blakeblackshear.frigate/frigate/record/maintainer.py
2023-11-18 15:37:06 -06:00

529 lines
20 KiB
Python

"""Maintain recording segments in cache."""
import asyncio
import datetime
import logging
import multiprocessing as mp
import os
import queue
import random
import string
import threading
from collections import defaultdict
from multiprocessing.synchronize import Event as MpEvent
from pathlib import Path
from typing import Any, Optional, Tuple
import numpy as np
import psutil
from frigate.config import FrigateConfig, RetainModeEnum
from frigate.const import (
CACHE_DIR,
CACHE_SEGMENT_FORMAT,
INSERT_MANY_RECORDINGS,
MAX_SEGMENT_DURATION,
MAX_SEGMENTS_IN_CACHE,
RECORD_DIR,
)
from frigate.models import Event, Recordings
from frigate.types import FeatureMetricsTypes
from frigate.util.image import area
from frigate.util.services import get_video_properties
logger = logging.getLogger(__name__)
QUEUE_READ_TIMEOUT = 0.00001 # seconds
class SegmentInfo:
def __init__(
self, motion_box_count: int, active_object_count: int, average_dBFS: int
) -> None:
self.motion_box_count = motion_box_count
self.active_object_count = active_object_count
self.average_dBFS = average_dBFS
def should_discard_segment(self, retain_mode: RetainModeEnum) -> bool:
return (
retain_mode == RetainModeEnum.motion
and self.motion_box_count == 0
and self.average_dBFS == 0
) or (
retain_mode == RetainModeEnum.active_objects
and self.active_object_count == 0
)
class RecordingMaintainer(threading.Thread):
def __init__(
self,
config: FrigateConfig,
inter_process_queue: mp.Queue,
object_recordings_info_queue: mp.Queue,
audio_recordings_info_queue: Optional[mp.Queue],
process_info: dict[str, FeatureMetricsTypes],
stop_event: MpEvent,
):
threading.Thread.__init__(self)
self.name = "recording_maintainer"
self.config = config
self.inter_process_queue = inter_process_queue
self.object_recordings_info_queue = object_recordings_info_queue
self.audio_recordings_info_queue = audio_recordings_info_queue
self.process_info = process_info
self.stop_event = stop_event
self.object_recordings_info: dict[str, list] = defaultdict(list)
self.audio_recordings_info: dict[str, list] = defaultdict(list)
self.end_time_cache: dict[str, Tuple[datetime.datetime, float]] = {}
async def move_files(self) -> None:
cache_files = [
d
for d in os.listdir(CACHE_DIR)
if os.path.isfile(os.path.join(CACHE_DIR, d))
and d.endswith(".mp4")
and not d.startswith("clip_")
]
files_in_use = []
for process in psutil.process_iter():
try:
if process.name() != "ffmpeg":
continue
flist = process.open_files()
if flist:
for nt in flist:
if nt.path.startswith(CACHE_DIR):
files_in_use.append(nt.path.split("/")[-1])
except psutil.Error:
continue
# group recordings by camera
grouped_recordings: defaultdict[str, list[dict[str, Any]]] = defaultdict(list)
for cache in cache_files:
# Skip files currently in use
if cache in files_in_use:
continue
cache_path = os.path.join(CACHE_DIR, cache)
basename = os.path.splitext(cache)[0]
camera, date = basename.rsplit("@", maxsplit=1)
# important that start_time is utc because recordings are stored and compared in utc
start_time = datetime.datetime.strptime(
date, CACHE_SEGMENT_FORMAT
).astimezone(datetime.timezone.utc)
grouped_recordings[camera].append(
{
"cache_path": cache_path,
"start_time": start_time,
}
)
# delete all cached files past the most recent MAX_SEGMENTS_IN_CACHE
keep_count = MAX_SEGMENTS_IN_CACHE
for camera in grouped_recordings.keys():
# sort based on start time
grouped_recordings[camera] = sorted(
grouped_recordings[camera], key=lambda s: s["start_time"]
)
segment_count = len(grouped_recordings[camera])
if segment_count > keep_count:
logger.warning(
f"Unable to keep up with recording segments in cache for {camera}. Keeping the {keep_count} most recent segments out of {segment_count} and discarding the rest..."
