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Author SHA1 Message Date
dependabot[bot]
cb1cb2ec6a
Merge c238e62ad7 into f448b259a2 2026-05-05 09:48:11 +02:00
Josh Hawkins
f448b259a2
Settings UI improvements (#23109)
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* use badge with popover to show which cameras override each global config section

* don't use shorthand

* use label i18n
2026-05-04 09:50:00 -06:00
Nicolas Mowen
ef9d7e07b7
Rewrite intel stats (#23108)
* Rewrite intel GPU stats to use file descriptors instead of intel_gpu_top, leading to significantly better API for interaction and more accurate results

* Update tests

* Update docs

* Adjust approach

* Update strings
2026-05-04 10:36:32 -05:00
dependabot[bot]
c238e62ad7
Bump tailwindcss from 3.4.9 to 4.2.4 in /web
Bumps [tailwindcss](https://github.com/tailwindlabs/tailwindcss/tree/HEAD/packages/tailwindcss) from 3.4.9 to 4.2.4.
- [Release notes](https://github.com/tailwindlabs/tailwindcss/releases)
- [Changelog](https://github.com/tailwindlabs/tailwindcss/blob/main/CHANGELOG.md)
- [Commits](https://github.com/tailwindlabs/tailwindcss/commits/v4.2.4/packages/tailwindcss)

---
updated-dependencies:
- dependency-name: tailwindcss
  dependency-version: 4.2.4
  dependency-type: direct:development
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
2026-05-01 13:18:56 +00:00
13 changed files with 950 additions and 737 deletions

View File

@ -136,90 +136,32 @@ ffmpeg:
</TabItem>
</ConfigTabs>
### Configuring Intel GPU Stats in Docker
### Configuring Intel GPU Stats
Additional configuration is needed for the Docker container to be able to access the `intel_gpu_top` command for GPU stats. There are two options:
Frigate reads Intel GPU utilization directly from the kernel's per-client DRM usage counters exposed at `/proc/<pid>/fdinfo/<fd>`. This requires:
1. Run the container as privileged.
2. Add the `CAP_PERFMON` capability (note: you might need to set the `perf_event_paranoid` low enough to allow access to the performance event system.)
- Linux kernel **5.19 or newer** for the `i915` driver, or any release of the `xe` driver.
- Frigate running with permission to read other processes' fdinfo. Running as root inside the container (the default) satisfies this; non-root setups may need `CAP_SYS_PTRACE`.
#### Run as privileged
No `intel_gpu_top` binary, `CAP_PERFMON`, privileged mode, or `perf_event_paranoid` tuning is required.
This method works, but it gives more permissions to the container than are actually needed.
#### Stats for SR-IOV or specific devices
##### Docker Compose - Privileged
```yaml
services:
frigate:
...
image: ghcr.io/blakeblackshear/frigate:stable
# highlight-next-line
privileged: true
```
##### Docker Run CLI - Privileged
```bash {4}
docker run -d \
--name frigate \
...
--privileged \
ghcr.io/blakeblackshear/frigate:stable
```
#### CAP_PERFMON
Only recent versions of Docker support the `CAP_PERFMON` capability. You can test to see if yours supports it by running: `docker run --cap-add=CAP_PERFMON hello-world`
##### Docker Compose - CAP_PERFMON
```yaml {5,6}
services:
frigate:
...
image: ghcr.io/blakeblackshear/frigate:stable
cap_add:
- CAP_PERFMON
```
##### Docker Run CLI - CAP_PERFMON
```bash {4}
docker run -d \
--name frigate \
...
--cap-add=CAP_PERFMON \
ghcr.io/blakeblackshear/frigate:stable
```
#### perf_event_paranoid
_Note: This setting must be changed for the entire system._
For more information on the various values across different distributions, see https://askubuntu.com/questions/1400874/what-does-perf-paranoia-level-four-do.
Depending on your OS and kernel configuration, you may need to change the `/proc/sys/kernel/perf_event_paranoid` kernel tunable. You can test the change by running `sudo sh -c 'echo 2 >/proc/sys/kernel/perf_event_paranoid'` which will persist until a reboot. Make it permanent by running `sudo sh -c 'echo kernel.perf_event_paranoid=2 >> /etc/sysctl.d/local.conf'`
#### Stats for SR-IOV or other devices
When using virtualized GPUs via SR-IOV, you need to specify the device path to use to gather stats from `intel_gpu_top`. This example may work for some systems using SR-IOV:
If the host has more than one Intel GPU (e.g. an iGPU plus a discrete GPU, or SR-IOV virtual functions), pin stats collection to a specific device by setting `intel_gpu_device` to either its PCI bus address or a DRM card/render-node path:
```yaml
telemetry:
stats:
intel_gpu_device: "sriov"
intel_gpu_device: "0000:00:02.0"
```
For other virtualized GPUs, try specifying the direct path to the device instead:
```yaml
telemetry:
stats:
intel_gpu_device: "drm:/dev/dri/card0"
intel_gpu_device: "/dev/dri/card1"
```
If you are passing in a device path, make sure you've passed the device through to the container.
When passing a device path, make sure the device is also passed through to the container.
## AMD-based CPUs

View File

@ -25,8 +25,8 @@ class StatsConfig(FrigateBaseModel):
)
intel_gpu_device: Optional[str] = Field(
default=None,
title="SR-IOV device",
description="Device identifier used when treating Intel GPUs as SR-IOV to fix GPU stats.",
title="Intel GPU device",
description="PCI bus address or DRM device path (e.g. /dev/dri/card1) used to pin Intel GPU stats to a specific device when multiple are present.",
)

