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Increase ruff coverage (#23644)
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Browse Source 
* Pin ruff

* Add python upgrade fixes

This enables python upgrade checks in ruff to look for deprecated types and patterns. This namely fixes:
- usage of deprecated `Typing` which is now built in
- some specific exceptions which are caught and have new aliases

Some specific UP checks were also ignored as they are stylistic / unimportant and likely to cause bugs

* Remove async blocking calls

Use asyncio.to_thread on two remaining blocking calls to fix hanging event thread loop. Enable this specific rule to block it in the future.

* Use proper logging mechanism

* Correctly format logs

* Raise with context

When raising an exception include the from context to improve debugging

* Cleanup
This commit is contained in:
Nicolas Mowen 2026-07-06 09:28:02 -08:00 committed by GitHub
parent 455b8687e8
commit 4ee12e6237
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
169 changed files with 1053 additions and 1150 deletions
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2
docker/main/requirements-dev.txt
View File

@ -1,4 +1,4 @@
ruff
ruff == 0.15.20
# types
types-peewee == 3.17.*

6
docker/rockchip/conv2rknn.py
View File

@ -11,10 +11,10 @@ except FileNotFoundError:
pass
try:
with open("/config/conv2rknn.yaml", "r") as config_file:
with open("/config/conv2rknn.yaml") as config_file:
configuration = yaml.safe_load(config_file)
except FileNotFoundError:
raise Exception("Please place a config file at /config/conv2rknn.yaml")
raise Exception("Please place a config file at /config/conv2rknn.yaml") from None
if configuration["config"] != None:
rknn_config = configuration["config"]
@ -31,7 +31,7 @@ if "soc" not in configuration:
with open("/proc/device-tree/compatible") as file:
soc = file.read().split(",")[-1].strip("\x00")
except FileNotFoundError:
raise Exception("Make sure to run docker in privileged mode.")
raise Exception("Make sure to run docker in privileged mode.") from None
configuration["soc"] = [
soc,

5
frigate/__main__.py
View File

@ -4,7 +4,6 @@ import multiprocessing as mp
import signal
import sys
import threading
from typing import Union
import ruamel.yaml
from pydantic import ValidationError
@ -54,7 +53,7 @@ def main() -> None:
print("*************************************************************\n")
# Attempt to get the original config file for line number tracking
config_path = find_config_file()
with open(config_path, "r") as f:
with open(config_path) as f:
yaml_config = ruamel.yaml.YAML()
yaml_config.preserve_quotes = True
full_config = yaml_config.load(f)
@ -68,7 +67,7 @@ def main() -> None:
try:
for i, part in enumerate(error_path):
key: Union[int, str] = (
key: int | str = (
int(part) if isinstance(part, str) and part.isdigit() else part
)

68
frigate/api/app.py
View File

@ -12,7 +12,7 @@ from datetime import datetime, timedelta
from functools import reduce
from io import StringIO
from pathlib import Path as FilePath
from typing import Any, Dict, List, Optional
from typing import Any
import aiofiles
import ruamel.yaml
@ -113,7 +113,7 @@ def version():
@router.get("/stats", dependencies=[Depends(allow_any_authenticated())])
def stats(
request: Request,
allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
):
stats_data = request.app.stats_emitter.get_latest_stats()
@ -164,7 +164,7 @@ def metrics(request: Request):
# Retrieve the latest statistics and update the Prometheus metrics
stats = request.app.stats_emitter.get_latest_stats()
# query DB for count of events by camera, label
event_counts: List[Dict[str, Any]] = (
event_counts: list[dict[str, Any]] = (
Event.select(Event.camera, Event.label, fn.Count())
.group_by(Event.camera, Event.label)
.dicts()
@ -250,7 +250,7 @@ async def genai_probe(body: GenAIProbeBody):
asyncio.to_thread(client.list_models),
timeout=_PROBE_OUTER_TIMEOUT_SECONDS,
)
except asyncio.TimeoutError:
except TimeoutError:
return JSONResponse(
content={"success": False, "message": "Probe timed out"},
)
@ -374,7 +374,7 @@ def config(request: Request):
if model_path:
model_json_path = FilePath(model_path).with_suffix(".json")
try:
with open(model_json_path, "r") as f:
with open(model_json_path) as f:
model_plus_data = json.load(f)
config["model"]["plus"] = model_plus_data
except FileNotFoundError:
@ -502,7 +502,7 @@ def config_raw():
status_code=404,
)
with open(config_file, "r") as f:
with open(config_file) as f:
raw_config = f.read()
f.close()
@ -807,7 +807,7 @@ def config_set(request: Request, body: AppConfigSetBody):
try:
with lock:
with open(config_file, "r") as f:
with open(config_file) as f:
old_raw_config = f.read()
try:
@ -854,7 +854,7 @@ def config_set(request: Request, body: AppConfigSetBody):
update_yaml_file_bulk(config_file, updates)
# validate the updated config
with open(config_file, "r") as f:
with open(config_file) as f:
new_raw_config = f.read()
try:
@ -1028,16 +1028,16 @@ def nvinfo():
)
async def logs(
service: str = Path(enum=["frigate", "nginx", "go2rtc"]),
download: Optional[str] = None,
stream: Optional[bool] = False,
start: Optional[int] = 0,
end: Optional[int] = None,
download: str | None = None,
stream: bool | None = False,
start: int | None = 0,
end: int | None = None,
):
"""Get logs for the requested service (frigate/nginx/go2rtc)"""
def download_logs(service_location: str):
try:
file = open(service_location, "r")
file = open(service_location)
contents = file.read()
file.close()
return JSONResponse(jsonable_encoder(contents))
@ -1052,7 +1052,7 @@ async def logs(
"""Asynchronously stream log lines."""
buffer = ""
try:
async with aiofiles.open(file_path, "r") as file:
async with aiofiles.open(file_path) as file:
await file.seek(0, 2)
while True:
line = await file.readline()
@ -1090,7 +1090,7 @@ async def logs(
# For full logs initially
try:
async with aiofiles.open(service_location, "r") as file:
async with aiofiles.open(service_location) as file:
contents = await file.read()
total_lines, log_lines = process_logs(contents, service, start, end)
@ -1231,7 +1231,7 @@ def get_media_sync_status(job_id: str):
@router.get("/labels", dependencies=[Depends(allow_any_authenticated())])
def get_labels(
camera: str = "",
allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
):
try:
if camera:
@ -1263,8 +1263,8 @@ def get_labels(
@router.get("/sub_labels", dependencies=[Depends(allow_any_authenticated())])
def get_sub_labels(
split_joined: Optional[int] = None,
allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
split_joined: int | None = None,
allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
):
try:
events = (
@ -1351,8 +1351,8 @@ def plusModels(request: Request, filterByCurrentModelDetector: bool = False):
"/recognized_license_plates", dependencies=[Depends(allow_any_authenticated())]
)
def get_recognized_license_plates(
split_joined: Optional[int] = None,
allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
split_joined: int | None = None,
allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
):
try:
query = (
@ -1393,8 +1393,8 @@ def get_recognized_license_plates(
def timeline(
camera: str = "all",
limit: int = 100,
source_id: Optional[str] = None,
allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
source_id: str | None = None,
allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
):
clauses = []
@ -1408,20 +1408,20 @@ def timeline(
]
if camera != "all":
clauses.append((Timeline.camera == camera))
clauses.append(Timeline.camera == camera)
if source_id:
source_ids = [sid.strip() for sid in source_id.split(",")]
if len(source_ids) == 1:
clauses.append((Timeline.source_id == source_ids[0]))
clauses.append(Timeline.source_id == source_ids[0])
else:
clauses.append((Timeline.source_id.in_(source_ids)))
clauses.append(Timeline.source_id.in_(source_ids))
# Enforce per-camera access control
clauses.append((Timeline.camera << allowed_cameras))
clauses.append(Timeline.camera << allowed_cameras)
if len(clauses) == 0:
clauses.append((True))
clauses.append(True)
timeline = (
Timeline.select(*selected_columns)
@ -1437,7 +1437,7 @@ def timeline(
@router.get("/timeline/hourly", dependencies=[Depends(allow_any_authenticated())])
def hourly_timeline(
params: AppTimelineHourlyQueryParameters = Depends(),
allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
):
"""Get hourly summary for timeline."""
cameras = params.cameras
@ -1454,23 +1454,23 @@ def hourly_timeline(
if cameras != "all":
camera_list = cameras.split(",")
clauses.append((Timeline.camera << camera_list))
clauses.append(Timeline.camera << camera_list)
# Enforce per-camera access control
clauses.append((Timeline.camera << allowed_cameras))
clauses.append(Timeline.camera << allowed_cameras)
if labels != "all":
label_list = labels.split(",")
clauses.append((Timeline.data["label"] << label_list))
clauses.append(Timeline.data["label"] << label_list)
if before:
clauses.append((Timeline.timestamp < before))
clauses.append(Timeline.timestamp < before)
if after:
clauses.append((Timeline.timestamp > after))
clauses.append(Timeline.timestamp > after)
if len(clauses) == 0:
clauses.append((True))
clauses.append(True)
timeline = (
Timeline.select(

13
frigate/api/auth.py
View File

@ -11,7 +11,6 @@ import secrets
import time
from datetime import datetime
from pathlib import Path
from typing import List, Optional
from urllib.parse import parse_qs, urlparse
from fastapi import APIRouter, Depends, HTTPException, Request, Response
@ -390,7 +389,7 @@ def verify_password(password, password_hash):
return secrets.compare_digest(password_hash, compare_hash)
def validate_password_strength(password: str) -> tuple[bool, Optional[str]]:
def validate_password_strength(password: str) -> tuple[bool, str | None]:
"""
Validate password strength.
@ -445,7 +444,7 @@ async def get_current_user(request: Request):
return {"username": username, "role": role}
def require_role(required_roles: List[str]):
def require_role(required_roles: list[str]):
async def role_checker(request: Request):
proxy_config: ProxyConfig = request.app.frigate_config.proxy
config_roles = list(request.app.frigate_config.auth.roles.keys())
@ -1083,7 +1082,7 @@ async def update_role(
async def require_camera_access(
camera_name: Optional[str] = None,
camera_name: str | None = None,
request: Request = None,
):
"""Dependency to enforce camera access based on user role."""
@ -1148,8 +1147,8 @@ GO2RTC_STREAM_PROXY_PATHS = frozenset(
def deny_response_for_go2rtc_stream(
original_url: Optional[str], role: Optional[str], request: Request
) -> Optional[int]:
original_url: str | None, role: str | None, request: Request
) -> int | None:
"""Block role-restricted users from go2rtc live streams they cannot access.
Returns 403 when any `src` stream named in `original_url` resolves to a
@ -1194,7 +1193,7 @@ def deny_response_for_go2rtc_stream(
async def require_go2rtc_stream_access(
stream_name: Optional[str] = None,
stream_name: str | None = None,
request: Request = None,
):
"""Dependency to enforce go2rtc stream access based on owning camera access."""

11
frigate/api/camera.py
View File

@ -74,7 +74,7 @@ def _is_valid_host(host: str) -> bool:
@router.get("/go2rtc/streams", dependencies=[Depends(allow_any_authenticated())])
async def go2rtc_streams(request: Request):
r = requests.get("http://127.0.0.1:1984/api/streams")
r = await asyncio.to_thread(requests.get, "http://127.0.0.1:1984/api/streams")
if not r.ok:
logger.error("Failed to fetch streams from go2rtc")
return JSONResponse(
@ -1187,14 +1187,14 @@ async def delete_camera(
try:
with lock:
with open(config_file, "r") as f:
with open(config_file) as f:
old_raw_config = f.read()
try:
yaml = YAML()
yaml.indent(mapping=2, sequence=4, offset=2)
with open(config_file, "r") as f:
with open(config_file) as f:
data = yaml.load(f)
# Remove camera from config
@ -1223,7 +1223,7 @@ async def delete_camera(
with open(config_file, "w") as f:
yaml.dump(data, f)
with open(config_file, "r") as f:
with open(config_file) as f:
new_raw_config = f.read()
try:
@ -1285,7 +1285,8 @@ async def delete_camera(
# Best-effort go2rtc stream removal
try:
requests.delete(
await asyncio.to_thread(
requests.delete,
"http://127.0.0.1:1984/api/streams",
params={"src": camera_name},
timeout=5,

21
frigate/api/chat.py
View File

@ -7,7 +7,7 @@ import operator
import time
from datetime import datetime
from functools import reduce
from typing import Any, Optional
from typing import Any
import cv2
from fastapi import APIRouter, Body, Depends, HTTPException, Request
@ -201,7 +201,7 @@ async def _execute_search_objects(
# Return it as-is for the LLM
return response
except Exception as e:
logger.error(f"Error executing search_objects: {e}", exc_info=True)
logger.exception(f"Error executing search_objects: {e}")
return JSONResponse(
content={
"success": False,
@ -611,7 +611,7 @@ async def _execute_get_live_context(
return result
except Exception as e:
logger.error(f"Error executing get_live_context: {e}", exc_info=True)
logger.exception(f"Error executing get_live_context: {e}")
return {
"error": "Error getting live context",
}
@ -621,7 +621,7 @@ async def _get_live_frame_image_url(
request: Request,
camera: str,
allowed_cameras: list[str],
) -> Optional[str]:
) -> str | None:
"""
Fetch the current live frame for a camera as a base64 data URL.
@ -801,7 +801,7 @@ async def _execute_start_camera_watch(
zones=zones,
)
except RuntimeError as e:
logger.error("Failed to start VLM watch job: %s", e, exc_info=True)
logger.exception("Failed to start VLM watch job: %s", e)
return {"error": "Failed to start VLM watch job."}
return {
@ -979,7 +979,7 @@ def _execute_get_recap(
return {"events": events}
except Exception as e:
logger.error("Error executing get_recap: %s", e, exc_info=True)
logger.exception("Error executing get_recap: %s", e)
return {"error": "Failed to fetch recap data."}
@ -1072,13 +1072,12 @@ async def _execute_pending_tools(
}
)
except Exception as e:
logger.error(
logger.exception(
"Error executing tool %s (id: %s): %s. Arguments: %s",
tool_name,
tool_call_id,
e,
json.dumps(tool_args),
exc_info=True,
)
error_content = json.dumps({"error": f"Tool execution failed: {str(e)}"})
tool_calls_out.append(
@ -1186,7 +1185,7 @@ async def chat_completion(
async def stream_body_llm():
nonlocal conversation, stream_iterations
def _emit_chain(extra: Optional[list[dict[str, Any]]] = None):
def _emit_chain(extra: list[dict[str, Any]] | None = None):
# Return the full conversation (including the system message) so
# the client persists and replays it verbatim next turn.
chain = conversation + (extra or [])
@ -1414,7 +1413,7 @@ async def chat_completion(
)
except Exception as e:
logger.error(f"Error in chat completion: {e}", exc_info=True)
logger.exception(f"Error in chat completion: {e}")
return JSONResponse(
content={
"error": "An error occurred while processing your request.",
@ -1477,7 +1476,7 @@ async def start_vlm_monitor(
username=request.headers.get("remote-user", ""),
)
except RuntimeError as e:
logger.error("Failed to start VLM watch job: %s", e, exc_info=True)
logger.exception("Failed to start VLM watch job: %s", e)
return JSONResponse(
content={"success": False, "message": "Failed to start VLM watch job."},
status_code=409,

21
frigate/api/chat_util.py
View File

@ -9,8 +9,9 @@ loop state — all inputs and outputs are plain data.
import logging
import math
import time
from collections.abc import Generator
from datetime import datetime
from typing import Any, Dict, Generator, List, Optional
from typing import Any
from frigate.embeddings.util import ZScoreNormalization
from frigate.models import Event
@ -30,7 +31,7 @@ def chunk_content(content: str, chunk_size: int = 80) -> Generator[str, None, No
if not content:
return
words = content.split(" ")
current: List[str] = []
current: list[str] = []
current_len = 0
for w in words:
current.append(w)
@ -44,8 +45,8 @@ def chunk_content(content: str, chunk_size: int = 80) -> Generator[str, None, No
def format_events_with_local_time(
events_list: List[Dict[str, Any]],
) -> List[Dict[str, Any]]:
events_list: list[dict[str, Any]],
) -> list[dict[str, Any]]:
"""Add human-readable local start/end times to each event for the LLM."""
result = []
for evt in events_list:
@ -84,9 +85,9 @@ def distance_to_score(distance: float, stats: ZScoreNormalization) -> float:
def fuse_scores(
visual_score: Optional[float],
description_score: Optional[float],
) -> Optional[float]:
visual_score: float | None,
description_score: float | None,
) -> float | None:
"""Weighted fusion of visual and description similarity scores.
If one side is missing (e.g., no description embedding for this event),
@ -102,7 +103,7 @@ def fuse_scores(
return VISUAL_WEIGHT * visual_score + DESCRIPTION_WEIGHT * description_score
def parse_iso_to_timestamp(value: Optional[str]) -> Optional[float]:
def parse_iso_to_timestamp(value: str | None) -> float | None:
"""Parse an ISO-8601 string as server-local time -> unix timestamp.
Mirrors the parsing _execute_search_objects uses so both tools accept the
@ -119,9 +120,9 @@ def parse_iso_to_timestamp(value: Optional[str]) -> Optional[float]:
return None
def hydrate_event(event: Event, score: Optional[float] = None) -> Dict[str, Any]:
def hydrate_event(event: Event, score: float | None = None) -> dict[str, Any]:
"""Convert an Event row into the dict shape returned by find_similar_objects."""
data: Dict[str, Any] = {
data: dict[str, Any] = {
"id": event.id,
"camera": event.camera,
"label": event.label,

14
frigate/api/defs/query/app_query_parameters.py
View File

@ -1,12 +1,10 @@
from typing import Optional
from pydantic import BaseModel
class AppTimelineHourlyQueryParameters(BaseModel):
cameras: Optional[str] = "all"
labels: Optional[str] = "all"
after: Optional[float] = None
before: Optional[float] = None
limit: Optional[int] = 200
timezone: Optional[str] = "utc"
cameras: str | None = "all"
labels: str | None = "all"
after: float | None = None
before: float | None = None
limit: int | None = 200
timezone: str | None = "utc"

