mirror of
https://github.com/blakeblackshear/frigate.git
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* Don't warn when event ids have expired for trigger sync * Import faster_whisper conditinally to avoid illegal instruction * Catch OpenVINO runtime error * fix race condition in detail stream context navigating between tracked objects in Explore would sometimes prevent the object track from appearing * Handle case where classification images are deleted * Adjust default rounded corners on larger screens * Improve flow handling for classification state * Remove images when wizard is cancelled * Improve deletion handling for classes * Set constraints on review buffers * Update to support correct data format * Set minimum duration for recording based review items * Use friendly name in review genai prompt --------- Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
172 lines
5.9 KiB
Python
172 lines
5.9 KiB
Python
# this uses the base model because the color is an extra attribute
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import logging
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from typing import Optional, Union
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import numpy as np
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from pydantic import BaseModel, Field, PrivateAttr, field_validator, model_validator
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from .objects import FilterConfig
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__all__ = ["ZoneConfig"]
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logger = logging.getLogger(__name__)
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class ZoneConfig(BaseModel):
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friendly_name: Optional[str] = Field(
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None, title="Zone friendly name used in the Frigate UI."
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)
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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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distances: Optional[Union[str, list[str]]] = Field(
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default_factory=list,
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title="Real-world distances for the sides of quadrilateral for the defined zone.",
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)
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inertia: int = Field(
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default=3,
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title="Number of consecutive frames required for object to be considered present in the zone.",
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gt=0,
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)
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loitering_time: int = Field(
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default=0,
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ge=0,
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title="Number of seconds that an object must loiter to be considered in the zone.",
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)
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speed_threshold: Optional[float] = Field(
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default=None,
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ge=0.1,
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title="Minimum speed value for an object to be considered in the zone.",
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)
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objects: Union[str, 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 get_formatted_name(self, zone_name: str) -> str:
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"""Return the friendly name if set, otherwise return a formatted version of the zone name."""
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if self.friendly_name:
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return self.friendly_name
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return zone_name.replace("_", " ").title()
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@field_validator("objects", mode="before")
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@classmethod
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def validate_objects(cls, v):
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if isinstance(v, str) and "," not in v:
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return [v]
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return v
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@field_validator("distances", mode="before")
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@classmethod
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def validate_distances(cls, v):
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if v is None:
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return None
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if isinstance(v, str):
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distances = list(map(str, map(float, v.split(","))))
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elif isinstance(v, list):
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distances = [str(float(val)) for val in v]
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else:
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raise ValueError("Invalid type for distances")
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if len(distances) != 4:
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raise ValueError("distances must have exactly 4 values")
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return distances
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@model_validator(mode="after")
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def check_loitering_time_constraints(self):
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if self.loitering_time > 0 and (
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self.speed_threshold is not None or len(self.distances) > 0
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):
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logger.warning(
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"loitering_time should not be set on a zone if speed_threshold or distances is set."
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)
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return self
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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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self._contour = config.get("contour", np.array([]))
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def generate_contour(self, frame_shape: tuple[int, int]):
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coordinates = self.coordinates
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# masks and zones are saved as relative coordinates
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# we know if any points are > 1 then it is using the
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# old native resolution coordinates
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if isinstance(coordinates, list):
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explicit = any(p.split(",")[0] > "1.0" for p in coordinates)
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try:
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self._contour = np.array(
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[
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(
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[int(p.split(",")[0]), int(p.split(",")[1])]
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if explicit
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else [
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int(float(p.split(",")[0]) * frame_shape[1]),
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int(float(p.split(",")[1]) * frame_shape[0]),
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]
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)
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for p in coordinates
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]
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)
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except ValueError:
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raise ValueError(
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f"Invalid coordinates found in configuration file. Coordinates must be relative (between 0-1): {coordinates}"
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)
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if explicit:
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self.coordinates = ",".join(
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[
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f"{round(int(p.split(',')[0]) / frame_shape[1], 3)},{round(int(p.split(',')[1]) / frame_shape[0], 3)}"
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for p in coordinates
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]
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)
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elif isinstance(coordinates, str):
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points = coordinates.split(",")
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explicit = any(p > "1.0" for p in points)
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try:
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self._contour = np.array(
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[
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(
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[int(points[i]), int(points[i + 1])]
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if explicit
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else [
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int(float(points[i]) * frame_shape[1]),
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int(float(points[i + 1]) * frame_shape[0]),
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]
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)
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for i in range(0, len(points), 2)
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]
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)
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except ValueError:
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raise ValueError(
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f"Invalid coordinates found in configuration file. Coordinates must be relative (between 0-1): {coordinates}"
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)
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if explicit:
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self.coordinates = ",".join(
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[
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f"{round(int(points[i]) / frame_shape[1], 3)},{round(int(points[i + 1]) / frame_shape[0], 3)}"
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for i in range(0, len(points), 2)
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]
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)
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else:
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self._contour = np.array([])
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