blakeblackshear.frigate/frigate/config.py
2021-06-23 08:15:15 -05:00

1184 lines
36 KiB
Python

from __future__ import annotations
import base64
import dataclasses
import datetime
import json
import logging
import os
from typing import Any, Dict, List, Optional, Tuple, Union
import matplotlib.pyplot as plt
import numpy as np
import voluptuous as vol
import yaml
from frigate.const import BASE_DIR, RECORD_DIR, CLIPS_DIR, CACHE_DIR
from frigate.util import create_mask
logger = logging.getLogger(__name__)
# TODO: Identify what the default format to display timestamps is
DEFAULT_TIME_FORMAT = "%m/%d/%Y %H:%M:%S"
# German Style:
# DEFAULT_TIME_FORMAT = "%d.%m.%Y %H:%M:%S"
DEFAULT_TRACKED_OBJECTS = ["person"]
DEFAULT_RGB_COLOR = {"red": 255, "green": 255, "blue": 255}
DEFAULT_DETECTORS = {"coral": {"type": "edgetpu", "device": "usb"}}
DETECTORS_SCHEMA = vol.Schema(
{
vol.Required(str): {
vol.Required("type", default="edgetpu"): vol.In(["cpu", "edgetpu"]),
vol.Optional("device", default="usb"): str,
vol.Optional("num_threads", default=3): int,
}
}
)
@dataclasses.dataclass(frozen=True)
class DetectorConfig:
type: str
device: str
num_threads: int
@classmethod
def build(cls, config) -> DetectorConfig:
return DetectorConfig(config["type"], config["device"], config["num_threads"])
def to_dict(self) -> Dict[str, Any]:
return dataclasses.asdict(self)
MQTT_SCHEMA = vol.Schema(
{
vol.Required("host"): str,
vol.Optional("port", default=1883): int,
vol.Optional("topic_prefix", default="frigate"): str,
vol.Optional("client_id", default="frigate"): str,
vol.Optional("stats_interval", default=60): int,
vol.Inclusive("user", "auth"): str,
vol.Inclusive("password", "auth"): str,
vol.Optional("tls_ca_certs"): str,
vol.Optional("tls_client_cert"): str,
vol.Optional("tls_client_key"): str,
vol.Optional("tls_insecure"): bool,
}
)
@dataclasses.dataclass(frozen=True)
class MqttConfig:
host: str
port: int
topic_prefix: str
client_id: str
stats_interval: int
user: Optional[str]
password: Optional[str]
tls_ca_certs: Optional[str]
tls_client_cert: Optional[str]
tls_client_key: Optional[str]
tls_insecure: Optional[bool]
@classmethod
def build(cls, config) -> MqttConfig:
return MqttConfig(
config["host"],
config["port"],
config["topic_prefix"],
config["client_id"],
config["stats_interval"],
config.get("user"),
config.get("password"),
config.get("tls_ca_certs"),
config.get("tls_client_cert"),
config.get("tls_client_key"),
config.get("tls_insecure"),
)
def to_dict(self) -> Dict[str, Any]:
return dataclasses.asdict(self)
RETAIN_SCHEMA = vol.Schema(
{vol.Required("default", default=10): int, "objects": {str: int}}
)
@dataclasses.dataclass(frozen=True)
class RetainConfig:
default: int
objects: Dict[str, int]
@classmethod
def build(cls, config, global_config={}) -> RetainConfig:
return RetainConfig(
config.get("default", global_config.get("default")),
config.get("objects", global_config.get("objects", {})),
)
def to_dict(self) -> Dict[str, Any]:
return dataclasses.asdict(self)
CLIPS_SCHEMA = vol.Schema(
{
vol.Optional("max_seconds", default=300): int,
vol.Optional("retain", default={}): RETAIN_SCHEMA,
}
)
@dataclasses.dataclass(frozen=True)
class ClipsConfig:
max_seconds: int
retain: RetainConfig
@classmethod
def build(cls, config) -> ClipsConfig:
return ClipsConfig(
config["max_seconds"],
RetainConfig.build(config["retain"]),
)
def to_dict(self) -> Dict[str, Any]:
return {
"max_seconds": self.max_seconds,
"retain": self.retain.to_dict(),
}
MOTION_SCHEMA = vol.Schema(
{
"mask": vol.Any(str, [str]),