112
frigate/api/defs/query/events_query_parameters.py
View File

@ -1,28 +1,26 @@
from typing import Optional
from pydantic import BaseModel, Field
DEFAULT_TIME_RANGE = "00:00,24:00"
class EventsQueryParams(BaseModel):
camera: Optional[str] = "all"
cameras: Optional[str] = "all"
label: Optional[str] = "all"
labels: Optional[str] = "all"
sub_label: Optional[str] = "all"
sub_labels: Optional[str] = "all"
attributes: Optional[str] = "all"
zone: Optional[str] = "all"
zones: Optional[str] = "all"
limit: Optional[int] = 100
after: Optional[float] = None
before: Optional[float] = None
time_range: Optional[str] = DEFAULT_TIME_RANGE
has_clip: Optional[int] = None
has_snapshot: Optional[int] = None
in_progress: Optional[int] = None
include_thumbnails: Optional[int] = Field(
camera: str | None = "all"
cameras: str | None = "all"
label: str | None = "all"
labels: str | None = "all"
sub_label: str | None = "all"
sub_labels: str | None = "all"
attributes: str | None = "all"
zone: str | None = "all"
zones: str | None = "all"
limit: int | None = 100
after: float | None = None
before: float | None = None
time_range: str | None = DEFAULT_TIME_RANGE
has_clip: int | None = None
has_snapshot: int | None = None
in_progress: int | None = None
include_thumbnails: int | None = Field(
1,
description=(
"Deprecated. Thumbnail data is no longer included in the response. "
@ -30,25 +28,25 @@ class EventsQueryParams(BaseModel):
),
deprecated=True,
)
favorites: Optional[int] = None
min_score: Optional[float] = None
max_score: Optional[float] = None
min_speed: Optional[float] = None
max_speed: Optional[float] = None
recognized_license_plate: Optional[str] = "all"
is_submitted: Optional[int] = None
min_length: Optional[float] = None
max_length: Optional[float] = None
event_id: Optional[str] = None
sort: Optional[str] = None
timezone: Optional[str] = "utc"
favorites: int | None = None
min_score: float | None = None
max_score: float | None = None
min_speed: float | None = None
max_speed: float | None = None
recognized_license_plate: str | None = "all"
is_submitted: int | None = None
min_length: float | None = None
max_length: float | None = None
event_id: str | None = None
sort: str | None = None
timezone: str | None = "utc"
class EventsSearchQueryParams(BaseModel):
query: Optional[str] = None
event_id: Optional[str] = None
search_type: Optional[str] = "thumbnail"
include_thumbnails: Optional[int] = Field(
query: str | None = None
event_id: str | None = None
search_type: str | None = "thumbnail"
include_thumbnails: int | None = Field(
1,
description=(
"Deprecated. Thumbnail data is no longer included in the response. "
@ -56,28 +54,28 @@ class EventsSearchQueryParams(BaseModel):
),
deprecated=True,
)
limit: Optional[int] = 50
cameras: Optional[str] = "all"
labels: Optional[str] = "all"
sub_labels: Optional[str] = "all"
attributes: Optional[str] = "all"
zones: Optional[str] = "all"
after: Optional[float] = None
before: Optional[float] = None
time_range: Optional[str] = DEFAULT_TIME_RANGE
has_clip: Optional[bool] = None
has_snapshot: Optional[bool] = None
is_submitted: Optional[bool] = None
timezone: Optional[str] = "utc"
min_score: Optional[float] = None
max_score: Optional[float] = None
min_speed: Optional[float] = None
max_speed: Optional[float] = None
recognized_license_plate: Optional[str] = "all"
sort: Optional[str] = None
limit: int | None = 50
cameras: str | None = "all"
labels: str | None = "all"
sub_labels: str | None = "all"
attributes: str | None = "all"
zones: str | None = "all"
after: float | None = None
before: float | None = None
time_range: str | None = DEFAULT_TIME_RANGE
has_clip: bool | None = None
has_snapshot: bool | None = None
is_submitted: bool | None = None
timezone: str | None = "utc"
min_score: float | None = None
max_score: float | None = None
min_speed: float | None = None
max_speed: float | None = None
recognized_license_plate: str | None = "all"
sort: str | None = None
class EventsSummaryQueryParams(BaseModel):
timezone: Optional[str] = "utc"
has_clip: Optional[int] = None
has_snapshot: Optional[int] = None
timezone: str | None = "utc"
has_clip: int | None = None
has_snapshot: int | None = None

45
frigate/api/defs/query/media_query_parameters.py
View File

@ -1,5 +1,4 @@
from enum import Enum
from typing import Optional
from pydantic import BaseModel
@ -17,33 +16,33 @@ class Extension(str, Enum):
class MediaLatestFrameQueryParams(BaseModel):
bbox: Optional[int] = None
timestamp: Optional[int] = None
zones: Optional[int] = None
mask: Optional[int] = None
motion: Optional[int] = None
paths: Optional[int] = None
regions: Optional[int] = None
quality: Optional[int] = 70
height: Optional[int] = None
store: Optional[int] = None
bbox: int | None = None
timestamp: int | None = None
zones: int | None = None
mask: int | None = None
motion: int | None = None
paths: int | None = None
regions: int | None = None
quality: int | None = 70
height: int | None = None
store: int | None = None
class MediaEventsSnapshotQueryParams(BaseModel):
download: Optional[bool] = False
timestamp: Optional[int] = None
bbox: Optional[int] = None
crop: Optional[int] = None
height: Optional[int] = None
quality: Optional[int] = None
download: bool | None = False
timestamp: int | None = None
bbox: int | None = None
crop: int | None = None
height: int | None = None
quality: int | None = None
class MediaMjpegFeedQueryParams(BaseModel):
fps: int = 3
height: int = 360
bbox: Optional[int] = None
timestamp: Optional[int] = None
zones: Optional[int] = None
mask: Optional[int] = None
motion: Optional[int] = None
regions: Optional[int] = None
bbox: int | None = None
timestamp: int | None = None
zones: int | None = None
mask: int | None = None
motion: int | None = None
regions: int | None = None

12
frigate/api/defs/query/recordings_query_parameters.py
View File

@ -1,21 +1,19 @@
from typing import Optional, Union
from pydantic import BaseModel
from pydantic.json_schema import SkipJsonSchema
class MediaRecordingsSummaryQueryParams(BaseModel):
timezone: str = "utc"
cameras: Optional[str] = "all"
cameras: str | None = "all"
class MediaRecordingsAvailabilityQueryParams(BaseModel):
cameras: str = "all"
before: Union[float, SkipJsonSchema[None]] = None
after: Union[float, SkipJsonSchema[None]] = None
before: float | SkipJsonSchema[None] = None
after: float | SkipJsonSchema[None] = None
scale: int = 30
class RecordingsDeleteQueryParams(BaseModel):
keep: Optional[str] = None
cameras: Optional[str] = "all"
keep: str | None = None
cameras: str | None = "all"

6
frigate/api/defs/query/regenerate_query_parameters.py
View File

@ -1,13 +1,11 @@
from typing import Optional
from pydantic import BaseModel, Field
from frigate.events.types import RegenerateDescriptionEnum
class RegenerateQueryParameters(BaseModel):
source: Optional[RegenerateDescriptionEnum] = RegenerateDescriptionEnum.thumbnails
force: Optional[bool] = Field(
source: RegenerateDescriptionEnum | None = RegenerateDescriptionEnum.thumbnails
force: bool | None = Field(
default=False,
description="Force (re)generating the description even if GenAI is disabled for this camera.",
)

16
frigate/api/defs/query/review_query_parameters.py
View File

@ -1,5 +1,3 @@
from typing import Union
from pydantic import BaseModel
from pydantic.json_schema import SkipJsonSchema
@ -10,11 +8,11 @@ class ReviewQueryParams(BaseModel):
cameras: str = "all"
labels: str = "all"
zones: str = "all"
reviewed: Union[int, SkipJsonSchema[None]] = None
limit: Union[int, SkipJsonSchema[None]] = None
severity: Union[SeverityEnum, SkipJsonSchema[None]] = None
before: Union[float, SkipJsonSchema[None]] = None
after: Union[float, SkipJsonSchema[None]] = None
reviewed: int | SkipJsonSchema[None] = None
limit: int | SkipJsonSchema[None] = None
severity: SeverityEnum | SkipJsonSchema[None] = None
before: float | SkipJsonSchema[None] = None
after: float | SkipJsonSchema[None] = None
class ReviewSummaryQueryParams(BaseModel):
@ -26,6 +24,6 @@ class ReviewSummaryQueryParams(BaseModel):
class ReviewActivityMotionQueryParams(BaseModel):
cameras: str = "all"
before: Union[float, SkipJsonSchema[None]] = None
after: Union[float, SkipJsonSchema[None]] = None
before: float | SkipJsonSchema[None] = None
after: float | SkipJsonSchema[None] = None
scale: int = 30

16
frigate/api/defs/request/app_body.py
View File

@ -1,4 +1,4 @@
from typing import Any, Dict, List, Optional
from typing import Any
from pydantic import BaseModel, Field
@ -8,26 +8,26 @@ from frigate.config import GenAIProviderEnum
class AppConfigSetBody(BaseModel):
requires_restart: int = 1
update_topic: str | None = None
config_data: Optional[Dict[str, Any]] = None
config_data: dict[str, Any] | None = None
skip_save: bool = False
class GenAIProbeBody(BaseModel):
provider: GenAIProviderEnum
api_key: Optional[str] = None
base_url: Optional[str] = None
provider_options: Dict[str, Any] = Field(default_factory=dict)
api_key: str | None = None
base_url: str | None = None
provider_options: dict[str, Any] = Field(default_factory=dict)
class AppPutPasswordBody(BaseModel):
password: str
old_password: Optional[str] = None
old_password: str | None = None
class AppPostUsersBody(BaseModel):
username: str
password: str
role: Optional[str] = "viewer"
role: str | None = "viewer"
class AppPostLoginBody(BaseModel):
@ -47,7 +47,7 @@ class MediaSyncBody(BaseModel):
dry_run: bool = Field(
default=True, description="If True, only report orphans without deleting them"
)
media_types: List[str] = Field(
media_types: list[str] = Field(
default=["all"],
description="Types of media to sync: 'all', 'event_snapshots', 'event_thumbnails', 'review_thumbnails', 'previews', 'exports', 'recordings'",
)

16
frigate/api/defs/request/batch_export_body.py
View File

@ -1,5 +1,3 @@
from typing import List, Optional
from pydantic import BaseModel, Field, model_validator
MAX_BATCH_EXPORT_ITEMS = 50
@ -9,18 +7,18 @@ class BatchExportItem(BaseModel):
camera: str = Field(title="Camera name")
start_time: float = Field(title="Start time")
end_time: float = Field(title="End time")
image_path: Optional[str] = Field(
image_path: str | None = Field(
default=None,
title="Existing thumbnail path",
description="Optional existing image to use as the export thumbnail",
)
friendly_name: Optional[str] = Field(
friendly_name: str | None = Field(
default=None,
title="Friendly name",
max_length=256,
description="Optional friendly name for this specific export item",
)
client_item_id: Optional[str] = Field(
client_item_id: str | None = Field(
default=None,
title="Client item ID",
max_length=128,
@ -29,13 +27,13 @@ class BatchExportItem(BaseModel):
class BatchExportBody(BaseModel):
items: List[BatchExportItem] = Field(
items: list[BatchExportItem] = Field(
title="Items",
min_length=1,
max_length=MAX_BATCH_EXPORT_ITEMS,
description="List of export items. Each item has its own camera and time range.",
)
export_case_id: Optional[str] = Field(
export_case_id: str | None = Field(
default=None,
title="Export case ID",
max_length=30,
@ -44,13 +42,13 @@ class BatchExportBody(BaseModel):
"existing case is temporarily admin-only until case-level ACLs exist."
),
)
new_case_name: Optional[str] = Field(
new_case_name: str | None = Field(
default=None,
title="New case name",
max_length=100,
description="Name of a new export case to create when export_case_id is omitted",
)
new_case_description: Optional[str] = Field(
new_case_description: str | None = Field(
default=None,
title="New case description",
description="Optional description for a newly created export case",

12
frigate/api/defs/request/chat_body.py
View File

@ -1,6 +1,6 @@
"""Chat API request models."""
from typing import Any, Optional
from typing import Any
from pydantic import BaseModel, Field
@ -11,7 +11,7 @@ class ChatMessage(BaseModel):
role: str = Field(
description="Message role: 'user', 'assistant', 'system', or 'tool'"
)
content: Optional[Any] = Field(
content: Any | None = Field(
default=None,
description=(
"Message content. Usually a string, but may be a multimodal content "
@ -19,13 +19,13 @@ class ChatMessage(BaseModel):
"request tool calls."
),
)
tool_call_id: Optional[str] = Field(
tool_call_id: str | None = Field(
default=None, description="For tool messages, the ID of the tool call"
)
name: Optional[str] = Field(
name: str | None = Field(
default=None, description="For tool messages, the tool name"
)
tool_calls: Optional[list[dict[str, Any]]] = Field(
tool_calls: list[dict[str, Any]] | None = Field(
default=None,
description=(
"For assistant messages replayed from prior turns, the OpenAI-format "
@ -52,7 +52,7 @@ class ChatCompletionRequest(BaseModel):
default=False,
description="If true, stream the final assistant response in the body as newline-delimited JSON.",
)
enable_thinking: Optional[bool] = Field(
enable_thinking: bool | None = Field(
default=None,
description=(
"Per-request thinking toggle. None means use the provider default. "

6
frigate/api/defs/request/classification_body.py
View File

@ -1,5 +1,3 @@
from typing import Dict, List, Tuple
from pydantic import BaseModel, Field
@ -12,14 +10,14 @@ class AudioTranscriptionBody(BaseModel):
class DeleteFaceImagesBody(BaseModel):
ids: List[str] = Field(
ids: list[str] = Field(
description="List of image filenames to delete from the face folder"
)
class GenerateStateExamplesBody(BaseModel):
model_name: str = Field(description="Name of the classification model")
cameras: Dict[str, Tuple[float, float, float, float]] = Field(
cameras: dict[str, tuple[float, float, float, float]] = Field(
description="Dictionary mapping camera names to normalized crop coordinates in [x1, y1, x2, y2] format (values 0-1)"
)

30
frigate/api/defs/request/events_body.py
View File

@ -1,5 +1,3 @@
from typing import List, Optional, Union
from pydantic import BaseModel, Field
from frigate.config.classification import TriggerType
@ -7,49 +5,47 @@ from frigate.config.classification import TriggerType
class EventsSubLabelBody(BaseModel):
subLabel: str = Field(title="Sub label", max_length=100)
subLabelScore: Optional[float] = Field(
subLabelScore: float | None = Field(
title="Score for sub label", default=None, gt=0.0, le=1.0
)
camera: Optional[str] = Field(
title="Camera this object is detected on.", default=None
)
camera: str | None = Field(title="Camera this object is detected on.", default=None)
class EventsLPRBody(BaseModel):
recognizedLicensePlate: str = Field(
title="Recognized License Plate", max_length=100
)
recognizedLicensePlateScore: Optional[float] = Field(
recognizedLicensePlateScore: float | None = Field(
title="Score for recognized license plate", default=None, gt=0.0, le=1.0
)
class EventsAttributesBody(BaseModel):
attributes: List[str] = Field(
attributes: list[str] = Field(
title="Selected classification attributes for the event",
default_factory=list,
)
class EventsDescriptionBody(BaseModel):
description: Union[str, None] = Field(title="The description of the event")
description: str | None = Field(title="The description of the event")
class EventsCreateBody(BaseModel):
sub_label: Optional[str] = None
score: Optional[float] = 0
duration: Optional[int] = 30
include_recording: Optional[bool] = True
draw: Optional[dict] = {}
pre_capture: Optional[int] = None
sub_label: str | None = None
score: float | None = 0
duration: int | None = 30
include_recording: bool | None = True
draw: dict | None = {}
pre_capture: int | None = None
class EventsEndBody(BaseModel):
end_time: Optional[float] = None
end_time: float | None = None
class EventsDeleteBody(BaseModel):
event_ids: List[str] = Field(title="The event IDs to delete")
event_ids: list[str] = Field(title="The event IDs to delete")
class SubmitPlusBody(BaseModel):

4
frigate/api/defs/request/export_bulk_body.py
View File

@ -1,7 +1,5 @@
"""Request bodies for bulk export operations."""
from typing import Optional
from pydantic import BaseModel, Field, conlist, constr
@ -17,7 +15,7 @@ class ExportBulkReassignBody(BaseModel):
# List of export IDs with at least one element and each element with at least one char
ids: conlist(constr(min_length=1), min_length=1)
export_case_id: Optional[str] = Field(
export_case_id: str | None = Field(
default=None,
max_length=30,
description="Case ID to assign to, or null to unassign from current case",

8
frigate/api/defs/request/export_case_body.py
View File

@ -1,5 +1,3 @@
from typing import Optional
from pydantic import BaseModel, Field
@ -7,7 +5,7 @@ class ExportCaseCreateBody(BaseModel):
"""Request body for creating a new export case."""
name: str = Field(max_length=100, description="Friendly name of the export case")
description: Optional[str] = Field(
description: str | None = Field(
default=None, description="Optional description of the export case"
)
@ -15,11 +13,11 @@ class ExportCaseCreateBody(BaseModel):
class ExportCaseUpdateBody(BaseModel):
"""Request body for updating an existing export case."""
name: Optional[str] = Field(
name: str | None = Field(
default=None,
max_length=100,
description="Updated friendly name of the export case",
)
description: Optional[str] = Field(
description: str | None = Field(
default=None, description="Updated description of the export case"
)

