mirror of
https://github.com/blakeblackshear/frigate.git
synced 2024-12-23 19:11:14 +01:00
270 lines
9.3 KiB
Python
270 lines
9.3 KiB
Python
import base64
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import datetime
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import logging
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import os
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import time
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from functools import reduce
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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,
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make_response, request)
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from peewee import SqliteDatabase, operator, fn, DoesNotExist
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from playhouse.shortcuts import model_to_dict
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from frigate.models import Event
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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, camera_metrics, detectors, detected_frames_processor):
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app = Flask(__name__)
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@app.before_request
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def _db_connect():
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database.connect()
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@app.teardown_request
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def _db_close(exc):
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if not database.is_closed():
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database.close()
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app.frigate_config = frigate_config
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app.camera_metrics = camera_metrics
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app.detectors = detectors
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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():
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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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groups = (
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Event
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.select(
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Event.camera,
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Event.label,
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fn.strftime('%Y-%m-%d', fn.datetime(Event.start_time, 'unixepoch', 'localtime')).alias('day'),
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Event.zones,
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fn.COUNT(Event.id).alias('count')
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)
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.group_by(
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Event.camera,
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Event.label,
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fn.strftime('%Y-%m-%d', fn.datetime(Event.start_time, 'unixepoch', 'localtime')),
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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>')
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def event(id):
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try:
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return model_to_dict(Event.get(Event.id == id))
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except DoesNotExist:
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return "Event not found", 404
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@bp.route('/events/<id>/snapshot.jpg')
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def event_snapshot(id):
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format = request.args.get('format', 'ios')
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thumbnail_bytes = None
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try:
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event = Event.get(Event.id == id)
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thumbnail_bytes = base64.b64decode(event.thumbnail)
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except DoesNotExist:
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# see if the object is currently being tracked
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try:
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for camera_state in current_app.detected_frames_processor.camera_states.values():
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if id in camera_state.tracked_objects:
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tracked_obj = camera_state.tracked_objects.get(id)
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if not tracked_obj is None:
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thumbnail_bytes = tracked_obj.get_jpg_bytes()
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except:
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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':
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jpg_as_np = np.frombuffer(thumbnail_bytes, dtype=np.uint8)
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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))
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ret, jpg = cv2.imencode('.jpg', thumbnail)
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thumbnail_bytes = jpg.tobytes()
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response = make_response(thumbnail_bytes)
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response.headers['Content-Type'] = 'image/jpg'
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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)
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camera = request.args.get('camera')
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label = request.args.get('label')
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zone = request.args.get('zone')
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after = request.args.get('after', type=int)
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before = request.args.get('before', type=int)
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clauses = []
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if camera:
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clauses.append((Event.camera == camera))
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if label:
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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:
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clauses.append((Event.start_time >= after))
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if before:
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clauses.append((Event.start_time <= before))
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if len(clauses) == 0:
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clauses.append((1 == 1))
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events = (Event.select()
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.where(reduce(operator.and_, clauses))
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.order_by(Event.start_time.desc())
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.limit(limit))
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return jsonify([model_to_dict(e) 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.to_dict())
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@bp.route('/version')
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def version():
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return VERSION
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@bp.route('/stats')
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def stats():
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camera_metrics = current_app.camera_metrics
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stats = {}
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total_detection_fps = 0
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for name, camera_stats in camera_metrics.items():
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total_detection_fps += camera_stats['detection_fps'].value
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stats[name] = {
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'camera_fps': round(camera_stats['camera_fps'].value, 2),
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'process_fps': round(camera_stats['process_fps'].value, 2),
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'skipped_fps': round(camera_stats['skipped_fps'].value, 2),
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'detection_fps': round(camera_stats['detection_fps'].value, 2),
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'pid': camera_stats['process'].pid,
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'capture_pid': camera_stats['capture_process'].pid
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}
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stats['detectors'] = {}
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for name, detector in current_app.detectors.items():
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stats['detectors'][name] = {
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'inference_speed': round(detector.avg_inference_speed.value*1000, 2),
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'detection_start': detector.detection_start.value,
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'pid': detector.detect_process.pid
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}
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stats['detection_fps'] = round(total_detection_fps, 2)
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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:
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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))
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region = calculate_region(best_frame.shape, box[0], box[1], box[2], box[3], 1.1)
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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])))
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width = int(height*best_frame.shape[1]/best_frame.shape[0])
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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)
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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
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else:
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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'))
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height = int(request.args.get('h', '360'))
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draw_options = {
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'bounding_boxes': request.args.get('bbox', type=int),
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'timestamp': request.args.get('timestamp', type=int),
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'zones': request.args.get('zones', type=int),
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'mask': request.args.get('mask', type=int),
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'motion_boxes': request.args.get('motion', type=int),
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'regions': request.args.get('regions', type=int),
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}
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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),
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mimetype='multipart/x-mixed-replace; boundary=frame')
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else:
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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):
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draw_options = {
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'bounding_boxes': request.args.get('bbox', type=int),
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'timestamp': request.args.get('timestamp', type=int),
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'zones': request.args.get('zones', type=int),
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'mask': request.args.get('mask', type=int),
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'motion_boxes': request.args.get('motion', type=int),
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'regions': request.args.get('regions', type=int),
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}
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if camera_name in current_app.frigate_config.cameras:
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# max out at specified FPS
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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])))
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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_AREA)
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ret, jpg = cv2.imencode('.jpg', frame)
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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
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else:
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return "Camera named {} not found".format(camera_name), 404
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def imagestream(detected_frames_processor, camera_name, fps, height, draw_options):
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while True:
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# max out at specified FPS
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time.sleep(1/fps)
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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)
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yield (b'--frame\r\n'
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b'Content-Type: image/jpeg\r\n\r\n' + jpg.tobytes() + b'\r\n\r\n')
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