mirror of
https://github.com/blakeblackshear/frigate.git
synced 2024-11-26 19:06:11 +01:00
1184 lines
36 KiB
Python
1184 lines
36 KiB
Python
from __future__ import annotations
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import base64
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import dataclasses
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import datetime
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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, Tuple, Union
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import matplotlib.pyplot as plt
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import numpy as np
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import voluptuous as vol
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import yaml
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from frigate.const import BASE_DIR, RECORD_DIR, CLIPS_DIR, CACHE_DIR
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from frigate.util import create_mask
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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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DEFAULT_TRACKED_OBJECTS = ["person"]
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DEFAULT_RGB_COLOR = {"red": 255, "green": 255, "blue": 255}
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DEFAULT_DETECTORS = {"coral": {"type": "edgetpu", "device": "usb"}}
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DETECTORS_SCHEMA = vol.Schema(
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{
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vol.Required(str): {
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vol.Required("type", default="edgetpu"): vol.In(["cpu", "edgetpu"]),
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vol.Optional("device", default="usb"): str,
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vol.Optional("num_threads", default=3): int,
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}
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}
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)
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@dataclasses.dataclass(frozen=True)
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class DetectorConfig:
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type: str
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device: str
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num_threads: int
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@classmethod
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def build(cls, config) -> DetectorConfig:
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return DetectorConfig(config["type"], config["device"], config["num_threads"])
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def to_dict(self) -> Dict[str, Any]:
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return dataclasses.asdict(self)
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MQTT_SCHEMA = vol.Schema(
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{
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vol.Required("host"): str,
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vol.Optional("port", default=1883): int,
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vol.Optional("topic_prefix", default="frigate"): str,
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vol.Optional("client_id", default="frigate"): str,
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vol.Optional("stats_interval", default=60): int,
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vol.Inclusive("user", "auth"): str,
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vol.Inclusive("password", "auth"): str,
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vol.Optional("tls_ca_certs"): str,
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vol.Optional("tls_client_cert"): str,
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vol.Optional("tls_client_key"): str,
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vol.Optional("tls_insecure"): bool,
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}
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)
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@dataclasses.dataclass(frozen=True)
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class MqttConfig:
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host: str
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port: int
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topic_prefix: str
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client_id: str
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stats_interval: int
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user: Optional[str]
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password: Optional[str]
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tls_ca_certs: Optional[str]
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tls_client_cert: Optional[str]
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tls_client_key: Optional[str]
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tls_insecure: Optional[bool]
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@classmethod
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def build(cls, config) -> MqttConfig:
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return MqttConfig(
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config["host"],
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config["port"],
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config["topic_prefix"],
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config["client_id"],
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config["stats_interval"],
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config.get("user"),
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config.get("password"),
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config.get("tls_ca_certs"),
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config.get("tls_client_cert"),
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config.get("tls_client_key"),
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config.get("tls_insecure"),
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)
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def to_dict(self) -> Dict[str, Any]:
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return dataclasses.asdict(self)
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RETAIN_SCHEMA = vol.Schema(
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{vol.Required("default", default=10): int, "objects": {str: int}}
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)
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@dataclasses.dataclass(frozen=True)
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class RetainConfig:
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default: int
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objects: Dict[str, int]
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@classmethod
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def build(cls, config, global_config={}) -> RetainConfig:
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return RetainConfig(
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config.get("default", global_config.get("default")),
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config.get("objects", global_config.get("objects", {})),
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)
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def to_dict(self) -> Dict[str, Any]:
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return dataclasses.asdict(self)
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CLIPS_SCHEMA = vol.Schema(
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{
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vol.Optional("max_seconds", default=300): int,
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vol.Optional("retain", default={}): RETAIN_SCHEMA,
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}
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)
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@dataclasses.dataclass(frozen=True)
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class ClipsConfig:
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max_seconds: int
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retain: RetainConfig
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@classmethod
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def build(cls, config) -> ClipsConfig:
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return ClipsConfig(
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config["max_seconds"],
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RetainConfig.build(config["retain"]),
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)
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def to_dict(self) -> Dict[str, Any]:
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return {
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"max_seconds": self.max_seconds,
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"retain": self.retain.to_dict(),
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}
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MOTION_SCHEMA = vol.Schema(
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{
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"mask": vol.Any(str, [str]),
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"threshold": vol.Range(min=1, max=255),
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"contour_area": int,
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"delta_alpha": float,
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"frame_alpha": float,
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"frame_height": int,
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}
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)
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@dataclasses.dataclass(frozen=True)
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class MotionConfig:
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raw_mask: Union[str, List[str]]
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mask: np.ndarray
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threshold: int
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contour_area: int
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delta_alpha: float
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frame_alpha: float
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frame_height: int
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@classmethod