View File

@ -7,8 +7,6 @@ from frigate.util.services import get_amd_gpu_stats, get_intel_gpu_stats
class TestGpuStats(unittest.TestCase):
def setUp(self):
self.amd_results = "Unknown Radeon card. <= R500 won't work, new cards might.\nDumping to -, line limit 1.\n1664070990.607556: bus 10, gpu 4.17%, ee 0.00%, vgt 0.00%, ta 0.00%, tc 0.00%, sx 0.00%, sh 0.00%, spi 0.83%, smx 0.00%, cr 0.00%, sc 0.00%, pa 0.00%, db 0.00%, cb 0.00%, vram 60.37% 294.04mb, gtt 0.33% 52.21mb, mclk 100.00% 1.800ghz, sclk 26.65% 0.533ghz\n"
self.intel_results = """{"period":{"duration":1.194033,"unit":"ms"},"frequency":{"requested":0.000000,"actual":0.000000,"unit":"MHz"},"interrupts":{"count":3349.991164,"unit":"irq/s"},"rc6":{"value":47.844741,"unit":"%"},"engines":{"Render/3D/0":{"busy":0.000000,"sema":0.000000,"wait":0.000000,"unit":"%"},"Blitter/0":{"busy":0.000000,"sema":0.000000,"wait":0.000000,"unit":"%"},"Video/0":{"busy":4.533124,"sema":0.000000,"wait":0.000000,"unit":"%"},"Video/1":{"busy":6.194385,"sema":0.000000,"wait":0.000000,"unit":"%"},"VideoEnhance/0":{"busy":0.000000,"sema":0.000000,"wait":0.000000,"unit":"%"}}},{"period":{"duration":1.189291,"unit":"ms"},"frequency":{"requested":0.000000,"actual":0.000000,"unit":"MHz"},"interrupts":{"count":0.000000,"unit":"irq/s"},"rc6":{"value":100.000000,"unit":"%"},"engines":{"Render/3D/0":{"busy":0.000000,"sema":0.000000,"wait":0.000000,"unit":"%"},"Blitter/0":{"busy":0.000000,"sema":0.000000,"wait":0.000000,"unit":"%"},"Video/0":{"busy":0.000000,"sema":0.000000,"wait":0.000000,"unit":"%"},"Video/1":{"busy":0.000000,"sema":0.000000,"wait":0.000000,"unit":"%"},"VideoEnhance/0":{"busy":0.000000,"sema":0.000000,"wait":0.000000,"unit":"%"}}}"""
self.nvidia_results = "name, utilization.gpu [%], memory.used [MiB], memory.total [MiB]\nNVIDIA GeForce RTX 3050, 42 %, 5036 MiB, 8192 MiB\n"
@patch("subprocess.run")
def test_amd_gpu_stats(self, sp):
@ -19,32 +17,76 @@ class TestGpuStats(unittest.TestCase):
amd_stats = get_amd_gpu_stats()
assert amd_stats == {"gpu": "4.17%", "mem": "60.37%"}
# @patch("subprocess.run")
# def test_nvidia_gpu_stats(self, sp):
# process = MagicMock()
# process.returncode = 0
# process.stdout = self.nvidia_results
# sp.return_value = process
# nvidia_stats = get_nvidia_gpu_stats()
# assert nvidia_stats == {
# "name": "NVIDIA GeForce RTX 3050",
# "gpu": "42 %",
# "mem": "61.5 %",
# }
@patch("frigate.util.services.time.sleep")
@patch("frigate.util.services.time.monotonic")
@patch("frigate.util.services._read_intel_drm_fdinfo")
def test_intel_gpu_stats_fdinfo(self, read_fdinfo, monotonic, sleep):
# 1 second of wall clock between snapshots
monotonic.side_effect = [0.0, 1.0]
@patch("subprocess.run")
def test_intel_gpu_stats(self, sp):
process = MagicMock()
process.returncode = 124
process.stdout = self.intel_results
sp.return_value = process
intel_stats = get_intel_gpu_stats(False)
# rc6 values: 47.844741 and 100.0 → avg 73.92 → gpu = 100 - 73.92 = 26.08%
# Render/3D/0: 0.0 and 0.0 → enc = 0.0%
# Video/0: 4.533124 and 0.0 → dec = 2.27%
assert intel_stats == {
"gpu": "26.08%",
"mem": "-%",
"compute": "0.0%",
"dec": "2.27%",
# Two i915 clients on the same iGPU. Engine values are cumulative ns.
# Deltas over the 1s window:
# client A (pid 100): render +200_000_000 (20%), video +500_000_000 (50%),
# video-enhance +100_000_000 (10%)
# client B (pid 200): compute +100_000_000 (10%)
# Engine totals → render 20, video 50, video-enhance 10, compute 10
# → compute = render + compute = 30
# → dec = video + video-enhance = 60
# → gpu = compute + dec = 90
snapshot_a = {
("0000:00:02.0", "1", "100"): {
"driver": "i915",
"pid": "100",
"engines": {
"render": (1_000_000_000, 0),
"video": (5_000_000_000, 0),
"video-enhance": (200_000_000, 0),
"compute": (0, 0),
},
},
("0000:00:02.0", "2", "200"): {
"driver": "i915",
"pid": "200",
"engines": {
"render": (0, 0),
"compute": (2_000_000_000, 0),
},
},
}
snapshot_b = {
("0000:00:02.0", "1", "100"): {
"driver": "i915",
"pid": "100",
"engines": {
"render": (1_200_000_000, 0),
"video": (5_500_000_000, 0),
"video-enhance": (300_000_000, 0),
"compute": (0, 0),
},
},
("0000:00:02.0", "2", "200"): {
"driver": "i915",
"pid": "200",
"engines": {
"render": (0, 0),
"compute": (2_100_000_000, 0),
},
},
}
read_fdinfo.side_effect = [snapshot_a, snapshot_b]
intel_stats = get_intel_gpu_stats(None)
sleep.assert_called_once()
assert intel_stats == {
"gpu": "90.0%",
"mem": "-%",
"compute": "30.0%",
"dec": "60.0%",
"clients": {"100": "80.0%", "200": "10.0%"},
}
@patch("frigate.util.services._read_intel_drm_fdinfo")
def test_intel_gpu_stats_no_clients(self, read_fdinfo):
read_fdinfo.return_value = {}
assert get_intel_gpu_stats(None) is None

