Files
blakeblackshear.frigate/frigate/util/builtin.py
Nicolas Mowen 1caf8b97c4 Use Fork-Server As Spawn Method (#18682)
* Set runtime

* Use count correctly

* Don't assume camera sizes

* Use separate zmq proxy for object detection

* Correct order

* Use forkserver

* Only store PID instead of entire process reference

* Cleanup

* Catch correct errors

* Fix typing

* Remove before_run from process util

The before_run never actually ran because:

You're right to suspect an issue with before_run not being called and a potential deadlock. The way you've implemented the run_wrapper using __getattribute__ for the run method of BaseProcess is a common pitfall in Python's multiprocessing, especially when combined with how multiprocessing.Process works internally.

Here's a breakdown of why before_run isn't being called and why you might be experiencing a deadlock:

The Problem: __getattribute__ and Process Serialization
When you create a multiprocessing.Process object and call start(), the multiprocessing module needs to serialize the process object (or at least enough of it to re-create the process in the new interpreter). It then pickles this serialized object and sends it to the newly spawned process.

The issue with your __getattribute__ implementation for run is that:

run is retrieved during serialization: When multiprocessing tries to pickle your Process object to send to the new process, it will likely access the run attribute. This triggers your __getattribute__ wrapper, which then tries to bind run_wrapper to self.
run_wrapper is bound to the parent process's self: The run_wrapper closure, when created in the parent process, captures the self (the Process instance) from the parent's memory space.
Deserialization creates a new object: In the child process, a new Process object is created by deserializing the pickled data. However, the run_wrapper method that was pickled still holds a reference to the self from the parent process. This is a subtle but critical distinction.
The child's run is not your wrapped run: When the child process starts, it internally calls its own run method. Because of the serialization and deserialization process, the run method that's ultimately executed in the child process is the original multiprocessing.Process.run or the Process.run if you had directly overridden it. Your __getattribute__ magic, which wraps run, isn't correctly applied to the Process object within the child's context.

* Cleanup

* Logging bugfix (#18465)

* use mp Manager to handle logging queues

A Python bug (https://github.com/python/cpython/issues/91555) was preventing logs from the embeddings maintainer process from printing. The bug is fixed in Python 3.14, but a viable workaround is to use the multiprocessing Manager, which better manages mp queues and causes the logging to work correctly.

* consolidate

* fix typing

* Fix typing

* Use global log queue

* Move to using process for logging

* Convert camera tracking to process

* Add more processes

* Finalize process

* Cleanup

* Cleanup typing

* Formatting

* Remove daemon

---------

Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>
2025-08-16 10:20:33 -05:00

424 lines
13 KiB
Python

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