"threshold": vol.Range(min=1, max=255),
"contour_area": int,
"delta_alpha": float,
"frame_alpha": float,
"frame_height": int,
}
)
@dataclasses.dataclass(frozen=True)
class MotionConfig:
raw_mask: Union[str, List[str]]
mask: np.ndarray
threshold: int
contour_area: int
delta_alpha: float
frame_alpha: float
frame_height: int
@classmethod
def build(cls, config, global_config, frame_shape) -> MotionConfig:
raw_mask = config.get("mask")
if raw_mask:
mask = create_mask(frame_shape, raw_mask)
else:
mask = np.zeros(frame_shape, np.uint8)
mask[:] = 255
return MotionConfig(
raw_mask,
mask,
config.get("threshold", global_config.get("threshold", 25)),
config.get("contour_area", global_config.get("contour_area", 100)),
config.get("delta_alpha", global_config.get("delta_alpha", 0.2)),
config.get("frame_alpha", global_config.get("frame_alpha", 0.2)),
config.get(
"frame_height", global_config.get("frame_height", frame_shape[0] // 6)
),
)
def to_dict(self) -> Dict[str, Any]:
return {
"mask": self.raw_mask,
"threshold": self.threshold,
"contour_area": self.contour_area,
"delta_alpha": self.delta_alpha,
"frame_alpha": self.frame_alpha,
"frame_height": self.frame_height,
}
GLOBAL_DETECT_SCHEMA = vol.Schema({"max_disappeared": int})
DETECT_SCHEMA = GLOBAL_DETECT_SCHEMA.extend(
{vol.Optional("enabled", default=True): bool}
)
@dataclasses.dataclass
class DetectConfig:
enabled: bool
max_disappeared: int
@classmethod
def build(cls, config, global_config, camera_fps) -> DetectConfig:
return DetectConfig(
config["enabled"],
config.get(
"max_disappeared", global_config.get("max_disappeared", camera_fps * 5)
),
)
def to_dict(self) -> Dict[str, Any]:
return {
"enabled": self.enabled,
"max_disappeared": self.max_disappeared,
}
ZONE_FILTER_SCHEMA = vol.Schema(
{
str: {
"min_area": int,
"max_area": int,
"threshold": float,
}
}
)
FILTER_SCHEMA = ZONE_FILTER_SCHEMA.extend(
{
str: {
"min_score": float,
"mask": vol.Any(str, [str]),
}
}
)
@dataclasses.dataclass(frozen=True)
class FilterConfig:
min_area: int
max_area: int
threshold: float
min_score: float
mask: Optional[np.ndarray]
raw_mask: Union[str, List[str]]
@classmethod
def build(
cls, config, global_config={}, global_mask=None, frame_shape=None
) -> FilterConfig:
raw_mask = []
if global_mask:
if isinstance(global_mask, list):
raw_mask += global_mask
elif isinstance(global_mask, str):
raw_mask += [global_mask]
config_mask = config.get("mask")
if config_mask:
if isinstance(config_mask, list):
raw_mask += config_mask
elif isinstance(config_mask, str):
raw_mask += [config_mask]
mask = create_mask(frame_shape, raw_mask) if raw_mask else None
return FilterConfig(
min_area=config.get("min_area", global_config.get("min_area", 0)),
max_area=config.get("max_area", global_config.get("max_area", 24000000)),
threshold=config.get("threshold", global_config.get("threshold", 0.7)),
min_score=config.get("min_score", global_config.get("min_score", 0.5)),
mask=mask,
raw_mask=raw_mask,
)
def to_dict(self) -> Dict[str, Any]:
return {
"min_area": self.min_area,
"max_area": self.max_area,
"threshold": self.threshold,
"min_score": self.min_score,
"mask": self.raw_mask,
}
ZONE_SCHEMA = {
str: {
vol.Required("coordinates"): vol.Any(str, [str]),
vol.Optional("filters", default={}): ZONE_FILTER_SCHEMA,
}
}
@dataclasses.dataclass(frozen=True)
class ZoneConfig:
filters: Dict[str, FilterConfig]
coordinates: Union[str, List[str]]
contour: np.ndarray
color: Tuple[int, int, int]
@classmethod
def build(cls, config, color: Tuple[int, int, int]) -> ZoneConfig:
