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- import os
- from flask import (
- Flask, Blueprint, jsonify
- )
- from peewee import SqliteDatabase
- from playhouse.shortcuts import model_to_dict
- from frigate.models import Event
- bp = Blueprint('frigate', __name__)
- def create_app(database: SqliteDatabase):
- app = Flask(__name__)
- @app.before_request
- def _db_connect():
- database.connect()
- @app.teardown_request
- def _db_close(exc):
- if not database.is_closed():
- database.close()
-
- app.register_blueprint(bp)
- return app
- @bp.route('/')
- def is_healthy():
- return "Frigate is running. Alive and healthy!"
- @bp.route('/events')
- def events():
- events = Event.select()
- return jsonify([model_to_dict(e) for e in events])
- # @app.route('/debug/stats')
- # def stats():
- # stats = {}
- # total_detection_fps = 0
- # for name, camera_stats in camera_process_info.items():
- # total_detection_fps += camera_stats['detection_fps'].value
- # stats[name] = {
- # 'camera_fps': round(camera_stats['camera_fps'].value, 2),
- # 'process_fps': round(camera_stats['process_fps'].value, 2),
- # 'skipped_fps': round(camera_stats['skipped_fps'].value, 2),
- # 'detection_fps': round(camera_stats['detection_fps'].value, 2),
- # 'pid': camera_stats['process'].pid,
- # 'capture_pid': camera_stats['capture_process'].pid,
- # 'frame_info': {
- # 'detect': camera_stats['detection_frame'].value,
- # 'process': object_processor.camera_data[name]['current_frame_time']
- # }
- # }
-
- # stats['detectors'] = {}
- # for name, detector in detectors.items():
- # stats['detectors'][name] = {
- # 'inference_speed': round(detector.avg_inference_speed.value*1000, 2),
- # 'detection_start': detector.detection_start.value,
- # 'pid': detector.detect_process.pid
- # }
- # stats['detection_fps'] = round(total_detection_fps, 2)
- # return jsonify(stats)
- # @app.route('/<camera_name>/<label>/best.jpg')
- # def best(camera_name, label):
- # if camera_name in CONFIG['cameras']:
- # best_object = object_processor.get_best(camera_name, label)
- # best_frame = best_object.get('frame')
- # if best_frame is None:
- # best_frame = np.zeros((720,1280,3), np.uint8)
- # else:
- # best_frame = cv2.cvtColor(best_frame, cv2.COLOR_YUV2BGR_I420)
-
- # crop = bool(request.args.get('crop', 0, type=int))
- # if crop:
- # region = best_object.get('region', [0,0,300,300])
- # best_frame = best_frame[region[1]:region[3], region[0]:region[2]]
-
- # height = int(request.args.get('h', str(best_frame.shape[0])))
- # width = int(height*best_frame.shape[1]/best_frame.shape[0])
- # best_frame = cv2.resize(best_frame, dsize=(width, height), interpolation=cv2.INTER_AREA)
- # ret, jpg = cv2.imencode('.jpg', best_frame)
- # response = make_response(jpg.tobytes())
- # response.headers['Content-Type'] = 'image/jpg'
- # return response
- # else:
- # return "Camera named {} not found".format(camera_name), 404
- # @app.route('/<camera_name>')
- # def mjpeg_feed(camera_name):
- # fps = int(request.args.get('fps', '3'))
- # height = int(request.args.get('h', '360'))
- # if camera_name in CONFIG['cameras']:
- # # return a multipart response
- # return Response(imagestream(camera_name, fps, height),
- # mimetype='multipart/x-mixed-replace; boundary=frame')
- # else:
- # return "Camera named {} not found".format(camera_name), 404
- # @app.route('/<camera_name>/latest.jpg')
- # def latest_frame(camera_name):
- # if camera_name in CONFIG['cameras']:
- # # max out at specified FPS
- # frame = object_processor.get_current_frame(camera_name)
- # if frame is None:
- # frame = np.zeros((720,1280,3), np.uint8)
- # height = int(request.args.get('h', str(frame.shape[0])))
- # width = int(height*frame.shape[1]/frame.shape[0])
- # frame = cv2.resize(frame, dsize=(width, height), interpolation=cv2.INTER_AREA)
- # ret, jpg = cv2.imencode('.jpg', frame)
- # response = make_response(jpg.tobytes())
- # response.headers['Content-Type'] = 'image/jpg'
- # return response
- # else:
- # return "Camera named {} not found".format(camera_name), 404
-
- # def imagestream(camera_name, fps, height):
- # while True:
- # # max out at specified FPS
- # time.sleep(1/fps)
- # frame = object_processor.get_current_frame(camera_name, draw=True)
- # if frame is None:
- # frame = np.zeros((height,int(height*16/9),3), np.uint8)
- # width = int(height*frame.shape[1]/frame.shape[0])
- # frame = cv2.resize(frame, dsize=(width, height), interpolation=cv2.INTER_LINEAR)
- # ret, jpg = cv2.imencode('.jpg', frame)
- # yield (b'--frame\r\n'
- # b'Content-Type: image/jpeg\r\n\r\n' + jpg.tobytes() + b'\r\n\r\n')
- # app.run(host='0.0.0.0', port=WEB_PORT, debug=False)
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