18
frigate/api/defs/request/export_recordings_body.py
View File

@ -1,5 +1,3 @@
from typing import Optional, Union
from pydantic import BaseModel, Field
from pydantic.json_schema import SkipJsonSchema
@ -13,15 +11,15 @@ class ExportRecordingsBody(BaseModel):
source: PlaybackSourceEnum = Field(
default=PlaybackSourceEnum.recordings, title="Playback source"
)
name: Optional[str] = Field(title="Friendly name", default=None, max_length=256)
image_path: Union[str, SkipJsonSchema[None]] = None
export_case_id: Optional[str] = Field(
name: str | None = Field(title="Friendly name", default=None, max_length=256)
image_path: str | SkipJsonSchema[None] = None
export_case_id: str | None = Field(
default=None,
title="Export case ID",
max_length=30,
description="ID of the export case to assign this export to",
)
chapters: Optional[ChaptersEnum] = Field(
chapters: ChaptersEnum | None = Field(
default=None,
title="Chapter mode",
description=(
@ -36,19 +34,19 @@ class ExportRecordingsCustomBody(BaseModel):
default=PlaybackSourceEnum.recordings, title="Playback source"
)
name: str = Field(title="Friendly name", default=None, max_length=256)
image_path: Union[str, SkipJsonSchema[None]] = None
export_case_id: Optional[str] = Field(
image_path: str | SkipJsonSchema[None] = None
export_case_id: str | None = Field(
default=None,
title="Export case ID",
max_length=30,
description="ID of the export case to assign this export to",
)
ffmpeg_input_args: Optional[str] = Field(
ffmpeg_input_args: str | None = Field(
default=None,
title="FFmpeg input arguments",
description="Custom FFmpeg input arguments. If not provided, defaults to timelapse input args.",
)
ffmpeg_output_args: Optional[str] = Field(
ffmpeg_output_args: str | None = Field(
default=None,
title="FFmpeg output arguments",
description="Custom FFmpeg output arguments. If not provided, defaults to timelapse output args.",

8
frigate/api/defs/response/chat_response.py
View File

@ -1,6 +1,6 @@
"""Chat API response models."""
from typing import Any, Optional
from typing import Any
from pydantic import BaseModel, Field
@ -17,14 +17,14 @@ class ChatMessageResponse(BaseModel):
"""A message in the chat response."""
role: str = Field(description="Message role")
content: Optional[str] = Field(
content: str | None = Field(
default=None, description="Message content (None if tool calls present)"
)
reasoning: Optional[str] = Field(
reasoning: str | None = Field(
default=None,
description="Separated reasoning/thinking trace if the model emitted one",
)
tool_calls: Optional[list[ToolCallInvocation]] = Field(
tool_calls: list[ToolCallInvocation] | None = Field(
default=None, description="Tool calls if LLM wants to call tools"
)

10
frigate/api/defs/response/classification_response.py
View File

@ -1,9 +1,7 @@
from typing import Dict, List, Optional
from pydantic import BaseModel, Field, RootModel
class FacesResponse(RootModel[Dict[str, List[str]]]):
class FacesResponse(RootModel[dict[str, list[str]]]):
"""Response model for the get_faces endpoint.
Returns a mapping of face names to lists of image filenames.
@ -17,7 +15,7 @@ class FacesResponse(RootModel[Dict[str, List[str]]]):
}
"""
root: Dict[str, List[str]] = Field(
root: dict[str, list[str]] = Field(
default_factory=dict,
description="Dictionary mapping face names to lists of image filenames",
)
@ -30,9 +28,9 @@ class FaceRecognitionResponse(BaseModel):
"""
success: bool = Field(description="Whether the face recognition was successful")
score: Optional[float] = Field(
score: float | None = Field(
default=None, description="Confidence score of the recognition (0-1)"
)
face_name: Optional[str] = Field(
face_name: str | None = Field(
default=None, description="The recognized face name if successful"
)

18
frigate/api/defs/response/event_response.py
View File

@ -1,4 +1,4 @@
from typing import Any, Optional
from typing import Any
from pydantic import BaseModel, ConfigDict
@ -6,20 +6,20 @@ from pydantic import BaseModel, ConfigDict
class EventResponse(BaseModel):
id: str
label: str
sub_label: Optional[str]
sub_label: str | None
camera: str
start_time: float
end_time: Optional[float]
false_positive: Optional[bool]
end_time: float | None
false_positive: bool | None
zones: list[str]
thumbnail: Optional[str]
thumbnail: str | None
has_clip: bool
has_snapshot: bool
retain_indefinitely: bool
plus_id: Optional[str]
model_hash: Optional[str]
detector_type: Optional[str]
model_type: Optional[str]
plus_id: str | None
model_hash: str | None
detector_type: str | None
model_type: str | None
data: dict[str, Any]
model_config = ConfigDict(protected_namespaces=())

6
frigate/api/defs/response/export_case_response.py
View File

@ -1,5 +1,3 @@
from typing import List, Optional
from pydantic import BaseModel, Field
@ -8,7 +6,7 @@ class ExportCaseModel(BaseModel):
id: str = Field(description="Unique identifier for the export case")
name: str = Field(description="Friendly name of the export case")
description: Optional[str] = Field(
description: str | None = Field(
default=None, description="Optional description of the export case"
)
created_at: float = Field(
@ -19,4 +17,4 @@ class ExportCaseModel(BaseModel):
)
ExportCasesResponse = List[ExportCaseModel]
ExportCasesResponse = list[ExportCaseModel]

40
frigate/api/defs/response/export_response.py
View File

@ -1,4 +1,4 @@
from typing import Any, List, Optional
from typing import Any
from pydantic import BaseModel, Field
@ -15,7 +15,7 @@ class ExportModel(BaseModel):
in_progress: bool = Field(
description="Whether the export is currently being processed"
)
export_case_id: Optional[str] = Field(
export_case_id: str | None = Field(
default=None, description="ID of the export case this export belongs to"
)
@ -25,10 +25,10 @@ class StartExportResponse(BaseModel):
success: bool = Field(description="Whether the export was started successfully")
message: str = Field(description="Status or error message")
export_id: Optional[str] = Field(
export_id: str | None = Field(
default=None, description="The export ID if successfully started"
)
status: Optional[str] = Field(
status: str | None = Field(
default=None,
description="Queue status for the export job",
)
@ -38,24 +38,24 @@ class BatchExportResultModel(BaseModel):
"""Per-item result for a batch export request."""
camera: str = Field(description="Camera name for this export attempt")
export_id: Optional[str] = Field(
export_id: str | None = Field(
default=None,
description="The export ID when the export was successfully queued",
)
success: bool = Field(description="Whether the export was successfully queued")
status: Optional[str] = Field(
status: str | None = Field(
default=None,
description="Queue status for this camera export",
)
error: Optional[str] = Field(
error: str | None = Field(
default=None,
description="Validation or queueing error for this item, if any",
)
item_index: Optional[int] = Field(
item_index: int | None = Field(
default=None,
description="Zero-based index of this result within the request items list",
)
client_item_id: Optional[str] = Field(
client_item_id: str | None = Field(
default=None,
description="Opaque client-supplied item identifier echoed from the request",
)
@ -64,12 +64,12 @@ class BatchExportResultModel(BaseModel):
class BatchExportResponse(BaseModel):
"""Response model for starting an export batch."""
export_case_id: Optional[str] = Field(
export_case_id: str | None = Field(
default=None,
description="Export case ID associated with the batch",
)
export_ids: List[str] = Field(description="Export IDs successfully queued")
results: List[BatchExportResultModel] = Field(
export_ids: list[str] = Field(description="Export IDs successfully queued")
results: list[BatchExportResultModel] = Field(
description="Per-item batch export results"
)
@ -81,29 +81,29 @@ class ExportJobModel(BaseModel):
job_type: str = Field(description="Job type")
status: str = Field(description="Current job status")
camera: str = Field(description="Camera associated with this export job")
name: Optional[str] = Field(
name: str | None = Field(
default=None,
description="Friendly name for the export",
)
export_case_id: Optional[str] = Field(
export_case_id: str | None = Field(
default=None,
description="ID of the export case this export belongs to",
)
request_start_time: float = Field(description="Requested export start time")
request_end_time: float = Field(description="Requested export end time")
start_time: Optional[float] = Field(
start_time: float | None = Field(
default=None,
description="Unix timestamp when execution started",
)
end_time: Optional[float] = Field(
end_time: float | None = Field(
default=None,
description="Unix timestamp when execution completed",
)
error_message: Optional[str] = Field(
error_message: str | None = Field(
default=None,
description="Error message for failed jobs",
)
results: Optional[dict[str, Any]] = Field(
results: dict[str, Any] | None = Field(
default=None,
description="Result metadata for completed jobs",
)
@ -117,7 +117,7 @@ class ExportJobModel(BaseModel):
)
ExportJobsResponse = List[ExportJobModel]
ExportJobsResponse = list[ExportJobModel]
ExportsResponse = List[ExportModel]
ExportsResponse = list[ExportModel]

6
frigate/api/defs/response/preview_response.py
View File

@ -1,5 +1,3 @@
from typing import List
from pydantic import BaseModel, Field
@ -13,5 +11,5 @@ class PreviewModel(BaseModel):
end: float = Field(description="Unix timestamp when the preview ends")
PreviewsResponse = List[PreviewModel]
PreviewFramesResponse = List[str]
PreviewsResponse = list[PreviewModel]
PreviewFramesResponse = list[str]

3
frigate/api/defs/response/review_response.py
View File

@ -1,5 +1,4 @@
from datetime import datetime
from typing import Dict
from pydantic import BaseModel, Json
@ -34,7 +33,7 @@ class DayReview(BaseModel):
class ReviewSummaryResponse(BaseModel):
last24Hours: Last24HoursReview
root: Dict[str, DayReview]
root: dict[str, DayReview]
class ReviewActivityMotionResponse(BaseModel):

141
frigate/api/event.py
View File

@ -10,7 +10,6 @@ import random
import string
from functools import reduce
from pathlib import Path
from typing import List
from urllib.parse import unquote
import numpy as np
@ -97,7 +96,7 @@ def _build_attribute_filter_clause(attributes: str):
)
def events(
params: EventsQueryParams = Depends(),
allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
):
camera = params.camera
cameras = params.cameras
@ -171,7 +170,7 @@ def events(
]
if camera != "all":
clauses.append((Event.camera == camera))
clauses.append(Event.camera == camera)
if cameras != "all":
requested = set(cameras.split(","))
@ -181,11 +180,11 @@ def events(
camera_list = list(filtered)
else:
camera_list = allowed_cameras
clauses.append((Event.camera << camera_list))
clauses.append(Event.camera << camera_list)
if labels != "all":
label_list = labels.split(",")
clauses.append((Event.label << label_list))
clauses.append(Event.label << label_list)
if sub_labels != "all":
# use matching so joined sub labels are included
@ -196,24 +195,24 @@ def events(
if "None" in filtered_sub_labels:
filtered_sub_labels.remove("None")
sub_label_clauses.append((Event.sub_label.is_null()))
sub_label_clauses.append(Event.sub_label.is_null())
for label in filtered_sub_labels:
lowered = label.lower()
sub_label_clauses.append(
(fn.LOWER(Event.sub_label.cast("text")) == lowered)
fn.LOWER(Event.sub_label.cast("text")) == lowered
) # include exact matches (case-insensitive)
# include this label when part of a list (LIKE is case-insensitive in sqlite for ASCII)
sub_label_clauses.append(
(fn.LOWER(Event.sub_label.cast("text")) % f"*{lowered},*")
fn.LOWER(Event.sub_label.cast("text")) % f"*{lowered},*"
)
sub_label_clauses.append(
(fn.LOWER(Event.sub_label.cast("text")) % f"*, {lowered}*")
fn.LOWER(Event.sub_label.cast("text")) % f"*, {lowered}*"
)
sub_label_clause = reduce(operator.or_, sub_label_clauses)
clauses.append((sub_label_clause))
clauses.append(sub_label_clause)
if attributes != "all":
# Custom classification results are stored as data[model_name] = result_value
@ -257,19 +256,19 @@ def events(
if "None" in filtered_zones:
filtered_zones.remove("None")
zone_clauses.append((Event.zones.length() == 0))
zone_clauses.append(Event.zones.length() == 0)
for zone in filtered_zones:
zone_clauses.append((Event.zones.cast("text") % f'*"{zone}"*'))
zone_clauses.append(Event.zones.cast("text") % f'*"{zone}"*')
zone_clause = reduce(operator.or_, zone_clauses)
clauses.append((zone_clause))
clauses.append(zone_clause)
if after:
clauses.append((Event.start_time > after))
clauses.append(Event.start_time > after)
if before:
clauses.append((Event.start_time < before))
clauses.append(Event.start_time < before)
if time_range != DEFAULT_TIME_RANGE:
# get timezone arg to ensure browser times are used
@ -289,62 +288,60 @@ def events(
# should use or operator
if time_after > time_before:
clauses.append(
(
reduce(
operator.or_,
[(start_hour_fun > time_after), (start_hour_fun < time_before)],
)
reduce(
operator.or_,
[(start_hour_fun > time_after), (start_hour_fun < time_before)],
)
)
# all other cases should be and operator
else:
clauses.append((start_hour_fun > time_after))
clauses.append((start_hour_fun < time_before))
clauses.append(start_hour_fun > time_after)
clauses.append(start_hour_fun < time_before)
if has_clip is not None:
clauses.append((Event.has_clip == has_clip))
clauses.append(Event.has_clip == has_clip)
if has_snapshot is not None:
clauses.append((Event.has_snapshot == has_snapshot))
clauses.append(Event.has_snapshot == has_snapshot)
if in_progress is not None:
clauses.append((Event.end_time.is_null(in_progress)))
clauses.append(Event.end_time.is_null(in_progress))
if include_thumbnails:
selected_columns.append(Event.thumbnail)
if favorites:
clauses.append((Event.retain_indefinitely == favorites))
clauses.append(Event.retain_indefinitely == favorites)
if max_score is not None:
clauses.append((Event.data["score"] <= max_score))
clauses.append(Event.data["score"] <= max_score)
if min_score is not None:
clauses.append((Event.data["score"] >= min_score))
clauses.append(Event.data["score"] >= min_score)
if max_speed is not None:
clauses.append((Event.data["average_estimated_speed"] <= max_speed))
clauses.append(Event.data["average_estimated_speed"] <= max_speed)
if min_speed is not None:
clauses.append((Event.data["average_estimated_speed"] >= min_speed))
clauses.append(Event.data["average_estimated_speed"] >= min_speed)
if min_length is not None:
clauses.append(((Event.end_time - Event.start_time) >= min_length))
clauses.append((Event.end_time - Event.start_time) >= min_length)
if max_length is not None:
clauses.append(((Event.end_time - Event.start_time) <= max_length))
clauses.append((Event.end_time - Event.start_time) <= max_length)
if is_submitted is not None:
if is_submitted == 0:
clauses.append((Event.plus_id.is_null()))
clauses.append(Event.plus_id.is_null())
elif is_submitted > 0:
clauses.append((Event.plus_id != ""))
clauses.append(Event.plus_id != "")
if event_id is not None:
clauses.append((Event.id == event_id))
clauses.append(Event.id == event_id)
if len(clauses) == 0:
clauses.append((True))
clauses.append(True)
if sort:
if sort == "score_asc":
@ -387,7 +384,7 @@ def events(
)
def events_explore(
limit: int = 10,
allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
):
# get distinct labels for all events
distinct_labels = (
@ -515,7 +512,7 @@ async def event_ids(ids: str, request: Request):
def events_search(
request: Request,
params: EventsSearchQueryParams = Depends(),
allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
):
query = params.query
search_type = params.search_type
@ -595,12 +592,12 @@ def events_search(
filtered = requested.intersection(allowed_cameras)
if not filtered:
return JSONResponse(content=[])
event_filters.append((Event.camera << list(filtered)))
event_filters.append(Event.camera << list(filtered))
else:
event_filters.append((Event.camera << allowed_cameras))
event_filters.append(Event.camera << allowed_cameras)
if labels != "all":
event_filters.append((Event.label << labels.split(",")))
event_filters.append(Event.label << labels.split(","))
if sub_labels != "all":
# use matching so joined sub labels are included
@ -611,23 +608,23 @@ def events_search(
if "None" in filtered_sub_labels:
filtered_sub_labels.remove("None")
sub_label_clauses.append((Event.sub_label.is_null()))
sub_label_clauses.append(Event.sub_label.is_null())
for label in filtered_sub_labels:
lowered = label.lower()
sub_label_clauses.append(
(fn.LOWER(Event.sub_label.cast("text")) == lowered)
fn.LOWER(Event.sub_label.cast("text")) == lowered
) # include exact matches (case-insensitive)
# include this label when part of a list (LIKE is case-insensitive in sqlite for ASCII)
sub_label_clauses.append(
(fn.LOWER(Event.sub_label.cast("text")) % f"*{lowered},*")
fn.LOWER(Event.sub_label.cast("text")) % f"*{lowered},*"
)
sub_label_clauses.append(
(fn.LOWER(Event.sub_label.cast("text")) % f"*, {lowered}*")
fn.LOWER(Event.sub_label.cast("text")) % f"*, {lowered}*"
)
event_filters.append((reduce(operator.or_, sub_label_clauses)))
event_filters.append(reduce(operator.or_, sub_label_clauses))
if attributes != "all":
# Custom classification results are stored as data[model_name] = result_value
@ -641,12 +638,12 @@ def events_search(
if "None" in filtered_zones:
filtered_zones.remove("None")
zone_clauses.append((Event.zones.length() == 0))
zone_clauses.append(Event.zones.length() == 0)
for zone in filtered_zones:
zone_clauses.append((Event.zones.cast("text") % f'*"{zone}"*'))
zone_clauses.append(Event.zones.cast("text") % f'*"{zone}"*')
event_filters.append((reduce(operator.or_, zone_clauses)))
event_filters.append(reduce(operator.or_, zone_clauses))
if recognized_license_plate != "all":
filtered_recognized_license_plates = recognized_license_plate.split(",")
@ -674,43 +671,43 @@ def events_search(
)
recognized_license_plate_clause = reduce(operator.or_, clauses_for_plates)
event_filters.append((recognized_license_plate_clause))
event_filters.append(recognized_license_plate_clause)
if after:
event_filters.append((Event.start_time > after))
event_filters.append(Event.start_time > after)
if before:
event_filters.append((Event.start_time < before))
event_filters.append(Event.start_time < before)
if has_clip is not None:
event_filters.append((Event.has_clip == has_clip))
event_filters.append(Event.has_clip == has_clip)
if has_snapshot is not None:
event_filters.append((Event.has_snapshot == has_snapshot))
event_filters.append(Event.has_snapshot == has_snapshot)
if is_submitted is not None:
if is_submitted == 0:
event_filters.append((Event.plus_id.is_null()))
event_filters.append(Event.plus_id.is_null())
elif is_submitted > 0:
event_filters.append((Event.plus_id != ""))
event_filters.append(Event.plus_id != "")
if min_score is not None and max_score is not None:
event_filters.append((Event.data["score"].between(min_score, max_score)))
event_filters.append(Event.data["score"].between(min_score, max_score))
else:
if min_score is not None:
event_filters.append((Event.data["score"] >= min_score))
event_filters.append(Event.data["score"] >= min_score)
if max_score is not None:
event_filters.append((Event.data["score"] <= max_score))
event_filters.append(Event.data["score"] <= max_score)
if min_speed is not None and max_speed is not None:
event_filters.append(
(Event.data["average_estimated_speed"].between(min_speed, max_speed))
Event.data["average_estimated_speed"].between(min_speed, max_speed)
)
else:
if min_speed is not None:
event_filters.append((Event.data["average_estimated_speed"] >= min_speed))
event_filters.append(Event.data["average_estimated_speed"] >= min_speed)
if max_speed is not None:
event_filters.append((Event.data["average_estimated_speed"] <= max_speed))
event_filters.append(Event.data["average_estimated_speed"] <= max_speed)
if time_range != DEFAULT_TIME_RANGE:
tz_name = params.timezone
@ -728,17 +725,15 @@ def events_search(
# should use or operator
if time_after > time_before:
event_filters.append(
(
reduce(
operator.or_,
[(start_hour_fun > time_after), (start_hour_fun < time_before)],
)
reduce(
operator.or_,
[(start_hour_fun > time_after), (start_hour_fun < time_before)],
)
)
# all other cases should be and operator
else:
event_filters.append((start_hour_fun > time_after))
event_filters.append((start_hour_fun < time_before))
event_filters.append(start_hour_fun > time_after)
event_filters.append(start_hour_fun < time_before)
# Perform semantic search
search_results = {}
@ -894,7 +889,7 @@ def events_search(
@router.get("/events/summary", dependencies=[Depends(allow_any_authenticated())])
def events_summary(
params: EventsSummaryQueryParams = Depends(),
allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
):
tz_name = params.timezone
has_clip = params.has_clip
@ -903,13 +898,13 @@ def events_summary(
clauses = []
if has_clip is not None:
clauses.append((Event.has_clip == has_clip))
clauses.append(Event.has_clip == has_clip)
if has_snapshot is not None:
clauses.append((Event.has_snapshot == has_snapshot))
clauses.append(Event.has_snapshot == has_snapshot)
if len(clauses) == 0:
clauses.append((True))
clauses.append(True)
time_range_query = (
Event.select(

