blakeblackshear.frigate/frigate/http.py
2020-12-05 08:48:46 -06:00

142 lines
5.0 KiB
Python

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)