mirror of
https://github.com/blakeblackshear/frigate.git
synced 2025-08-04 13:47:37 +02:00
57bb0cc397
* semantic trigger test * database and model * config * embeddings maintainer and trigger post-processor * api to create, edit, delete triggers * frontend and i18n keys * use thumbnail and description for trigger types * image picker tweaks * initial sync * thumbnail file management * clean up logs and use saved thumbnail on frontend * publish mqtt messages * webpush changes to enable trigger notifications * add enabled switch * add triggers from explore * renaming and deletion fixes * fix typing * UI updates and add last triggering event time and link * log exception instead of return in endpoint * highlight entry in UI when triggered * save and delete thumbnails directly * remove alert action for now and add descriptions * tweaks * clean up * fix types * docs * docs tweaks * docs * reuse enum
447 lines
14 KiB
Python
447 lines
14 KiB
Python
"""Utilities for builtin types manipulation."""
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import ast
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import copy
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import datetime
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import logging
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import math
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import multiprocessing.queues
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import queue
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import re
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import shlex
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import struct
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import urllib.parse
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from collections.abc import Mapping
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from multiprocessing.sharedctypes import Synchronized
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from pathlib import Path
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from typing import Any, Dict, Optional, Tuple, Union
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from zoneinfo import ZoneInfoNotFoundError
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import numpy as np
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import pytz
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from ruamel.yaml import YAML
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from tzlocal import get_localzone
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from frigate.const import REGEX_HTTP_CAMERA_USER_PASS, REGEX_RTSP_CAMERA_USER_PASS
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logger = logging.getLogger(__name__)
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class EventsPerSecond:
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def __init__(self, max_events=1000, last_n_seconds=10) -> None:
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self._start = None
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self._max_events = max_events
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self._last_n_seconds = last_n_seconds
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self._timestamps = []
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def start(self) -> None:
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self._start = datetime.datetime.now().timestamp()
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def update(self) -> None:
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now = datetime.datetime.now().timestamp()
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if self._start is None:
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self._start = now
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self._timestamps.append(now)
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# truncate the list when it goes 100 over the max_size
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if len(self._timestamps) > self._max_events + 100:
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self._timestamps = self._timestamps[(1 - self._max_events) :]
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self.expire_timestamps(now)
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def eps(self) -> float:
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now = datetime.datetime.now().timestamp()
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if self._start is None:
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self._start = now
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# compute the (approximate) events in the last n seconds
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self.expire_timestamps(now)
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seconds = min(now - self._start, self._last_n_seconds)
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# avoid divide by zero
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if seconds == 0:
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seconds = 1
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return len(self._timestamps) / seconds
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# remove aged out timestamps
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def expire_timestamps(self, now: float) -> None:
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threshold = now - self._last_n_seconds
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while self._timestamps and self._timestamps[0] < threshold:
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del self._timestamps[0]
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class InferenceSpeed:
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def __init__(self, metric: Synchronized) -> None:
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self.__metric = metric
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self.__initialized = False
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def update(self, inference_time: float) -> None:
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if not self.__initialized:
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self.__metric.value = inference_time
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self.__initialized = True
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return
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self.__metric.value = (self.__metric.value * 9 + inference_time) / 10
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def current(self) -> float:
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return self.__metric.value
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def deep_merge(dct1: dict, dct2: dict, override=False, merge_lists=False) -> dict:
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"""
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:param dct1: First dict to merge
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:param dct2: Second dict to merge
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:param override: if same key exists in both dictionaries, should override? otherwise ignore. (default=True)
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:return: The merge dictionary
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"""
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merged = copy.deepcopy(dct1)
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for k, v2 in dct2.items():
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if k in merged:
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v1 = merged[k]
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if isinstance(v1, dict) and isinstance(v2, Mapping):
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merged[k] = deep_merge(v1, v2, override)
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elif isinstance(v1, list) and isinstance(v2, list):
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if merge_lists:
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merged[k] = v1 + v2
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else:
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if override:
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merged[k] = copy.deepcopy(v2)
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else:
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merged[k] = copy.deepcopy(v2)
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return merged
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def clean_camera_user_pass(line: str) -> str:
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"""Removes user and password from line."""
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rtsp_cleaned = re.sub(REGEX_RTSP_CAMERA_USER_PASS, "://*:*@", line)
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return re.sub(REGEX_HTTP_CAMERA_USER_PASS, "user=*&password=*", rtsp_cleaned)
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def escape_special_characters(path: str) -> str:
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"""Cleans reserved characters to encodings for ffmpeg."""
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if len(path) > 1000:
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return ValueError("Input too long to check")
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try:
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found = re.search(REGEX_RTSP_CAMERA_USER_PASS, path).group(0)[3:-1]
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pw = found[(found.index(":") + 1) :]
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return path.replace(pw, urllib.parse.quote_plus(pw))
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except AttributeError:
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# path does not have user:pass
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return path
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def get_ffmpeg_arg_list(arg: Any) -> list:
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"""Use arg if list or convert to list format."""
