mirror of
https://github.com/blakeblackshear/frigate.git
synced 2024-11-21 19:07:46 +01:00
815 lines
28 KiB
Python
815 lines
28 KiB
Python
from __future__ import annotations
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from enum import Enum
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import json
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import logging
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import os
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from typing import Dict, List, Optional, Tuple, Union
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import matplotlib.pyplot as plt
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import numpy as np
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from pydantic import BaseModel, Field, validator
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from pydantic.fields import PrivateAttr
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import yaml
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from frigate.const import BASE_DIR, RECORD_DIR, CACHE_DIR
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from frigate.edgetpu import load_labels
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from frigate.util import create_mask, deep_merge
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logger = logging.getLogger(__name__)
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# TODO: Identify what the default format to display timestamps is
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DEFAULT_TIME_FORMAT = "%m/%d/%Y %H:%M:%S"
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# German Style:
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# DEFAULT_TIME_FORMAT = "%d.%m.%Y %H:%M:%S"
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FRIGATE_ENV_VARS = {k: v for k, v in os.environ.items() if k.startswith("FRIGATE_")}
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DEFAULT_TRACKED_OBJECTS = ["person"]
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DEFAULT_DETECTORS = {"coral": {"type": "edgetpu", "device": "usb"}}
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class DetectorTypeEnum(str, Enum):
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edgetpu = "edgetpu"
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cpu = "cpu"
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class DetectorConfig(BaseModel):
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type: DetectorTypeEnum = Field(
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default=DetectorTypeEnum.edgetpu, title="Detector Type"
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)
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device: str = Field(default="usb", title="Device Type")
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num_threads: int = Field(default=3, title="Number of detection threads")
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class MqttConfig(BaseModel):
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host: str = Field(title="MQTT Host")
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port: int = Field(default=1883, title="MQTT Port")
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topic_prefix: str = Field(default="frigate", title="MQTT Topic Prefix")
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client_id: str = Field(default="frigate", title="MQTT Client ID")
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stats_interval: int = Field(default=60, title="MQTT Camera Stats Interval")
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user: Optional[str] = Field(title="MQTT Username")
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password: Optional[str] = Field(title="MQTT Password")
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tls_ca_certs: Optional[str] = Field(title="MQTT TLS CA Certificates")
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tls_client_cert: Optional[str] = Field(title="MQTT TLS Client Certificate")
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tls_client_key: Optional[str] = Field(title="MQTT TLS Client Key")
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tls_insecure: Optional[bool] = Field(title="MQTT TLS Insecure")
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@validator("password", pre=True, always=True)
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def validate_password(cls, v, values):
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if (v is None) != (values["user"] is None):
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raise ValueError("Password must be provided with username.")
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return v
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class RetainConfig(BaseModel):
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default: int = Field(default=10, title="Default retention period.")
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objects: Dict[str, int] = Field(
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default_factory=dict, title="Object retention period."
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)
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class ClipsConfig(BaseModel):
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max_seconds: int = Field(default=300, title="Maximum clip duration.")
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retain: RetainConfig = Field(
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default_factory=RetainConfig, title="Clip retention settings."
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)
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class MotionConfig(BaseModel):
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threshold: int = Field(
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default=25,
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title="Motion detection threshold (1-255).",
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ge=1,
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le=255,
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)
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contour_area: Optional[int] = Field(title="Contour Area")
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delta_alpha: float = Field(default=0.2, title="Delta Alpha")
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frame_alpha: float = Field(default=0.2, title="Frame Alpha")
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frame_height: Optional[int] = Field(title="Frame Height")
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mask: Union[str, List[str]] = Field(
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default="", title="Coordinates polygon for the motion mask."
