blakeblackshear.frigate/frigate/http.py

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Python
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import base64
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from collections import OrderedDict
from datetime import datetime, timedelta
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import json
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import glob
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import logging
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import os
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import re
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import time
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from functools import reduce
from pathlib import Path
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import cv2
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import numpy as np
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from flask import (
Blueprint,
Flask,
Response,
current_app,
jsonify,
make_response,
request,
)
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from peewee import SqliteDatabase, operator, fn, DoesNotExist, Value
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from playhouse.shortcuts import model_to_dict
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from frigate.const import CLIPS_DIR, RECORD_DIR
from frigate.models import Event, Recordings
from frigate.stats import stats_snapshot
from frigate.util import calculate_region
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from frigate.version import VERSION
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logger = logging.getLogger(__name__)
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bp = Blueprint("frigate", __name__)
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def create_app(
frigate_config,
database: SqliteDatabase,
stats_tracking,
detected_frames_processor,
):
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app = Flask(__name__)
@app.before_request
def _db_connect():
if database.is_closed():
database.connect()
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@app.teardown_request
def _db_close(exc):
if not database.is_closed():
database.close()
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app.frigate_config = frigate_config
app.stats_tracking = stats_tracking
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app.detected_frames_processor = detected_frames_processor
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app.register_blueprint(bp)
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return app
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@bp.route("/")
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def is_healthy():
return "Frigate is running. Alive and healthy!"
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@bp.route("/events/summary")
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def events_summary():
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has_clip = request.args.get("has_clip", type=int)
has_snapshot = request.args.get("has_snapshot", type=int)
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clauses = []
if not has_clip is None:
clauses.append((Event.has_clip == has_clip))
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if not has_snapshot is None:
clauses.append((Event.has_snapshot == has_snapshot))
if len(clauses) == 0:
clauses.append((True))
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groups = (
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Event.select(
Event.camera,
Event.label,
fn.strftime(
"%Y-%m-%d", fn.datetime(Event.start_time, "unixepoch", "localtime")
).alias("day"),
Event.zones,
fn.COUNT(Event.id).alias("count"),
)
.where(reduce(operator.and_, clauses))
.group_by(
Event.camera,
Event.label,
fn.strftime(
"%Y-%m-%d", fn.datetime(Event.start_time, "unixepoch", "localtime")
),
Event.zones,
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)
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)
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return jsonify([e for e in groups.dicts()])
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@bp.route("/events/<id>", methods=("GET",))
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def event(id):
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try:
return model_to_dict(Event.get(Event.id == id))
except DoesNotExist:
return "Event not found", 404
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@bp.route("/events/<id>", methods=("DELETE",))
def delete_event(id):
try:
event = Event.get(Event.id == id)
except DoesNotExist:
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return make_response(
jsonify({"success": False, "message": "Event" + id + " not found"}), 404
)
media_name = f"{event.camera}-{event.id}"
if event.has_snapshot:
media = Path(f"{os.path.join(CLIPS_DIR, media_name)}.jpg")
media.unlink(missing_ok=True)
if event.has_clip:
media = Path(f"{os.path.join(CLIPS_DIR, media_name)}.mp4")
media.unlink(missing_ok=True)
event.delete_instance()
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return make_response(
jsonify({"success": True, "message": "Event" + id + " deleted"}), 200
)
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@bp.route("/events/<id>/thumbnail.jpg")
def event_thumbnail(id):
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format = request.args.get("format", "ios")
thumbnail_bytes = None
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try:
event = Event.get(Event.id == id)
thumbnail_bytes = base64.b64decode(event.thumbnail)
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except DoesNotExist:
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# see if the object is currently being tracked
try:
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camera_states = current_app.detected_frames_processor.camera_states.values()
for camera_state in camera_states:
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if id in camera_state.tracked_objects:
tracked_obj = camera_state.tracked_objects.get(id)
if not tracked_obj is None:
thumbnail_bytes = tracked_obj.get_thumbnail()
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except:
return "Event not found", 404
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if thumbnail_bytes is None:
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return "Event not found", 404
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# android notifications prefer a 2:1 ratio
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if format == "android":
jpg_as_np = np.frombuffer(thumbnail_bytes, dtype=np.uint8)
img = cv2.imdecode(jpg_as_np, flags=1)
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thumbnail = cv2.copyMakeBorder(
img,
0,
0,
int(img.shape[1] * 0.5),
int(img.shape[1] * 0.5),
cv2.BORDER_CONSTANT,
(0, 0, 0),
)
ret, jpg = cv2.imencode(".jpg", thumbnail, [int(cv2.IMWRITE_JPEG_QUALITY), 70])
thumbnail_bytes = jpg.tobytes()
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response = make_response(thumbnail_bytes)
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response.headers["Content-Type"] = "image/jpg"
return response
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@bp.route("/events/<id>/snapshot.jpg")
def event_snapshot(id):
jpg_bytes = None
try:
event = Event.get(Event.id == id)
if not event.has_snapshot:
return "Snapshot not available", 404
# read snapshot from disk
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with open(
os.path.join(CLIPS_DIR, f"{event.camera}-{id}.jpg"), "rb"
) as image_file:
jpg_bytes = image_file.read()
except DoesNotExist:
# see if the object is currently being tracked
try:
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camera_states = current_app.detected_frames_processor.camera_states.values()
for camera_state in camera_states:
if id in camera_state.tracked_objects:
tracked_obj = camera_state.tracked_objects.get(id)
if not tracked_obj is None:
jpg_bytes = tracked_obj.get_jpg_bytes(
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timestamp=request.args.get("timestamp", type=int),
bounding_box=request.args.get("bbox", type=int),
crop=request.args.get("crop", type=int),
height=request.args.get("h", type=int),
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quality=request.args.get("quality", default=70, type=int),
)
except:
return "Event not found", 404
except:
return "Event not found", 404
if jpg_bytes is None:
return "Event not found", 404
response = make_response(jpg_bytes)
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response.headers["Content-Type"] = "image/jpg"
return response
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@bp.route("/events")
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def events():
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limit = request.args.get("limit", 100)
camera = request.args.get("camera")
label = request.args.get("label")
zone = request.args.get("zone")
after = request.args.get("after", type=float)
before = request.args.get("before", type=float)
has_clip = request.args.get("has_clip", type=int)
has_snapshot = request.args.get("has_snapshot", type=int)
include_thumbnails = request.args.get("include_thumbnails", default=1, type=int)
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clauses = []
excluded_fields = []
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if camera:
clauses.append((Event.camera == camera))
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if label:
clauses.append((Event.label == label))
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if zone:
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clauses.append((Event.zones.cast("text") % f'*"{zone}"*'))
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if after:
clauses.append((Event.start_time >= after))
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if before:
clauses.append((Event.start_time <= before))
if not has_clip is None:
clauses.append((Event.has_clip == has_clip))
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if not has_snapshot is None:
clauses.append((Event.has_snapshot == has_snapshot))
if not include_thumbnails:
excluded_fields.append(Event.thumbnail)
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if len(clauses) == 0:
clauses.append((True))
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events = (
Event.select()
.where(reduce(operator.and_, clauses))
.order_by(Event.start_time.desc())
.limit(limit)
)
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return jsonify([model_to_dict(e, exclude=excluded_fields) for e in events])
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@bp.route("/config")
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def config():
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return jsonify(current_app.frigate_config.dict())
@bp.route("/config/schema")
def config_schema():
return current_app.response_class(
current_app.frigate_config.schema_json(), mimetype="application/json"
)
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@bp.route("/version")
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def version():
return VERSION
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@bp.route("/stats")
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def stats():
stats = stats_snapshot(current_app.stats_tracking)
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return jsonify(stats)
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@bp.route("/<camera_name>/<label>/best.jpg")
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def best(camera_name, label):
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if camera_name in current_app.frigate_config.cameras:
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best_object = current_app.detected_frames_processor.get_best(camera_name, label)
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best_frame = best_object.get("frame")
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if best_frame is None:
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best_frame = np.zeros((720, 1280, 3), np.uint8)
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else:
best_frame = cv2.cvtColor(best_frame, cv2.COLOR_YUV2BGR_I420)
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crop = bool(request.args.get("crop", 0, type=int))
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if crop:
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box = best_object.get("box", (0, 0, 300, 300))
region = calculate_region(
best_frame.shape, box[0], box[1], box[2], box[3], 1.1
)
best_frame = best_frame[region[1] : region[3], region[0] : region[2]]
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height = int(request.args.get("h", str(best_frame.shape[0])))
width = int(height * best_frame.shape[1] / best_frame.shape[0])
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resize_quality = request.args.get("quality", default=70, type=int)
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best_frame = cv2.resize(
best_frame, dsize=(width, height), interpolation=cv2.INTER_AREA
)
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ret, jpg = cv2.imencode(
".jpg", best_frame, [int(cv2.IMWRITE_JPEG_QUALITY), resize_quality]
)
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response = make_response(jpg.tobytes())
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response.headers["Content-Type"] = "image/jpg"
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return response
else:
return "Camera named {} not found".format(camera_name), 404
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@bp.route("/<camera_name>")
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def mjpeg_feed(camera_name):
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fps = int(request.args.get("fps", "3"))
height = int(request.args.get("h", "360"))
draw_options = {
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"bounding_boxes": request.args.get("bbox", type=int),
"timestamp": request.args.get("timestamp", type=int),
"zones": request.args.get("zones", type=int),
"mask": request.args.get("mask", type=int),
"motion_boxes": request.args.get("motion", type=int),
"regions": request.args.get("regions", type=int),
}
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if camera_name in current_app.frigate_config.cameras:
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# return a multipart response
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return Response(
imagestream(
current_app.detected_frames_processor,
camera_name,
fps,
height,
draw_options,
),
mimetype="multipart/x-mixed-replace; boundary=frame",
)
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else:
return "Camera named {} not found".format(camera_name), 404
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@bp.route("/<camera_name>/latest.jpg")
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def latest_frame(camera_name):
draw_options = {
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"bounding_boxes": request.args.get("bbox", type=int),
"timestamp": request.args.get("timestamp", type=int),
"zones": request.args.get("zones", type=int),
"mask": request.args.get("mask", type=int),
"motion_boxes": request.args.get("motion", type=int),
"regions": request.args.get("regions", type=int),
}
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resize_quality = request.args.get("quality", default=70, type=int)
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if camera_name in current_app.frigate_config.cameras:
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frame = current_app.detected_frames_processor.get_current_frame(
camera_name, draw_options
)
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if frame is None:
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frame = np.zeros((720, 1280, 3), np.uint8)
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height = int(request.args.get("h", str(frame.shape[0])))
width = int(height * frame.shape[1] / frame.shape[0])
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frame = cv2.resize(frame, dsize=(width, height), interpolation=cv2.INTER_AREA)
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ret, jpg = cv2.imencode(
".jpg", frame, [int(cv2.IMWRITE_JPEG_QUALITY), resize_quality]
)
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response = make_response(jpg.tobytes())
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response.headers["Content-Type"] = "image/jpg"
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return response
else:
return "Camera named {} not found".format(camera_name), 404
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@bp.route("/<camera_name>/recordings")
def recordings(camera_name):
dates = OrderedDict()
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# Retrieve all recordings for this camera
recordings = (
Recordings.select()
.where(Recordings.camera == camera_name)
.order_by(Recordings.start_time.asc())
)
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last_end = 0
recording: Recordings
for recording in recordings:
date = datetime.fromtimestamp(recording.start_time)
key = date.strftime("%Y-%m-%d")
hour = date.strftime("%H")
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# Create Day Record
if key not in dates:
dates[key] = OrderedDict()
# Create Hour Record
if hour not in dates[key]:
dates[key][hour] = {"delay": {}, "events": []}
# Check for delay
the_hour = datetime.strptime(f"{key} {hour}", "%Y-%m-%d %H").timestamp()
# diff current recording start time and the greater of the previous end time or top of the hour
diff = recording.start_time - max(last_end, the_hour)
# Determine seconds into recording
seconds = 0
if datetime.fromtimestamp(last_end).strftime("%H") == hour:
seconds = int(last_end - the_hour)
# Determine the delay
delay = min(int(diff), 3600 - seconds)
if delay > 1:
# Add an offset for any delay greater than a second
dates[key][hour]["delay"][seconds] = delay
last_end = recording.end_time
# Packing intervals to return all events with same label and overlapping times as one row.
# See: https://blogs.solidq.com/en/sqlserver/packing-intervals/
events = Event.raw(
"""WITH C1 AS
(
SELECT id, label, camera, top_score, start_time AS ts, +1 AS type, 1 AS sub
FROM event
WHERE camera = ?
