mirror of
https://github.com/blakeblackshear/frigate.git
synced 2026-02-15 15:45:27 +03:00
Drop significant_motion
This commit is contained in:
Rui Alves
parent
be68e3690c
commit
81f75551cc
@ -3,7 +3,7 @@ from typing import Union
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from pydantic import BaseModel
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from pydantic.json_schema import SkipJsonSchema
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from frigate.api.defs.severity_enum import SeverityEnum
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from frigate.review.maintainer import SeverityEnum
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class ReviewQueryParams(BaseModel):
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@ -3,7 +3,7 @@ from typing import Dict
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from pydantic import BaseModel, Json
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from frigate.api.defs.severity_enum import SeverityEnum
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from frigate.review.maintainer import SeverityEnum
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class ReviewSegmentResponse(BaseModel):
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@ -20,7 +20,6 @@ class ReviewSegmentResponse(BaseModel):
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class Last24HoursReview(BaseModel):
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reviewed_alert: int
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reviewed_detection: int
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reviewed_motion: int
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total_alert: int
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total_detection: int
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total_motion: int
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@ -30,7 +29,6 @@ class DayReview(BaseModel):
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day: datetime
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reviewed_alert: int
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reviewed_detection: int
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reviewed_motion: int
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total_alert: int
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total_detection: int
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total_motion: int
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@ -45,8 +43,3 @@ class ReviewActivityMotionResponse(BaseModel):
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start_time: int
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motion: float
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camera: str
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class ReviewActivityAudioResponse(BaseModel):
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start_time: int
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audio: int
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@ -1,7 +0,0 @@
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from enum import Enum
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class SeverityEnum(str, Enum):
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alert = "alert"
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detection = "detection"
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significant_motion = "significant_motion"
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@ -1,7 +1,6 @@
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"""Review apis."""
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import datetime
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import json
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import logging
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from functools import reduce
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from pathlib import Path
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@ -24,7 +23,6 @@ from frigate.api.defs.review_query_parameters import (
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ReviewSummaryQueryParams,
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)
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from frigate.api.defs.review_responses import (
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ReviewActivityAudioResponse,
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ReviewActivityMotionResponse,
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ReviewSegmentResponse,
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ReviewSummaryResponse,
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@ -185,18 +183,6 @@ def review_summary(params: ReviewSummaryQueryParams = Depends()):
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0,
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)
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).alias("reviewed_detection"),
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fn.SUM(
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Case(
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None,
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[
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(
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(ReviewSegment.severity == "significant_motion"),
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ReviewSegment.has_been_reviewed,
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)
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],
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0,
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)
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).alias("reviewed_motion"),
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fn.SUM(
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Case(
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None,
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@ -221,18 +207,6 @@ def review_summary(params: ReviewSummaryQueryParams = Depends()):
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0,
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)
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).alias("total_detection"),
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fn.SUM(
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Case(
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None,
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[
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(
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(ReviewSegment.severity == "significant_motion"),
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1,
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)
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],
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0,
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)
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).alias("total_motion"),
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)
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.where(reduce(operator.and_, clauses))
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.dicts()
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@ -294,18 +268,6 @@ def review_summary(params: ReviewSummaryQueryParams = Depends()):
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0,
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)
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).alias("reviewed_detection"),
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fn.SUM(
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Case(
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None,
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[
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(
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(ReviewSegment.severity == "significant_motion"),
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ReviewSegment.has_been_reviewed,
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)
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],
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0,
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)
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).alias("reviewed_motion"),
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fn.SUM(
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Case(
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None,
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@ -330,18 +292,6 @@ def review_summary(params: ReviewSummaryQueryParams = Depends()):
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0,
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)
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).alias("total_detection"),
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fn.SUM(
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Case(
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None,
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[
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(
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(ReviewSegment.severity == "significant_motion"),
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1,
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)
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],
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0,
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)
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).alias("total_motion"),
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)
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.where(reduce(operator.and_, clauses))
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.group_by(
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@ -495,71 +445,6 @@ def motion_activity(params: ReviewActivityMotionQueryParams = Depends()):
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return JSONResponse(content=normalized)
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@router.get("/review/activity/audio", response_model=list[ReviewActivityAudioResponse])
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def audio_activity(params: ReviewActivityMotionQueryParams = Depends()):
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"""Get motion and audio activity."""