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)
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class RuntimeMotionConfig(MotionConfig):
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raw_mask: Union[str, List[str]] = ""
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mask: np.ndarray = None
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def __init__(self, **config):
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frame_shape = config.get("frame_shape", (1, 1))
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if "frame_height" not in config:
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config["frame_height"] = max(frame_shape[0] // 6, 180)
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if "contour_area" not in config:
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frame_width = frame_shape[1] * config["frame_height"] / frame_shape[0]
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config["contour_area"] = (
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config["frame_height"] * frame_width * 0.00173611111
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)
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mask = config.get("mask", "")
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config["raw_mask"] = mask
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if mask:
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config["mask"] = create_mask(frame_shape, mask)
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else:
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empty_mask = np.zeros(frame_shape, np.uint8)
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empty_mask[:] = 255
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config["mask"] = empty_mask
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super().__init__(**config)
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def dict(self, **kwargs):
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ret = super().dict(**kwargs)
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if "mask" in ret:
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ret["mask"] = ret["raw_mask"]
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ret.pop("raw_mask")
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return ret
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class Config:
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arbitrary_types_allowed = True
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class DetectConfig(BaseModel):
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enabled: bool = Field(default=True, title="Detection Enabled.")
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max_disappeared: Optional[int] = Field(
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title="Maximum number of frames the object can dissapear before detection ends."
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)
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class FilterConfig(BaseModel):
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min_area: int = Field(
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default=0, title="Minimum area of bounding box for object to be counted."
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)
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max_area: int = Field(
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default=24000000, title="Maximum area of bounding box for object to be counted."
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)
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threshold: float = Field(
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default=0.7,
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title="Average detection confidence threshold for object to be counted.",
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)
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min_score: float = Field(
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default=0.5, title="Minimum detection confidence for object to be counted."
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)
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mask: Optional[Union[str, List[str]]] = Field(
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title="Detection area polygon mask for this filter configuration.",
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)
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class RuntimeFilterConfig(FilterConfig):
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mask: Optional[np.ndarray]
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raw_mask: Optional[Union[str, List[str]]]
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def __init__(self, **config):
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mask = config.get("mask")
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config["raw_mask"] = mask
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if mask is not None:
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config["mask"] = create_mask(config.get("frame_shape", (1, 1)), mask)
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super().__init__(**config)
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def dict(self, **kwargs):
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ret = super().dict(**kwargs)
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if "mask" in ret:
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ret["mask"] = ret["raw_mask"]
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ret.pop("raw_mask")
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return ret
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class Config:
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arbitrary_types_allowed = True
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class ZoneConfig(BaseModel):
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filters: Dict[str, FilterConfig] = Field(
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default_factory=dict, title="Zone filters."
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)
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coordinates: Union[str, List[str]] = Field(
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title="Coordinates polygon for the defined zone."
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)
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objects: List[str] = Field(
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default_factory=list,
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title="List of objects that can trigger the zone.",
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)
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_color: Optional[Tuple[int, int, int]] = PrivateAttr()
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_contour: np.ndarray = PrivateAttr()
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@property
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def color(self) -> Tuple[int, int, int]:
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return self._color
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@property
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def contour(self) -> np.ndarray:
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return self._contour
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def __init__(self, **config):
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super().__init__(**config)
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self._color = config.get("color", (0, 0, 0))
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coordinates = config["coordinates"]
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if isinstance(coordinates, list):
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self._contour = np.array(
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[[int(p.split(",")[0]), int(p.split(",")[1])] for p in coordinates]
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)
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elif isinstance(coordinates, str):
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points = coordinates.split(",")
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self._contour = np.array(
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[[int(points[i]), int(points[i + 1])] for i in range(0, len(points), 2)]
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)
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else:
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self._contour = np.array([])
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class ObjectConfig(BaseModel):
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track: List[str] = Field(default=DEFAULT_TRACKED_OBJECTS, title="Objects to track.")
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filters: Optional[Dict[str, FilterConfig]] = Field(title="Object filters.")
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mask: Union[str, List[str]] = Field(default="", title="Object mask.")
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class BirdseyeModeEnum(str, Enum):
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objects = "objects"
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motion = "motion"
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continuous = "continuous"
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class BirdseyeConfig(BaseModel):
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enabled: bool = Field(default=True, title="Enable birdseye view.")
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width: int = Field(default=1280, title="Birdseye width.")
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height: int = Field(default=720, title="Birdseye height.")