coordinates = config["coordinates"]
if isinstance(coordinates, list):
contour = np.array(
[[int(p.split(",")[0]), int(p.split(",")[1])] for p in coordinates]
)
elif isinstance(coordinates, str):
points = coordinates.split(",")
contour = np.array(
[[int(points[i]), int(points[i + 1])] for i in range(0, len(points), 2)]
)
else:
contour = np.array([])
return ZoneConfig(
{name: FilterConfig.build(c) for name, c in config["filters"].items()},
coordinates,
contour,
color=color,
)
def to_dict(self) -> Dict[str, Any]:
return {
"filters": {k: f.to_dict() for k, f in self.filters.items()},
"coordinates": self.coordinates,
}
def filters_for_all_tracked_objects(object_config):
for tracked_object in object_config.get("track", DEFAULT_TRACKED_OBJECTS):
if not "filters" in object_config:
object_config["filters"] = {}
if not tracked_object in object_config["filters"]:
object_config["filters"][tracked_object] = {}
return object_config
OBJECTS_SCHEMA = vol.Schema(
vol.All(
filters_for_all_tracked_objects,
{
"track": [str],
"mask": vol.Any(str, [str]),
vol.Optional("filters", default={}): FILTER_SCHEMA,
},
)
)
@dataclasses.dataclass(frozen=True)
class ObjectConfig:
track: List[str]
filters: Dict[str, FilterConfig]
raw_mask: Optional[Union[str, List[str]]]
@classmethod
def build(cls, config, global_config, frame_shape) -> ObjectConfig:
track = config.get("track", global_config.get("track", DEFAULT_TRACKED_OBJECTS))
raw_mask = config.get("mask")
return ObjectConfig(
track,
{
name: FilterConfig.build(
config["filters"].get(name, {}),
global_config["filters"].get(name, {}),
raw_mask,
frame_shape,
)
for name in track
},
raw_mask,
)
def to_dict(self) -> Dict[str, Any]:
return {
"track": self.track,
"mask": self.raw_mask,
"filters": {k: f.to_dict() for k, f in self.filters.items()},
}
BIRDSEYE_SCHEMA = vol.Schema(
{
vol.Optional("enabled", default=True): bool,
vol.Optional("width", default=1280): int,
vol.Optional("height", default=720): int,
vol.Optional("quality", default=8): vol.Range(min=1, max=31),
vol.Optional("mode", default="objects"): vol.In(
["objects", "motion", "continuous"]
),
}
)
@dataclasses.dataclass(frozen=True)
class BirdseyeConfig:
enabled: bool
width: int
height: int
quality: int
mode: str
@classmethod
def build(cls, config) -> BirdseyeConfig:
return BirdseyeConfig(
config["enabled"],
config["width"],
config["height"],
config["quality"],
config["mode"],
)
def to_dict(self) -> Dict[str, Any]:
return dataclasses.asdict(self)
FFMPEG_GLOBAL_ARGS_DEFAULT = ["-hide_banner", "-loglevel", "warning"]
FFMPEG_INPUT_ARGS_DEFAULT = [
"-avoid_negative_ts",
"make_zero",
"-fflags",
"+genpts+discardcorrupt",
"-rtsp_transport",
"tcp",
"-stimeout",
"5000000",
"-use_wallclock_as_timestamps",
"1",
]
DETECT_FFMPEG_OUTPUT_ARGS_DEFAULT = ["-f", "rawvideo", "-pix_fmt", "yuv420p"]
RTMP_FFMPEG_OUTPUT_ARGS_DEFAULT = ["-c", "copy", "-f", "flv"]
SAVE_CLIPS_FFMPEG_OUTPUT_ARGS_DEFAULT = [
"-f",
"segment",
"-segment_time",
"10",
"-segment_format",
"mp4",
"-reset_timestamps",
"1",
"-strftime",
"1",
"-c",
"copy",
"-an",
]
RECORD_FFMPEG_OUTPUT_ARGS_DEFAULT = [
"-f",
"segment",
"-segment_time",
"60",
"-segment_format",
"mp4",
"-reset_timestamps",
"1",
"-strftime",
"1",
"-c",
"copy",
"-an",
]
GLOBAL_FFMPEG_SCHEMA = vol.Schema(
{
vol.Optional("global_args", default=FFMPEG_GLOBAL_ARGS_DEFAULT): vol.Any(
str, [str]
),
vol.Optional("hwaccel_args", default=[]): vol.Any(str, [str]),
vol.Optional("input_args", default=FFMPEG_INPUT_ARGS_DEFAULT): vol.Any(
str, [str]
),
vol.Optional("output_args", default={}): {