UNION ALL
SELECT id, label, camera, top_score, end_time + 15 AS ts, -1 AS type, 0 AS sub
FROM event
WHERE camera = ?
),
C2 AS
(
SELECT C1.*,
SUM(type) OVER(PARTITION BY label ORDER BY ts, type DESC
ROWS BETWEEN UNBOUNDED PRECEDING
AND CURRENT ROW) - sub AS cnt
FROM C1
),
C3 AS
(
SELECT id, label, camera, top_score, ts,
(ROW_NUMBER() OVER(PARTITION BY label ORDER BY ts) - 1) / 2 + 1
AS grpnum
FROM C2
WHERE cnt = 0
)
SELECT MIN(id) as id, label, camera, MAX(top_score) as top_score, MIN(ts) AS start_time, max(ts) AS end_time
FROM C3
GROUP BY label, grpnum
ORDER BY start_time;""",
camera_name,
camera_name,
)
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event: Event
for event in events:
date = datetime.fromtimestamp(event.start_time)
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key = date.strftime("%Y-%m-%d")
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hour = date.strftime("%H")
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if key in dates and hour in dates[key]:
dates[key][hour]["events"].append(
model_to_dict(
event,
exclude=[
Event.false_positive,
Event.zones,
Event.thumbnail,
Event.has_clip,
Event.has_snapshot,
],
)
)
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return jsonify(
[
{
"date": date,
"events": sum([len(value["events"]) for value in hours.values()]),
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"recordings": [
{"hour": hour, "delay": value["delay"], "events": value["events"]}
for hour, value in hours.items()
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],
}
for date, hours in dates.items()
]
)
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@bp.route("/vod/<year_month>/<day>/<hour>/<camera>")
def vod(year_month, day, hour, camera):
start_date = datetime.strptime(f"{year_month}-{day} {hour}", "%Y-%m-%d %H")
end_date = start_date + timedelta(hours=1) - timedelta(milliseconds=1)
start_ts = start_date.timestamp()
end_ts = end_date.timestamp()
# Select all recordings where either the start or end dates fall in the requested hour
recordings = (
Recordings.select()
.where(
(Recordings.start_time.between(start_ts, end_ts))
| (Recordings.end_time.between(start_ts, end_ts))
)
.where(Recordings.camera == camera)
.order_by(Recordings.start_time.asc())
)
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clips = []
durations = []
recording: Recordings
for recording in recordings:
clip = {"type": "source", "path": recording.path}
duration = int(recording.duration * 1000)
# Determine if offset is needed for first clip
if recording.start_time < start_ts:
offset = int((start_ts - recording.start_time) * 1000)
clip["clipFrom"] = offset
duration -= offset
# Determine if we need to end the last clip early
if recording.end_time > end_ts:
duration -= int((recording.end_time - end_ts) * 1000)
clips.append(clip)
durations.append(duration)
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return jsonify(
{
"cache": datetime.now() - timedelta(hours=1) > start_date,
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"discontinuity": False,
"durations": durations,
"sequences": [{"clips": clips}],
}
)
def imagestream(detected_frames_processor, camera_name, fps, height, draw_options):
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while True:
# max out at specified FPS
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time.sleep(1 / fps)
frame = detected_frames_processor.get_current_frame(camera_name, draw_options)
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if frame is None:
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frame = np.zeros((height, int(height * 16 / 9), 3), np.uint8)
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width = int(height * frame.shape[1] / frame.shape[0])
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frame = cv2.resize(frame, dsize=(width, height), interpolation=cv2.INTER_LINEAR)
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ret, jpg = cv2.imencode(".jpg", frame, [int(cv2.IMWRITE_JPEG_QUALITY), 70])
yield (
b"--frame\r\n"
b"Content-Type: image/jpeg\r\n\r\n" + jpg.tobytes() + b"\r\n\r\n"
)