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quality: int = Field(
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default=8,
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title="Encoding quality.",
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ge=1,
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le=31,
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)
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mode: BirdseyeModeEnum = Field(
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default=BirdseyeModeEnum.objects, title="Tracking mode."
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)
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FFMPEG_GLOBAL_ARGS_DEFAULT = ["-hide_banner", "-loglevel", "warning"]
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FFMPEG_INPUT_ARGS_DEFAULT = [
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"-avoid_negative_ts",
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"make_zero",
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"-fflags",
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"+genpts+discardcorrupt",
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"-rtsp_transport",
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"tcp",
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"-stimeout",
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"5000000",
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"-use_wallclock_as_timestamps",
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"1",
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]
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DETECT_FFMPEG_OUTPUT_ARGS_DEFAULT = ["-f", "rawvideo", "-pix_fmt", "yuv420p"]
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RTMP_FFMPEG_OUTPUT_ARGS_DEFAULT = ["-c", "copy", "-f", "flv"]
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SAVE_CLIPS_FFMPEG_OUTPUT_ARGS_DEFAULT = [
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"-f",
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"segment",
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"-segment_time",
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"10",
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"-segment_format",
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"mp4",
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"-reset_timestamps",
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"1",
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"-strftime",
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"1",
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"-c",
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"copy",
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"-an",
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]
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RECORD_FFMPEG_OUTPUT_ARGS_DEFAULT = [
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"-f",
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"segment",
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"-segment_time",
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"60",
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"-segment_format",
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"mp4",
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"-reset_timestamps",
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"1",
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"-strftime",
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"1",
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"-c",
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"copy",
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"-an",
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]
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class FfmpegOutputArgsConfig(BaseModel):
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detect: Union[str, List[str]] = Field(
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default=DETECT_FFMPEG_OUTPUT_ARGS_DEFAULT,
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title="Detect role FFmpeg output arguments.",
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)
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record: Union[str, List[str]] = Field(
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default=RECORD_FFMPEG_OUTPUT_ARGS_DEFAULT,
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title="Record role FFmpeg output arguments.",
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)
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clips: Union[str, List[str]] = Field(
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default=SAVE_CLIPS_FFMPEG_OUTPUT_ARGS_DEFAULT,
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title="Clips role FFmpeg output arguments.",
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)
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rtmp: Union[str, List[str]] = Field(
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default=RTMP_FFMPEG_OUTPUT_ARGS_DEFAULT,
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title="RTMP role FFmpeg output arguments.",
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)
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class FfmpegConfig(BaseModel):
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global_args: Union[str, List[str]] = Field(
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default=FFMPEG_GLOBAL_ARGS_DEFAULT, title="Global FFmpeg arguments."
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)
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hwaccel_args: Union[str, List[str]] = Field(
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default_factory=list, title="FFmpeg hardware acceleration arguments."
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)
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input_args: Union[str, List[str]] = Field(
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default=FFMPEG_INPUT_ARGS_DEFAULT, title="FFmpeg input arguments."
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)
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output_args: FfmpegOutputArgsConfig = Field(
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default_factory=FfmpegOutputArgsConfig,
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title="FFmpeg output arguments per role.",
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)
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class CameraInput(BaseModel):
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path: str = Field(title="Camera input path.")
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roles: List[str] = Field(title="Roles assigned to this input.")
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global_args: Union[str, List[str]] = Field(
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default_factory=list, title="FFmpeg global arguments."
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)
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hwaccel_args: Union[str, List[str]] = Field(
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default_factory=list, title="FFmpeg hardware acceleration arguments."
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)
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input_args: Union[str, List[str]] = Field(
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default_factory=list, title="FFmpeg input arguments."
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)
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class CameraFfmpegConfig(FfmpegConfig):
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inputs: List[CameraInput] = Field(title="Camera inputs.")
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@validator("inputs")
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def validate_roles(cls, v):
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roles = [role for i in v for role in i.roles]
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roles_set = set(roles)
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if len(roles) > len(roles_set):
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raise ValueError("Each input role may only be used once.")
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if not "detect" in roles:
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raise ValueError("The detect role is required.")