vol.Optional("detect", default=DETECT_FFMPEG_OUTPUT_ARGS_DEFAULT): vol.Any(
str, [str]
),
vol.Optional("record", default=RECORD_FFMPEG_OUTPUT_ARGS_DEFAULT): vol.Any(
str, [str]
),
vol.Optional(
"clips", default=SAVE_CLIPS_FFMPEG_OUTPUT_ARGS_DEFAULT
): vol.Any(str, [str]),
vol.Optional("rtmp", default=RTMP_FFMPEG_OUTPUT_ARGS_DEFAULT): vol.Any(
str, [str]
),
},
}
)
def each_role_used_once(inputs):
roles = [role for i in inputs for role in i["roles"]]
roles_set = set(roles)
if len(roles) > len(roles_set):
raise ValueError
return inputs
def detect_is_required(inputs):
roles = [role for i in inputs for role in i["roles"]]
if not "detect" in roles:
raise ValueError
return inputs
CAMERA_FFMPEG_SCHEMA = vol.Schema(
{
vol.Required("inputs"): vol.All(
[
{
vol.Required("path"): str,
vol.Required("roles"): ["detect", "clips", "record", "rtmp"],
"global_args": vol.Any(str, [str]),
"hwaccel_args": vol.Any(str, [str]),
"input_args": vol.Any(str, [str]),
}
],
vol.Msg(each_role_used_once, msg="Each input role may only be used once"),
vol.Msg(detect_is_required, msg="The detect role is required"),
),
"global_args": vol.Any(str, [str]),
"hwaccel_args": vol.Any(str, [str]),
"input_args": vol.Any(str, [str]),
"output_args": {
vol.Optional("detect", default=DETECT_FFMPEG_OUTPUT_ARGS_DEFAULT): vol.Any(
str, [str]
),
vol.Optional("record", default=RECORD_FFMPEG_OUTPUT_ARGS_DEFAULT): vol.Any(
str, [str]
),
vol.Optional(
"clips", default=SAVE_CLIPS_FFMPEG_OUTPUT_ARGS_DEFAULT
): vol.Any(str, [str]),
vol.Optional("rtmp", default=RTMP_FFMPEG_OUTPUT_ARGS_DEFAULT): vol.Any(
str, [str]
),
},
}
)
@dataclasses.dataclass(frozen=True)
class CameraFfmpegConfig:
inputs: List[CameraInput]
output_args: Dict[str, List[str]]
@classmethod
def build(cls, config, global_config):
output_args = config.get("output_args", global_config["output_args"])
output_args = {
k: v if isinstance(v, list) else v.split(" ")
for k, v in output_args.items()
}
return CameraFfmpegConfig(
[CameraInput.build(i, config, global_config) for i in config["inputs"]],
output_args,
)
@dataclasses.dataclass(frozen=True)
class CameraInput:
path: str
roles: List[str]
global_args: List[str]
hwaccel_args: List[str]
input_args: List[str]
@classmethod
def build(cls, ffmpeg_input, camera_config, global_config) -> CameraInput:
return CameraInput(
ffmpeg_input["path"],
ffmpeg_input["roles"],
CameraInput._extract_args(
"global_args", ffmpeg_input, camera_config, global_config
),
CameraInput._extract_args(
"hwaccel_args", ffmpeg_input, camera_config, global_config
),
CameraInput._extract_args(
"input_args", ffmpeg_input, camera_config, global_config
),
)
@staticmethod
def _extract_args(name, ffmpeg_input, camera_config, global_config):
args = ffmpeg_input.get(name, camera_config.get(name, global_config[name]))
return args if isinstance(args, list) else args.split(" ")
def ensure_zones_and_cameras_have_different_names(cameras):
zones = [zone for camera in cameras.values() for zone in camera["zones"].keys()]
for zone in zones:
if zone in cameras.keys():
raise ValueError
return cameras
def ensure_timeformat_is_legit(format_string):
datetime.datetime.now().strftime(format_string)
return format_string
RGB_COLOR_SCHEMA = vol.Schema(
{
vol.Required("red"): vol.Range(min=0, max=255),
vol.Required("green"): vol.Range(min=0, max=255),
vol.Required("blue"): vol.Range(min=0, max=255),
}
)
CAMERAS_SCHEMA = vol.Schema(
vol.All(
{
str: {
vol.Required("ffmpeg"): CAMERA_FFMPEG_SCHEMA,
vol.Required("height"): int,
vol.Required("width"): int,
