mirror of
https://github.com/blakeblackshear/frigate.git
synced 2026-10-13 10:12:47 +03:00
Masks and zones improvements (#22163)
* migrator and runtime config changes * component changes to use rasterized_mask * frontend * convert none to empty string for config save * i18n * update tests * add enabled config to zones * zones frontend * i18n * docs * tweaks * use dashed stroke to indicate disabled * allow toggle from icon * use filelock to ensure atomic config updates from endpoint * enforce atomic config update in the frontend * toggle via mqtt * fix global object masks * correctly handle global object masks in dispatcher * ws hooks * render masks and zones based on ws enabled state * use enabled_in_config for zones and masks * frontend for enabled_in_config * tweaks * i18n * publish websocket on config save * i18n tweaks * pydantic title and description * i18n generation * tweaks * fix typing
This commit is contained in:
Josh Hawkins
+159
-53
@@ -3,7 +3,7 @@ from __future__ import annotations
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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 Any, Dict, List, Optional, Union
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from typing import Any, Dict, Optional
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import numpy as np
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from pydantic import (
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@@ -46,6 +46,7 @@ from .camera.birdseye import BirdseyeConfig
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from .camera.detect import DetectConfig
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from .camera.ffmpeg import FfmpegConfig
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from .camera.genai import GenAIConfig, GenAIRoleEnum
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from .camera.mask import ObjectMaskConfig
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from .camera.motion import MotionConfig
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from .camera.notification import NotificationConfig
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from .camera.objects import FilterConfig, ObjectConfig
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@@ -93,54 +94,111 @@ stream_info_retriever = StreamInfoRetriever()
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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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"""Runtime version of MotionConfig with rasterized masks."""
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# The rasterized numpy mask (combination of all enabled masks)
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rasterized_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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mask = get_relative_coordinates(config.get("mask", ""), frame_shape)
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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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# Store original mask dict for serialization
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original_mask = config.get("mask", {})
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if isinstance(original_mask, dict):
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# Process the new dict format - update raw_coordinates for each mask
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processed_mask = {}
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for mask_id, mask_config in original_mask.items():
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if isinstance(mask_config, dict):
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coords = mask_config.get("coordinates", "")
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relative_coords = get_relative_coordinates(coords, frame_shape)
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mask_config_copy = mask_config.copy()
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mask_config_copy["raw_coordinates"] = (
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relative_coords if relative_coords else coords
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)
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mask_config_copy["coordinates"] = (
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relative_coords if relative_coords else coords
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)
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processed_mask[mask_id] = mask_config_copy
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else:
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processed_mask[mask_id] = mask_config
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config["mask"] = processed_mask
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config["raw_mask"] = processed_mask
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super().__init__(**config)
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# Rasterize only enabled masks
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enabled_coords = []
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for mask_config in self.mask.values():
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if mask_config.enabled and mask_config.coordinates:
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coords = mask_config.coordinates
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if isinstance(coords, list):
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enabled_coords.extend(coords)
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else:
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enabled_coords.append(coords)
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if enabled_coords:
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self.rasterized_mask = create_mask(frame_shape, enabled_coords)
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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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self.rasterized_mask = empty_mask
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def dict(self, **kwargs):
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ret = super().model_dump(**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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if "rasterized_mask" in ret:
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ret.pop("rasterized_mask")
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return ret
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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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return self.raw_mask
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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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@field_serializer("rasterized_mask", when_used="json")
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def serialize_rasterized_mask(self, value: Any, info):
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return None
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model_config = ConfigDict(arbitrary_types_allowed=True, extra="ignore")
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class RuntimeFilterConfig(FilterConfig):
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mask: Optional[np.ndarray] = None
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raw_mask: Optional[Union[str, List[str]]] = None
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"""Runtime version of FilterConfig with rasterized masks."""