View File

@ -264,156 +264,214 @@ def get_amd_gpu_stats() -> Optional[dict[str, str]]:
return results
def get_intel_gpu_stats(intel_gpu_device: Optional[str]) -> Optional[dict[str, str]]:
"""Get stats using intel_gpu_top.
_INTEL_FDINFO_SAMPLE_SECONDS = 1.0
Returns overall GPU usage derived from rc6 residency (idle time),
plus individual engine breakdowns:
- enc: Render/3D engine (compute/shader encoder, used by QSV)
- dec: Video engines (fixed-function codec, used by VAAPI)
# Engines we track. Render/3D and Compute are pooled into "compute"; Video and
# VideoEnhance into "dec" (VideoEnhance is the post-process engine that handles
# VAAPI scaling/deinterlace/CSC, e.g. ffmpeg `-vf scale_vaapi=...`). The Copy
# (DMA blitter) engine is intentionally ignored — it represents transparent
# memory transfers, not user-visible GPU work.
# i915 fdinfo keys (cumulative ns) → logical engine name.
_I915_ENGINE_KEYS = {
"drm-engine-render": "render",
"drm-engine-video": "video",
"drm-engine-video-enhance": "video-enhance",
"drm-engine-compute": "compute",
}
# Xe fdinfo suffixes (cumulative cycles, paired with drm-total-cycles-*).
_XE_ENGINE_KEYS = {
"rcs": "render",
"vcs": "video",
"vecs": "video-enhance",
"ccs": "compute",
}
def _resolve_intel_gpu_pdev(device: Optional[str]) -> Optional[str]:
"""Map a configured GPU hint (/dev/dri/card1, renderD128, or a PCI bus
address) to its drm-pdev string so we can filter fdinfo entries to that
device. Returns None when no hint is supplied or it cannot be resolved."""
if not device:
return None
if re.match(r"^[0-9a-fA-F]{4}:[0-9a-fA-F]{2}:[0-9a-fA-F]{2}\.[0-9a-fA-F]$", device):
return device
name = os.path.basename(device.rstrip("/"))
try:
return os.path.basename(os.path.realpath(f"/sys/class/drm/{name}/device"))
except OSError:
return None
def _read_intel_drm_fdinfo(target_pdev: Optional[str]) -> dict:
"""Snapshot DRM fdinfo for every Intel client visible in /proc.
Returns a dict keyed by (pdev, drm-client-id, pid) so the same context
seen via multiple file descriptors on a single process collapses to one
entry.
"""
def get_stats_manually(output: str) -> dict[str, str]:
"""Find global stats via regex when json fails to parse."""
reading = "".join(output)
results: dict[str, str] = {}
# rc6 residency for overall GPU usage
rc6_match = re.search(r'"rc6":\{"value":([\d.]+)', reading)
if rc6_match:
rc6_value = float(rc6_match.group(1))
results["gpu"] = f"{round(100.0 - rc6_value, 2)}%"
else:
results["gpu"] = "-%"
results["mem"] = "-%"
# Render/3D is the compute/encode engine
render = []
for result in re.findall(r'"Render/3D/0":{[a-z":\d.,%]+}', reading):
packet = json.loads(result[14:])
single = packet.get("busy", 0.0)
render.append(float(single))
if render:
results["compute"] = f"{round(sum(render) / len(render), 2)}%"
# Video engines are the fixed-function decode engines
video = []
for result in re.findall(r'"Video/\d":{[a-z":\d.,%]+}', reading):
packet = json.loads(result[10:])
single = packet.get("busy", 0.0)
video.append(float(single))
if video:
results["dec"] = f"{round(sum(video) / len(video), 2)}%"
return results
intel_gpu_top_command = [
"timeout",
"0.5s",
"intel_gpu_top",
"-J",
"-o",
"-",
"-s",
"1000", # Intel changed this from seconds to milliseconds in 2024+ versions
]
if intel_gpu_device:
intel_gpu_top_command += ["-d", intel_gpu_device]
snapshot: dict = {}
try:
p = sp.run(
intel_gpu_top_command,
encoding="ascii",
capture_output=True,
)
except UnicodeDecodeError:
return None
proc_entries = os.listdir("/proc")
except OSError:
return snapshot
# timeout has a non-zero returncode when timeout is reached
if p.returncode != 124:
logger.error(f"Unable to poll intel GPU stats: {p.stderr}")
return None
else:
output = "".join(p.stdout.split())
for entry in proc_entries:
if not entry.isdigit():
continue
fdinfo_dir = f"/proc/{entry}/fdinfo"
try:
data = json.loads(f"[{output}]")
except json.JSONDecodeError:
return get_stats_manually(output)
fds = os.listdir(fdinfo_dir)
except (FileNotFoundError, PermissionError, NotADirectoryError, OSError):
continue
results: dict[str, str] = {}
rc6_values = []
render_global = []
video_global = []
# per-client: {pid: [total_busy_per_sample, ...]}
client_usages: dict[str, list[float]] = {}
for fd in fds:
try:
with open(f"{fdinfo_dir}/{fd}") as f:
content = f.read()
except (FileNotFoundError, PermissionError, OSError):
continue
for block in data:
# rc6 residency: percentage of time GPU is idle
rc6 = block.get("rc6", {}).get("value")
if rc6 is not None:
rc6_values.append(float(rc6))
if "drm-driver" not in content:
continue
global_engine = block.get("engines")
fields: dict[str, str] = {}
for line in content.splitlines():
key, sep, value = line.partition(":")
if sep:
fields[key.strip()] = value.strip()
if global_engine:
render_frame = global_engine.get("Render/3D/0", {}).get("busy")
video_frame = global_engine.get("Video/0", {}).get("busy")
driver = fields.get("drm-driver")
if driver not in ("i915", "xe"):
continue
if render_frame is not None:
render_global.append(float(render_frame))
pdev = fields.get("drm-pdev", "")
if target_pdev and pdev != target_pdev:
continue
if video_frame is not None:
video_global.append(float(video_frame))
client_id = fields.get("drm-client-id")
if not client_id:
continue
clients = block.get("clients", {})
key = (pdev, client_id, entry)
if key in snapshot:
continue
if clients:
for client_block in clients.values():
pid = client_block["pid"]
engines: dict[str, tuple[int, int]] = {}
if pid not in client_usages:
client_usages[pid] = []
if driver == "i915":
for fkey, engine in _I915_ENGINE_KEYS.items():
raw = fields.get(fkey)
if not raw:
continue
try:
engines[engine] = (int(raw.split()[0]), 0)
except (ValueError, IndexError):
continue
else:
for suffix, engine in _XE_ENGINE_KEYS.items():
busy_raw = fields.get(f"drm-cycles-{suffix}")
total_raw = fields.get(f"drm-total-cycles-{suffix}")
if not (busy_raw and total_raw):
continue
try:
engines[engine] = (
int(busy_raw.split()[0]),
int(total_raw.split()[0]),
)
except (ValueError, IndexError):
continue
# Sum all engine-class busy values for this client
total_busy = 0.0
for engine in client_block.get("engine-classes", {}).values():
busy = engine.get("busy")
if busy is not None:
total_busy += float(busy)
if not engines:
continue
client_usages[pid].append(total_busy)
snapshot[key] = {"driver": driver, "pid": entry, "engines": engines}
# Overall GPU usage from rc6 (idle) residency
if rc6_values:
rc6_avg = sum(rc6_values) / len(rc6_values)
results["gpu"] = f"{round(100.0 - rc6_avg, 2)}%"
return snapshot
results["mem"] = "-%"
# Compute: Render/3D engine (compute/shader workloads and QSV encode)
if render_global:
results["compute"] = f"{round(sum(render_global) / len(render_global), 2)}%"
def get_intel_gpu_stats(intel_gpu_device: Optional[str]) -> Optional[dict[str, Any]]:
"""Get stats by reading DRM fdinfo files.
# Decoder: Video engine (fixed-function codec)
if video_global:
results["dec"] = f"{round(sum(video_global) / len(video_global), 2)}%"
Each DRM client FD exposes monotonic per-engine busy counters via
/proc/<pid>/fdinfo/<fd> (i915 since kernel 5.19, Xe since first release).
We sample twice and divide busy-time deltas by wall-clock to derive
utilization. Render/3D and Compute are pooled into "compute"; Video and
VideoEnhance into "dec". Overall "gpu" is the sum of those pools (clamped
to 100%).
"""
target_pdev = _resolve_intel_gpu_pdev(intel_gpu_device)
# Per-client GPU usage (sum of all engines per process)
if client_usages:
results["clients"] = {}
snapshot_a = _read_intel_drm_fdinfo(target_pdev)
if not snapshot_a:
return None
for pid, samples in client_usages.items():
if samples:
results["clients"][pid] = (
f"{round(sum(samples) / len(samples), 2)}%"
)
start = time.monotonic()
time.sleep(_INTEL_FDINFO_SAMPLE_SECONDS)
elapsed_ns = (time.monotonic() - start) * 1e9
return results
snapshot_b = _read_intel_drm_fdinfo(target_pdev)
if not snapshot_b or elapsed_ns <= 0:
return None
engine_pct: dict[str, float] = {
"render": 0.0,
"video": 0.0,
"video-enhance": 0.0,
"compute": 0.0,
}
pid_pct: dict[str, float] = {}
for key, data_b in snapshot_b.items():
data_a = snapshot_a.get(key)
if not data_a or data_a["driver"] != data_b["driver"]:
continue
client_total = 0.0
for engine, (busy_b, total_b) in data_b["engines"].items():
if engine not in engine_pct:
continue
busy_a, total_a = data_a["engines"].get(engine, (busy_b, total_b))
if data_b["driver"] == "i915":
delta = max(0, busy_b - busy_a)
pct = min(100.0, delta / elapsed_ns * 100.0)
else:
delta_busy = max(0, busy_b - busy_a)
delta_total = total_b - total_a
if delta_total <= 0:
continue
pct = min(100.0, delta_busy / delta_total * 100.0)
engine_pct[engine] += pct
client_total += pct
pid_pct[data_b["pid"]] = pid_pct.get(data_b["pid"], 0.0) + client_total
for engine in engine_pct:
engine_pct[engine] = min(100.0, engine_pct[engine])
compute_pct = min(100.0, engine_pct["render"] + engine_pct["compute"])
dec_pct = min(100.0, engine_pct["video"] + engine_pct["video-enhance"])
overall_pct = min(100.0, compute_pct + dec_pct)
results: dict[str, Any] = {
"gpu": f"{round(overall_pct, 2)}%",
"mem": "-%",
"compute": f"{round(compute_pct, 2)}%",
"dec": f"{round(dec_pct, 2)}%",
}
if pid_pct:
results["clients"] = {
pid: f"{round(min(100.0, pct), 2)}%" for pid, pct in pid_pct.items()
}
return results
def get_openvino_npu_stats() -> Optional[dict[str, str]]:

519
web/package-lock.json generated
View File

@ -120,7 +120,7 @@
"postcss": "^8.5.8",
"prettier": "^3.3.3",
"prettier-plugin-tailwindcss": "^0.6.5",
"tailwindcss": "^3.4.9",
"tailwindcss": "^4.2.4",
"typescript": "^5.9.3",
"vite": "^6.4.2",
"vitest": "^3.0.7"
@ -142,17 +142,6 @@
"dev": true,
"license": "MIT"
},
"node_modules/@alloc/quick-lru": {
"version": "5.2.0",
"resolved": "https://registry.npmjs.org/@alloc/quick-lru/-/quick-lru-5.2.0.tgz",
"integrity": "sha512-UrcABB+4bUrFABwbluTIBErXwvbsU/V7TZWfmbgJfbkwiBuziS9gxdODUyuiecfdGQ85jglMW6juS3+z5TsKLw==",
"engines": {
"node": ">=10"
},
"funding": {
"url": "https://github.com/sponsors/sindresorhus"
}
},
"node_modules/@ampproject/remapping": {
"version": "2.3.0",
"resolved": "https://registry.npmjs.org/@ampproject/remapping/-/remapping-2.3.0.tgz",
@ -1322,6 +1311,7 @@
"version": "0.3.5",
"resolved": "https://registry.npmjs.org/@jridgewell/gen-mapping/-/gen-mapping-0.3.5.tgz",
"integrity": "sha512-IzL8ZoEDIBRWEzlCcRhOaCupYyN5gdIK+Q6fbFdPDg6HqX6jpkItn7DFIpW9LQzXG6Df9sA7+OKnq0qlz/GaQg==",
"dev": true,
"license": "MIT",
"dependencies": {
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@ -1336,6 +1326,7 @@
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"integrity": "sha512-Y/arvbn+rrz3JCKl9C4kVNfTfSm2/mEp5FSz5EsZSANGPSlQrpRI5M4PKF+mJnE52jOO90PnPSc3Ur3bTQw0gA=="
},
"node_modules/tslib": {
"version": "2.8.1",
"resolved": "https://registry.npmjs.org/tslib/-/tslib-2.8.1.tgz",
@ -13971,11 +13558,6 @@
"react": "^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0"
}
},
"node_modules/util-deprecate": {
"version": "1.0.2",
"resolved": "https://registry.npmjs.org/util-deprecate/-/util-deprecate-1.0.2.tgz",
"integrity": "sha512-EPD5q1uXyFxJpCrLnCc1nHnq3gOa6DZBocAIiI2TaSCA7VCJ1UJDMagCzIkXNsUYfD1daK//LTEQ8xiIbrHtcw=="
},
"node_modules/uuid": {
"version": "13.0.0",
"resolved": "https://registry.npmjs.org/uuid/-/uuid-13.0.0.tgz",
@ -14475,7 +14057,8 @@
"node_modules/wrappy": {
"version": "1.0.2",
"resolved": "https://registry.npmjs.org/wrappy/-/wrappy-1.0.2.tgz",
"integrity": "sha512-l4Sp/DRseor9wL6EvV2+TuQn63dMkPjZ/sp9XkghTEbV9KlPS1xUsZ3u7/IQO4wxtcFB4bgpQPRcR3QCvezPcQ=="
"integrity": "sha512-l4Sp/DRseor9wL6EvV2+TuQn63dMkPjZ/sp9XkghTEbV9KlPS1xUsZ3u7/IQO4wxtcFB4bgpQPRcR3QCvezPcQ==",
"dev": true
},
"node_modules/ws": {
"version": "8.18.0",