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return v
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class CameraSnapshotsConfig(BaseModel):
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enabled: bool = Field(default=False, title="Snapshots enabled.")
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clean_copy: bool = Field(
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default=True, title="Create a clean copy of the snapshot image."
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)
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timestamp: bool = Field(
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default=False, title="Add a timestamp overlay on the snapshot."
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)
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bounding_box: bool = Field(
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default=True, title="Add a bounding box overlay on the snapshot."
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)
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crop: bool = Field(default=False, title="Crop the snapshot to the detected object.")
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required_zones: List[str] = Field(
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default_factory=list,
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title="List of required zones to be entered in order to save a snapshot.",
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)
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height: Optional[int] = Field(title="Snapshot image height.")
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retain: RetainConfig = Field(
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default_factory=RetainConfig, title="Snapshot retention."
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)
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quality: int = Field(
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default=70,
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title="Quality of the encoded jpeg (0-100).",
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ge=0,
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le=100,
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)
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class ColorConfig(BaseModel):
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red: int = Field(default=255, le=0, ge=255, title="Red")
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green: int = Field(default=255, le=0, ge=255, title="Green")
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blue: int = Field(default=255, le=0, ge=255, title="Blue")
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class TimestampStyleConfig(BaseModel):
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position: str = Field(default="tl", title="Timestamp position.")
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format: str = Field(default=DEFAULT_TIME_FORMAT, title="Timestamp format.")
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color: ColorConfig = Field(default_factory=ColorConfig, title="Timestamp color.")
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scale: float = Field(default=1.0, title="Timestamp scale.")
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thickness: int = Field(default=2, title="Timestamp thickness.")
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effect: Optional[str] = Field(title="Timestamp effect.")
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class CameraMqttConfig(BaseModel):
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enabled: bool = Field(default=True, title="Send image over MQTT.")
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timestamp: bool = Field(default=True, title="Add timestamp to MQTT image.")
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bounding_box: bool = Field(default=True, title="Add bounding box to MQTT image.")
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crop: bool = Field(default=True, title="Crop MQTT image to detected object.")
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height: int = Field(default=270, title="MQTT image height.")
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required_zones: List[str] = Field(
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default_factory=list,
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title="List of required zones to be entered in order to send the image.",
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)
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quality: int = Field(
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default=70,
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title="Quality of the encoded jpeg (0-100).",
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ge=0,
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le=100,
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)
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class CameraClipsConfig(BaseModel):
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enabled: bool = Field(default=False, title="Save clips.")
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pre_capture: int = Field(default=5, title="Seconds to capture before event starts.")
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post_capture: int = Field(default=5, title="Seconds to capture after event ends.")
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required_zones: List[str] = Field(
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default_factory=list,
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title="List of required zones to be entered in order to save the clip.",
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)
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objects: Optional[List[str]] = Field(
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title="List of objects to be detected in order to save the clip.",
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)
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retain: RetainConfig = Field(default_factory=RetainConfig, title="Clip retention.")
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class CameraRtmpConfig(BaseModel):
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enabled: bool = Field(default=True, title="RTMP restreaming enabled.")
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class CameraLiveConfig(BaseModel):
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height: Optional[int] = Field(title="Live camera view height")
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width: Optional[int] = Field(title="Live camera view width")
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quality: int = Field(default=8, ge=1, le=31, title="Live camera view quality")
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class RecordConfig(BaseModel):
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enabled: bool = Field(default=False, title="Enable record on all cameras.")
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retain_days: int = Field(default=30, title="Recording retention period in days.")
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class CameraConfig(BaseModel):
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name: Optional[str] = Field(title="Camera name.")
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ffmpeg: CameraFfmpegConfig = Field(title="FFmpeg configuration for the camera.")
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height: int = Field(title="Height of the stream for the detect role.")
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width: int = Field(title="Width of the stream for the detect role.")
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fps: Optional[int] = Field(
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title="Number of frames per second to process through Frigate."
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)
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best_image_timeout: int = Field(
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default=60,
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title="How long to wait for the image with the highest confidence score.",
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)
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zones: Dict[str, ZoneConfig] = Field(
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default_factory=dict, title="Zone configuration."