48
frigate/api/export.py
View File

@ -7,8 +7,8 @@ import string
import time
import zipfile
from collections import deque
from collections.abc import Iterator
from pathlib import Path
from typing import Iterator, List, Optional
import psutil
from fastapi import APIRouter, Depends, Query, Request
@ -89,7 +89,7 @@ def _generate_export_id(camera_name: str) -> str:
def _create_export_case_record(
name: str,
description: Optional[str],
description: str | None,
) -> ExportCase:
now = datetime.datetime.fromtimestamp(time.time())
return ExportCase.create(
@ -101,7 +101,7 @@ def _create_export_case_record(
)
def _validate_camera_name(request: Request, camera_name: str) -> Optional[JSONResponse]:
def _validate_camera_name(request: Request, camera_name: str) -> JSONResponse | None:
if camera_name and request.app.frigate_config.cameras.get(camera_name):
return None
@ -111,7 +111,7 @@ def _validate_camera_name(request: Request, camera_name: str) -> Optional[JSONRe
)
def _validate_export_case(export_case_id: Optional[str]) -> Optional[JSONResponse]:
def _validate_export_case(export_case_id: str | None) -> JSONResponse | None:
if export_case_id is None:
return None
@ -127,8 +127,8 @@ def _validate_export_case(export_case_id: Optional[str]) -> Optional[JSONRespons
def _sanitize_existing_image(
image_path: Optional[str],
) -> tuple[Optional[str], Optional[JSONResponse]]:
image_path: str | None,
) -> tuple[str | None, JSONResponse | None]:
# sanitize_filepath normalizes "\" to "/" but leaves ".." intact, so a path
# like "clips\..\..\etc/passwd" passes the CLIPS_DIR prefix check yet still
# escapes the directory once resolved. A valid snapshot path never uses "..".
@ -154,7 +154,7 @@ def _validate_export_source(
start_time: float,
end_time: float,
playback_source: PlaybackSourceEnum,
) -> Optional[str]:
) -> str | None:
if playback_source == PlaybackSourceEnum.recordings:
recordings_count = (
Recordings.select()
@ -257,14 +257,14 @@ def _build_export_job(
camera_name: str,
start_time: float,
end_time: float,
friendly_name: Optional[str],
existing_image: Optional[str],
friendly_name: str | None,
existing_image: str | None,
playback_source: PlaybackSourceEnum,
export_case_id: Optional[str],
ffmpeg_input_args: Optional[str] = None,
ffmpeg_output_args: Optional[str] = None,
export_case_id: str | None,
ffmpeg_input_args: str | None = None,
ffmpeg_output_args: str | None = None,
cpu_fallback: bool = False,
chapters: Optional[ChaptersEnum] = None,
chapters: ChaptersEnum | None = None,
) -> ExportJob:
return ExportJob(
id=_generate_export_id(camera_name),
@ -302,11 +302,11 @@ def _export_case_to_dict(case: ExportCase) -> dict[str, object]:
Returns a list of exports ordered by date (most recent first).""",
)
def get_exports(
allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
export_case_id: Optional[str] = None,
cameras: Optional[str] = Query(default="all"),
start_date: Optional[float] = None,
end_date: Optional[float] = None,
allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
export_case_id: str | None = None,
cameras: str | None = Query(default="all"),
start_date: float | None = None,
end_date: float | None = None,
):
query = Export.select().where(Export.camera << allowed_cameras)
@ -422,7 +422,7 @@ def _unique_archive_name(export: Export, used: set[str]) -> str:
return candidate
def _stream_case_archive(exports: List[Export]) -> Iterator[bytes]:
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()
@ -466,7 +466,7 @@ def _stream_case_archive(exports: List[Export]) -> Iterator[bytes]:
)
def download_export_case(
case_id: str,
allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
):
try:
case = ExportCase.get(ExportCase.id == case_id)
@ -580,7 +580,7 @@ def delete_export_case(case_id: str, request: Request, delete_exports: bool = Fa
)
def get_active_export_jobs(
request: Request,
allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
):
jobs = list_active_export_jobs(request.app.frigate_config)
return JSONResponse(
@ -622,7 +622,7 @@ async def get_export_job_status(export_id: str, request: Request):
def export_recordings_batch(
request: Request,
body: BatchExportBody,
allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
current_user: dict = Depends(get_current_user),
):
if isinstance(current_user, JSONResponse):
@ -662,7 +662,7 @@ def export_recordings_batch(
# Sanitize each item's image_path up front. A bad path in any item
# kills the whole request, consistent with single-export behavior.
sanitized_images: list[Optional[str]] = []
sanitized_images: list[str | None] = []
for item in body.items:
existing_image, image_validation_error = _sanitize_existing_image(
item.image_path
@ -713,7 +713,7 @@ def export_recordings_batch(
export_case_id = export_case.id
export_ids: list[str] = []
results: list[dict[str, Optional[str] | bool | int]] = []
results: list[dict[str, str | None | bool | int]] = []
for index, item in enumerate(body.items):
if index in item_errors:
results.append(

7
frigate/api/fastapi_app.py
View File

@ -1,7 +1,6 @@
import asyncio
import logging
import re
from typing import Optional
from fastapi import Depends, FastAPI, Request
from fastapi.responses import JSONResponse
@ -64,7 +63,7 @@ class RemoteUserPlugin(Plugin):
def create_fastapi_app(
frigate_config: FrigateConfig,
database: SqliteQueueDatabase,
embeddings: Optional[EmbeddingsContext],
embeddings: EmbeddingsContext | None,
detected_frames_processor,
storage_maintainer: StorageMaintainer,
onvif: OnvifController,
@ -72,8 +71,8 @@ def create_fastapi_app(
event_metadata_updater: EventMetadataPublisher,
config_publisher: CameraConfigUpdatePublisher,
replay_manager: DebugReplayManager,
dispatcher: Optional[Dispatcher] = None,
profile_manager: Optional[ProfileManager] = None,
dispatcher: Dispatcher | None = None,
profile_manager: ProfileManager | None = None,
enforce_default_admin: bool = True,
):
logger.info("Starting FastAPI app")

21
frigate/api/media.py
View File

@ -7,7 +7,7 @@ import math
import os
import subprocess as sp
import time
from datetime import datetime, timedelta, timezone
from datetime import UTC, datetime, timedelta
from pathlib import Path as FilePath
from typing import Any
from urllib.parse import unquote
@ -314,10 +314,8 @@ async def get_snapshot_from_recording(
Recordings.start_time,
)
.where(
(
(frame_time >= Recordings.start_time)
& (frame_time <= Recordings.end_time)
)
(frame_time >= Recordings.start_time)
& (frame_time <= Recordings.end_time)
)
.where(Recordings.camera == camera_name)
.order_by(Recordings.start_time.desc())
@ -335,10 +333,8 @@ async def get_snapshot_from_recording(
Recordings.start_time,
)
.where(
(
(frame_time >= Recordings.start_time)
& (frame_time <= Recordings.end_time)
)
(frame_time >= Recordings.start_time)
& (frame_time <= Recordings.end_time)
)
.where(Recordings.camera == camera_name)
.order_by(Recordings.start_time.desc())
@ -398,10 +394,7 @@ async def submit_recording_snapshot_to_plus(
Recordings.start_time,
)
.where(
(
(frame_time >= Recordings.start_time)
& (frame_time <= Recordings.end_time)
)
(frame_time >= Recordings.start_time) & (frame_time <= Recordings.end_time)
)
.where(Recordings.camera == camera_name)
.order_by(Recordings.start_time.desc())
@ -719,7 +712,7 @@ async def vod_hour(
):
parts = year_month.split("-")
start_date = (
datetime(int(parts[0]), int(parts[1]), day, hour, tzinfo=timezone.utc)
datetime(int(parts[0]), int(parts[1]), day, hour, tzinfo=UTC)
- datetime.now(pytz.timezone(tz_name.replace(",", "/"))).utcoffset()
)
end_date = start_date + timedelta(hours=1) - timedelta(milliseconds=1)

31
frigate/api/media_auth.py
View File

@ -14,7 +14,6 @@ from __future__ import annotations
import logging
import os
from enum import Enum
from typing import Optional
from urllib.parse import unquote, urlparse
from peewee import DoesNotExist
@ -42,7 +41,7 @@ class MediaAuthResolution(str, Enum):
UNKNOWN = "unknown"
def extract_path(original_url: Optional[str]) -> Optional[str]:
def extract_path(original_url: str | None) -> str | None:
"""Return the decoded path component of nginx's `X-Original-URL` header.
nginx forwards the *raw* request URI (with `..` segments intact) via
@ -72,8 +71,8 @@ def extract_path(original_url: Optional[str]) -> Optional[str]:
def resolve_media_uri(
uri: str, frigate_config: Optional[FrigateConfig] = None
) -> tuple[MediaAuthResolution, Optional[str]]:
uri: str, frigate_config: FrigateConfig | None = None
) -> tuple[MediaAuthResolution, str | None]:
"""Classify a URI and return the owning camera if applicable.
`frigate_config` is used to disambiguate clip/review filenames whose
@ -100,7 +99,7 @@ def resolve_media_uri(
def _resolve_recording(
parts: list[str],
) -> tuple[MediaAuthResolution, Optional[str]]:
) -> tuple[MediaAuthResolution, str | None]:
# /recordings → neutral
# /recordings/{date} → neutral
# /recordings/{date}/{hour} → multi-camera listing
@ -113,8 +112,8 @@ def _resolve_recording(
def _resolve_clip(
parts: list[str], frigate_config: Optional[FrigateConfig]
) -> tuple[MediaAuthResolution, Optional[str]]:
parts: list[str], frigate_config: FrigateConfig | None
) -> tuple[MediaAuthResolution, str | None]:
# /clips → multi-camera listing
# /clips/thumbs/{cam}/... → camera
# /clips/previews/{cam}/... → camera
@ -159,8 +158,8 @@ def _resolve_clip(
def _longest_prefix_camera(
stem: str, frigate_config: Optional[FrigateConfig]
) -> Optional[str]:
stem: str, frigate_config: FrigateConfig | None
) -> str | None:
if frigate_config is None:
return None
for cam in sorted(frigate_config.cameras.keys(), key=len, reverse=True):
@ -170,8 +169,8 @@ def _longest_prefix_camera(
def _camera_from_clip_filename(
filename: str, frigate_config: Optional[FrigateConfig]
) -> Optional[str]:
filename: str, frigate_config: FrigateConfig | None
) -> str | None:
"""Match a flat clip filename `{camera}-{event_id}[-clean].{ext}` against
configured camera names. Longest-prefix wins so camera names containing
hyphens (e.g. `front-door`) resolve correctly.
@ -182,8 +181,8 @@ def _camera_from_clip_filename(
def _camera_from_thumb_filename(
filename: str, frigate_config: Optional[FrigateConfig]
) -> Optional[str]:
filename: str, frigate_config: FrigateConfig | None
) -> str | None:
"""Match a review thumbnail filename `thumb-{camera}-{review_id}.webp`."""
if not filename.startswith("thumb-"):
return None
@ -194,7 +193,7 @@ def _camera_from_thumb_filename(
def _resolve_export(
parts: list[str],
) -> tuple[MediaAuthResolution, Optional[str]]:
) -> tuple[MediaAuthResolution, str | None]:
# /exports → multi-camera listing
# /exports/{filename}.mp4 → camera (DB lookup by exact path)
if len(parts) == 1:
@ -240,8 +239,8 @@ def is_role_restricted(role: str, frigate_config: FrigateConfig) -> bool:
def deny_response_for_media_uri(
original_url: Optional[str], role: Optional[str], frigate_config: FrigateConfig
) -> Optional[int]:
original_url: str | None, role: str | None, frigate_config: FrigateConfig
) -> int | None:
"""Decide whether the current role should be blocked from `original_url`.
Returns an HTTP status code (403) when access should be denied, or `None`

16
frigate/api/motion_search.py
View File

@ -1,7 +1,7 @@
"""Motion search API for detecting changes within a region of interest."""
import logging
from typing import Any, List, Optional
from typing import Any
from fastapi import APIRouter, Depends, Request
from fastapi.responses import JSONResponse
@ -26,7 +26,7 @@ class MotionSearchRequest(BaseModel):
start_time: float = Field(description="Start timestamp for the search range")
end_time: float = Field(description="End timestamp for the search range")
polygon_points: List[List[float]] = Field(
polygon_points: list[list[float]] = Field(
description="List of [x, y] normalized coordinates (0-1) defining the ROI polygon"
)
threshold: int = Field(
@ -87,12 +87,12 @@ class MotionSearchStatusResponse(BaseModel):
success: bool
message: str
status: str # "queued", "running", "success", "failed", or "cancelled"
results: Optional[List[MotionSearchResult]] = None
total_frames_processed: Optional[int] = None
error_message: Optional[str] = None
metrics: Optional[MotionSearchMetricsResponse] = None
scanning_timestamp: Optional[float] = None
progress: Optional[float] = None
results: list[MotionSearchResult] | None = None
total_frames_processed: int | None = None
error_message: str | None = None
metrics: MotionSearchMetricsResponse | None = None
scanning_timestamp: float | None = None
progress: float | None = None
@router.post(

4
frigate/api/preview.py
View File

@ -4,7 +4,7 @@ import bisect
import logging
import os
import threading
from datetime import datetime, timedelta, timezone
from datetime import UTC, datetime, timedelta
import pytz
from fastapi import APIRouter, Depends, HTTPException
@ -125,7 +125,7 @@ def preview_hour(
"""Get all mp4 previews relevant for time period given the timezone"""
parts = year_month.split("-")
start_date = (
datetime(int(parts[0]), int(parts[1]), int(day), int(hour), tzinfo=timezone.utc)
datetime(int(parts[0]), int(parts[1]), int(day), int(hour), tzinfo=UTC)
- datetime.now(pytz.timezone(tz_name.replace(",", "/"))).utcoffset()
)
end_date = start_date + timedelta(hours=1) - timedelta(milliseconds=1)

7
frigate/api/record.py
View File

@ -5,7 +5,6 @@ import logging
from datetime import datetime, timedelta
from functools import reduce
from pathlib import Path
from typing import List
from urllib.parse import unquote
from fastapi import APIRouter, Depends, Request
@ -63,7 +62,7 @@ def get_recordings_storage_usage(request: Request):
def all_recordings_summary(
request: Request,
params: MediaRecordingsSummaryQueryParams = Depends(),
allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
):
"""Returns true/false by day indicating if recordings exist"""
@ -263,7 +262,7 @@ async def recordings(
async def no_recordings(
request: Request,
params: MediaRecordingsAvailabilityQueryParams = Depends(),
allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
):
"""Get time ranges with no recordings."""
cameras = params.cameras
@ -365,7 +364,7 @@ async def delete_recordings(
start: float = PathParam(..., description="Start timestamp (unix)"),
end: float = PathParam(..., description="End timestamp (unix)"),
params: RecordingsDeleteQueryParams = Depends(),
allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
):
"""Delete recordings in the specified time range."""
if start >= end:

21
frigate/api/review.py
View File

@ -4,7 +4,6 @@ import datetime
import logging
from functools import reduce
from pathlib import Path
from typing import List
import pandas as pd
from fastapi import APIRouter, Request
@ -51,7 +50,7 @@ router = APIRouter(tags=[Tags.review])
async def review(
params: ReviewQueryParams = Depends(),
current_user: dict = Depends(get_current_user),
allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
):
if isinstance(current_user, JSONResponse):
return current_user
@ -83,7 +82,7 @@ async def review(
camera_list = list(filtered)
else:
camera_list = allowed_cameras
clauses.append((ReviewSegment.camera << camera_list))
clauses.append(ReviewSegment.camera << camera_list)
if labels != "all":
# use matching so segments with multiple labels
@ -106,12 +105,12 @@ async def review(
for zone in filtered_zones:
zone_clauses.append(
(ReviewSegment.data["zones"].cast("text") % f'*"{zone}"*')
ReviewSegment.data["zones"].cast("text") % f'*"{zone}"*'
)
clauses.append(reduce(operator.or_, zone_clauses))
if severity:
clauses.append((ReviewSegment.severity == severity))
clauses.append(ReviewSegment.severity == severity)
# Join with UserReviewStatus to get per-user review status
review_query = (
@ -204,7 +203,7 @@ async def review_ids(request: Request, ids: str):
async def review_summary(
params: ReviewSummaryQueryParams = Depends(),
current_user: dict = Depends(get_current_user),
allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
):
if isinstance(current_user, JSONResponse):
return current_user
@ -227,7 +226,7 @@ async def review_summary(
camera_list = list(filtered)
else:
camera_list = allowed_cameras
clauses.append((ReviewSegment.camera << camera_list))
clauses.append(ReviewSegment.camera << camera_list)
if labels != "all":
# use matching so segments with multiple labels
@ -328,7 +327,7 @@ async def review_summary(
camera_list = list(filtered)
else:
camera_list = allowed_cameras
clauses.append((ReviewSegment.camera << camera_list))
clauses.append(ReviewSegment.camera << camera_list)
if labels != "all":
# use matching so segments with multiple labels
@ -584,7 +583,7 @@ def delete_reviews(body: ReviewModifyMultipleBody):
)
def motion_activity(
params: ReviewActivityMotionQueryParams = Depends(),
allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
):
"""Get motion and audio activity."""
cameras = params.cameras
@ -597,7 +596,7 @@ def motion_activity(
scale = params.scale
clauses = [(Recordings.start_time > after) & (Recordings.end_time < before)]
clauses.append((Recordings.motion > 0))
clauses.append(Recordings.motion > 0)
if cameras != "all":
requested = set(cameras.split(","))
@ -608,7 +607,7 @@ def motion_activity(
else:
camera_list = list(allowed_cameras)
clauses.append((Recordings.camera << camera_list))
clauses.append(Recordings.camera << camera_list)
data: list[Recordings] = (
Recordings.select(

8
frigate/app.py
View File

@ -4,11 +4,11 @@ import multiprocessing as mp
import os
import secrets
import shutil
from collections.abc import Callable
from multiprocessing import Queue
from multiprocessing.managers import DictProxy, SyncManager
from multiprocessing.synchronize import Event as MpEvent
from pathlib import Path
from typing import Callable, Optional
import psutil
import uvicorn
@ -95,7 +95,7 @@ class FrigateApp:
self, config: FrigateConfig, manager: SyncManager, stop_event: MpEvent
) -> None:
self.metrics_manager = manager
self.audio_process: Optional[mp.Process] = None
self.audio_process: mp.Process | None = None
self.stop_event = stop_event
self.detection_queue: Queue = mp.Queue()
self.detectors: dict[str, ObjectDetectProcess] = {}
@ -120,8 +120,8 @@ class FrigateApp:
)
self.ptz_metrics: dict[str, PTZMetrics] = {}
self.processes: dict[str, int] = {}
self.embeddings: Optional[EmbeddingsContext] = None
self.profile_manager: Optional[ProfileManager] = None
self.embeddings: EmbeddingsContext | None = None
self.profile_manager: ProfileManager | None = None
self.config = config
def ensure_dirs(self) -> None:

3
frigate/camera/activity_manager.py
View File

@ -6,7 +6,8 @@ import logging
import random
import string
from collections import Counter
from typing import Any, Callable
from collections.abc import Callable
from typing import Any
from frigate.comms.event_metadata_updater import (
EventMetadataPublisher,

3
frigate/camera/state.py
View File

@ -5,7 +5,8 @@ import logging
import os
import threading
from collections import defaultdict
from typing import Any, Callable
from collections.abc import Callable
from typing import Any
import cv2
import numpy as np

3
frigate/comms/base_communicator.py
View File

@ -1,5 +1,6 @@
from abc import ABC, abstractmethod
from typing import Any, Callable
from collections.abc import Callable
from typing import Any
class Communicator(ABC):

8
frigate/comms/dispatcher.py
View File

@ -3,8 +3,8 @@
import datetime
import json
import logging
from collections.abc import Iterable
from typing import Any, Callable, Optional, cast
from collections.abc import Callable, Iterable
from typing import Any, cast
from frigate.camera import PTZMetrics
from frigate.camera.activity_manager import AudioActivityManager, CameraActivityManager
@ -97,7 +97,7 @@ class Dispatcher:
"notifications": self._on_global_notification_command,
"profile": self._on_profile_command,
}
self.profile_manager: Optional[ProfileManager] = None
self.profile_manager: ProfileManager | None = None
for comm in self.comms:
comm.subscribe(self._receive)
@ -106,7 +106,7 @@ class Dispatcher:
(comm for comm in communicators if isinstance(comm, WebPushClient)), None
)
def _receive(self, topic: str, payload: Any) -> Optional[Any]:
def _receive(self, topic: str, payload: Any) -> Any | None:
"""Handle receiving of payload from communicators."""
def handle_camera_command(

3
frigate/comms/embeddings_updater.py
View File

@ -1,8 +1,9 @@
"""Facilitates communication between processes."""
import logging
from collections.abc import Callable
from enum import Enum
from typing import Any, Callable
from typing import Any
import zmq

3
frigate/comms/inter_process.py
View File

@ -3,8 +3,9 @@
import logging
import multiprocessing as mp
import threading
from collections.abc import Callable
from multiprocessing.synchronize import Event as MpEvent
from typing import Any, Callable
from typing import Any
import zmq

7
frigate/comms/mqtt.py
View File

@ -1,6 +1,7 @@
import logging
import threading
from typing import Any, Callable
from collections.abc import Callable
from typing import Any
import paho.mqtt.client as mqtt
from paho.mqtt.enums import CallbackAPIVersion
@ -214,8 +215,8 @@ class MqttClient(Communicator):
logger.error("Unable to connect to MQTT server: MQTT Not authorized")
else:
logger.error(
"Unable to connect to MQTT server: Connection refused. Error code: "
+ reason_code.getName()
"Unable to connect to MQTT server: Connection refused. Error code: %s",
reason_code.getName(),
)
self.connected = True

2
frigate/comms/runtime_state.py
View File

@ -146,7 +146,7 @@ class RuntimeStatePersistence:
if not os.path.exists(self._path):
return {}
try:
with open(self._path, "r") as f:
with open(self._path) as f:
data = json.load(f)
except (OSError, json.JSONDecodeError):
logger.exception(

3
frigate/comms/webpush.py
View File

@ -6,9 +6,10 @@ import logging
import os
import queue
import threading
from collections.abc import Callable
from dataclasses import dataclass
from multiprocessing.synchronize import Event as MpEvent
from typing import Any, Callable
from typing import Any
from py_vapid import Vapid01
from pywebpush import WebPusher

3
frigate/comms/ws.py
View File

@ -4,7 +4,8 @@ import errno
import json
import logging
import threading
from typing import Any, Callable
from collections.abc import Callable
from typing import Any
from wsgiref.simple_server import make_server
from ws4py.server.wsgirefserver import (

10
frigate/config/auth.py
View File

@ -1,5 +1,3 @@
from typing import Dict, List, Optional
from pydantic import Field, field_validator, model_validator
from .base import FrigateBaseModel
@ -41,7 +39,7 @@ class AuthConfig(FrigateBaseModel):
description="When a session is within this many seconds of expiring, refresh it back to full length.",
ge=30,
)
failed_login_rate_limit: Optional[str] = Field(
failed_login_rate_limit: str | None = Field(
default=None,
title="Failed login limits",
description="Rate limiting rules for failed login attempts to reduce brute-force attacks.",
@ -57,12 +55,12 @@ class AuthConfig(FrigateBaseModel):
title="Hash iterations",
description="Number of PBKDF2-SHA256 iterations to use when hashing user passwords.",
)
roles: Dict[str, List[str]] = Field(
roles: dict[str, list[str]] = Field(
default_factory=dict,
title="Role mappings",
description="Map roles to camera lists. An empty list grants access to all cameras for the role.",
)
admin_first_time_login: Optional[bool] = Field(
admin_first_time_login: bool | None = Field(
default=False,
title="First-time admin flag",
description=(
@ -72,7 +70,7 @@ class AuthConfig(FrigateBaseModel):
@field_validator("roles")
@classmethod
def validate_roles(cls, v: Dict[str, List[str]]) -> Dict[str, List[str]]:
def validate_roles(cls, v: dict[str, list[str]]) -> dict[str, list[str]]:
# Ensure role names are valid (alphanumeric with underscores)
for role in v.keys():
if not role.replace("_", "").isalnum():

6
frigate/config/camera/audio.py
View File

@ -1,5 +1,3 @@
from typing import Optional
from pydantic import Field
from frigate.const import AUDIO_MIN_CONFIDENCE
@ -43,12 +41,12 @@ class AudioConfig(FrigateBaseModel):
title="Listen types",
description="List of audio event types to detect (for example: bark, fire_alarm, speech, yell).",
)
filters: Optional[dict[str, AudioFilterConfig]] = Field(
filters: dict[str, AudioFilterConfig] | None = Field(
None,
title="Audio filters",
description="Per-audio-type filter settings such as confidence thresholds used to reduce false positives.",
)
enabled_in_config: Optional[bool] = Field(
enabled_in_config: bool | None = Field(
None,
title="Original audio state",
description="Indicates whether audio detection was originally enabled in the static config file.",

3
frigate/config/camera/birdseye.py
View File

@ -1,5 +1,4 @@
from enum import Enum
from typing import Optional
from pydantic import BaseModel, Field
@ -35,7 +34,7 @@ class BirdseyeLayoutConfig(FrigateBaseModel):
ge=1.0,
le=5.0,
)
max_cameras: Optional[int] = Field(
max_cameras: int | None = Field(
default=None,
title="Max cameras",
description="Maximum number of cameras to display at once in Birdseye; shows the most recent cameras.",

9
frigate/config/camera/camera.py
View File

@ -1,6 +1,5 @@
import os
from enum import Enum
from typing import Optional
from pydantic import Field, PrivateAttr, model_validator
@ -51,14 +50,14 @@ class CameraTypeEnum(str, Enum):
class CameraConfig(FrigateBaseModel):
name: Optional[str] = Field(
name: str | None = Field(
None,
title="Camera name",
description="Camera name is required",
pattern=REGEX_CAMERA_NAME,
)
friendly_name: Optional[str] = Field(
friendly_name: str | None = Field(
None,
title="Friendly name",
description="Camera friendly name used in the Frigate UI",
@ -180,7 +179,7 @@ class CameraConfig(FrigateBaseModel):
title="Camera UI",
description="Display ordering and visibility for this camera in the UI. Ordering affects the default dashboard. For more granular control, use camera groups.",
)
webui_url: Optional[str] = Field(
webui_url: str | None = Field(
None,
title="Camera URL",
description="URL to visit the camera directly from system page",
@ -196,7 +195,7 @@ class CameraConfig(FrigateBaseModel):
title="Zones",
description="Zones allow you to define a specific area of the frame so you can determine whether or not an object is within a particular area.",
)
enabled_in_config: Optional[bool] = Field(
enabled_in_config: bool | None = Field(
default=None,
title="Original camera state",
description="Keep track of original state of camera.",

16
frigate/config/camera/detect.py
View File

@ -1,5 +1,3 @@
from typing import Optional
from pydantic import Field, model_validator
from ..base import FrigateBaseModel
@ -8,7 +6,7 @@ __all__ = ["DetectConfig", "StationaryConfig", "StationaryMaxFramesConfig"]
class StationaryMaxFramesConfig(FrigateBaseModel):
default: Optional[int] = Field(
default: int | None = Field(
default=None,
title="Default max frames",
description="Default maximum frames to track a stationary object before stopping.",
@ -22,13 +20,13 @@ class StationaryMaxFramesConfig(FrigateBaseModel):
class StationaryConfig(FrigateBaseModel):
interval: Optional[int] = Field(
interval: int | None = Field(
default=None,
title="Stationary interval",
description="How often (in frames) to run a detection check to confirm a stationary object.",
gt=0,
)
threshold: Optional[int] = Field(
threshold: int | None = Field(
default=None,
title="Stationary threshold",
description="Number of frames with no position change required to mark an object as stationary.",
@ -52,12 +50,12 @@ class DetectConfig(FrigateBaseModel):
title="Enable object detection",
description="Enable or disable object detection for all cameras; can be overridden per-camera.",
)
height: Optional[int] = Field(
height: int | None = Field(
default=None,
title="Detect height",
description="Height (pixels) of frames used for the detect stream; leave empty to use the native stream resolution.",
)
width: Optional[int] = Field(
width: int | None = Field(
default=None,
title="Detect width",
description="Width (pixels) of frames used for the detect stream; leave empty to use the native stream resolution.",
@ -67,13 +65,13 @@ class DetectConfig(FrigateBaseModel):
title="Detect FPS",
description="Desired frames per second to run detection on; lower values reduce CPU usage (recommended value is 5, only set higher - at most 10 - if tracking extremely fast moving objects).",
)
min_initialized: Optional[int] = Field(
min_initialized: int | None = Field(
default=None,
title="Minimum initialization frames",
description="Number of consecutive detection hits required before creating a tracked object. Increase to reduce false initializations. Default value is fps divided by 2.",
ge=2,
)
max_disappeared: Optional[int] = Field(
max_disappeared: int | None = Field(
default=None,
title="Maximum disappeared frames",
description="Number of frames without a detection before a tracked object is considered gone.",

17
frigate/config/camera/ffmpeg.py
View File

@ -1,5 +1,4 @@
from enum import Enum
from typing import Union
from pydantic import Field, field_validator
@ -33,12 +32,12 @@ DETECT_FFMPEG_OUTPUT_ARGS_DEFAULT = [
class FfmpegOutputArgsConfig(FrigateBaseModel):
detect: Union[str, list[str]] = Field(
detect: str | list[str] = Field(
default=DETECT_FFMPEG_OUTPUT_ARGS_DEFAULT,
title="Detect output arguments",
description="Default output arguments for detect role streams.",
)
record: Union[str, list[str]] = Field(
record: str | list[str] = Field(
default=RECORD_FFMPEG_OUTPUT_ARGS_DEFAULT,
title="Record output arguments",
description="Default output arguments for record role streams.",
@ -51,17 +50,17 @@ class FfmpegConfig(FrigateBaseModel):
title="FFmpeg path",
description='Path to the FFmpeg binary to use or a version alias ("7.0" or "8.0").',
)
global_args: Union[str, list[str]] = Field(
global_args: str | list[str] = Field(
default=FFMPEG_GLOBAL_ARGS_DEFAULT,
title="FFmpeg global arguments",
description="Global arguments passed to FFmpeg processes.",
)
hwaccel_args: Union[str, list[str]] = Field(
hwaccel_args: str | list[str] = Field(
default="auto",
title="Hardware acceleration arguments",
description="Hardware acceleration arguments for FFmpeg. Provider-specific presets are recommended.",
)
input_args: Union[str, list[str]] = Field(
input_args: str | list[str] = Field(
default=FFMPEG_INPUT_ARGS_DEFAULT,
title="Input arguments",
description="Input arguments applied to FFmpeg input streams.",
@ -112,17 +111,17 @@ class CameraInput(FrigateBaseModel):
title="Input roles",
description="Roles for this input stream.",
)
global_args: Union[str, list[str]] = Field(
global_args: str | list[str] = Field(
default_factory=list,
title="FFmpeg global arguments",
description="FFmpeg global arguments for this input stream.",
)
hwaccel_args: Union[str, list[str]] = Field(
hwaccel_args: str | list[str] = Field(
default_factory=list,
title="Hardware acceleration arguments",
description="Hardware acceleration arguments for this input stream.",
)
input_args: Union[str, list[str]] = Field(
input_args: str | list[str] = Field(
default_factory=list,
title="Input arguments",
description="Input arguments specific to this stream.",

6
frigate/config/camera/genai.py
View File

@ -1,5 +1,5 @@
from enum import Enum
from typing import Any, Optional
from typing import Any
from pydantic import Field
@ -26,12 +26,12 @@ class GenAIRoleEnum(str, Enum):
class GenAIConfig(FrigateBaseModel):
"""Primary GenAI Config to define GenAI Provider."""
api_key: Optional[EnvString] = Field(
api_key: EnvString | None = Field(
default=None,
title="API key",
description="API key required by some providers (can also be set via environment variables).",
)
base_url: Optional[str] = Field(
base_url: str | None = Field(
default=None,
title="Base URL",
description="Base URL for self-hosted or compatible providers (for example an Ollama instance).",

4
frigate/config/camera/live.py
View File

@ -1,5 +1,3 @@
from typing import Dict
from pydantic import Field
from ..base import FrigateBaseModel
@ -8,7 +6,7 @@ __all__ = ["CameraLiveConfig"]
class CameraLiveConfig(FrigateBaseModel):
streams: Dict[str, str] = Field(
streams: dict[str, str] = Field(
default_factory=list,
title="Live stream names",
description="Mapping of configured stream names to restream/go2rtc names used for live playback.",

18
frigate/config/camera/mask.py
View File

@ -1,6 +1,6 @@
"""Mask configuration for motion and object masks."""
from typing import Any, Optional, Union
from typing import Any
from pydantic import Field, field_serializer
@ -12,7 +12,7 @@ __all__ = ["MotionMaskConfig", "ObjectMaskConfig"]
class MotionMaskConfig(FrigateBaseModel):
"""Configuration for a single motion mask."""
friendly_name: Optional[str] = Field(
friendly_name: str | None = Field(
default=None,
title="Friendly name",
description="A friendly name for this motion mask used in the Frigate UI",
@ -22,13 +22,13 @@ class MotionMaskConfig(FrigateBaseModel):
title="Enabled",
description="Enable or disable this motion mask",
)
coordinates: Union[str, list[str]] = Field(
coordinates: str | list[str] = Field(
default="",
title="Coordinates",
description="Ordered x,y coordinates defining the motion mask polygon used to include/exclude areas.",
)
raw_coordinates: Union[str, list[str]] = ""
enabled_in_config: Optional[bool] = Field(
raw_coordinates: str | list[str] = ""
enabled_in_config: bool | None = Field(
default=None, title="Keep track of original state of motion mask."
)
@ -50,7 +50,7 @@ class MotionMaskConfig(FrigateBaseModel):
class ObjectMaskConfig(FrigateBaseModel):
"""Configuration for a single object mask."""
friendly_name: Optional[str] = Field(
friendly_name: str | None = Field(
default=None,
title="Friendly name",
description="A friendly name for this object mask used in the Frigate UI",
@ -60,13 +60,13 @@ class ObjectMaskConfig(FrigateBaseModel):
title="Enabled",
description="Enable or disable this object mask",
)
coordinates: Union[str, list[str]] = Field(
coordinates: str | list[str] = Field(
default="",
title="Coordinates",
description="Ordered x,y coordinates defining the object mask polygon used to include/exclude areas.",
)
raw_coordinates: Union[str, list[str]] = ""
enabled_in_config: Optional[bool] = Field(
raw_coordinates: str | list[str] = ""
enabled_in_config: bool | None = Field(
default=None, title="Keep track of original state of object mask."
)