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return arg if isinstance(arg, list) else shlex.split(arg)
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def load_labels(path: Optional[str], encoding="utf-8", prefill=91):
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"""Loads labels from file (with or without index numbers).
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Args:
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path: path to label file.
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encoding: label file encoding.
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Returns:
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Dictionary mapping indices to labels.
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"""
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if path is None:
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return {}
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with open(path, "r", encoding=encoding) as f:
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labels = {index: "unknown" for index in range(prefill)}
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lines = f.readlines()
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if not lines:
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return {}
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if lines[0].split(" ", maxsplit=1)[0].isdigit():
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pairs = [line.split(" ", maxsplit=1) for line in lines]
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labels.update({int(index): label.strip() for index, label in pairs})
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else:
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labels.update({index: line.strip() for index, line in enumerate(lines)})
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return labels
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def get_tz_modifiers(tz_name: str) -> Tuple[str, str, float]:
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seconds_offset = (
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datetime.datetime.now(pytz.timezone(tz_name)).utcoffset().total_seconds()
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)
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hours_offset = int(seconds_offset / 60 / 60)
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minutes_offset = int(seconds_offset / 60 - hours_offset * 60)
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hour_modifier = f"{hours_offset} hour"
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minute_modifier = f"{minutes_offset} minute"
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return hour_modifier, minute_modifier, seconds_offset
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def to_relative_box(
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width: int, height: int, box: Tuple[int, int, int, int]
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) -> Tuple[int | float, int | float, int | float, int | float]:
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return (
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box[0] / width, # x
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box[1] / height, # y
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(box[2] - box[0]) / width, # w
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(box[3] - box[1]) / height, # h
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)
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def create_mask(frame_shape, mask):
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mask_img = np.zeros(frame_shape, np.uint8)
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mask_img[:] = 255
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def process_config_query_string(query_string: Dict[str, list]) -> Dict[str, Any]:
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updates = {}
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for key_path_str, new_value_list in query_string.items():
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# use the string key as-is for updates dictionary
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if len(new_value_list) > 1:
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updates[key_path_str] = new_value_list
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else:
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value = new_value_list[0]
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try:
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# no need to convert if we have a mask/zone string
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value = ast.literal_eval(value) if "," not in value else value
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except (ValueError, SyntaxError):
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pass
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updates[key_path_str] = value
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return updates
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def flatten_config_data(
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config_data: Dict[str, Any], parent_key: str = ""
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) -> Dict[str, Any]:
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items = []
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for key, value in config_data.items():
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new_key = f"{parent_key}.{key}" if parent_key else key
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if isinstance(value, dict):
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items.extend(flatten_config_data(value, new_key).items())
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else:
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items.append((new_key, value))
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return dict(items)
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def update_yaml_file_bulk(file_path: str, updates: Dict[str, Any]):
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yaml = YAML()
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yaml.indent(mapping=2, sequence=4, offset=2)
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try:
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with open(file_path, "r") as f:
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data = yaml.load(f)
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except FileNotFoundError:
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logger.error(
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f"Unable to read from Frigate config file {file_path}. Make sure it exists and is readable."
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)
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return
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# Apply all updates
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for key_path_str, new_value in updates.items():
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key_path = key_path_str.split(".")
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for i in range(len(key_path)):
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try:
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index = int(key_path[i])
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key_path[i] = (key_path[i - 1], index)
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key_path.pop(i - 1)
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except ValueError:
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pass
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data = update_yaml(data, key_path, new_value)
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try:
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with open(file_path, "w") as f:
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yaml.dump(data, f)
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except Exception as e:
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logger.error(f"Unable to write to Frigate config file {file_path}: {e}")
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def update_yaml(data, key_path, new_value):
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temp = data
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for key in key_path[:-1]:
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if isinstance(key, tuple):
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if key[0] not in temp:
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temp[key[0]] = [{}] * max(1, key[1] + 1)
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elif len(temp[key[0]]) <= key[1]:
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temp[key[0]] += [{}] * (key[1] - len(temp[key[0]]) + 1)
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temp = temp[key[0]][key[1]]
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else:
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if key not in temp or temp[key] is None:
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temp[key] = {}
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temp = temp[key]
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last_key = key_path[-1]
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if new_value == "":
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if isinstance(last_key, tuple):
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del temp[last_key[0]][last_key[1]]
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else:
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del temp[last_key]
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else:
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if isinstance(last_key, tuple):
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if last_key[0] not in temp:
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temp[last_key[0]] = [{}] * max(1, last_key[1] + 1)
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elif len(temp[last_key[0]]) <= last_key[1]:
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temp[last_key[0]] += [{}] * (last_key[1] - len(temp[last_key[0]]) + 1)
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temp[last_key[0]][last_key[1]] = new_value
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else:
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if (
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last_key in temp
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and isinstance(temp[last_key], dict)
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and isinstance(new_value, dict)
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):
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temp[last_key].update(new_value)
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else:
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temp[last_key] = new_value
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return data
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def find_by_key(dictionary, target_key):
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if target_key in dictionary:
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return dictionary[target_key]
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else:
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for value in dictionary.values():
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if isinstance(value, dict):
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result = find_by_key(value, target_key)
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if result is not None:
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return result
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return None
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def get_tomorrow_at_time(hour: int) -> datetime.datetime:
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"""Returns the datetime of the following day at 2am."""