"fps": int,
vol.Optional("best_image_timeout", default=60): int,
vol.Optional("zones", default={}): ZONE_SCHEMA,
vol.Optional("clips", default={}): {
vol.Optional("enabled", default=False): bool,
vol.Optional("pre_capture", default=5): int,
vol.Optional("post_capture", default=5): int,
vol.Optional("required_zones", default=[]): [str],
"objects": [str],
vol.Optional("retain", default={}): RETAIN_SCHEMA,
},
vol.Optional("record", default={}): {
"enabled": bool,
"retain_days": int,
},
vol.Optional("rtmp", default={}): {
vol.Required("enabled", default=True): bool,
},
vol.Optional("snapshots", default={}): {
vol.Optional("enabled", default=False): bool,
vol.Optional("clean_copy", default=True): bool,
vol.Optional("timestamp", default=False): bool,
vol.Optional("bounding_box", default=False): bool,
vol.Optional("crop", default=False): bool,
vol.Optional("required_zones", default=[]): [str],
"height": int,
vol.Optional("retain", default={}): RETAIN_SCHEMA,
},
vol.Optional("mqtt", default={}): {
vol.Optional("enabled", default=True): bool,
vol.Optional("timestamp", default=True): bool,
vol.Optional("bounding_box", default=True): bool,
vol.Optional("crop", default=True): bool,
vol.Optional("height", default=270): int,
vol.Optional("required_zones", default=[]): [str],
},
vol.Optional("objects", default={}): OBJECTS_SCHEMA,
vol.Optional("motion", default={}): MOTION_SCHEMA,
vol.Optional("detect", default={}): DETECT_SCHEMA,
vol.Optional("timestamp_style", default={}): {
vol.Optional("position", default="tl"): vol.In(
["tl", "tr", "bl", "br"]
),
vol.Optional(
"format", default=DEFAULT_TIME_FORMAT
): ensure_timeformat_is_legit,
vol.Optional("color", default=DEFAULT_RGB_COLOR): RGB_COLOR_SCHEMA,
vol.Optional("scale", default=1.0): float,
vol.Optional("thickness", default=2): int,
vol.Optional("effect", default=None): vol.In(
[None, "solid", "shadow"]
),
},
}
},
vol.Msg(
ensure_zones_and_cameras_have_different_names,
msg="Zones cannot share names with cameras",
),
)
)
@dataclasses.dataclass
class CameraSnapshotsConfig:
enabled: bool
clean_copy: bool
timestamp: bool
bounding_box: bool
crop: bool
required_zones: List[str]
height: Optional[int]
retain: RetainConfig
@classmethod
def build(cls, config, global_config) -> CameraSnapshotsConfig:
return CameraSnapshotsConfig(
enabled=config["enabled"],
clean_copy=config["clean_copy"],
timestamp=config["timestamp"],
bounding_box=config["bounding_box"],
crop=config["crop"],
required_zones=config["required_zones"],
height=config.get("height"),
retain=RetainConfig.build(
config["retain"], global_config["snapshots"]["retain"]
),
)
def to_dict(self) -> Dict[str, Any]:
return {
"enabled": self.enabled,
"clean_copy": self.clean_copy,
"timestamp": self.timestamp,
"bounding_box": self.bounding_box,
"crop": self.crop,
"height": self.height,
"retain": self.retain.to_dict(),
"required_zones": self.required_zones,
}
@dataclasses.dataclass
class CameraMqttConfig:
enabled: bool
timestamp: bool
bounding_box: bool
crop: bool
height: int
required_zones: List[str]
@classmethod
def build(cls, config) -> CameraMqttConfig:
return CameraMqttConfig(
config["enabled"],
config["timestamp"],
config["bounding_box"],
config["crop"],
config.get("height"),
config["required_zones"],
)
def to_dict(self) -> Dict[str, Any]:
return dataclasses.asdict(self)
@dataclasses.dataclass
class TimestampStyleConfig:
position: str
format: str
color: Tuple[int, int, int]
scale: float
thickness: int
effect: str
@classmethod
def build(cls, config) -> TimestampStyleConfig:
return TimestampStyleConfig(
config["position"],
config["format"],
(config["color"]["red"], config["color"]["green"], config["color"]["blue"]),
config["scale"],
config["thickness"],
config["effect"],
)
def to_dict(self) -> Dict[str, Any]:
return dataclasses.asdict(self)
@dataclasses.dataclass
class CameraClipsConfig:
enabled: bool
pre_capture: int
post_capture: int
required_zones: List[str]
objects: Optional[List[str]]
retain: RetainConfig
@classmethod
def build(cls, config, global_config) -> CameraClipsConfig:
return CameraClipsConfig(
enabled=config["enabled"],
pre_capture=config["pre_capture"],
post_capture=config["post_capture"],
required_zones=config["required_zones"],
objects=config.get("objects"),
retain=RetainConfig.build(
config["retain"],
global_config["clips"]["retain"],
),
)
def to_dict(self) -> Dict[str, Any]:
return {
"enabled": self.enabled,
"pre_capture": self.pre_capture,
"post_capture": self.post_capture,
"objects": self.objects,
"retain": self.retain.to_dict(),
"required_zones": self.required_zones,
}
@dataclasses.dataclass
class CameraRtmpConfig:
enabled: bool
@classmethod
def build(cls, config) -> CameraRtmpConfig:
return CameraRtmpConfig(config["enabled"])
def to_dict(self) -> Dict[str, Any]:
return dataclasses.asdict(self)
@dataclasses.dataclass(frozen=True)
class CameraConfig:
name: str
ffmpeg: CameraFfmpegConfig
height: int
width: int
fps: Optional[int]
best_image_timeout: int
zones: Dict[str, ZoneConfig]
clips: CameraClipsConfig
record: RecordConfig
rtmp: CameraRtmpConfig
snapshots: CameraSnapshotsConfig
mqtt: CameraMqttConfig
objects: ObjectConfig
motion: MotionConfig
detect: DetectConfig
timestamp_style: TimestampStyleConfig
@property
def frame_shape(self) -> Tuple[int, int]:
return self.height, self.width
@property
def frame_shape_yuv(self) -> Tuple[int, int]:
return self.height * 3 // 2, self.width
@property
def ffmpeg_cmds(self) -> List[Dict[str, List[str]]]:
ffmpeg_cmds = []
for ffmpeg_input in self.ffmpeg.inputs:
ffmpeg_cmd = self._get_ffmpeg_cmd(ffmpeg_input)
if ffmpeg_cmd is None:
continue
ffmpeg_cmds.append({"roles": ffmpeg_input.roles, "cmd": ffmpeg_cmd})
return ffmpeg_cmds
@classmethod
def build(cls, name, config, global_config) -> CameraConfig:
colors = plt.cm.get_cmap("tab10", len(config["zones"]))
zones = {
name: ZoneConfig.build(z, tuple(round(255 * c) for c in colors(idx)[:3]))
for idx, (name, z) in enumerate(config["zones"].items())
}
frame_shape = config["height"], config["width"]
return CameraConfig(
name=name,
ffmpeg=CameraFfmpegConfig.build(config["ffmpeg"], global_config["ffmpeg"]),
height=config["height"],
width=config["width"],
fps=config.get("fps"),
best_image_timeout=config["best_image_timeout"],
zones=zones,
clips=CameraClipsConfig.build(config["clips"], global_config),
record=RecordConfig.build(config["record"], global_config["record"]),
rtmp=CameraRtmpConfig.build(config["rtmp"]),
snapshots=CameraSnapshotsConfig.build(config["snapshots"], global_config),
mqtt=CameraMqttConfig.build(config["mqtt"]),
objects=ObjectConfig.build(
config.get("objects", {}), global_config["objects"], frame_shape
),
motion=MotionConfig.build(
config["motion"], global_config["motion"], frame_shape
),
detect=DetectConfig.build(
config["detect"], global_config["detect"], config.get("fps", 5)
),
timestamp_style=TimestampStyleConfig.build(config["timestamp_style"]),
)
def _get_ffmpeg_cmd(self, ffmpeg_input):
ffmpeg_output_args = []
if "detect" in ffmpeg_input.roles:
ffmpeg_output_args = (