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)
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clips: CameraClipsConfig = Field(
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default_factory=CameraClipsConfig, title="Clip configuration."
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)
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record: RecordConfig = Field(
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default_factory=RecordConfig, title="Record configuration."
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)
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rtmp: CameraRtmpConfig = Field(
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default_factory=CameraRtmpConfig, title="RTMP restreaming configuration."
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)
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live: Optional[CameraLiveConfig] = Field(title="Live playback settings.")
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snapshots: CameraSnapshotsConfig = Field(
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default_factory=CameraSnapshotsConfig, title="Snapshot configuration."
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)
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mqtt: CameraMqttConfig = Field(
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default_factory=CameraMqttConfig, title="MQTT configuration."
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)
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objects: ObjectConfig = Field(
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default_factory=ObjectConfig, title="Object configuration."
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)
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motion: Optional[MotionConfig] = Field(title="Motion detection configuration.")
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detect: Optional[DetectConfig] = Field(title="Object detection configuration.")
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timestamp_style: TimestampStyleConfig = Field(
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default_factory=TimestampStyleConfig, title="Timestamp style configuration."
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)
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def __init__(self, **config):
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# Set zone colors
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if "zones" in config:
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colors = plt.cm.get_cmap("tab10", len(config["zones"]))
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config["zones"] = {
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name: {**z, "color": tuple(round(255 * c) for c in colors(idx)[:3])}
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for idx, (name, z) in enumerate(config["zones"].items())
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}
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super().__init__(**config)
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@property
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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
|
|
|
|
def _get_ffmpeg_cmd(self, ffmpeg_input: CameraInput):
|
|
ffmpeg_output_args = []
|
|
if "detect" in ffmpeg_input.roles:
|
|
detect_args = (
|
|
self.ffmpeg.output_args.detect
|
|
if isinstance(self.ffmpeg.output_args.detect, list)
|
|
else self.ffmpeg.output_args.detect.split(" ")
|
|
)
|
|
ffmpeg_output_args = detect_args + 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:
|
|
rtmp_args = (
|
|
self.ffmpeg.output_args.rtmp
|
|
if isinstance(self.ffmpeg.output_args.rtmp, list)
|
|
else self.ffmpeg.output_args.rtmp.split(" ")
|
|
)
|
|
ffmpeg_output_args = (
|
|
rtmp_args + [f"rtmp://127.0.0.1/live/{self.name}"] + ffmpeg_output_args
|
|
)
|
|
if "clips" in ffmpeg_input.roles:
|
|
clips_args = (
|
|
self.ffmpeg.output_args.clips
|
|
if isinstance(self.ffmpeg.output_args.clips, list)
|
|
else self.ffmpeg.output_args.clips.split(" ")
|
|
)
|
|
ffmpeg_output_args = (
|
|
clips_args
|
|
+ [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:
|
|
record_args = (
|
|
self.ffmpeg.output_args.record
|
|
if isinstance(self.ffmpeg.output_args.record, list)
|
|
else self.ffmpeg.output_args.record.split(" ")
|
|
)
|
|
ffmpeg_output_args = (
|
|
record_args
|
|
+ [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
|
|
|
|
global_args = ffmpeg_input.global_args or self.ffmpeg.global_args
|
|
hwaccel_args = ffmpeg_input.hwaccel_args or self.ffmpeg.hwaccel_args
|
|
input_args = ffmpeg_input.input_args or self.ffmpeg.input_args
|
|
|
|
global_args = (
|
|
global_args if isinstance(global_args, list) else global_args.split(" ")
|
|
)
|
|
hwaccel_args = (
|
|
hwaccel_args if isinstance(hwaccel_args, list) else hwaccel_args.split(" ")
|
|
)
|
|
input_args = (
|
|
input_args if isinstance(input_args, list) else input_args.split(" ")
|
|
)
|
|
|
|
cmd = (
|
|
["ffmpeg"]
|
|
+ global_args
|
|
+ hwaccel_args
|
|
+ input_args
|
|
+ ["-i", ffmpeg_input.path]
|
|
+ ffmpeg_output_args
|
|
)
|
|
|
|
return [part for part in cmd if part != ""]
|
|
|
|
|
|
class DatabaseConfig(BaseModel):
|
|
path: str = Field(
|
|
default=os.path.join(BASE_DIR, "frigate.db"), title="Database path."