)
to_remove = grouped_recordings[camera][:-keep_count]
for rec in to_remove:
cache_path = rec["cache_path"]
Path(cache_path).unlink(missing_ok=True)
self.end_time_cache.pop(cache_path, None)
grouped_recordings[camera] = grouped_recordings[camera][-keep_count:]
tasks = []
for camera, recordings in grouped_recordings.items():
# clear out all the object recording info for old frames
while (
len(self.object_recordings_info[camera]) > 0
and self.object_recordings_info[camera][0][0]
< recordings[0]["start_time"].timestamp()
):
self.object_recordings_info[camera].pop(0)
# clear out all the audio recording info for old frames
while (
len(self.audio_recordings_info[camera]) > 0
and self.audio_recordings_info[camera][0][0]
< recordings[0]["start_time"].timestamp()
):
self.audio_recordings_info[camera].pop(0)
# get all events with the end time after the start of the oldest cache file
# or with end_time None
events: Event = (
Event.select(
Event.start_time,
Event.end_time,
)
.where(
Event.camera == camera,
(Event.end_time == None)
| (Event.end_time >= recordings[0]["start_time"].timestamp()),
Event.has_clip,
)
.order_by(Event.start_time)
)
tasks.extend(
[self.validate_and_move_segment(camera, events, r) for r in recordings]
)
recordings_to_insert: list[Optional[Recordings]] = await asyncio.gather(*tasks)
# fire and forget recordings entries
self.inter_process_queue.put(
(INSERT_MANY_RECORDINGS, [r for r in recordings_to_insert if r is not None])
)
async def validate_and_move_segment(
self, camera: str, events: Event, recording: dict[str, any]
) -> None:
cache_path = recording["cache_path"]
start_time = recording["start_time"]
# Just delete files if recordings are turned off
if (
camera not in self.config.cameras
or not self.process_info[camera]["record_enabled"].value
):
Path(cache_path).unlink(missing_ok=True)
self.end_time_cache.pop(cache_path, None)
return
if cache_path in self.end_time_cache:
end_time, duration = self.end_time_cache[cache_path]
else:
segment_info = await get_video_properties(cache_path, get_duration=True)
if segment_info["duration"]:
duration = float(segment_info["duration"])
else:
duration = -1
# ensure duration is within expected length
if 0 < duration < MAX_SEGMENT_DURATION:
end_time = start_time + datetime.timedelta(seconds=duration)
self.end_time_cache[cache_path] = (end_time, duration)
else:
if duration == -1:
logger.warning(f"Failed to probe corrupt segment {cache_path}")
logger.warning(f"Discarding a corrupt recording segment: {cache_path}")
Path(cache_path).unlink(missing_ok=True)
return
# if cached file's start_time is earlier than the retain days for the camera
if start_time <= (
datetime.datetime.now().astimezone(datetime.timezone.utc)
- datetime.timedelta(days=self.config.cameras[camera].record.retain.days)
):
# if the cached segment overlaps with the events:
overlaps = False
for event in events:
# if the event starts in the future, stop checking events
# and remove this segment
if event.start_time > end_time.timestamp():
overlaps = False
Path(cache_path).unlink(missing_ok=True)
self.end_time_cache.pop(cache_path, None)
break
# if the event is in progress or ends after the recording starts, keep it
# and stop looking at events
if event.end_time is None or event.end_time >= start_time.timestamp():
overlaps = True
break
if overlaps:
record_mode = self.config.cameras[camera].record.events.retain.mode
# move from cache to recordings immediately
return await self.move_segment(
camera,
start_time,
end_time,
duration,
cache_path,
record_mode,
)
# if it doesn't overlap with an event, go ahead and drop the segment
# if it ends more than the configured pre_capture for the camera
else:
pre_capture = self.config.cameras[camera].record.events.pre_capture
camera_info = self.object_recordings_info[camera]
most_recently_processed_frame_time = (
camera_info[-1][0] if len(camera_info) > 0 else 0
)
retain_cutoff = datetime.datetime.fromtimestamp(
most_recently_processed_frame_time - pre_capture
).astimezone(datetime.timezone.utc)
if end_time < retain_cutoff:
Path(cache_path).unlink(missing_ok=True)
self.end_time_cache.pop(cache_path, None)
# else retain days includes this segment
else:
# assume that empty means the relevant recording info has not been received yet
camera_info = self.object_recordings_info[camera]
most_recently_processed_frame_time = (
camera_info[-1][0] if len(camera_info) > 0 else 0
)
# ensure delayed segment info does not lead to lost segments
if (
datetime.datetime.fromtimestamp(
most_recently_processed_frame_time
).astimezone(datetime.timezone.utc)
>= end_time
):
record_mode = self.config.cameras[camera].record.retain.mode
return await self.move_segment(
camera, start_time, end_time, duration, cache_path, record_mode
)
def segment_stats(
self, camera: str, start_time: datetime.datetime, end_time: datetime.datetime
) -> SegmentInfo:
active_count = 0
motion_count = 0
for frame in self.object_recordings_info[camera]:
# frame is after end time of segment
if frame[0] > end_time.timestamp():
break
# frame is before start time of segment
if frame[0] < start_time.timestamp():
continue
active_count += len(
[
o
for o in frame[1]