View File

@ -134,7 +134,7 @@
"postcss": "^8.5.8",
"prettier": "^3.3.3",
"prettier-plugin-tailwindcss": "^0.6.5",
"tailwindcss": "^3.4.9",
"tailwindcss": "^4.2.4",
"typescript": "^5.9.3",
"vite": "^6.4.2",
"vitest": "^3.0.7"

View File

@ -485,6 +485,10 @@
"hwaccel_args": {
"label": "Export hwaccel args",
"description": "Hardware acceleration args to use for export/transcode operations."
},
"max_concurrent": {
"label": "Maximum concurrent exports",
"description": "Maximum number of export jobs to process at the same time."
}
},
"preview": {

View File

@ -242,8 +242,8 @@
"description": "Enable per-process network bandwidth monitoring for camera ffmpeg processes and detectors (requires capabilities)."
},
"intel_gpu_device": {
"label": "SR-IOV device",
"description": "Device identifier used when treating Intel GPUs as SR-IOV to fix GPU stats."
"label": "Intel GPU device",
"description": "PCI bus address or DRM device path (e.g. /dev/dri/card1) used to pin Intel GPU stats to a specific device when multiple are present."
}
},
"version_check": {
@ -1000,6 +1000,10 @@
"hwaccel_args": {
"label": "Export hwaccel args",
"description": "Hardware acceleration args to use for export/transcode operations."
},
"max_concurrent": {
"label": "Maximum concurrent exports",
"description": "Maximum number of export jobs to process at the same time."
}
},
"preview": {

View File

@ -20,7 +20,18 @@
"overriddenGlobal": "Overridden (Global)",
"overriddenGlobalTooltip": "This camera overrides global configuration settings in this section",
"overriddenBaseConfig": "Overridden (Base Config)",
"overriddenBaseConfigTooltip": "The {{profile}} profile overrides configuration settings in this section"
"overriddenBaseConfigTooltip": "The {{profile}} profile overrides configuration settings in this section",
"overriddenInCameras": {
"label_one": "Overridden in {{count}} camera",
"label_other": "Overridden in {{count}} cameras",
"tooltip_one": "{{count}} camera overrides values in this section. Click to see details.",
"tooltip_other": "{{count}} cameras override values in this section. Click to see details.",
"heading_one": "This global section has fields that are overridden in {{count}} camera.",
"heading_other": "This global section has fields that are overridden in {{count}} cameras.",
"othersField_one": "{{count}} other",
"othersField_other": "{{count}} others",
"profilePrefix": "{{profile}} profile: {{fields}}"
}
},
"menu": {
"general": "General",

View File

@ -25,6 +25,7 @@ import {
} from "./section-special-cases";
import { getSectionValidation } from "../section-validations";
import { useConfigOverride } from "@/hooks/use-config-override";
import { CameraOverridesBadge } from "./CameraOverridesBadge";
import { useSectionSchema } from "@/hooks/use-config-schema";
import type { FrigateConfig } from "@/types/frigateConfig";
import { Badge } from "@/components/ui/badge";
@ -1263,6 +1264,9 @@ export function ConfigSection({
</TooltipContent>
</Tooltip>
)}
{showOverrideIndicator && effectiveLevel === "global" && (
<CameraOverridesBadge sectionPath={sectionPath} />
)}
{hasChanges && (
<Badge variant="outline" className="text-xs">
{t("button.modified", {
@ -1334,6 +1338,9 @@ export function ConfigSection({
</TooltipContent>
</Tooltip>
)}
{showOverrideIndicator && effectiveLevel === "global" && (
<CameraOverridesBadge sectionPath={sectionPath} />
)}
{hasChanges && (
<Badge
variant="secondary"