14
frigate/config/camera/motion.py
View File

@ -1,4 +1,4 @@
from typing import Any, Optional
from typing import Any
from pydantic import Field, field_serializer
@ -28,7 +28,7 @@ class MotionConfig(FrigateBaseModel):
ge=0.3,
le=1.0,
)
skip_motion_threshold: Optional[float] = Field(
skip_motion_threshold: float | None = Field(
default=None,
title="Skip motion threshold",
description="If set to a value between 0.0 and 1.0, and more than this fraction of the image changes in a single frame, the detector will return no motion boxes and immediately recalibrate. This can save CPU and reduce false positives during lightning, storms, etc., but may miss real events such as a PTZ camera auto‑tracking an object. The trade‑off is between dropping a few megabytes of recordings versus reviewing a couple short clips. Leave unset (None) to disable this feature.",
@ -40,7 +40,7 @@ class MotionConfig(FrigateBaseModel):
title="Improve contrast",
description="Apply contrast improvement to frames before motion analysis to help detection.",
)
contour_area: Optional[int] = Field(
contour_area: int | None = Field(
default=10,
title="Contour area",
description="Minimum contour area in pixels required for a motion contour to be counted.",
@ -55,12 +55,12 @@ class MotionConfig(FrigateBaseModel):
title="Frame alpha",
description="Alpha value used when blending frames for motion preprocessing.",
)
frame_height: Optional[int] = Field(
frame_height: int | None = Field(
default=100,
title="Frame height",
description="Height in pixels to scale frames to when computing motion.",
)
mask: dict[str, Optional[MotionMaskConfig]] = Field(
mask: dict[str, MotionMaskConfig | None] = Field(
default_factory=dict,
title="Mask coordinates",
description="Ordered x,y coordinates defining the motion mask polygon used to include/exclude areas.",
@ -70,12 +70,12 @@ class MotionConfig(FrigateBaseModel):
title="MQTT off delay",
description="Seconds to wait after last motion before publishing an MQTT 'off' state.",
)
enabled_in_config: Optional[bool] = Field(
enabled_in_config: bool | None = Field(
default=None,
title="Original motion state",
description="Indicates whether motion detection was enabled in the original static configuration.",
)
raw_mask: dict[str, Optional[MotionMaskConfig]] = Field(
raw_mask: dict[str, MotionMaskConfig | None] = Field(
default_factory=dict, exclude=True
)

6
frigate/config/camera/notification.py
View File

@ -1,5 +1,3 @@
from typing import Optional
from pydantic import Field
from ..base import FrigateBaseModel
@ -13,7 +11,7 @@ class NotificationConfig(FrigateBaseModel):
title="Enable notifications",
description="Enable or disable notifications for all cameras; can be overridden per-camera.",
)
email: Optional[str] = Field(
email: str | None = Field(
default=None,
title="Notification email",
description="Email address used for push notifications or required by certain notification providers.",
@ -24,7 +22,7 @@ class NotificationConfig(FrigateBaseModel):
title="Cooldown period",
description="Cooldown (seconds) between notifications to avoid spamming recipients.",
)
enabled_in_config: Optional[bool] = Field(
enabled_in_config: bool | None = Field(
default=None,
title="Original notifications state",
description="Indicates whether notifications were enabled in the original static configuration.",

22
frigate/config/camera/objects.py
View File

@ -1,4 +1,4 @@
from typing import Any, Optional, Union
from typing import Any
from pydantic import Field, PrivateAttr, field_serializer, field_validator
@ -12,12 +12,12 @@ DEFAULT_TRACKED_OBJECTS = ["person"]
class FilterConfig(FrigateBaseModel):
min_area: Union[int, float] = Field(
min_area: int | float = Field(
default=0,
title="Minimum object area",
description="Minimum bounding box area (pixels or percentage) required for this object type. Can be pixels (int) or percentage (float between 0.000001 and 0.99).",
)
max_area: Union[int, float] = Field(
max_area: int | float = Field(
default=24000000,
title="Maximum object area",
description="Maximum bounding box area (pixels or percentage) allowed for this object type. Can be pixels (int) or percentage (float between 0.000001 and 0.99).",
@ -42,12 +42,12 @@ class FilterConfig(FrigateBaseModel):
title="Minimum confidence",
description="Minimum single-frame detection confidence required for the object to be counted.",
)
mask: dict[str, Optional[ObjectMaskConfig]] = Field(
mask: dict[str, ObjectMaskConfig | None] = Field(
default_factory=dict,
title="Filter mask",
description="Polygon coordinates defining where this filter applies within the frame.",
)
raw_mask: dict[str, Optional[ObjectMaskConfig]] = Field(
raw_mask: dict[str, ObjectMaskConfig | None] = Field(
default_factory=dict, exclude=True
)
@ -68,7 +68,7 @@ class GenAIObjectTriggerConfig(FrigateBaseModel):
title="Send on end",
description="Send a request to GenAI when the tracked object ends.",
)
after_significant_updates: Optional[int] = Field(
after_significant_updates: int | None = Field(
default=None,
title="Early GenAI trigger",
description="Send a request to GenAI after a specified number of significant updates for the tracked object.",
@ -98,12 +98,12 @@ class GenAIObjectConfig(FrigateBaseModel):
description="Per-object prompts to customize GenAI outputs for specific labels.",
)
objects: Union[str, list[str]] = Field(
objects: str | list[str] = Field(
default_factory=list,
title="GenAI objects",
description="List of object labels to send to GenAI by default.",
)
required_zones: Union[str, list[str]] = Field(
required_zones: str | list[str] = Field(
default_factory=list,
title="Required zones",
description="Zones that must be entered for objects to qualify for GenAI description generation.",
@ -118,7 +118,7 @@ class GenAIObjectConfig(FrigateBaseModel):
title="GenAI triggers",
description="Defines when frames should be sent to GenAI (on end, after updates, etc.).",
)
enabled_in_config: Optional[bool] = Field(
enabled_in_config: bool | None = Field(
default=None,
title="Original GenAI state",
description="Indicates whether GenAI was enabled in the original static config.",
@ -144,12 +144,12 @@ class ObjectConfig(FrigateBaseModel):
title="Object filters",
description="Filters applied to detected objects to reduce false positives (area, ratio, confidence).",
)
mask: dict[str, Optional[ObjectMaskConfig]] = Field(
mask: dict[str, ObjectMaskConfig | None] = Field(
default_factory=dict,
title="Object mask",
description="Mask polygon used to prevent object detection in specified areas.",
)
raw_mask: dict[str, Optional[ObjectMaskConfig]] = Field(
raw_mask: dict[str, ObjectMaskConfig | None] = Field(
default_factory=dict, exclude=True
)
genai: GenAIObjectConfig = Field(

11
frigate/config/camera/onvif.py
View File

@ -1,5 +1,4 @@
from enum import Enum
from typing import Optional, Union
from pydantic import Field, field_validator
@ -59,12 +58,12 @@ class PtzAutotrackConfig(FrigateBaseModel):
title="Return timeout",
description="Wait this many seconds after losing tracking before returning camera to preset position.",
)
movement_weights: Optional[Union[str, list[str]]] = Field(
movement_weights: str | list[str] | None = Field(
default_factory=list,
title="Movement weights",
description="Calibration values automatically generated by camera calibration. Do not modify manually.",
)
enabled_in_config: Optional[bool] = Field(
enabled_in_config: bool | None = Field(
default=None,
title="Original autotrack state",
description="Internal field to track whether autotracking was enabled in configuration.",
@ -102,12 +101,12 @@ class OnvifConfig(FrigateBaseModel):
title="ONVIF port",
description="Port number for the ONVIF service.",
)
user: Optional[EnvString] = Field(
user: EnvString | None = Field(
default=None,
title="ONVIF username",
description="Username for ONVIF authentication; some devices require admin user for ONVIF.",
)
password: Optional[EnvString] = Field(
password: EnvString | None = Field(
default=None,
title="ONVIF password",
description="Password for ONVIF authentication.",
@ -117,7 +116,7 @@ class OnvifConfig(FrigateBaseModel):
title="Disable TLS verify",
description="Skip TLS verification and disable digest auth for ONVIF (unsafe; use in safe networks only).",
)
profile: Optional[str] = Field(
profile: str | None = Field(
default=None,
title="ONVIF profile",
description="Specific ONVIF media profile to use for PTZ control, matched by token or name. If not set, the first profile with valid PTZ configuration is selected automatically.",

28
frigate/config/camera/profile.py
View File

@ -1,7 +1,5 @@
"""Camera profile configuration for named config overrides."""
from typing import Optional
from ..base import FrigateBaseModel
from ..classification import (
CameraFaceRecognitionConfig,
@ -29,16 +27,16 @@ class CameraProfileConfig(FrigateBaseModel):
explicitly-set fields are used as overrides via exclude_unset.
"""
enabled: Optional[bool] = None
audio: Optional[AudioConfig] = None
birdseye: Optional[BirdseyeCameraConfig] = None
detect: Optional[DetectConfig] = None
face_recognition: Optional[CameraFaceRecognitionConfig] = None
lpr: Optional[CameraLicensePlateRecognitionConfig] = None
motion: Optional[MotionConfig] = None
notifications: Optional[NotificationConfig] = None
objects: Optional[ObjectConfig] = None
record: Optional[RecordConfig] = None
review: Optional[ReviewConfig] = None
snapshots: Optional[SnapshotsConfig] = None
zones: Optional[dict[str, ZoneConfig]] = None
enabled: bool | None = None
audio: AudioConfig | None = None
birdseye: BirdseyeCameraConfig | None = None
detect: DetectConfig | None = None
face_recognition: CameraFaceRecognitionConfig | None = None
lpr: CameraLicensePlateRecognitionConfig | None = None
motion: MotionConfig | None = None
notifications: NotificationConfig | None = None
objects: ObjectConfig | None = None
record: RecordConfig | None = None
review: ReviewConfig | None = None
snapshots: SnapshotsConfig | None = None
zones: dict[str, ZoneConfig] | None = None

5
frigate/config/camera/record.py
View File

@ -1,5 +1,4 @@
from enum import Enum
from typing import Optional, Union
from pydantic import Field
@ -94,7 +93,7 @@ class ChaptersEnum(str, Enum):
class RecordExportConfig(FrigateBaseModel):
hwaccel_args: Union[str, list[str]] = Field(
hwaccel_args: str | list[str] = Field(
default="auto",
title="Export hwaccel args",
description="Hardware acceleration args to use for export/transcode operations.",
@ -152,7 +151,7 @@ class RecordConfig(FrigateBaseModel):
title="Preview config",
description="Settings controlling the quality of recording previews shown in the UI.",
)
enabled_in_config: Optional[bool] = Field(
enabled_in_config: bool | None = Field(
default=None,
title="Original recording state",
description="Indicates whether recording was enabled in the original static configuration.",

13
frigate/config/camera/review.py
View File

@ -1,5 +1,4 @@
from enum import Enum
from typing import Optional, Union
from pydantic import Field, field_validator
@ -32,13 +31,13 @@ class AlertsConfig(FrigateBaseModel):
title="Alert labels",
description="List of object labels that qualify as alerts (for example: car, person).",
)
required_zones: Union[str, list[str]] = Field(
required_zones: str | list[str] = Field(
default_factory=list,
title="Required zones",
description="Zones that an object must enter to be considered an alert; leave empty to allow any zone.",
)
enabled_in_config: Optional[bool] = Field(
enabled_in_config: bool | None = Field(
default=None,
title="Original alerts state",
description="Tracks whether alerts were originally enabled in the static configuration.",
@ -67,12 +66,12 @@ class DetectionsConfig(FrigateBaseModel):
description="Enable or disable detection events for all cameras; can be overridden per-camera.",
)
labels: Optional[list[str]] = Field(
labels: list[str] | None = Field(
default=None,
title="Detection labels",
description="List of object labels that qualify as detection events.",
)
required_zones: Union[str, list[str]] = Field(
required_zones: str | list[str] = Field(
default_factory=list,
title="Required zones",
description="Zones that an object must enter to be considered a detection; leave empty to allow any zone.",
@ -83,7 +82,7 @@ class DetectionsConfig(FrigateBaseModel):
description="Seconds to wait after no detection-causing activity before cutting off a detection.",
)
enabled_in_config: Optional[bool] = Field(
enabled_in_config: bool | None = Field(
default=None,
title="Original detections state",
description="Tracks whether detections were originally enabled in the static configuration.",
@ -129,7 +128,7 @@ class GenAIReviewConfig(FrigateBaseModel):
title="Save thumbnails",
description="Save thumbnails that are sent to the GenAI provider for debugging and review.",
)
enabled_in_config: Optional[bool] = Field(
enabled_in_config: bool | None = Field(
default=None,
title="Original GenAI state",
description="Tracks whether GenAI review was originally enabled in the static configuration.",

4
frigate/config/camera/snapshots.py
View File

@ -1,5 +1,3 @@
from typing import Optional
from pydantic import Field
from ..base import FrigateBaseModel
@ -46,7 +44,7 @@ class SnapshotsConfig(FrigateBaseModel):
title="Required zones",
description="Zones an object must enter for a snapshot to be saved.",
)
height: Optional[int] = Field(
height: int | None = Field(
default=None,
title="Snapshot height",
description="Height (pixels) to resize snapshots from API to; leave empty to preserve original size.",

3
frigate/config/camera/timestamp.py
View File

@ -1,5 +1,4 @@
from enum import Enum
from typing import Optional
from pydantic import Field
@ -76,7 +75,7 @@ class TimestampStyleConfig(FrigateBaseModel):
title="Timestamp thickness",
description="Line thickness of the timestamp text.",
)
effect: Optional[TimestampEffectEnum] = Field(
effect: TimestampEffectEnum | None = Field(
default=None,
title="Timestamp effect",
description="Visual effect for the timestamp text (none, solid, shadow).",

19
frigate/config/camera/zone.py
View File

@ -1,6 +1,5 @@
# this uses the base model because the color is an extra attribute
import logging
from typing import Optional, Union
import numpy as np
from pydantic import BaseModel, Field, PrivateAttr, field_validator, model_validator
@ -13,7 +12,7 @@ logger = logging.getLogger(__name__)
class ZoneConfig(BaseModel):
friendly_name: Optional[str] = Field(
friendly_name: str | None = Field(
None,
title="Zone name",
description="A user-friendly name for the zone, displayed in the Frigate UI. If not set, a formatted version of the zone name will be used.",
@ -23,7 +22,7 @@ class ZoneConfig(BaseModel):
title="Enabled",
description="Enable or disable this zone. Disabled zones are ignored at runtime.",
)
enabled_in_config: Optional[bool] = Field(
enabled_in_config: bool | None = Field(
default=None, title="Keep track of original state of zone."
)
filters: dict[str, FilterConfig] = Field(
@ -31,11 +30,11 @@ class ZoneConfig(BaseModel):
title="Zone filters",
description="Filters to apply to objects within this zone. Used to reduce false positives or restrict which objects are considered present in the zone.",
)
coordinates: Union[str, list[str]] = Field(
coordinates: str | list[str] = Field(
title="Coordinates",
description="Polygon coordinates that define the zone area. Can be a comma-separated string or a list of coordinate strings. Coordinates should be relative (0-1) or absolute (legacy).",
)
distances: Optional[Union[str, list[str]]] = Field(
distances: str | list[str] | None = Field(
default_factory=list,
title="Real-world distances",
description="Optional real-world distances for each side of the zone quadrilateral, used for speed or distance calculations. Must have exactly 4 values if set.",
@ -52,18 +51,18 @@ class ZoneConfig(BaseModel):
title="Loitering seconds",
description="Number of seconds an object must remain in the zone to be considered as loitering. Set to 0 to disable loitering detection.",
)
speed_threshold: Optional[float] = Field(
speed_threshold: float | None = Field(
default=None,
ge=0.1,
title="Minimum speed",
description="Minimum speed (in real-world units if distances are set) required for an object to be considered present in the zone. Used for speed-based zone triggers.",
)
objects: Union[str, list[str]] = Field(
objects: str | list[str] = Field(
default_factory=list,
title="Trigger objects",
description="List of object types (from labelmap) that can trigger this zone. Can be a string or a list of strings. If empty, all objects are considered.",
)
_color: Optional[tuple[int, int, int]] = PrivateAttr()
_color: tuple[int, int, int] | None = PrivateAttr()
_contour: np.ndarray = PrivateAttr()
@property
@ -147,7 +146,7 @@ class ZoneConfig(BaseModel):
except ValueError:
raise ValueError(
f"Invalid coordinates found in configuration file. Coordinates must be relative (between 0-1): {coordinates}"
)
) from None
if explicit:
self.coordinates = ",".join(
@ -176,7 +175,7 @@ class ZoneConfig(BaseModel):
except ValueError:
raise ValueError(
f"Invalid coordinates found in configuration file. Coordinates must be relative (between 0-1): {coordinates}"
)
) from None
if explicit:
self.coordinates = ",".join(

4
frigate/config/camera_group.py
View File

@ -1,5 +1,3 @@
from typing import Union
from pydantic import Field, field_validator
from .base import FrigateBaseModel
@ -8,7 +6,7 @@ __all__ = ["CameraGroupConfig"]
class CameraGroupConfig(FrigateBaseModel):
cameras: Union[str, list[str]] = Field(
cameras: str | list[str] = Field(
default_factory=list,
title="Camera list",
description="Array of camera names included in this group.",