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cameras = params.cameras
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before = params.before or datetime.datetime.now().timestamp()
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after = (
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params.after
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or (datetime.datetime.now() - datetime.timedelta(hours=1)).timestamp()
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)
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# get scale in seconds
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scale = params.scale
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clauses = [(Recordings.start_time > after) & (Recordings.end_time < before)]
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if cameras != "all":
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camera_list = cameras.split(",")
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clauses.append((Recordings.camera << camera_list))
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all_recordings: list[Recordings] = (
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Recordings.select(
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Recordings.start_time,
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Recordings.duration,
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Recordings.objects,
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Recordings.dBFS,
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)
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.where(reduce(operator.and_, clauses))
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.order_by(Recordings.start_time.asc())
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.iterator()
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)
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# format is: { timestamp: segment_start_ts, motion: [0-100], audio: [0 - -100] }
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# periods where active objects / audio was detected will cause audio to be scaled down
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data: list[dict[str, float]] = []
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for rec in all_recordings:
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data.append(
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{
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"start_time": rec.start_time,
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"audio": rec.dBFS if rec.objects == 0 else 0,
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}
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)
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# resample data using pandas to get activity on scaled basis
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df = pd.DataFrame(data, columns=["start_time", "audio"])
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df = df.astype(dtype={"audio": "float16"})
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# set date as datetime index
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df["start_time"] = pd.to_datetime(df["start_time"], unit="s")
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df.set_index(["start_time"], inplace=True)
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# normalize data
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df = df.resample(f"{scale}S").mean().fillna(0.0)
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# FIXME: If min/max audio is the same then we get division by 0 and as such audio is 'nan'
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df["audio"] = (
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(df["audio"] - df["audio"].max())
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/ (df["audio"].min() - df["audio"].max())
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* -100
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)
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# change types for output
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df.index = df.index.astype(int) // (10**9)
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normalized = json.loads(df.reset_index().to_json(orient="records"))
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return JSONResponse(content=normalized)
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@router.get("/review/event/{event_id}", response_model=ReviewSegmentResponse)
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def get_review_from_event(event_id: str):
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try:
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@ -93,7 +93,7 @@ class ReviewSegment(Model): # type: ignore[misc]
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start_time = DateTimeField()
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end_time = DateTimeField()
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has_been_reviewed = BooleanField(default=False)
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severity = CharField(max_length=30) # alert, detection, significant_motion
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severity = CharField(max_length=30) # alert, detection
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thumb_path = CharField(unique=True)
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data = JSONField() # additional data about detection like list of labels, zone, areas of significant motion
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@ -407,10 +407,6 @@ export default function Events() {
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review.severity == "detection"
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? item.reviewed_detection + 1
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: item.reviewed_detection,
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reviewed_motion:
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review.severity == "significant_motion"
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? item.reviewed_motion + 1
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: item.reviewed_motion,
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},
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};
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},
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@ -42,7 +42,6 @@ type ReviewSummaryDay = {
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day: string;
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reviewed_alert: number;
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reviewed_detection: number;
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reviewed_motion: number;
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total_alert: number;
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total_detection: number;
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total_motion: number;
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@ -117,13 +117,11 @@ export default function EventView({
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return {
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alert: summary.total_alert ?? 0,
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detection: summary.total_detection ?? 0,
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significant_motion: summary.total_motion ?? 0,
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};
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} else {
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return {
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alert: summary.total_alert - summary.reviewed_alert,
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detection: summary.total_detection - summary.reviewed_detection,
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significant_motion: summary.total_motion - summary.reviewed_motion,
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};
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}
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}, [filter, showReviewed, reviewSummary]);
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