|
|
)
|
|
|
|
|
|
class ModelConfig(BaseModel):
|
|
width: int = Field(default=320, title="Object detection model input width.")
|
|
height: int = Field(default=320, title="Object detection model input height.")
|
|
labelmap: Dict[int, str] = Field(
|
|
default_factory=dict, title="Labelmap customization."
|
|
)
|
|
_merged_labelmap: Optional[Dict[int, str]] = PrivateAttr()
|
|
|
|
@property
|
|
def merged_labelmap(self) -> Dict[int, str]:
|
|
return self._merged_labelmap
|
|
|
|
def __init__(self, **config):
|
|
super().__init__(**config)
|
|
|
|
self._merged_labelmap = {
|
|
**load_labels("/labelmap.txt"),
|
|
**config.get("labelmap", {}),
|
|
}
|
|
|
|
|
|
class LogLevelEnum(str, Enum):
|
|
debug = "debug"
|
|
info = "info"
|
|
warning = "warning"
|
|
error = "error"
|
|
critical = "critical"
|
|
|
|
|
|
class LoggerConfig(BaseModel):
|
|
default: LogLevelEnum = Field(
|
|
default=LogLevelEnum.info, title="Default logging level."
|
|
)
|
|
logs: Dict[str, LogLevelEnum] = Field(
|
|
default_factory=dict, title="Log level for specified processes."
|
|
)
|
|
|
|
|
|
class SnapshotsConfig(BaseModel):
|
|
retain: RetainConfig = Field(
|
|
default_factory=RetainConfig, title="Global snapshot retention configuration."
|
|
)
|
|
|
|
|
|
class FrigateConfig(BaseModel):
|
|
mqtt: MqttConfig = Field(title="MQTT Configuration.")
|
|
database: DatabaseConfig = Field(
|
|
default_factory=DatabaseConfig, title="Database configuration."
|
|
)
|
|
environment_vars: Dict[str, str] = Field(
|
|
default_factory=dict, title="Frigate environment variables."
|
|
)
|
|
model: ModelConfig = Field(
|
|
default_factory=ModelConfig, title="Detection model configuration."
|
|
)
|
|
detectors: Dict[str, DetectorConfig] = Field(
|
|
default={name: DetectorConfig(**d) for name, d in DEFAULT_DETECTORS.items()},
|
|
title="Detector hardware configuration.",
|
|
)
|
|
logger: LoggerConfig = Field(
|
|
default_factory=LoggerConfig, title="Logging configuration."
|
|
)
|
|
clips: ClipsConfig = Field(
|
|
default_factory=ClipsConfig, title="Global clips configuration."
|
|
)
|
|
record: RecordConfig = Field(
|
|
default_factory=RecordConfig, title="Global record configuration."
|
|
)
|
|
snapshots: SnapshotsConfig = Field(
|
|
default_factory=SnapshotsConfig, title="Global snapshots configuration."
|
|
)
|
|
birdseye: BirdseyeConfig = Field(
|
|
default_factory=BirdseyeConfig, title="Birdseye configuration."
|
|
)
|
|
ffmpeg: FfmpegConfig = Field(
|
|
default_factory=FfmpegConfig, title="Global FFmpeg configuration."
|
|
)
|
|
objects: ObjectConfig = Field(
|
|
default_factory=ObjectConfig, title="Global object configuration."
|
|
)
|
|
motion: Optional[MotionConfig] = Field(
|
|
title="Global motion detection configuration."
|
|
)
|
|
detect: Optional[DetectConfig] = Field(
|
|
title="Global object tracking configuration."
|
|
)
|
|
cameras: Dict[str, CameraConfig] = Field(title="Camera configuration.")
|
|
|
|
@property
|
|
def runtime_config(self) -> FrigateConfig:
|
|
"""Merge camera config with globals."""
