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https://github.com/blakeblackshear/frigate.git
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34cc1208a6
* backend * frontend * i18n * docs * add test * clean up * clean up motion detection docs * formatting * make optional
91 lines
3.7 KiB
Python
91 lines
3.7 KiB
Python
from typing import Any, Optional
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from pydantic import Field, field_serializer
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from ..base import FrigateBaseModel
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from .mask import MotionMaskConfig
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__all__ = ["MotionConfig"]
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class MotionConfig(FrigateBaseModel):
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enabled: bool = Field(
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default=True,
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title="Enable motion detection",
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description="Enable or disable motion detection for all cameras; can be overridden per-camera.",
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)
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threshold: int = Field(
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default=30,
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title="Motion threshold",
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description="Pixel difference threshold used by the motion detector; higher values reduce sensitivity (range 1-255).",
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ge=1,
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le=255,
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)
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lightning_threshold: float = Field(
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default=0.8,
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title="Lightning threshold",
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description="Threshold to detect and ignore brief lighting spikes (lower is more sensitive, values between 0.3 and 1.0). This does not prevent motion detection entirely; it merely causes the detector to stop analyzing additional frames once the threshold is exceeded. Motion-based recordings are still created during these events.",
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ge=0.3,
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le=1.0,
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)
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skip_motion_threshold: Optional[float] = Field(
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default=None,
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title="Skip motion threshold",
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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.",
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ge=0.0,
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le=1.0,
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)
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improve_contrast: bool = Field(
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default=True,
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title="Improve contrast",
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description="Apply contrast improvement to frames before motion analysis to help detection.",
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)
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contour_area: Optional[int] = Field(
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default=10,
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title="Contour area",
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description="Minimum contour area in pixels required for a motion contour to be counted.",
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)
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delta_alpha: float = Field(
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default=0.2,
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title="Delta alpha",
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description="Alpha blending factor used in frame differencing for motion calculation.",
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)
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frame_alpha: float = Field(
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default=0.01,
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title="Frame alpha",
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description="Alpha value used when blending frames for motion preprocessing.",
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)
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frame_height: Optional[int] = Field(
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default=100,
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title="Frame height",
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description="Height in pixels to scale frames to when computing motion.",
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)
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mask: dict[str, Optional[MotionMaskConfig]] = Field(
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default_factory=dict,
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title="Mask coordinates",
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description="Ordered x,y coordinates defining the motion mask polygon used to include/exclude areas.",
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)
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mqtt_off_delay: int = Field(
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default=30,
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title="MQTT off delay",
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description="Seconds to wait after last motion before publishing an MQTT 'off' state.",
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)
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enabled_in_config: Optional[bool] = Field(
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default=None,
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title="Original motion state",
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description="Indicates whether motion detection was enabled in the original static configuration.",
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)
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raw_mask: dict[str, Optional[MotionMaskConfig]] = Field(
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default_factory=dict, exclude=True
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)
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@field_serializer("mask", when_used="json")
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def serialize_mask(self, value: Any, info):
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if self.raw_mask:
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return self.raw_mask
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return value
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@field_serializer("raw_mask", when_used="json")
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def serialize_raw_mask(self, value: Any, info):
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return None
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