blakeblackshear.frigate/frigate/review/maintainer.py

337 lines
12 KiB
Python

"""Maintain review segments in db."""
import logging
import os
import random
import string
import threading
from enum import Enum
from multiprocessing.synchronize import Event as MpEvent
from typing import Optional
import cv2
import numpy as np
from frigate.comms.config_updater import ConfigSubscriber
from frigate.comms.detections_updater import DetectionSubscriber, DetectionTypeEnum
from frigate.comms.inter_process import InterProcessRequestor
from frigate.config import CameraConfig, FrigateConfig
from frigate.const import CLIPS_DIR, UPSERT_REVIEW_SEGMENT
from frigate.models import ReviewSegment
from frigate.object_processing import TrackedObject
from frigate.util.image import SharedMemoryFrameManager, calculate_16_9_crop
logger = logging.getLogger(__name__)
THUMB_HEIGHT = 180
THUMB_WIDTH = 320
class SeverityEnum(str, Enum):
alert = "alert"
detection = "detection"
signification_motion = "significant_motion"
class PendingReviewSegment:
def __init__(
self,
camera: str,
frame_time: float,
severity: SeverityEnum,
detections: set[str] = set(),
objects: set[str] = set(),
sub_labels: set[str] = set(),
zones: set[str] = set(),
audio: set[str] = set(),
motion: list[int] = [],
):
rand_id = "".join(random.choices(string.ascii_lowercase + string.digits, k=6))
self.id = f"{frame_time}-{rand_id}"
self.camera = camera
self.start_time = frame_time
self.severity = severity
self.detections = detections
self.objects = objects
self.sub_labels = sub_labels
self.zones = zones
self.audio = audio
self.sig_motion_areas = motion
self.last_update = frame_time
# thumbnail
self.frame = np.zeros((THUMB_HEIGHT * 3 // 2, THUMB_WIDTH), np.uint8)
self.frame_active_count = 0
def update_frame(
self, camera_config: CameraConfig, frame, objects: list[TrackedObject]
):
min_x = camera_config.frame_shape[1]
min_y = camera_config.frame_shape[0]
max_x = 0
max_y = 0
# find bounds for all boxes
for o in objects:
min_x = min(o["box"][0], min_x)
min_y = min(o["box"][1], min_y)
max_x = max(o["box"][2], max_x)
max_y = max(o["box"][3], max_y)
region = calculate_16_9_crop(
camera_config.frame_shape, min_x, min_y, max_x, max_y
)
# could not find suitable 16:9 region
if not region:
return
self.frame_active_count = len(objects)
color_frame = cv2.cvtColor(frame, cv2.COLOR_YUV2BGR_I420)
color_frame = color_frame[region[1] : region[3], region[0] : region[2]]
width = int(THUMB_HEIGHT * color_frame.shape[1] / color_frame.shape[0])
self.frame = cv2.resize(
color_frame, dsize=(width, THUMB_HEIGHT), interpolation=cv2.INTER_AREA
)
def end(self) -> dict:
path = os.path.join(CLIPS_DIR, f"thumb-{self.camera}-{self.id}.jpg")
if self.frame is not None:
cv2.imwrite(path, self.frame)
return {
ReviewSegment.id: self.id,
ReviewSegment.camera: self.camera,
ReviewSegment.start_time: self.start_time,
ReviewSegment.end_time: self.last_update,
ReviewSegment.severity: self.severity.value,
ReviewSegment.thumb_path: path,
ReviewSegment.data: {
"detections": list(self.detections),
"objects": list(self.objects),
"sub_labels": list(self.sub_labels),
"zones": list(self.zones),
"audio": list(self.audio),
"significant_motion_areas": self.sig_motion_areas,
},
}
class ReviewSegmentMaintainer(threading.Thread):
"""Maintain review segments."""
def __init__(self, config: FrigateConfig, stop_event: MpEvent):
threading.Thread.__init__(self)
self.name = "review_segment_maintainer"
self.config = config
self.active_review_segments: dict[str, Optional[PendingReviewSegment]] = {}
self.frame_manager = SharedMemoryFrameManager()
# create communication for review segments
self.requestor = InterProcessRequestor()
self.config_subscriber = ConfigSubscriber("config/record/")
self.detection_subscriber = DetectionSubscriber(DetectionTypeEnum.all)
self.stop_event = stop_event
def end_segment(self, segment: PendingReviewSegment) -> None:
"""End segment."""
self.requestor.send_data(UPSERT_REVIEW_SEGMENT, segment.end())
self.active_review_segments[segment.camera] = None
def update_existing_segment(
self,
segment: PendingReviewSegment,
frame_time: float,
objects: list[TrackedObject],
motion: list,
) -> None:
"""Validate if existing review segment should continue."""