View File

@ -0,0 +1,303 @@
import useSWR from "swr";
import { useMemo } from "react";
import { useTranslation } from "react-i18next";
import { Link } from "react-router-dom";
import { LuChevronDown } from "react-icons/lu";
import { Badge } from "@/components/ui/badge";
import {
Popover,
PopoverContent,
PopoverTrigger,
} from "@/components/ui/popover";
import {
CameraOverrideEntry,
FieldDelta,
useCamerasOverridingSection,
} from "@/hooks/use-config-override";
import type { FrigateConfig } from "@/types/frigateConfig";
import type { ProfilesApiResponse } from "@/types/profile";
import { humanizeKey } from "@/components/config-form/theme/utils/i18n";
import { useCameraFriendlyName } from "@/hooks/use-camera-friendly-name";
import { formatList } from "@/utils/stringUtil";
import { getSectionConfig } from "@/utils/configUtil";
const CAMERA_PAGE_BY_SECTION: Record<string, string> = {
detect: "cameraDetect",
ffmpeg: "cameraFfmpeg",
record: "cameraRecording",
snapshots: "cameraSnapshots",
motion: "cameraMotion",
objects: "cameraObjects",
review: "cameraReview",
audio: "cameraAudioEvents",
audio_transcription: "cameraAudioTranscription",
notifications: "cameraNotifications",
live: "cameraLivePlayback",
birdseye: "cameraBirdseye",
face_recognition: "cameraFaceRecognition",
lpr: "cameraLpr",
timestamp_style: "cameraTimestampStyle",
};
const MAX_FIELDS_PER_CAMERA = 5;
/**
* Enrichment sections where the cross-camera override badge should be
* suppressed because they're effectively global-only (or per-camera
* configuration there isn't a useful affordance to surface here).
* Face recognition and LPR are intentionally omitted so the badge does show
* on those enrichment pages.
*/
const SECTIONS_WITHOUT_OVERRIDE_BADGE = new Set([
"semantic_search",
"genai",
"classification",
"audio_transcription",
]);
/**
* Match a delta path against a hidden-field pattern. Supports literal prefixes
* (so a hidden field "streams" also hides "streams.foo.bar") and `*` wildcards
* matching exactly one path segment (e.g. "filters.*.mask").
*/
function pathMatchesHiddenPattern(path: string, pattern: string): boolean {
if (!pattern) return false;
if (!pattern.includes("*")) {
return path === pattern || path.startsWith(`${pattern}.`);
}
const patternSegments = pattern.split(".");
const pathSegments = path.split(".");
if (pathSegments.length < patternSegments.length) return false;
for (let i = 0; i < patternSegments.length; i += 1) {
if (patternSegments[i] === "*") continue;
if (patternSegments[i] !== pathSegments[i]) return false;
}
return true;
}
type CameraEntryProps = {
sectionPath: string;
entry: CameraOverrideEntry;
cameraPage?: string;
};
type SourceGroup = {
/** undefined → camera-level; string → profile name */
profileName: string | undefined;
deltas: FieldDelta[];
};
function groupDeltasBySource(deltas: FieldDelta[]): SourceGroup[] {
const cameraDeltas: FieldDelta[] = [];
const byProfile = new Map<string, FieldDelta[]>();
for (const delta of deltas) {
if (delta.profileName) {
const arr = byProfile.get(delta.profileName) ?? [];
arr.push(delta);
byProfile.set(delta.profileName, arr);
} else {
cameraDeltas.push(delta);
}
}
const groups: SourceGroup[] = [];
if (cameraDeltas.length > 0) {
groups.push({ profileName: undefined, deltas: cameraDeltas });
}
for (const [profileName, group] of byProfile) {
groups.push({ profileName, deltas: group });
}
return groups;
}
function CameraEntry({ sectionPath, entry, cameraPage }: CameraEntryProps) {
const { t, i18n } = useTranslation([
"config/global",
"views/settings",
"objects",
]);
const friendlyName = useCameraFriendlyName(entry.camera);
const { data: profilesData } = useSWR<ProfilesApiResponse>("profiles");
const profileFriendlyNames = useMemo(() => {
const map = new Map<string, string>();
profilesData?.profiles?.forEach((p) => map.set(p.name, p.friendly_name));
return map;
}, [profilesData]);
const fieldLabel = (fieldPath: string) => {
if (!fieldPath) {
const sectionKey = `${sectionPath}.label`;
return i18n.exists(sectionKey, { ns: "config/global" })
? t(sectionKey, { ns: "config/global" })
: humanizeKey(sectionPath);
}
const segments = fieldPath.split(".");
// Most specific: try the full nested path
const fullKey = `${sectionPath}.${fieldPath}.label`;
if (i18n.exists(fullKey, { ns: "config/global" })) {
return t(fullKey, { ns: "config/global" });
}
// Try dropping each intermediate segment in turn — those are typically
// user-defined dict keys (object class names, zone names, etc.) that
// don't have their own label entries. Prepend the dropped segment as
// context to disambiguate (e.g. "Person · Minimum object area").
for (let i = 0; i < segments.length; i++) {
const reduced = [...segments.slice(0, i), ...segments.slice(i + 1)].join(
".",
);
if (!reduced) continue;
const reducedKey = `${sectionPath}.${reduced}.label`;
if (i18n.exists(reducedKey, { ns: "config/global" })) {
const resolvedLabel = t(reducedKey, { ns: "config/global" });
const dropped = segments[i];
// Object class names ("person", "car", "fox") have translations in
// the `objects` namespace; fall back to humanizing the raw key for
// anything that isn't a known label.
const droppedLabel = i18n.exists(dropped, { ns: "objects" })
? t(dropped, { ns: "objects" })
: humanizeKey(dropped);
return `${droppedLabel} · ${resolvedLabel}`;
}
}
// Last resort: humanize the leaf segment
return humanizeKey(segments[segments.length - 1]);
};
const formatDeltas = (deltas: FieldDelta[]) => {
const visibleLabels = deltas
.slice(0, MAX_FIELDS_PER_CAMERA)
.map((delta) => fieldLabel(delta.fieldPath));
const hiddenCount = deltas.length - visibleLabels.length;
const labelsForList =
hiddenCount > 0
? [
...visibleLabels,
t("button.overriddenInCameras.othersField", {
ns: "views/settings",
count: hiddenCount,
}),
]
: visibleLabels;
return formatList(labelsForList);
};
const groups = groupDeltasBySource(entry.fieldDeltas);
return (
<div className="flex flex-col gap-0.5 text-xs">
{cameraPage ? (
<Link
to={`/settings?page=${cameraPage}&camera=${encodeURIComponent(entry.camera)}`}
className="font-medium hover:underline"
>
{friendlyName}
</Link>
) : (
<span className="font-medium">{friendlyName}</span>
)}
{groups.map((group) => (
<span
key={group.profileName ?? "__camera__"}
className="ml-2 text-muted-foreground"
>
{group.profileName
? t("button.overriddenInCameras.profilePrefix", {
ns: "views/settings",
profile:
profileFriendlyNames.get(group.profileName) ??
group.profileName,
fields: formatDeltas(group.deltas),
})
: formatDeltas(group.deltas)}
</span>
))}
</div>
);
}
type Props = {
sectionPath: string;
className?: string;
};
export function CameraOverridesBadge({ sectionPath, className }: Props) {
const { data: config } = useSWR<FrigateConfig>("config");
const { t } = useTranslation(["views/settings"]);
const rawEntries = useCamerasOverridingSection(config, sectionPath);
const entries = useMemo(() => {
const hiddenFields =
getSectionConfig(sectionPath, "global").hiddenFields ?? [];
if (hiddenFields.length === 0) return rawEntries;
return rawEntries
.map((entry) => ({
...entry,
fieldDeltas: entry.fieldDeltas.filter(
(delta) =>
!hiddenFields.some((pattern) =>
pathMatchesHiddenPattern(delta.fieldPath, pattern),
),
),
}))
.filter((entry) => entry.fieldDeltas.length > 0);
}, [rawEntries, sectionPath]);
if (SECTIONS_WITHOUT_OVERRIDE_BADGE.has(sectionPath)) {
return null;
}
if (entries.length === 0) {
return null;
}
const cameraPage = CAMERA_PAGE_BY_SECTION[sectionPath];
const count = entries.length;
return (
<Popover>
<PopoverTrigger asChild>
<Badge
variant="secondary"
className={`cursor-pointer border-2 border-selected text-xs text-primary-variant ${className ?? ""}`}
aria-label={t("button.overriddenInCameras.tooltip", {
ns: "views/settings",
count: count,
})}
>
<span>
{t("button.overriddenInCameras.label", {
ns: "views/settings",
count: count,
})}
</span>
<LuChevronDown className="ml-1 size-3" />
</Badge>
</PopoverTrigger>
<PopoverContent align="start" className="w-80 max-w-[90vw] pr-0">
<div className="flex flex-col gap-3">
<div className="pr-4 text-xs text-primary-variant">
{t("button.overriddenInCameras.heading", {
ns: "views/settings",
count: count,
})}
</div>
<div className="scrollbar-container flex max-h-[40dvh] flex-col gap-2 overflow-y-auto pr-4">
{entries.map((entry) => (
<CameraEntry
key={entry.camera}
sectionPath={sectionPath}
entry={entry}
cameraPage={cameraPage}
/>
))}
</div>
</div>
</PopoverContent>
</Popover>
);
}