|
|
config = self.copy(deep=True)
|
|
|
|
# MQTT password substitution
|
|
if config.mqtt.password:
|
|
config.mqtt.password = config.mqtt.password.format(**FRIGATE_ENV_VARS)
|
|
|
|
# Global config to propegate down to camera level
|
|
global_config = config.dict(
|
|
include={
|
|
"clips": {"retain"},
|
|
"record": ...,
|
|
"snapshots": ...,
|
|
"objects": ...,
|
|
"motion": ...,
|
|
"detect": ...,
|
|
"ffmpeg": ...,
|
|
},
|
|
exclude_unset=True,
|
|
)
|
|
|
|
for name, camera in config.cameras.items():
|
|
merged_config = deep_merge(camera.dict(exclude_unset=True), global_config)
|
|
camera_config = CameraConfig.parse_obj({"name": name, **merged_config})
|
|
|
|
# FFMPEG input substitution
|
|
for input in camera_config.ffmpeg.inputs:
|
|
input.path = input.path.format(**FRIGATE_ENV_VARS)
|
|
|
|
# Add default filters
|
|
object_keys = camera_config.objects.track
|
|
if camera_config.objects.filters is None:
|
|
camera_config.objects.filters = {}
|
|
object_keys = object_keys - camera_config.objects.filters.keys()
|
|
for key in object_keys:
|
|
camera_config.objects.filters[key] = FilterConfig()
|
|
|
|
# Apply global object masks and convert masks to numpy array
|
|
for object, filter in camera_config.objects.filters.items():
|
|
if camera_config.objects.mask:
|
|
filter_mask = []
|
|
if filter.mask is not None:
|
|
filter_mask = (
|
|
filter.mask
|
|
if isinstance(filter.mask, list)
|
|
else [filter.mask]
|
|
)
|
|
object_mask = (
|
|
camera_config.objects.mask
|
|
if isinstance(camera_config.objects.mask, list)
|
|
else [camera_config.objects.mask]
|
|
)
|
|
filter.mask = filter_mask + object_mask
|
|
|
|
# Set runtime filter to create masks
|
|
camera_config.objects.filters[object] = RuntimeFilterConfig(
|
|
frame_shape=camera_config.frame_shape,
|
|
**filter.dict(exclude_unset=True),
|
|
)
|
|
|
|
# Convert motion configuration
|
|
if camera_config.motion is None:
|
|
camera_config.motion = RuntimeMotionConfig(
|
|
frame_shape=camera_config.frame_shape
|
|
)
|
|
else:
|
|
camera_config.motion = RuntimeMotionConfig(
|
|
frame_shape=camera_config.frame_shape,
|
|
raw_mask=camera_config.motion.mask,
|
|
**camera_config.motion.dict(exclude_unset=True),
|
|
)
|
|
|
|
# Default detect configuration
|
|
max_disappeared = (camera_config.fps or 5) * 5
|
|
if camera_config.detect:
|
|
if camera_config.detect.max_disappeared is None:
|
|
camera_config.detect.max_disappeared = max_disappeared
|
|
else:
|
|
camera_config.detect = DetectConfig(max_disappeared=max_disappeared)
|
|
|
|
# Default live configuration
|
|
if camera_config.live:
|
|
if (
|
|
camera_config.live.height
|
|
and camera_config.live.height <= camera_config.height
|
|
):
|
|
camera_config.live.width = int(
|
|
camera_config.live.height
|
|
* (camera_config.width / camera_config.height)
|
|
)
|
|
else:
|
|
camera_config.live.height = camera_config.height
|
|
camera_config.live.width = camera_config.width
|
|
else:
|
|
camera_config.live = CameraLiveConfig(
|
|
height=camera_config.height, width=camera_config.width
|
|
)
|
|
|
|
config.cameras[name] = camera_config
|
|
|
|
return config
|
|
|
|
@validator("cameras")
|
|
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():
|
|
raise ValueError("Zones cannot share names with cameras")
|
|
return v
|
|
|
|
@classmethod
|
|
def parse_file(cls, 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 cls.parse_obj(config)
|