self.ffmpeg.output_args["detect"] + ffmpeg_output_args + ["pipe:"]
)
if self.fps:
ffmpeg_output_args = ["-r", str(self.fps)] + ffmpeg_output_args
if "rtmp" in ffmpeg_input.roles and self.rtmp.enabled:
ffmpeg_output_args = (
self.ffmpeg.output_args["rtmp"]
+ [f"rtmp://127.0.0.1/live/{self.name}"]
+ ffmpeg_output_args
)
if "clips" in ffmpeg_input.roles:
ffmpeg_output_args = (
self.ffmpeg.output_args["clips"]
+ [f"{os.path.join(CACHE_DIR, self.name)}-%Y%m%d%H%M%S.mp4"]
+ ffmpeg_output_args
)
if "record" in ffmpeg_input.roles and self.record.enabled:
ffmpeg_output_args = (
self.ffmpeg.output_args["record"]
+ [f"{os.path.join(RECORD_DIR, self.name)}-%Y%m%d%H%M%S.mp4"]
+ ffmpeg_output_args
)
# if there arent any outputs enabled for this input
if len(ffmpeg_output_args) == 0:
return None
cmd = (
["ffmpeg"]
+ ffmpeg_input.global_args
+ ffmpeg_input.hwaccel_args
+ ffmpeg_input.input_args
+ ["-i", ffmpeg_input.path]
+ ffmpeg_output_args
)
return [part for part in cmd if part != ""]
def to_dict(self) -> Dict[str, Any]:
return {
"name": self.name,
"height": self.height,
"width": self.width,
"fps": self.fps,
"best_image_timeout": self.best_image_timeout,
"zones": {k: z.to_dict() for k, z in self.zones.items()},
"clips": self.clips.to_dict(),
"record": self.record.to_dict(),
"rtmp": self.rtmp.to_dict(),
"snapshots": self.snapshots.to_dict(),
"mqtt": self.mqtt.to_dict(),
"objects": self.objects.to_dict(),
"motion": self.motion.to_dict(),
"detect": self.detect.to_dict(),
"frame_shape": self.frame_shape,
"ffmpeg_cmds": [
{"roles": c["roles"], "cmd": " ".join(c["cmd"])}
for c in self.ffmpeg_cmds
],
"timestamp_style": self.timestamp_style.to_dict(),
}
FRIGATE_CONFIG_SCHEMA = vol.Schema(
{
vol.Optional("database", default={}): {
vol.Optional("path", default=os.path.join(BASE_DIR, "frigate.db")): str
},
vol.Optional("model", default={"width": 320, "height": 320}): {
vol.Required("width"): int,
vol.Required("height"): int,
},
vol.Optional("detectors", default=DEFAULT_DETECTORS): DETECTORS_SCHEMA,
"mqtt": MQTT_SCHEMA,
vol.Optional("logger", default={}): {
vol.Optional("default", default="info"): vol.In(
["info", "debug", "warning", "error", "critical"]
),
vol.Optional("logs", default={}): {
str: vol.In(["info", "debug", "warning", "error", "critical"])
},
},
vol.Optional("snapshots", default={}): {
vol.Optional("retain", default={}): RETAIN_SCHEMA
},
vol.Optional("clips", default={}): CLIPS_SCHEMA,
vol.Optional("record", default={}): {
vol.Optional("enabled", default=False): bool,
vol.Optional("retain_days", default=30): int,
},
vol.Optional("ffmpeg", default={}): GLOBAL_FFMPEG_SCHEMA,
vol.Optional("objects", default={}): OBJECTS_SCHEMA,
vol.Optional("motion", default={}): MOTION_SCHEMA,
vol.Optional("detect", default={}): GLOBAL_DETECT_SCHEMA,
vol.Optional("birdseye", default={}): BIRDSEYE_SCHEMA,
vol.Required("cameras", default={}): CAMERAS_SCHEMA,
vol.Optional("environment_vars", default={}): {str: str},
}
)
@dataclasses.dataclass(frozen=True)
class DatabaseConfig:
path: str
@classmethod
def build(cls, config) -> DatabaseConfig:
return DatabaseConfig(config["path"])
def to_dict(self) -> Dict[str, Any]:
return dataclasses.asdict(self)
@dataclasses.dataclass(frozen=True)
class ModelConfig:
width: int
height: int
@classmethod
def build(cls, config) -> ModelConfig:
return ModelConfig(config["width"], config["height"])
def to_dict(self) -> Dict[str, Any]:
return dataclasses.asdict(self)
@dataclasses.dataclass(frozen=True)
class LoggerConfig:
default: str
logs: Dict[str, str]
@classmethod