33
frigate/config/classification.py
View File

@ -1,5 +1,4 @@
from enum import Enum
from typing import Dict, List, Optional, Union
from pydantic import ConfigDict, Field, field_validator
@ -68,7 +67,7 @@ class AudioTranscriptionConfig(FrigateBaseModel):
title="Model size",
description="Model size to use for offline audio event transcription.",
)
live_enabled: Optional[bool] = Field(
live_enabled: bool | None = Field(
default=False,
title="Live transcription",
description="Enable streaming live transcription for audio as it is received.",
@ -98,7 +97,7 @@ class CustomClassificationStateCameraConfig(FrigateBaseModel):
class CustomClassificationStateConfig(FrigateBaseModel):
cameras: Dict[str, CustomClassificationStateCameraConfig] = Field(
cameras: dict[str, CustomClassificationStateCameraConfig] = Field(
title="Classification cameras",
description="Per-camera crop and settings for running state classification.",
)
@ -160,7 +159,7 @@ class ClassificationConfig(FrigateBaseModel):
title="Bird classification config",
description="Settings specific to bird classification models.",
)
custom: Dict[str, CustomClassificationConfig] = Field(
custom: dict[str, CustomClassificationConfig] = Field(
default={},
title="Custom Classification Models",
description="Configuration for custom classification models used for objects or state detection.",
@ -173,12 +172,12 @@ class SemanticSearchConfig(FrigateBaseModel):
title="Enable semantic search",
description="Enable or disable the semantic search feature.",
)
reindex: Optional[bool] = Field(
reindex: bool | None = Field(
default=False,
title="Reindex on startup",
description="Trigger a full reindex of historical tracked objects into the embeddings database.",
)
model: Optional[Union[SemanticSearchModelEnum, str]] = Field(
model: SemanticSearchModelEnum | str | None = Field(
default=SemanticSearchModelEnum.jinav1,
title="Semantic search model or GenAI provider name",
description="The embeddings model to use for semantic search (for example 'jinav1'), or the name of a GenAI provider with the embeddings role.",
@ -199,7 +198,7 @@ class SemanticSearchConfig(FrigateBaseModel):
title="Model size",
description="Select model size; 'small' runs on CPU and 'large' typically requires GPU.",
)
device: Optional[str] = Field(
device: str | None = Field(
default=None,
title="Device",
description="This is an override, to target a specific device. See https://onnxruntime.ai/docs/execution-providers/ for more information",
@ -207,7 +206,7 @@ class SemanticSearchConfig(FrigateBaseModel):
class TriggerConfig(FrigateBaseModel):
friendly_name: Optional[str] = Field(
friendly_name: str | None = Field(
None,
title="Friendly name",
description="Optional friendly name displayed in the UI for this trigger.",
@ -233,7 +232,7 @@ class TriggerConfig(FrigateBaseModel):
gt=0.0,
le=1.0,
)
actions: List[TriggerAction] = Field(
actions: list[TriggerAction] = Field(
default=[],
title="Trigger actions",
description="List of actions to execute when trigger matches (notification, sub_label, attribute).",
@ -243,7 +242,7 @@ class TriggerConfig(FrigateBaseModel):
class CameraSemanticSearchConfig(FrigateBaseModel):
triggers: Dict[str, TriggerConfig] = Field(
triggers: dict[str, TriggerConfig] = Field(
default={},
title="Triggers",
description="Actions and matching criteria for camera-specific semantic search triggers.",
@ -307,7 +306,7 @@ class FaceRecognitionConfig(FrigateBaseModel):
title="Blur confidence filter",
description="Adjust confidence scores based on image blur to reduce false positives for poor quality faces.",
)
device: Optional[str] = Field(
device: str | None = Field(
default=None,
title="Device",
description="This is an override, to target a specific device. See https://onnxruntime.ai/docs/execution-providers/ for more information",
@ -369,7 +368,7 @@ class LicensePlateRecognitionConfig(FrigateBaseModel):
title="Min plate length",
description="Minimum number of characters a recognized plate must contain to be considered valid.",
)
format: Optional[str] = Field(
format: str | None = Field(
default=None,
title="Plate format regex",
description="Optional regex to validate recognized plate strings against an expected format.",
@ -380,7 +379,7 @@ class LicensePlateRecognitionConfig(FrigateBaseModel):
description="Number of character mismatches allowed when comparing detected plates to known plates.",
ge=0,
)
known_plates: Optional[Dict[str, List[str]]] = Field(
known_plates: dict[str, list[str]] | None = Field(
default={},
title="Known plates",
description="List of plates or regexes to specially track or alert on.",
@ -397,12 +396,12 @@ class LicensePlateRecognitionConfig(FrigateBaseModel):
title="Save debug plates",
description="Save plate crop images for debugging LPR performance.",
)
device: Optional[str] = Field(
device: str | None = Field(
default=None,
title="Device",
description="This is an override, to target a specific device. See https://onnxruntime.ai/docs/execution-providers/ for more information",
)
replace_rules: List[ReplaceRule] = Field(
replace_rules: list[ReplaceRule] = Field(
default_factory=list,
title="Replacement rules",
description="Regex replacement rules used to normalize detected plate strings before matching.",
@ -443,10 +442,10 @@ class CameraAudioTranscriptionConfig(FrigateBaseModel):
title="Enable transcription",
description="Enable or disable manually triggered audio event transcription.",
)
enabled_in_config: Optional[bool] = Field(
enabled_in_config: bool | None = Field(
default=None, title="Original transcription state"
)
live_enabled: Optional[bool] = Field(
live_enabled: bool | None = Field(
default=False,
title="Live transcription",
description="Enable streaming live transcription for audio as it is received.",

27
frigate/config/config.py
View File

@ -4,7 +4,7 @@ import io
import json
import logging
import os
from typing import Any, Dict, Optional
from typing import Any, Self
import numpy as np
from pydantic import (
@ -17,7 +17,6 @@ from pydantic import (
model_validator,
)
from ruamel.yaml import YAML
from typing_extensions import Self
from frigate.const import REGEX_JSON
from frigate.detectors import DetectorConfig, ModelConfig
@ -174,7 +173,7 @@ class RuntimeMotionConfig(MotionConfig):
class RuntimeFilterConfig(FilterConfig):
"""Runtime version of FilterConfig with rasterized masks."""
rasterized_mask: Optional[np.ndarray] = Field(default=None, exclude=True)
rasterized_mask: np.ndarray | None = Field(default=None, exclude=True)
def __init__(self, **config):
frame_shape = config.get("frame_shape", (1, 1))
@ -293,7 +292,7 @@ def verify_recording_segments_setup_with_reasonable_time(
raise ValueError(
f"Camera {camera_config.name} has no segment_time in \
recording output args, segment args are required for record."
)
) from None
if int(record_args[seg_arg_index + 1]) > 60:
raise ValueError(
@ -420,7 +419,7 @@ def verify_lpr_and_face(
class FrigateConfig(FrigateBaseModel):
version: Optional[str] = Field(
version: str | None = Field(
default=None,
title="Current config version",
description="Numeric or string version of the active configuration to help detect migrations or format changes.",
@ -496,7 +495,7 @@ class FrigateConfig(FrigateBaseModel):
)
# Detector config
detectors: Dict[str, BaseDetectorConfig] = Field(
detectors: dict[str, BaseDetectorConfig] = Field(
default=DEFAULT_DETECTORS,
title="Detector hardware",
description="Configuration for object detectors (CPU, GPU, ONNX backends) and any detector-specific model settings.",
@ -508,14 +507,14 @@ class FrigateConfig(FrigateBaseModel):
)
# GenAI config (named provider configs: name -> GenAIConfig)
genai: Dict[str, GenAIConfig] = Field(
genai: dict[str, GenAIConfig] = Field(
default_factory=dict,
title="Generative AI configuration",
description="Settings for integrated generative AI providers used to generate object descriptions and review summaries.",
)
# Camera config
cameras: Dict[str, CameraConfig] = Field(title="Cameras", description="Cameras")
cameras: dict[str, CameraConfig] = Field(title="Cameras", description="Cameras")
audio: AudioConfig = Field(
default_factory=AudioConfig,
title="Audio detection",
@ -541,7 +540,7 @@ class FrigateConfig(FrigateBaseModel):
title="Live playback",
description="Settings to control the jsmpeg live stream resolution and quality. This does not affect restreamed cameras that use go2rtc for live view.",
)
motion: Optional[MotionConfig] = Field(
motion: MotionConfig | None = Field(
default=None,
title="Motion detection",
description="Default motion detection settings applied to cameras unless overridden per-camera.",
@ -599,19 +598,19 @@ class FrigateConfig(FrigateBaseModel):
description="License plate recognition settings including detection thresholds, formatting, and known plates.",
)
camera_groups: Dict[str, CameraGroupConfig] = Field(
camera_groups: dict[str, CameraGroupConfig] = Field(
default_factory=dict,
title="Camera groups",
description="Configuration for named camera groups used to organize cameras in the UI.",
)
profiles: Dict[str, ProfileDefinitionConfig] = Field(
profiles: dict[str, ProfileDefinitionConfig] = Field(
default_factory=dict,
title="Profiles",
description="Named profile definitions with friendly names. Camera profiles must reference names defined here.",
)
active_profile: Optional[str] = Field(
active_profile: str | None = Field(
default=None,
title="Active profile",
description="Currently active profile name. Runtime-only, not persisted in YAML.",
@ -1054,7 +1053,7 @@ class FrigateConfig(FrigateBaseModel):
@field_validator("cameras")
@classmethod
def ensure_zones_and_cameras_have_different_names(cls, v: Dict[str, CameraConfig]):
def ensure_zones_and_cameras_have_different_names(cls, v: dict[str, CameraConfig]):
zones = [zone for camera in v.values() for zone in camera.zones.keys()]
for zone in zones:
if zone in v.keys():
@ -1136,7 +1135,7 @@ class FrigateConfig(FrigateBaseModel):
@classmethod
def parse_object(
cls, obj: Any, *, plus_api: Optional[PlusApi] = None, install: bool = False
cls, obj: Any, *, plus_api: PlusApi | None = None, install: bool = False
):
return cls.model_validate(
obj, context={"plus_api": plus_api, "install": install}

3
frigate/config/logger.py
View File

@ -1,5 +1,6 @@
from typing import Self
from pydantic import Field, ValidationInfo, model_validator
from typing_extensions import Self
from frigate.log import LogLevel, apply_log_levels

15
frigate/config/mqtt.py
View File

@ -1,7 +1,6 @@
from typing import Optional
from typing import Self
from pydantic import Field, ValidationInfo, model_validator
from typing_extensions import Self
from frigate.const import FREQUENCY_STATS_POINTS
@ -43,33 +42,33 @@ class MqttConfig(FrigateBaseModel):
title="Stats interval",
description="Interval in seconds for publishing system and camera stats to MQTT.",
)
user: Optional[EnvString] = Field(
user: EnvString | None = Field(
default=None,
title="MQTT username",
description="Optional MQTT username; can be provided via environment variables or secrets.",
)
password: Optional[EnvString] = Field(
password: EnvString | None = Field(
default=None,
title="MQTT password",
description="Optional MQTT password; can be provided via environment variables or secrets.",
validate_default=True,
)
tls_ca_certs: Optional[str] = Field(
tls_ca_certs: str | None = Field(
default=None,
title="TLS CA certs",
description="Path to CA certificate for TLS connections to the broker (for self-signed certs).",
)
tls_client_cert: Optional[str] = Field(
tls_client_cert: str | None = Field(
default=None,
title="Client cert",
description="Client certificate path for TLS mutual authentication; do not set user/password when using client certs.",
)
tls_client_key: Optional[str] = Field(
tls_client_key: str | None = Field(
default=None,
title="Client key",
description="Private key path for the client certificate.",
)
tls_insecure: Optional[bool] = Field(
tls_insecure: bool | None = Field(
default=None,
title="TLS insecure",
description="Allow insecure TLS connections by skipping hostname verification (not recommended).",

6
frigate/config/network.py
View File

@ -1,5 +1,3 @@
from typing import Union
from pydantic import Field
from .base import FrigateBaseModel
@ -16,12 +14,12 @@ class IPv6Config(FrigateBaseModel):
class ListenConfig(FrigateBaseModel):
internal: Union[int, str] = Field(
internal: int | str = Field(
default=5000,
title="Internal port",
description="Internal listening port for Frigate (default 5000).",
)
external: Union[int, str] = Field(
external: int | str = Field(
default=8971,
title="External port",
description="External listening port for Frigate (default 8971).",

17
frigate/config/profile_manager.py
View File

@ -3,9 +3,10 @@
import copy
import json
import logging
from datetime import datetime, timezone
from collections.abc import Callable
from datetime import UTC, datetime
from pathlib import Path
from typing import Any, Callable, Optional
from typing import Any
from frigate.config.camera.updater import (
CameraConfigUpdateEnum,
@ -169,9 +170,9 @@ class ProfileManager:
def activate_profile(
self,
profile_name: Optional[str],
profile_name: str | None,
clear_runtime_overrides: bool = True,
) -> Optional[str]:
) -> str | None:
"""Activate a profile by name, or deactivate if None.
Args:
@ -256,7 +257,7 @@ class ProfileManager:
def _apply_profile_overrides(
self, profile_name: str, changed: dict[str, set[str]]
) -> Optional[str]:
) -> str | None:
"""Apply profile overrides for all cameras that have the named profile."""
for cam_name, cam_config in self.config.cameras.items():
profile = cam_config.profiles.get(profile_name)
@ -358,14 +359,14 @@ class ProfileManager:
retain=True,
)
def _persist_active_profile(self, profile_name: Optional[str]) -> None:
def _persist_active_profile(self, profile_name: str | None) -> None:
"""Persist the active profile state to disk as JSON."""
try:
data = self._load_persisted_data()
data["active"] = profile_name
if profile_name is not None:
data.setdefault("last_activated", {})[profile_name] = datetime.now(
timezone.utc
UTC
).timestamp()
PERSISTENCE_FILE.write_text(json.dumps(data))
except OSError:
@ -384,7 +385,7 @@ class ProfileManager:
return {"active": None, "last_activated": {}}
@staticmethod
def load_persisted_profile() -> Optional[str]:
def load_persisted_profile() -> str | None:
"""Load the persisted active profile name from disk."""
data = ProfileManager._load_persisted_data()
name = data.get("active")

12
frigate/config/proxy.py
View File

@ -1,5 +1,3 @@
from typing import Optional
from pydantic import Field, field_validator
from .base import FrigateBaseModel
@ -19,7 +17,7 @@ class HeaderMappingConfig(FrigateBaseModel):
title="Role header",
description="Header containing the authenticated user's role or groups from the upstream proxy.",
)
role_map: Optional[dict[str, list[str]]] = Field(
role_map: dict[str, list[str]] | None = Field(
default_factory=dict,
title=("Role mapping"),
description="Map upstream group values to Frigate roles (for example map admin groups to the admin role).",
@ -32,22 +30,22 @@ class ProxyConfig(FrigateBaseModel):
title="Header mapping",
description="Map incoming proxy headers to Frigate user and role fields for proxy-based auth.",
)
logout_url: Optional[str] = Field(
logout_url: str | None = Field(
default=None,
title="Logout URL",
description="URL to redirect users to when logging out via the proxy.",
)
auth_secret: Optional[EnvString] = Field(
auth_secret: EnvString | None = Field(
default=None,
title="Proxy secret",
description="Optional secret checked against the X-Proxy-Secret header to verify trusted proxies.",
)
default_role: Optional[str] = Field(
default_role: str | None = Field(
default="viewer",
title="Default role",
description="Default role assigned to proxy-authenticated users when no role mapping applies.",
)
separator: Optional[str] = Field(
separator: str | None = Field(
default=",",
title="Separator character",
description="Character used to split multiple values provided in proxy headers.",

4
frigate/config/telemetry.py
View File

@ -1,5 +1,3 @@
from typing import Optional
from pydantic import Field
from .base import FrigateBaseModel
@ -23,7 +21,7 @@ class StatsConfig(FrigateBaseModel):
title="Network bandwidth",
description="Enable per-process network bandwidth monitoring for camera ffmpeg processes and detectors (requires capabilities).",
)
intel_gpu_device: Optional[str] = Field(
intel_gpu_device: str | None = Field(
default=None,
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.",

3
frigate/config/ui.py
View File

@ -1,5 +1,4 @@
from enum import Enum
from typing import Optional
from pydantic import Field
@ -20,7 +19,7 @@ class UnitSystemEnum(str, Enum):
class UIConfig(FrigateBaseModel):
timezone: Optional[str] = Field(
timezone: str | None = Field(
default=None,
title="Timezone",
description="Optional timezone to display across the UI (defaults to browser local time if unset).",