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try:
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tomorrow = datetime.datetime.now(get_localzone()) + datetime.timedelta(days=1)
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except ZoneInfoNotFoundError:
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tomorrow = datetime.datetime.now(datetime.timezone.utc) + datetime.timedelta(
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days=1
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)
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logger.warning(
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"Using utc for maintenance due to missing or incorrect timezone set"
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)
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return tomorrow.replace(hour=hour, minute=0, second=0).astimezone(
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datetime.timezone.utc
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)
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def is_current_hour(timestamp: int) -> bool:
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"""Returns if timestamp is in the current UTC hour."""
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start_of_next_hour = (
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datetime.datetime.now(datetime.timezone.utc).replace(
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minute=0, second=0, microsecond=0
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)
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+ datetime.timedelta(hours=1)
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).timestamp()
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return timestamp < start_of_next_hour
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def clear_and_unlink(file: Path, missing_ok: bool = True) -> None:
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"""clear file then unlink to avoid space retained by file descriptors."""
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if not missing_ok and not file.exists():
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raise FileNotFoundError()
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# empty contents of file before unlinking https://github.com/blakeblackshear/frigate/issues/4769
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with open(file, "w"):
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pass
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file.unlink(missing_ok=missing_ok)
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def empty_and_close_queue(q):
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while True:
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try:
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q.get(block=True, timeout=0.5)
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except (queue.Empty, EOFError):
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break
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except Exception as e:
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logger.debug(f"Error while emptying queue: {e}")
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break
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# close the queue if it is a multiprocessing queue
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# manager proxy queues do not have close or join_thread method
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if isinstance(q, multiprocessing.queues.Queue):
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try:
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q.close()
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q.join_thread()
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except Exception:
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pass
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def generate_color_palette(n):
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# mimic matplotlib's color scheme
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base_colors = [
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(31, 119, 180), # blue
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(255, 127, 14), # orange
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(44, 160, 44), # green
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(214, 39, 40), # red
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(148, 103, 189), # purple
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(140, 86, 75), # brown
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(227, 119, 194), # pink
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(127, 127, 127), # gray
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(188, 189, 34), # olive
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(23, 190, 207), # cyan
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]
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def interpolate(color1, color2, factor):
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return tuple(int(c1 + (c2 - c1) * factor) for c1, c2 in zip(color1, color2))
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if n <= len(base_colors):
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return base_colors[:n]
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colors = base_colors.copy()
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step = 1 / (n - len(base_colors) + 1)
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extra_colors_needed = n - len(base_colors)
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# interpolate between the base colors to generate more if needed
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for i in range(extra_colors_needed):
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index = i % (len(base_colors) - 1)
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factor = (i + 1) * step
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color1 = base_colors[index]
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color2 = base_colors[index + 1]
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colors.append(interpolate(color1, color2, factor))
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return colors
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def serialize(
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vector: Union[list[float], np.ndarray, float], pack: bool = True
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) -> bytes:
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"""Serializes a list of floats, numpy array, or single float into a compact "raw bytes" format"""
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if isinstance(vector, np.ndarray):
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# Convert numpy array to list of floats
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vector = vector.flatten().tolist()
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elif isinstance(vector, (float, np.float32, np.float64)):
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# Handle single float values
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vector = [vector]
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elif not isinstance(vector, list):
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raise TypeError(
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f"Input must be a list of floats, a numpy array, or a single float. Got {type(vector)}"
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)
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try:
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if pack:
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return struct.pack("%sf" % len(vector), *vector)
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else:
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return vector
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except struct.error as e:
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raise ValueError(f"Failed to pack vector: {e}. Vector: {vector}")
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def deserialize(bytes_data: bytes) -> list[float]:
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"""Deserializes a compact "raw bytes" format into a list of floats"""
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return list(struct.unpack("%sf" % (len(bytes_data) // 4), bytes_data))
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def sanitize_float(value):
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"""Replace NaN or inf with 0.0."""
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if isinstance(value, (int, float)) and not math.isfinite(value):
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return 0.0
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return value
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def cosine_similarity(a: np.ndarray, b: np.ndarray) -> float:
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return 1 - cosine_distance(a, b)
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def cosine_distance(a: np.ndarray, b: np.ndarray) -> float:
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"""Returns cosine distance to match sqlite-vec's calculation."""
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dot = np.dot(a, b)
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a_mag = np.dot(a, a) # ||a||^2
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b_mag = np.dot(b, b) # ||b||^2
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if a_mag == 0 or b_mag == 0:
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return 1.0
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return 1.0 - (dot / (np.sqrt(a_mag) * np.sqrt(b_mag)))
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