camera_config = self.config.cameras[segment.camera]
active_objects = get_active_objects(frame_time, camera_config, objects)
if len(active_objects) > 0:
segment.last_update = frame_time
# update type for this segment now that active objects are detected
if segment.severity == SeverityEnum.signification_motion:
segment.severity = SeverityEnum.detection
if len(active_objects) > segment.frame_active_count:
frame_id = f"{camera_config.name}{frame_time}"
yuv_frame = self.frame_manager.get(
frame_id, camera_config.frame_shape_yuv
)
segment.update_frame(camera_config, yuv_frame, active_objects)
self.frame_manager.close(frame_id)
for object in active_objects:
segment.detections.add(object["id"])
segment.objects.add(object["label"])
if object["sub_label"]:
segment.sub_labels.add(object["sub_label"][0])
# if object is alert label and has qualified for recording
# mark this review as alert
if (
segment.severity == SeverityEnum.detection
and object["has_clip"]
and object["label"] in camera_config.objects.alert
):
segment.severity = SeverityEnum.alert
# keep zones up to date
if len(object["current_zones"]) > 0:
segment.zones.update(object["current_zones"])
elif (
segment.severity == SeverityEnum.signification_motion and len(motion) >= 20
):
segment.last_update = frame_time
else:
if segment.severity == SeverityEnum.alert and frame_time > (
segment.last_update + 60
):
self.end_segment(segment)
elif frame_time > (segment.last_update + 10):
self.end_segment(segment)
def check_if_new_segment(
self,
camera: str,
frame_time: float,
objects: list[TrackedObject],
motion: list,
) -> None:
"""Check if a new review segment should be created."""
camera_config = self.config.cameras[camera]
active_objects = get_active_objects(frame_time, camera_config, objects)
if len(active_objects) > 0:
has_sig_object = False
detections: set = set()
objects: set = set()
sub_labels: set = set()
zones: set = set()
for object in active_objects:
if (
not has_sig_object
and object["has_clip"]
and object["label"] in camera_config.objects.alert
):
has_sig_object = True
detections.add(object["id"])
objects.add(object["label"])
if object["sub_label"]:
sub_labels.add(object["sub_label"][0])
zones.update(object["current_zones"])
self.active_review_segments[camera] = PendingReviewSegment(
camera,
frame_time,
SeverityEnum.alert if has_sig_object else SeverityEnum.detection,
detections,
objects=objects,
sub_labels=sub_labels,
zones=zones,
)
frame_id = f"{camera_config.name}{frame_time}"
yuv_frame = self.frame_manager.get(frame_id, camera_config.frame_shape_yuv)
self.active_review_segments[camera].update_frame(
camera_config, yuv_frame, active_objects
)
self.frame_manager.close(frame_id)
elif len(motion) >= 20:
self.active_review_segments[camera] = PendingReviewSegment(
camera, frame_time, SeverityEnum.signification_motion, motion=motion
)
def run(self) -> None:
while not self.stop_event.is_set():
# check if there is an updated config
while True:
(
updated_topic,
updated_record_config,
) = self.config_subscriber.check_for_update()
if not updated_topic:
break
camera_name = updated_topic.rpartition("/")[-1]
self.config.cameras[camera_name].record = updated_record_config
(topic, data) = self.detection_subscriber.get_data(timeout=1)
if not topic:
continue
if topic == DetectionTypeEnum.video:
(
camera,
frame_time,
current_tracked_objects,
motion_boxes,
regions,
) = data
elif topic == DetectionTypeEnum.audio:
(
camera,
frame_time,
dBFS,
audio_detections,
) = data
if not self.config.cameras[camera].record.enabled:
continue
current_segment = self.active_review_segments.get(camera)
if current_segment is not None:
if topic == DetectionTypeEnum.video:
self.update_existing_segment(
current_segment,
frame_time,
current_tracked_objects,
motion_boxes,
)
elif topic == DetectionTypeEnum.audio and len(audio_detections) > 0:
current_segment.last_update = frame_time
current_segment.audio.update(audio_detections)
else:
if topic == DetectionTypeEnum.video:
self.check_if_new_segment(
camera,
frame_time,
current_tracked_objects,
motion_boxes,
)
elif topic == DetectionTypeEnum.audio and len(audio_detections) > 0:
self.active_review_segments[camera] = PendingReviewSegment(
camera,
frame_time,
SeverityEnum.detection,
audio=set(audio_detections),
)
def get_active_objects(
frame_time: float, camera_config: CameraConfig, all_objects: list[TrackedObject]
) -> list[TrackedObject]:
"""get active objects for detection."""
return [
o
for o in all_objects
if o["motionless_count"] < camera_config.detect.stationary.threshold
and o["position_changes"] > 0
and o["frame_time"] == frame_time
and not o["false_positive"]
]