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def build(cls, config, global_config, frame_shape) -> MotionConfig:
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raw_mask = config.get("mask")
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if raw_mask:
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mask = create_mask(frame_shape, raw_mask)
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else:
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mask = np.zeros(frame_shape, np.uint8)
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mask[:] = 255
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return MotionConfig(
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raw_mask,
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mask,
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config.get("threshold", global_config.get("threshold", 25)),
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config.get("contour_area", global_config.get("contour_area", 100)),
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config.get("delta_alpha", global_config.get("delta_alpha", 0.2)),
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config.get("frame_alpha", global_config.get("frame_alpha", 0.2)),
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config.get(
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"frame_height", global_config.get("frame_height", frame_shape[0] // 6)
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),
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)
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def to_dict(self) -> Dict[str, Any]:
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return {
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"mask": self.raw_mask,
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"threshold": self.threshold,
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"contour_area": self.contour_area,
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"delta_alpha": self.delta_alpha,
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"frame_alpha": self.frame_alpha,
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"frame_height": self.frame_height,
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}
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GLOBAL_DETECT_SCHEMA = vol.Schema({"max_disappeared": int})
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DETECT_SCHEMA = GLOBAL_DETECT_SCHEMA.extend(
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{vol.Optional("enabled", default=True): bool}
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)
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@dataclasses.dataclass
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class DetectConfig:
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enabled: bool
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max_disappeared: int
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@classmethod
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def build(cls, config, global_config, camera_fps) -> DetectConfig:
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return DetectConfig(
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config["enabled"],
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config.get(
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"max_disappeared", global_config.get("max_disappeared", camera_fps * 5)
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),
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)
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def to_dict(self) -> Dict[str, Any]:
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return {
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"enabled": self.enabled,
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"max_disappeared": self.max_disappeared,
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}
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ZONE_FILTER_SCHEMA = vol.Schema(
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{
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str: {
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"min_area": int,
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"max_area": int,
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"threshold": float,
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}
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}
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)
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FILTER_SCHEMA = ZONE_FILTER_SCHEMA.extend(
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{
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str: {
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"min_score": float,
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"mask": vol.Any(str, [str]),
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}
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}
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)
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@dataclasses.dataclass(frozen=True)
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class FilterConfig:
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min_area: int
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max_area: int
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threshold: float
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min_score: float
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mask: Optional[np.ndarray]
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raw_mask: Union[str, List[str]]
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@classmethod
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def build(
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cls, config, global_config={}, global_mask=None, frame_shape=None
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) -> FilterConfig:
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raw_mask = []
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if global_mask:
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if isinstance(global_mask, list):
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raw_mask += global_mask
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elif isinstance(global_mask, str):
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raw_mask += [global_mask]
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config_mask = config.get("mask")
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if config_mask:
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if isinstance(config_mask, list):
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raw_mask += config_mask
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elif isinstance(config_mask, str):
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raw_mask += [config_mask]
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mask = create_mask(frame_shape, raw_mask) if raw_mask else None
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return FilterConfig(
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min_area=config.get("min_area", global_config.get("min_area", 0)),
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max_area=config.get("max_area", global_config.get("max_area", 24000000)),
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threshold=config.get("threshold", global_config.get("threshold", 0.7)),
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min_score=config.get("min_score", global_config.get("min_score", 0.5)),
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mask=mask,
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raw_mask=raw_mask,
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)
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def to_dict(self) -> Dict[str, Any]:
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return {
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"min_area": self.min_area,
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"max_area": self.max_area,
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"threshold": self.threshold,
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"min_score": self.min_score,
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"mask": self.raw_mask,
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}
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ZONE_SCHEMA = {
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str: {
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vol.Required("coordinates"): vol.Any(str, [str]),
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vol.Optional("filters", default={}): ZONE_FILTER_SCHEMA,
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}
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}
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@dataclasses.dataclass(frozen=True)
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class ZoneConfig:
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filters: Dict[str, FilterConfig]
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coordinates: Union[str, List[str]]
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contour: np.ndarray
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color: Tuple[int, int, int]
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@classmethod
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def build(cls, config, color: Tuple[int, int, int]) -> ZoneConfig:
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coordinates = config["coordinates"]
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if isinstance(coordinates, list):
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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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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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contour = np.array([])
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return ZoneConfig(
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{name: FilterConfig.build(c) for name, c in config["filters"].items()},
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coordinates,
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contour,
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color=color,
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)
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def to_dict(self) -> Dict[str, Any]:
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return {
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"filters": {k: f.to_dict() for k, f in self.filters.items()},
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"coordinates": self.coordinates,