View File

@ -202,6 +202,49 @@ export function useConfigOverride({
}, [config, cameraName, sectionPath, compareFields]);
}
/**
* Sections that can be overridden per-camera, with optional compareFields
* filters that scope the override comparison to a subset of fields.
*/
export const OVERRIDABLE_SECTIONS: ReadonlyArray<{
key: string;
compareFields?: string[];
}> = [
{ key: "detect" },
{ key: "record" },
{ key: "snapshots" },
{ key: "motion" },
{ key: "objects" },
{ key: "review" },
{ key: "audio" },
{ key: "notifications" },
{ key: "live" },
{ key: "timestamp_style" },
{
key: "audio_transcription",
compareFields: ["enabled", "live_enabled"],
},
{ key: "birdseye", compareFields: ["enabled", "mode"] },
{ key: "face_recognition", compareFields: ["enabled", "min_area"] },
{
key: "ffmpeg",
compareFields: [
"path",
"global_args",
"hwaccel_args",
"input_args",
"output_args",
"retry_interval",
"apple_compatibility",
"gpu",
],
},
{
key: "lpr",
compareFields: ["enabled", "min_area", "enhancement"],
},
];
/**
* Hook to get all overridden fields for a camera
*/
@ -221,47 +264,7 @@ export function useAllCameraOverrides(
const overriddenSections: string[] = [];
// Check each section that can be overridden
const sectionsToCheck: Array<{
key: string;
compareFields?: string[];
}> = [
{ key: "detect" },
{ key: "record" },
{ key: "snapshots" },
{ key: "motion" },
{ key: "objects" },
{ key: "review" },
{ key: "audio" },
{ key: "notifications" },
{ key: "live" },
{ key: "timestamp_style" },
{
key: "audio_transcription",
compareFields: ["enabled", "live_enabled"],
},
{ key: "birdseye", compareFields: ["enabled", "mode"] },
{ key: "face_recognition", compareFields: ["enabled", "min_area"] },
{
key: "ffmpeg",
compareFields: [
"path",
"global_args",
"hwaccel_args",
"input_args",
"output_args",
"retry_interval",
"apple_compatibility",
"gpu",
],
},
{
key: "lpr",
compareFields: ["enabled", "min_area", "enhancement"],
},
];
for (const { key, compareFields } of sectionsToCheck) {
for (const { key, compareFields } of OVERRIDABLE_SECTIONS) {
const globalValue = normalizeConfigValue(get(config, key));
const cameraValue = normalizeConfigValue(
getBaseCameraSectionValue(config, cameraName, key),
@ -286,3 +289,252 @@ export function useAllCameraOverrides(
return overriddenSections;
}, [config, cameraName]);
}
export interface FieldDelta {
/** Path relative to the section (e.g. "genai.enabled") */
fieldPath: string;
globalValue: unknown;
cameraValue: unknown;
/** Profile name when the override originates from a profile; undefined for camera-level overrides */
profileName?: string;
}
export interface CameraOverrideEntry {
camera: string;
fieldDeltas: FieldDelta[];
}
/**
* Collect leaf-level field differences between a global section value
* and a camera section value. When compareFields is provided, only those
* paths are compared; otherwise the objects are walked recursively.
*/
function collectFieldDeltas(
globalValue: JsonValue,
cameraValue: JsonValue,
compareFields?: string[],
pathPrefix = "",
): FieldDelta[] {
if (compareFields) {
if (compareFields.length === 0) {
return [];
}
const deltas: FieldDelta[] = [];
for (const path of compareFields) {
const g = get(globalValue, path);
const c = get(cameraValue, path);
if (!isEqual(g, c)) {
deltas.push({ fieldPath: path, globalValue: g, cameraValue: c });
}
}
return deltas;
}
if (isJsonObject(globalValue) && isJsonObject(cameraValue)) {
const deltas: FieldDelta[] = [];
const keys = new Set([
...Object.keys(globalValue),
...Object.keys(cameraValue),
]);
for (const key of keys) {
const g = (globalValue as JsonObject)[key];
const c = (cameraValue as JsonObject)[key];
if (isEqual(g, c)) continue;
const childPath = pathPrefix ? `${pathPrefix}.${key}` : key;
if (isJsonObject(g) && isJsonObject(c)) {
deltas.push(...collectFieldDeltas(g, c, undefined, childPath));
} else {
deltas.push({ fieldPath: childPath, globalValue: g, cameraValue: c });
}
}
return deltas;
}
if (!isEqual(globalValue, cameraValue)) {
return [{ fieldPath: pathPrefix, globalValue, cameraValue }];
}
return [];
}
/**
* Walk a partial config object and return the dot-paths of every leaf value
* (primitive or array) actually defined on it. Used to limit profile-vs-global
* diffs to keys the profile actually sets, avoiding false "undefined" deltas
* for fields the profile leaves unspecified.
*/
function collectDefinedLeafPaths(value: JsonValue, prefix = ""): string[] {
if (!isJsonObject(value)) {
return prefix ? [prefix] : [];
}
const paths: string[] = [];
for (const [key, val] of Object.entries(value as JsonObject)) {
const childPath = prefix ? `${prefix}.${key}` : key;
if (isJsonObject(val)) {
paths.push(...collectDefinedLeafPaths(val as JsonValue, childPath));
} else {
paths.push(childPath);
}
}
return paths;
}
function isPathAllowed(path: string, compareFields?: string[]): boolean {
if (!compareFields) return true;
return compareFields.some(
(allowed) => path === allowed || path.startsWith(`${allowed}.`),
);
}
/**
* Some Frigate sections (notably `motion`) are dumped by the backend with
* `exclude_unset=True`, so when the user hasn't explicitly written the section
* in their global YAML the API returns null even though every camera still
* gets defaults applied at runtime. To still detect cross-camera differences
* in those sections we synthesize a baseline by taking the modal (most common)
* value at each leaf path across cameras cameras whose value diverges from
* the modal are treated as overriding.
*/
function deriveSyntheticGlobalValue(
cameraSectionValues: JsonValue[],
compareFields?: string[],
): JsonObject {
const cameras = cameraSectionValues.filter(isJsonObject) as JsonObject[];
if (cameras.length === 0) return {};
const allPaths = new Set<string>();
for (const cam of cameras) {
for (const path of collectDefinedLeafPaths(cam as JsonValue)) {
if (!isPathAllowed(path, compareFields)) continue;
allPaths.add(path);
}
}
const baseline: JsonObject = {};
for (const path of allPaths) {
const counts = new Map<string, { value: unknown; count: number }>();
for (const cam of cameras) {
const v = get(cam, path);
const key = JSON.stringify(v ?? null);
const existing = counts.get(key);
if (existing) {
existing.count += 1;
} else {
counts.set(key, { value: v, count: 1 });
}
}
let modal: { value: unknown; count: number } | undefined;
for (const entry of counts.values()) {
if (!modal || entry.count > modal.count) modal = entry;
}
if (modal) {
set(baseline, path, modal.value);
}
}
return baseline;
}
/**
* Paths that are intentionally hidden from the cross-camera override summary
* because they're inherently per-camera (mask polygons, zone definitions) and
* would otherwise dominate the popover with noise. Excludes any path where
* `mask` appears as a path segment, so nested keys under a mask dict (e.g.
* `mask.global_object_mask_1.coordinates`) are also filtered.
*/
function isCrossCameraIgnoredPath(path: string): boolean {
if (!path) return false;
return path.split(".").includes("mask");
}
/**
* Hook to find every camera that overrides a given global section. Returns
* one entry per overriding camera with the specific field-level deltas.
* Considers both the camera's own (pre-profile) section value and any of its
* defined profiles, so a field overridden only inside a profile still surfaces.
*
* @example
* ```tsx
* const entries = useCamerasOverridingSection(config, "review");
* // [{ camera: "front_door", fieldDeltas: [{ fieldPath: "genai.enabled", ... }] }]
* ```
*/
export function useCamerasOverridingSection(
config: FrigateConfig | undefined,
sectionPath: string,
): CameraOverrideEntry[] {
return useMemo(() => {
if (!config?.cameras || !sectionPath) {
return [];
}
const sectionMeta = OVERRIDABLE_SECTIONS.find((s) => s.key === sectionPath);
const compareFields = sectionMeta?.compareFields;
const cameraNames = Object.keys(config.cameras);
const cameraSectionValues = cameraNames.map((name) =>
normalizeConfigValue(
getBaseCameraSectionValue(config, name, sectionPath),
),
);
const rawGlobalValue = get(config, sectionPath);
const globalValue: JsonValue =
rawGlobalValue == null
? deriveSyntheticGlobalValue(cameraSectionValues, compareFields)
: normalizeConfigValue(rawGlobalValue);
const entries: CameraOverrideEntry[] = [];
for (let idx = 0; idx < cameraNames.length; idx += 1) {
const cameraName = cameraNames[idx];
const cameraConfig = config.cameras[cameraName];
const deltasByPath = new Map<string, FieldDelta>();
// 1. Camera-level overrides (uses base_config when a profile is active)
const cameraValue = cameraSectionValues[idx];
for (const delta of collectFieldDeltas(
globalValue,
cameraValue,
compareFields,
)) {
if (isCrossCameraIgnoredPath(delta.fieldPath)) continue;
deltasByPath.set(delta.fieldPath, delta);
}
// 2. Profile-level overrides — diff only the paths each profile actually
// defines, so unspecified-in-profile fields don't register as deltas.
const profiles = cameraConfig?.profiles ?? {};
for (const profileName of Object.keys(profiles)) {
const profileSection = (
profiles[profileName] as Record<string, unknown> | undefined
)?.[sectionPath];
if (profileSection === undefined) continue;
const normalizedProfile = normalizeConfigValue(
profileSection as JsonValue,
);
for (const path of collectDefinedLeafPaths(normalizedProfile)) {
if (deltasByPath.has(path)) continue;
if (isCrossCameraIgnoredPath(path)) continue;
if (!isPathAllowed(path, compareFields)) continue;
const g = get(globalValue, path);
const p = get(normalizedProfile, path);
if (!isEqual(g, p)) {
deltasByPath.set(path, {
fieldPath: path,
globalValue: g,
cameraValue: p,
profileName,
});
}
}
}
if (deltasByPath.size > 0) {
entries.push({
camera: cameraName,
fieldDeltas: Array.from(deltasByPath.values()),
});
}
}
return entries;
}, [config, sectionPath]);
}

