};
const flattenOverrides = (
value: JsonValue | undefined,
path: string[] = [],
): Array<{ path: string; value: JsonValue }> => {
if (value === undefined) return [];
if (value === null || typeof value !== "object" || Array.isArray(value)) {
return [{ path: path.join("."), value }];
}
const entries = Object.entries(value);
if (entries.length === 0) {
return [{ path: path.join("."), value: {} }];
}
return entries.flatMap(([key, entryValue]) =>
flattenOverrides(entryValue, [...path, key]),
);
};
const createSectionPage = (
sectionKey: string,
level: "global" | "camera",

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@ -219,6 +219,32 @@ export function buildOverrides(
return current;
}
// ---------------------------------------------------------------------------
// flattenOverrides — turn an overrides object into a list of leaf paths
// ---------------------------------------------------------------------------
// Walks a nested overrides value and produces a flat list of `{ path, value }`
// entries, one per leaf. Used by save/preview UIs to enumerate the individual
// fields that will be changed.
export function flattenOverrides(
value: JsonValue | undefined,
path: string[] = [],
): Array<{ path: string; value: JsonValue }> {
if (value === undefined) return [];
if (value === null || typeof value !== "object" || Array.isArray(value)) {
return [{ path: path.join("."), value }];
}
const entries = Object.entries(value);
if (entries.length === 0) {
return [{ path: path.join("."), value: {} }];
}
return entries.flatMap(([key, entryValue]) =>
flattenOverrides(entryValue, [...path, key]),
);
}
// ---------------------------------------------------------------------------
// sanitizeSectionData — normalize config values and strip hidden fields
// ---------------------------------------------------------------------------

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@ -14,7 +14,7 @@ import { useTranslation } from "react-i18next";
import CameraEditForm from "@/components/settings/CameraEditForm";
import CameraWizardDialog from "@/components/settings/CameraWizardDialog";
import DeleteCameraDialog from "@/components/overlay/dialog/DeleteCameraDialog";
import { LuPlus, LuTrash2 } from "react-icons/lu";
import { LuPencil, LuPlus, LuTrash2 } from "react-icons/lu";
import { IoMdArrowRoundBack } from "react-icons/io";
import { isDesktop } from "react-device-detect";
import { CameraNameLabel } from "@/components/camera/FriendlyNameLabel";
@ -26,6 +26,12 @@ import axios from "axios";
import ActivityIndicator from "@/components/indicators/activity-indicator";
import RestartDialog from "@/components/overlay/dialog/RestartDialog";
import RestartRequiredIndicator from "@/components/indicators/RestartRequiredIndicator";
import TextEntryDialog from "@/components/overlay/dialog/TextEntryDialog";
import {
Tooltip,
TooltipContent,
TooltipTrigger,
} from "@/components/ui/tooltip";
import type { ProfileState } from "@/types/profile";
import { getProfileColor } from "@/utils/profileColors";
import { cn } from "@/lib/utils";
@ -161,7 +167,13 @@ export default function CameraManagementView({
key={camera}
className="flex flex-row items-center justify-between"
>
<CameraNameLabel camera={camera} />
<div className="flex items-center gap-1">
<CameraNameLabel camera={camera} />
<CameraFriendlyNameEditor
cameraName={camera}
onConfigChanged={updateConfig}
/>
</div>
<CameraEnableSwitch cameraName={camera} />
</div>
))}
@ -297,6 +309,103 @@ function CameraEnableSwitch({ cameraName }: CameraEnableSwitchProps) {
);
}
type CameraFriendlyNameEditorProps = {
cameraName: string;
onConfigChanged: () => Promise<unknown>;
};
function CameraFriendlyNameEditor({
cameraName,
onConfigChanged,
}: CameraFriendlyNameEditorProps) {
const { t } = useTranslation(["views/settings", "common"]);
const { data: config } = useSWR<FrigateConfig>("config");
const [open, setOpen] = useState(false);
const [isSaving, setIsSaving] = useState(false);
const currentFriendlyName = config?.cameras?.[cameraName]?.friendly_name;
const onSave = useCallback(
async (text: string) => {
if (isSaving) return;
setIsSaving(true);
try {
await axios.put("config/set", {
requires_restart: 0,
config_data: {
cameras: {
[cameraName]: {
friendly_name: text.trim() || null,
},
},
},
});
await onConfigChanged();
setOpen(false);
toast.success(t("toast.save.success", { ns: "common" }), {
position: "top-center",
});
} catch (error) {
const errorMessage =
axios.isAxiosError(error) &&
(error.response?.data?.message || error.response?.data?.detail)
? error.response?.data?.message || error.response?.data?.detail
: t("toast.save.error.noMessage", { ns: "common" });
toast.error(
t("toast.save.error.title", { errorMessage, ns: "common" }),
{ position: "top-center" },
);
} finally {
setIsSaving(false);
}
},
[cameraName, isSaving, onConfigChanged, t],
);
const renameLabel = t("cameraManagement.streams.friendlyName.rename", {
ns: "views/settings",
});
return (
<>
<Tooltip>
<TooltipTrigger asChild>
<Button
variant="ghost"
size="icon"
className="size-7"
aria-label={renameLabel}
onClick={() => setOpen(true)}
disabled={isSaving}
>
<LuPencil className="size-3.5" />
</Button>
</TooltipTrigger>
<TooltipContent>{renameLabel}</TooltipContent>
</Tooltip>
<TextEntryDialog
open={open}
setOpen={setOpen}
title={t("cameraManagement.streams.friendlyName.title", {
ns: "views/settings",
})}
description={t("cameraManagement.streams.friendlyName.description", {
ns: "views/settings",
})}
defaultValue={currentFriendlyName ?? ""}
placeholder={currentFriendlyName ? undefined : cameraName}
allowEmpty
isSaving={isSaving}
onSave={onSave}
/>
</>
);
}
type CameraConfigEnableSwitchProps = {
cameraName: string;
setRestartDialogOpen: React.Dispatch<React.SetStateAction<boolean>>;