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}
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def filters_for_all_tracked_objects(object_config):
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for tracked_object in object_config.get("track", DEFAULT_TRACKED_OBJECTS):
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if not "filters" in object_config:
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object_config["filters"] = {}
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if not tracked_object in object_config["filters"]:
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object_config["filters"][tracked_object] = {}
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return object_config
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OBJECTS_SCHEMA = vol.Schema(
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vol.All(
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filters_for_all_tracked_objects,
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{
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"track": [str],
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"mask": vol.Any(str, [str]),
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vol.Optional("filters", default={}): FILTER_SCHEMA,
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},
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)
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)
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@dataclasses.dataclass(frozen=True)
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class ObjectConfig:
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track: List[str]
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filters: Dict[str, FilterConfig]
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raw_mask: Optional[Union[str, List[str]]]
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@classmethod
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def build(cls, config, global_config, frame_shape) -> ObjectConfig:
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track = config.get("track", global_config.get("track", DEFAULT_TRACKED_OBJECTS))
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raw_mask = config.get("mask")
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return ObjectConfig(
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track,
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{
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name: FilterConfig.build(
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config["filters"].get(name, {}),
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global_config["filters"].get(name, {}),
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raw_mask,
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frame_shape,
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)
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for name in track
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},
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raw_mask,
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)
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def to_dict(self) -> Dict[str, Any]:
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return {
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"track": self.track,
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"mask": self.raw_mask,
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"filters": {k: f.to_dict() for k, f in self.filters.items()},
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}
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BIRDSEYE_SCHEMA = vol.Schema(
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{
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vol.Optional("enabled", default=True): bool,
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vol.Optional("width", default=1280): int,
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vol.Optional("height", default=720): int,
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vol.Optional("quality", default=8): vol.Range(min=1, max=31),
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vol.Optional("mode", default="objects"): vol.In(
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["objects", "motion", "continuous"]
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),
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}
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)
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@dataclasses.dataclass(frozen=True)
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class BirdseyeConfig:
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enabled: bool
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width: int
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height: int
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quality: int
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mode: str
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@classmethod
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def build(cls, config) -> BirdseyeConfig:
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return BirdseyeConfig(
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config["enabled"],
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config["width"],
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config["height"],
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config["quality"],
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config["mode"],
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)
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def to_dict(self) -> Dict[str, Any]:
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return dataclasses.asdict(self)
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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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GLOBAL_FFMPEG_SCHEMA = vol.Schema(
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{
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vol.Optional("global_args", default=FFMPEG_GLOBAL_ARGS_DEFAULT): vol.Any(
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str, [str]
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),
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vol.Optional("hwaccel_args", default=[]): vol.Any(str, [str]),
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vol.Optional("input_args", default=FFMPEG_INPUT_ARGS_DEFAULT): vol.Any(
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str, [str]
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),
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vol.Optional("output_args", default={}): {
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vol.Optional("detect", default=DETECT_FFMPEG_OUTPUT_ARGS_DEFAULT): vol.Any(
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str, [str]
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),
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vol.Optional("record", default=RECORD_FFMPEG_OUTPUT_ARGS_DEFAULT): vol.Any(
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str, [str]
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),
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vol.Optional(
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"clips", default=SAVE_CLIPS_FFMPEG_OUTPUT_ARGS_DEFAULT
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): vol.Any(str, [str]),
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vol.Optional("rtmp", default=RTMP_FFMPEG_OUTPUT_ARGS_DEFAULT): vol.Any(
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str, [str]
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),
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},
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}
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)
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|
|
|
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def each_role_used_once(inputs):
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roles = [role for i in inputs 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
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return inputs
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def detect_is_required(inputs):
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roles = [role for i in inputs for role in i["roles"]]
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if not "detect" in roles:
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raise ValueError
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return inputs
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CAMERA_FFMPEG_SCHEMA = vol.Schema(
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{
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vol.Required("inputs"): vol.All(
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[
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{
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vol.Required("path"): str,
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vol.Required("roles"): ["detect", "clips", "record", "rtmp"],
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"global_args": vol.Any(str, [str]),
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"hwaccel_args": vol.Any(str, [str]),
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"input_args": vol.Any(str, [str]),
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}
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],
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vol.Msg(each_role_used_once, msg="Each input role may only be used once"),
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vol.Msg(detect_is_required, msg="The detect role is required"),
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),
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"global_args": vol.Any(str, [str]),
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"hwaccel_args": vol.Any(str, [str]),
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"input_args": vol.Any(str, [str]),
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"output_args": {
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vol.Optional("detect", default=DETECT_FFMPEG_OUTPUT_ARGS_DEFAULT): vol.Any(
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str, [str]
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),
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vol.Optional("record", default=RECORD_FFMPEG_OUTPUT_ARGS_DEFAULT): vol.Any(
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str, [str]
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),
|
|
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
|