View File

@ -2,6 +2,7 @@ import { useCallback, useMemo, useState } from "react";
import { useTranslation } from "react-i18next";
import type { SectionConfig } from "@/components/config-form/sections";
import { ConfigSectionTemplate } from "@/components/config-form/sections";
import { CameraOverridesBadge } from "@/components/config-form/sections/CameraOverridesBadge";
import type { PolygonType } from "@/types/canvas";
import { Badge } from "@/components/ui/badge";
import {
@ -167,6 +168,9 @@ export function SingleSectionPage({
</div>
{/* Desktop: badge inline next to title */}
<div className="hidden shrink-0 sm:flex sm:flex-wrap sm:items-center sm:gap-2">
{level === "global" && showOverrideIndicator && (
<CameraOverridesBadge sectionPath={sectionKey} />
)}
{level === "camera" &&
showOverrideIndicator &&
sectionStatus.isOverridden && (
@ -224,6 +228,9 @@ export function SingleSectionPage({
</div>
{/* Mobile: badge below title/description */}
<div className="flex flex-wrap items-center gap-2 sm:hidden">
{level === "global" && showOverrideIndicator && (
<CameraOverridesBadge sectionPath={sectionKey} />
)}
{level === "camera" &&
showOverrideIndicator &&
sectionStatus.isOverridden && (