def build(cls, config) -> LoggerConfig:
return LoggerConfig(
config["default"].upper(),
{k: v.upper() for k, v in config["logs"].items()},
)
def to_dict(self) -> Dict[str, Any]:
return dataclasses.asdict(self)
@dataclasses.dataclass(frozen=True)
class SnapshotsConfig:
retain: RetainConfig
@classmethod
def build(cls, config) -> SnapshotsConfig:
return SnapshotsConfig(RetainConfig.build(config["retain"]))
def to_dict(self) -> Dict[str, Any]:
return {"retain": self.retain.to_dict()}
@dataclasses.dataclass
class RecordConfig:
enabled: bool
retain_days: int
@classmethod
def build(cls, config, global_config) -> RecordConfig:
return RecordConfig(
config.get("enabled", global_config["enabled"]),
config.get("retain_days", global_config["retain_days"]),
)
def to_dict(self) -> Dict[str, Any]:
return dataclasses.asdict(self)
class FrigateConfig:
def __init__(self, config_file=None, config=None) -> None:
if config is None and config_file is None:
raise ValueError("config or config_file must be defined")
elif not config_file is None:
config = self._load_file(config_file)
config = FRIGATE_CONFIG_SCHEMA(config)
config = self._sub_env_vars(config)
self._database = DatabaseConfig.build(config["database"])
self._model = ModelConfig.build(config["model"])
self._detectors = {
name: DetectorConfig.build(d) for name, d in config["detectors"].items()
}
self._mqtt = MqttConfig.build(config["mqtt"])
self._clips = ClipsConfig.build(config["clips"])
self._snapshots = SnapshotsConfig.build(config["snapshots"])
self._birdseye = BirdseyeConfig.build(config["birdseye"])
self._cameras = {
name: CameraConfig.build(name, c, config)
for name, c in config["cameras"].items()
}
self._logger = LoggerConfig.build(config["logger"])
self._environment_vars = config["environment_vars"]
def _sub_env_vars(self, config):
frigate_env_vars = {
k: v for k, v in os.environ.items() if k.startswith("FRIGATE_")
}
if "password" in config["mqtt"]:
config["mqtt"]["password"] = config["mqtt"]["password"].format(
**frigate_env_vars
)
for camera in config["cameras"].values():
for i in camera["ffmpeg"]["inputs"]:
i["path"] = i["path"].format(**frigate_env_vars)
return config
def _load_file(self, config_file):
with open(config_file) as f:
raw_config = f.read()
if config_file.endswith(".yml"):
config = yaml.safe_load(raw_config)
elif config_file.endswith(".json"):
config = json.loads(raw_config)
return config
def to_dict(self) -> Dict[str, Any]:
return {
"database": self.database.to_dict(),
"model": self.model.to_dict(),
"detectors": {k: d.to_dict() for k, d in self.detectors.items()},
"mqtt": self.mqtt.to_dict(),
"clips": self.clips.to_dict(),
"snapshots": self.snapshots.to_dict(),
"birdseye": self.birdseye.to_dict(),
"cameras": {k: c.to_dict() for k, c in self.cameras.items()},
"logger": self.logger.to_dict(),
"environment_vars": self._environment_vars,
}
@property
def database(self) -> DatabaseConfig:
return self._database
@property
def model(self) -> ModelConfig:
return self._model
@property
def detectors(self) -> Dict[str, DetectorConfig]:
return self._detectors
@property
def logger(self) -> LoggerConfig:
return self._logger
@property
def mqtt(self) -> MqttConfig:
return self._mqtt
@property
def clips(self) -> ClipsConfig:
return self._clips
@property
def snapshots(self) -> SnapshotsConfig:
return self._snapshots
@property
def birdseye(self) -> BirdseyeConfig:
return self._birdseye
@property
def cameras(self) -> Dict[str, CameraConfig]:
return self._cameras
@property
def environment_vars(self):
return self._environment_vars