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# The rasterized numpy mask (combination of all enabled masks)
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rasterized_mask: Optional[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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mask = get_relative_coordinates(config.get("mask"), frame_shape)
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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(frame_shape, mask)
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# Store original mask dict for serialization
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original_mask = config.get("mask", {})
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if isinstance(original_mask, dict):
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# Process the new dict format - update raw_coordinates for each mask
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processed_mask = {}
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for mask_id, mask_config in original_mask.items():
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# Handle both dict and ObjectMaskConfig formats
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if hasattr(mask_config, "model_dump"):
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# It's an ObjectMaskConfig object
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mask_dict = mask_config.model_dump()
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coords = mask_dict.get("coordinates", "")
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relative_coords = get_relative_coordinates(coords, frame_shape)
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mask_dict["raw_coordinates"] = (
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relative_coords if relative_coords else coords
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)
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mask_dict["coordinates"] = (
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relative_coords if relative_coords else coords
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)
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processed_mask[mask_id] = mask_dict
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elif isinstance(mask_config, dict):
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coords = mask_config.get("coordinates", "")
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relative_coords = get_relative_coordinates(coords, frame_shape)
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mask_config_copy = mask_config.copy()
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mask_config_copy["raw_coordinates"] = (
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relative_coords if relative_coords else coords
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)
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mask_config_copy["coordinates"] = (
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relative_coords if relative_coords else coords
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)
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processed_mask[mask_id] = mask_config_copy
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else:
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processed_mask[mask_id] = mask_config
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config["mask"] = processed_mask
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config["raw_mask"] = processed_mask
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# Convert min_area and max_area to pixels if they're percentages
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if "min_area" in config:
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@@ -151,13 +209,31 @@ class RuntimeFilterConfig(FilterConfig):
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super().__init__(**config)
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# Rasterize only enabled masks
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enabled_coords = []
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for mask_config in self.mask.values():
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if mask_config.enabled and mask_config.coordinates:
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coords = mask_config.coordinates
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if isinstance(coords, list):
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enabled_coords.extend(coords)
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else:
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enabled_coords.append(coords)
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if enabled_coords:
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self.rasterized_mask = create_mask(frame_shape, enabled_coords)
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else:
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self.rasterized_mask = None
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def dict(self, **kwargs):
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ret = super().model_dump(**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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if "rasterized_mask" in ret:
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ret.pop("rasterized_mask")
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return ret
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@field_serializer("rasterized_mask", when_used="json")
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def serialize_rasterized_mask(self, value: Any, info):
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return None
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model_config = ConfigDict(arbitrary_types_allowed=True, extra="ignore")
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@@ -713,35 +789,63 @@ class FrigateConfig(FrigateBaseModel):
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for key in object_keys:
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camera_config.objects.filters[key] = FilterConfig()
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# Process global object masks to set raw_coordinates
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if camera_config.objects.mask:
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processed_global_masks = {}
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for mask_id, mask_config in camera_config.objects.mask.items():
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if mask_config:
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coords = mask_config.coordinates
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relative_coords = get_relative_coordinates(
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coords, camera_config.frame_shape
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)
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# Create a new ObjectMaskConfig with raw_coordinates set
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processed_global_masks[mask_id] = ObjectMaskConfig(
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friendly_name=mask_config.friendly_name,
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enabled=mask_config.enabled,
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coordinates=relative_coords if relative_coords else coords,
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raw_coordinates=relative_coords
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if relative_coords
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else coords,
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enabled_in_config=mask_config.enabled,
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)
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else:
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processed_global_masks[mask_id] = mask_config
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camera_config.objects.mask = processed_global_masks
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camera_config.objects.raw_mask = processed_global_masks
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# Apply global object masks and convert masks to numpy array
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for object, filter in camera_config.objects.filters.items():
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# Set enabled_in_config for per-object masks before processing
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for mask_config in filter.mask.values():
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if mask_config:
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mask_config.enabled_in_config = mask_config.enabled
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# Merge global object masks with per-object filter masks
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merged_mask = dict(filter.mask) # Copy filter-specific masks
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# Add global object masks if they exist
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if camera_config.objects.mask:
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filter_mask = []
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if filter.mask is not None:
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filter_mask = (
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filter.mask
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if isinstance(filter.mask, list)
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else [filter.mask]
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)
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object_mask = (
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get_relative_coordinates(
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(
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camera_config.objects.mask
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if isinstance(camera_config.objects.mask, list)
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else [camera_config.objects.mask]
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),
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camera_config.frame_shape,
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)
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or []
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)
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filter.mask = filter_mask + object_mask
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for mask_id, mask_config in camera_config.objects.mask.items():
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# Use a global prefix to avoid key collisions
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global_mask_id = f"global_{mask_id}"
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merged_mask[global_mask_id] = mask_config
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# Set runtime filter to create masks
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camera_config.objects.filters[object] = RuntimeFilterConfig(
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frame_shape=camera_config.frame_shape,
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**filter.model_dump(exclude_unset=True),
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mask=merged_mask,
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**filter.model_dump(
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exclude_unset=True, exclude={"mask", "raw_mask"}
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),
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)
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# Set enabled_in_config for motion masks to match config file state BEFORE creating RuntimeMotionConfig
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if camera_config.motion:
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camera_config.motion.enabled_in_config = camera_config.motion.enabled
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for mask_config in camera_config.motion.mask.values():
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if mask_config:
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mask_config.enabled_in_config = mask_config.enabled
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# Convert motion configuration
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if camera_config.motion is None:
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camera_config.motion = RuntimeMotionConfig(
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@@ -750,10 +854,8 @@ class FrigateConfig(FrigateBaseModel):
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else:
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camera_config.motion = RuntimeMotionConfig(
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frame_shape=camera_config.frame_shape,
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raw_mask=camera_config.motion.mask,
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**camera_config.motion.model_dump(exclude_unset=True),
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)
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camera_config.motion.enabled_in_config = camera_config.motion.enabled
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# generate zone contours
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if len(camera_config.zones) > 0:
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@@ -767,6 +869,10 @@ class FrigateConfig(FrigateBaseModel):
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zone.generate_contour(camera_config.frame_shape)
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# Set enabled_in_config for zones to match config file state
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for zone in camera_config.zones.values():
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zone.enabled_in_config = zone.enabled
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# Set live view stream if none is set
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if not camera_config.live.streams:
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camera_config.live.streams = {name: name}
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