if not o["false_positive"] and o["motionless_count"] == 0
]
)
motion_count += sum([area(box) for box in frame[2]])
audio_values = []
for frame in self.audio_recordings_info[camera]:
# frame is after end time of segment
if frame[0] > end_time.timestamp():
break
# frame is before start time of segment
if frame[0] < start_time.timestamp():
continue
# add active audio label count to count of active objects
active_count += len(frame[2])
# add sound level to audio values
audio_values.append(frame[1])
average_dBFS = 0 if not audio_values else np.average(audio_values)
return SegmentInfo(motion_count, active_count, round(average_dBFS))
async def move_segment(
self,
camera: str,
start_time: datetime.datetime,
end_time: datetime.datetime,
duration: float,
cache_path: str,
store_mode: RetainModeEnum,
) -> Optional[Recordings]:
segment_info = self.segment_stats(camera, start_time, end_time)
# check if the segment shouldn't be stored
if segment_info.should_discard_segment(store_mode):
Path(cache_path).unlink(missing_ok=True)
self.end_time_cache.pop(cache_path, None)
return
# directory will be in utc due to start_time being in utc
directory = os.path.join(
RECORD_DIR,
start_time.strftime("%Y-%m-%d/%H"),
camera,
)
if not os.path.exists(directory):
os.makedirs(directory)
# file will be in utc due to start_time being in utc
file_name = f"{start_time.strftime('%M.%S.mp4')}"
file_path = os.path.join(directory, file_name)
try:
if not os.path.exists(file_path):
start_frame = datetime.datetime.now().timestamp()
# add faststart to kept segments to improve metadata reading
p = await asyncio.create_subprocess_exec(
"ffmpeg",
"-hide_banner",
"-y",
"-i",
cache_path,
"-c",
"copy",
"-movflags",
"+faststart",
file_path,
stderr=asyncio.subprocess.PIPE,
stdout=asyncio.subprocess.DEVNULL,
)
await p.wait()
if p.returncode != 0:
logger.error(f"Unable to convert {cache_path} to {file_path}")
logger.error((await p.stderr.read()).decode("ascii"))
return None
else:
logger.debug(
f"Copied {file_path} in {datetime.datetime.now().timestamp()-start_frame} seconds."
)
try:
# get the segment size of the cache file
# file without faststart is same size
segment_size = round(
float(os.path.getsize(cache_path)) / pow(2, 20), 1
)
except OSError:
segment_size = 0
os.remove(cache_path)
rand_id = "".join(
random.choices(string.ascii_lowercase + string.digits, k=6)
)
return {
Recordings.id: f"{start_time.timestamp()}-{rand_id}",
Recordings.camera: camera,
Recordings.path: file_path,
Recordings.start_time: start_time.timestamp(),
Recordings.end_time: end_time.timestamp(),
Recordings.duration: duration,
Recordings.motion: segment_info.motion_box_count,
# TODO: update this to store list of active objects at some point
Recordings.objects: segment_info.active_object_count,
Recordings.dBFS: segment_info.average_dBFS,
Recordings.segment_size: segment_size,
}
except Exception as e:
logger.error(f"Unable to store recording segment {cache_path}")
Path(cache_path).unlink(missing_ok=True)
logger.error(e)
# clear end_time cache
self.end_time_cache.pop(cache_path, None)
return None
def run(self) -> None:
camera_count = sum(camera.enabled for camera in self.config.cameras.values())
# Check for new files every 5 seconds
wait_time = 0.0
while not self.stop_event.wait(wait_time):
run_start = datetime.datetime.now().timestamp()
stale_frame_count = 0
stale_frame_count_threshold = 10
# empty the object recordings info queue
while True:
try:
(
camera,
frame_time,
current_tracked_objects,
motion_boxes,
regions,
) = self.object_recordings_info_queue.get(
True, timeout=QUEUE_READ_TIMEOUT
)
if frame_time < run_start - stale_frame_count_threshold:
stale_frame_count += 1
if self.process_info[camera]["record_enabled"].value:
self.object_recordings_info[camera].append(
(
frame_time,
current_tracked_objects,
motion_boxes,
regions,
)
)
except queue.Empty:
q_size = self.object_recordings_info_queue.qsize()
if q_size > camera_count:
logger.debug(
f"object_recordings_info loop queue not empty ({q_size})."
)
break
if stale_frame_count > 0:
logger.debug(f"Found {stale_frame_count} old frames.")
# empty the audio recordings info queue if audio is enabled
if self.audio_recordings_info_queue:
stale_frame_count = 0
while True:
try:
(
camera,
frame_time,
dBFS,
audio_detections,
) = self.audio_recordings_info_queue.get(
True, timeout=QUEUE_READ_TIMEOUT
)
if frame_time < run_start - stale_frame_count_threshold:
stale_frame_count += 1
if self.process_info[camera]["record_enabled"].value:
self.audio_recordings_info[camera].append(
(
frame_time,
dBFS,
audio_detections,
)
)
except queue.Empty:
q_size = self.audio_recordings_info_queue.qsize()
if q_size > camera_count:
logger.debug(
f"object_recordings_info loop audio queue not empty ({q_size})."
)
break
if stale_frame_count > 0:
logger.error(
f"Found {stale_frame_count} old audio frames, segments from recordings may be missing"
)
try:
asyncio.run(self.move_files())
except Exception as e:
logger.error(
"Error occurred when attempting to maintain recording cache"
)
logger.error(e)
duration = datetime.datetime.now().timestamp() - run_start
wait_time = max(0, 5 - duration)
logger.info("Exiting recording maintenance...")