40
frigate/data_processing/common/license_plate/mixin.py
View File

@ -10,7 +10,7 @@ import random
import re
import string
from pathlib import Path
from typing import Any, List, Tuple
from typing import Any
import cv2
import numpy as np
@ -86,7 +86,7 @@ class LicensePlateProcessingMixin:
self.similarity_threshold = 0.8
self.cluster_threshold = 0.85
def _detect(self, image: np.ndarray, debug_frame_id: int) -> List[np.ndarray]:
def _detect(self, image: np.ndarray, debug_frame_id: int) -> list[np.ndarray]:
"""
Detect possible areas of text in the input image by first resizing and normalizing it,
running a detection model, and filtering out low-probability regions.
@ -132,8 +132,8 @@ class LicensePlateProcessingMixin:
return self._filter_polygon(boxes, (h, w)) # type: ignore[return-value,arg-type]
def _classify(
self, images: List[np.ndarray]
) -> Tuple[List[np.ndarray], List[Tuple[str, float]]] | None:
self, images: list[np.ndarray]
) -> tuple[list[np.ndarray], list[tuple[str, float]]] | None:
"""
Classify the orientation or category of each detected license plate.
@ -163,8 +163,8 @@ class LicensePlateProcessingMixin:
return self._process_classification_output(images, outputs)
def _recognize(
self, camera: str, images: List[np.ndarray]
) -> Tuple[List[str], List[List[float]]]:
self, camera: str, images: list[np.ndarray]
) -> tuple[list[str], list[list[float]]]:
"""
Recognize the characters on the detected license plates using the recognition model.
@ -205,7 +205,7 @@ class LicensePlateProcessingMixin:
def _process_license_plate(
self, camera: str, id: str, image: np.ndarray, debug_frame_id: int
) -> Tuple[List[str], List[List[float]], List[int]]:
) -> tuple[list[str], list[list[float]], list[int]]:
"""
Complete pipeline for detecting, classifying, and recognizing license plates in the input image.
Combines multi-line plates into a single plate string, grouping boxes by vertical alignment and ordering top to bottom,
@ -469,11 +469,11 @@ class LicensePlateProcessingMixin:
def _merge_nearby_boxes(
self,
boxes: List[np.ndarray],
boxes: list[np.ndarray],
plate_width: float,
gap_fraction: float = 0.1,
min_overlap_fraction: float = -0.2,
) -> List[np.ndarray]:
) -> list[np.ndarray]:
"""
Merge bounding boxes that are likely part of the same license plate based on proximity,
with a dynamic max_gap based on the provided width of the entire license plate.
@ -555,7 +555,7 @@ class LicensePlateProcessingMixin:
def _boxes_from_bitmap(
self, output: np.ndarray, mask: np.ndarray, dest_width: int, dest_height: int
) -> Tuple[np.ndarray, List[float]]:
) -> tuple[np.ndarray, list[float]]:
"""
Process the binary mask to extract bounding boxes and associated confidence scores.
@ -620,7 +620,7 @@ class LicensePlateProcessingMixin:
return np.array(boxes, dtype="int32"), scores
@staticmethod
def _get_min_boxes(contour: np.ndarray) -> Tuple[List[Tuple[float, float]], float]:
def _get_min_boxes(contour: np.ndarray) -> tuple[list[tuple[float, float]], float]:
"""
Calculate the minimum bounding box (rotated rectangle) for a given contour.
@ -659,7 +659,7 @@ class LicensePlateProcessingMixin:
return cv2.mean(bitmap[y1 : y2 + 1, x1 : x2 + 1], mask)[0]
@staticmethod
def _expand_box(points: List[Tuple[float, float]]) -> np.ndarray:
def _expand_box(points: list[tuple[float, float]]) -> np.ndarray:
"""
Expand a polygonal shape slightly by a factor determined by the area-to-perimeter ratio.
@ -677,7 +677,7 @@ class LicensePlateProcessingMixin:
return expanded
def _filter_polygon(
self, points: List[np.ndarray], shape: Tuple[int, int]
self, points: list[np.ndarray], shape: tuple[int, int]
) -> np.ndarray:
"""
Filter a set of polygons to include only valid ones that fit within an image shape
@ -839,8 +839,8 @@ class LicensePlateProcessingMixin:
return padded_image
def _process_classification_output(
self, images: List[np.ndarray], outputs: List[np.ndarray]
) -> Tuple[List[np.ndarray], List[Tuple[str, float]]]:
self, images: list[np.ndarray], outputs: list[np.ndarray]
) -> tuple[list[np.ndarray], list[tuple[str, float]]]:
"""
Process the classification model output by matching labels with confidence scores.
@ -1095,8 +1095,8 @@ class LicensePlateProcessingMixin:
return None # No detection above the threshold
def _get_cluster_rep(
self, plates: List[dict]
) -> Tuple[str, float, List[float], int]:
self, plates: list[dict]
) -> tuple[str, float, list[float], int]:
"""
Cluster plate variants and select the representative from the best cluster.
"""
@ -1704,7 +1704,7 @@ class CTCDecoder:
"""
self.characters = []
if character_dict_path and os.path.exists(character_dict_path):
with open(character_dict_path, "r", encoding="utf-8") as f:
with open(character_dict_path, encoding="utf-8") as f:
self.characters = (
["blank"] + [line.strip() for line in f if line.strip()] + [" "]
)
@ -1812,8 +1812,8 @@ class CTCDecoder:
self.char_map = {i: char for i, char in enumerate(self.characters)}
def __call__(
self, outputs: List[np.ndarray]
) -> Tuple[List[str], List[List[float]]]:
self, outputs: list[np.ndarray]
) -> tuple[list[str], list[list[float]]]:
"""
Decode a batch of model outputs into character sequences and their confidence scores.

9
frigate/data_processing/post/audio_transcription.py
View File

@ -4,7 +4,7 @@ import logging
import os
import threading
import time
from typing import Any, Optional
from typing import Any
from peewee import DoesNotExist
@ -142,7 +142,7 @@ class AudioTranscriptionPostProcessor(PostProcessorApi):
except Exception as e:
logger.error(f"Error in audio transcription post-processing: {e}")
def __transcribe_audio(self, audio_data: bytes) -> Optional[str]:
def __transcribe_audio(self, audio_data: bytes) -> str | None:
"""Transcribe WAV audio data using faster-whisper."""
if not self.recognizer:
logger.debug("Recognizer not initialized")
@ -168,8 +168,9 @@ class AudioTranscriptionPostProcessor(PostProcessorApi):
return None
logger.debug(
"Detected language '%s' with probability %f"
% (info.language, info.language_probability)
"Detected language '%s' with probability %f",
info.language,
info.language_probability,
)
return text

6
frigate/data_processing/post/license_plate.py
View File

@ -102,10 +102,8 @@ class LicensePlatePostProcessor(LicensePlateProcessingMixin, PostProcessorApi):
Recordings.start_time,
)
.where(
(
(frame_time >= Recordings.start_time)
& (frame_time <= Recordings.end_time)
)
(frame_time >= Recordings.start_time)
& (frame_time <= Recordings.end_time)
)
.where(Recordings.camera == camera_name)
.order_by(Recordings.start_time.desc())

2
frigate/data_processing/post/semantic_trigger.py
View File

@ -55,7 +55,7 @@ class SemanticTriggerProcessor(PostProcessorApi):
# load stats from disk
try:
with open(os.path.join(CONFIG_DIR, ".search_stats.json"), "r") as f:
with open(os.path.join(CONFIG_DIR, ".search_stats.json")) as f:
data = json.loads(f.read())
self.thumb_stats.from_dict(data["thumb_stats"])
self.desc_stats.from_dict(data["desc_stats"])

3
frigate/data_processing/real_time/api.py
View File

@ -4,9 +4,10 @@ import logging
import threading
from abc import ABC, abstractmethod
from collections import deque
from collections.abc import Callable
from concurrent.futures import Future
from queue import Empty, Full, Queue
from typing import Any, Callable
from typing import Any
import numpy as np

6
frigate/data_processing/real_time/audio_transcription.py
View File

@ -4,7 +4,7 @@ import logging
import os
import queue
import threading
from typing import Any, Optional
from typing import Any
import numpy as np
@ -75,9 +75,7 @@ class AudioTranscriptionRealTimeProcessor(RealTimeProcessorApi):
f"Failed to initialize live streaming audio transcription: {e}"
)
def __process_audio_stream(
self, audio_data: np.ndarray
) -> Optional[tuple[str, bool]]:
def __process_audio_stream(self, audio_data: np.ndarray) -> tuple[str, bool] | None:
if (
self.model_runner.model is None
and self.config.audio_transcription.model_size == "small"

4
frigate/data_processing/real_time/face.py
View File

@ -7,7 +7,7 @@ import logging
import os
import shutil
from pathlib import Path
from typing import Any, Optional
from typing import Any
import cv2
import numpy as np
@ -219,7 +219,7 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
logger.debug("Not processing due to hitting max rec attempts.")
return
face: Optional[dict[str, Any]] = None
face: dict[str, Any] | None = None
if self.requires_face_detection:
logger.debug("Running manual face detection.")

2
frigate/data_processing/real_time/whisper_online.py
View File

@ -1053,7 +1053,7 @@ if __name__ == "__main__":
SAMPLING_RATE = 16000
duration = len(load_audio(audio_path)) / SAMPLING_RATE
logger.info("Audio duration is: %2.2f seconds" % duration)
logger.info("Audio duration is: %2.2f seconds", duration)
asr, online = asr_factory(args, logfile=logfile)
if args.vac:

2
frigate/debug_replay.py
View File

@ -131,7 +131,7 @@ class DebugReplayManager:
config_file = find_config_file()
yaml_parser = YAML()
with open(config_file, "r") as f:
with open(config_file) as f:
config_data = yaml_parser.load(f)
if "cameras" not in config_data or config_data["cameras"] is None:

3
frigate/detectors/detection_api.py
View File

@ -1,6 +1,5 @@
import logging
from abc import ABC, abstractmethod
from typing import List
import numpy as np
@ -11,7 +10,7 @@ logger = logging.getLogger(__name__)
class DetectionApi(ABC):
type_key: str
supported_models: List[ModelTypeEnum]
supported_models: list[ModelTypeEnum]
@abstractmethod
def __init__(self, detector_config: BaseDetectorConfig):

2
frigate/detectors/detection_runners.py
View File

@ -491,7 +491,7 @@ class RKNNModelRunner(BaseModelRunner):
except ImportError:
logger.error("RKNN Lite not available")
raise ImportError("RKNN Lite not available")
raise ImportError("RKNN Lite not available") from None
except Exception as e:
logger.error(f"Error loading RKNN model: {e}")
raise

24
frigate/detectors/detector_config.py
View File

@ -3,7 +3,7 @@ import json
import logging
import os
from enum import Enum
from typing import Any, Dict, Optional, Tuple
from typing import Any
import requests
from pydantic import BaseModel, ConfigDict, Field
@ -45,12 +45,12 @@ class ModelTypeEnum(str, Enum):
class ModelConfig(BaseModel):
path: Optional[str] = Field(
path: str | None = Field(
None,
title="Custom object detector model path",
description="Path to a custom detection model file (or plus://<model_id> for Frigate+ models).",
)
labelmap_path: Optional[str] = Field(
labelmap_path: str | None = Field(
None,
title="Label map for custom object detector",
description="Path to a labelmap file that maps numeric classes to string labels for the detector.",
@ -65,12 +65,12 @@ class ModelConfig(BaseModel):
title="Object detection model input height",
description="Height of the model input tensor in pixels.",
)
labelmap: Dict[int, str] = Field(
labelmap: dict[int, str] = Field(
default_factory=dict,
title="Labelmap customization",
description="Overrides or remapping entries to merge into the standard labelmap.",
)
attributes_map: Dict[str, list[str]] = Field(
attributes_map: dict[str, list[str]] = Field(
default=DEFAULT_ATTRIBUTE_LABEL_MAP,
title="Map of object labels to their attribute labels",
description="Mapping from object labels to attribute labels used to attach metadata (for example 'car' -> ['license_plate']).",
@ -95,18 +95,18 @@ class ModelConfig(BaseModel):
title="Object Detection Model Type",
description="Detector model architecture type (ssd, yolox, yolonas) used by some detectors for optimization.",
)
_merged_labelmap: Optional[Dict[int, str]] = PrivateAttr()
_colormap: Dict[int, Tuple[int, int, int]] = PrivateAttr()
_merged_labelmap: dict[int, str] | None = PrivateAttr()
_colormap: dict[int, tuple[int, int, int]] = PrivateAttr()
_all_attributes: list[str] = PrivateAttr()
_all_attribute_logos: list[str] = PrivateAttr()
_model_hash: str = PrivateAttr()
@property
def merged_labelmap(self) -> Dict[int, str]:
def merged_labelmap(self) -> dict[int, str]:
return self._merged_labelmap
@property
def colormap(self) -> Dict[int, Tuple[int, int, int]]:
def colormap(self) -> dict[int, tuple[int, int, int]]:
return self._colormap
@property
@ -171,7 +171,7 @@ class ModelConfig(BaseModel):
with open(model_info_path, "w") as f:
json.dump(model_info, f)
else:
with open(model_info_path, "r") as f:
with open(model_info_path) as f:
model_info: dict[str, Any] = json.load(f)
if detector and detector not in model_info["supportedDetectors"]:
@ -240,12 +240,12 @@ class BaseDetectorConfig(BaseModel):
title="Detector Type",
description="Type of detector to use for object detection (for example 'cpu', 'edgetpu', 'openvino').",
)
model: Optional[ModelConfig] = Field(
model: ModelConfig | None = Field(
default=None,
title="Detector specific model configuration",
description="Detector-specific model configuration options (path, input size, etc.).",
)
model_path: Optional[str] = Field(
model_path: str | None = Field(
default=None,
title="Detector specific model path",
description="File path to the detector model binary if required by the chosen detector.",

5
frigate/detectors/detector_types.py
View File

@ -2,10 +2,9 @@ import importlib
import logging
import pkgutil
from enum import Enum
from typing import Union
from typing import Annotated, Union
from pydantic import Field
from typing_extensions import Annotated
from . import plugins
from .detection_api import DetectionApi
@ -37,6 +36,6 @@ class StrEnum(str, Enum):
DetectorTypeEnum = StrEnum("DetectorTypeEnum", {k: k for k in api_types})
DetectorConfig = Annotated[
Union[tuple(BaseDetectorConfig.__subclasses__())],
Union[tuple(BaseDetectorConfig.__subclasses__())], # noqa: UP007
Field(discriminator="type"),
]

3
frigate/detectors/plugins/axengine.py
View File

@ -39,8 +39,7 @@ class Axengine(DetectionApi):
try:
import axengine as axe
except ModuleNotFoundError:
raise ImportError("AXEngine is not installed.")
return
raise ImportError("AXEngine is not installed.") from None
logger.info("__init__ axengine")
super().__init__(config)

2
frigate/detectors/plugins/cpu_tfl.py
View File

@ -1,7 +1,7 @@
import logging
from typing import Literal
from pydantic import ConfigDict, Field
from typing_extensions import Literal
from frigate.detectors.detection_api import DetectionApi
from frigate.detectors.detector_config import BaseDetectorConfig

2
frigate/detectors/plugins/deepstack.py
View File

@ -1,11 +1,11 @@
import io
import logging
from typing import Literal
import numpy as np
import requests
from PIL import Image
from pydantic import ConfigDict, Field
from typing_extensions import Literal
from frigate.detectors.detection_api import DetectionApi
from frigate.detectors.detector_config import BaseDetectorConfig

4
frigate/detectors/plugins/degirum.py
View File

@ -1,9 +1,9 @@
import logging
import queue
from typing import Literal
import numpy as np
from pydantic import ConfigDict, Field
from typing_extensions import Literal
from frigate.detectors.detection_api import DetectionApi
from frigate.detectors.detector_config import BaseDetectorConfig
@ -46,7 +46,7 @@ class DGDetector(DetectionApi):
try:
import degirum as dg
except ModuleNotFoundError:
raise ImportError("Unable to import DeGirum detector.")
raise ImportError("Unable to import DeGirum detector.") from None
self._queue = queue.Queue()
self._zoo = dg.connect(

2
frigate/detectors/plugins/edgetpu_tfl.py
View File

@ -1,11 +1,11 @@
import logging
import math
import os
from typing import Literal
import cv2
import numpy as np
from pydantic import ConfigDict, Field
from typing_extensions import Literal
from frigate.detectors.detection_api import DetectionApi
from frigate.detectors.detector_config import BaseDetectorConfig, ModelTypeEnum

19
frigate/detectors/plugins/hailo8l.py
View File

@ -4,12 +4,11 @@ import subprocess
import threading
import urllib.request
from functools import partial
from typing import Dict, List, Optional, Tuple
from typing import Literal
import cv2
import numpy as np
from pydantic import ConfigDict, Field
from typing_extensions import Literal
from frigate.const import MODEL_CACHE_DIR
from frigate.detectors.detection_api import DetectionApi
@ -83,8 +82,8 @@ class HailoAsyncInference:
input_store: RequestStore,
output_store: ResponseStore,
batch_size: int = 1,
input_type: Optional[str] = None,
output_type: Optional[Dict[str, str]] = None,
input_type: str | None = None,
output_type: dict[str, str] | None = None,
send_original_frame: bool = False,
) -> None:
# when importing hailo it activates the driver
@ -125,9 +124,9 @@ class HailoAsyncInference:
def callback(
self,
completion_info,
bindings_list: List,
input_batch: List,
request_ids: List[int],
bindings_list: list,
input_batch: list,
request_ids: list[int],
):
if completion_info.exception:
logger.error(f"Inference error: {completion_info.exception}")
@ -163,7 +162,7 @@ class HailoAsyncInference:
}
return configured_infer_model.create_bindings(output_buffers=output_buffers)
def get_input_shape(self) -> Tuple[int, ...]:
def get_input_shape(self) -> tuple[int, ...]:
return self.hef.get_input_vstream_infos()[0].shape
def run(self) -> None:
@ -304,7 +303,7 @@ class HailoDetector(DetectionApi):
urllib.request.urlretrieve(url, destination)
logger.debug(f"Downloaded model to {destination}")
except Exception as e:
raise RuntimeError(f"Failed to download model from {url}: {str(e)}")
raise RuntimeError(f"Failed to download model from {url}: {str(e)}") from e
def check_and_prepare(self) -> str:
if not os.path.exists(self.cache_dir):
@ -350,7 +349,7 @@ class HailoDetector(DetectionApi):
if not self.inference_thread.is_alive():
raise RuntimeError(
"HailoRT inference thread has stopped, restart required."
)
) from None
return np.zeros((20, 6), dtype=np.float32)

4
frigate/detectors/plugins/memryx.py
View File

@ -5,11 +5,11 @@ import shutil
import urllib.request
import zipfile
from queue import Queue
from typing import Literal
import cv2
import numpy as np
from pydantic import BaseModel, ConfigDict, Field
from typing_extensions import Literal
from frigate.detectors.detection_api import DetectionApi
from frigate.detectors.detector_config import (
@ -61,7 +61,7 @@ class MemryXDetector(DetectionApi):
except ModuleNotFoundError:
raise ImportError(
"MemryX SDK is not installed. Install it and set up MIX environment."
)
) from None
return
# Initialize stop_event as None, will be set later by set_stop_event()

2
frigate/detectors/plugins/onnx.py
View File

@ -1,8 +1,8 @@
import logging
from typing import Literal
import numpy as np
from pydantic import ConfigDict, Field
from typing_extensions import Literal
from frigate.detectors.detection_api import DetectionApi
from frigate.detectors.detection_runners import get_optimized_runner

2
frigate/detectors/plugins/openvino.py
View File

@ -1,9 +1,9 @@
import logging
from typing import Literal
import numpy as np
import openvino as ov
from pydantic import ConfigDict, Field
from typing_extensions import Literal
from frigate.detectors.detection_api import DetectionApi
from frigate.detectors.detection_runners import OpenVINOModelRunner

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