mirror of
https://github.com/blakeblackshear/frigate.git
synced 2024-11-21 19:07:46 +01:00
add back all endpoints
This commit is contained in:
Blake Blackshear
parent
7ee6bfe855
commit
37ee746ebb
@ -113,7 +113,7 @@ class FrigateApp():
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self.db.create_tables(models, safe=True)
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def init_web_server(self):
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self.flask_app = create_app(self.db)
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self.flask_app = create_app(self.config, self.db, self.camera_metrics, self.detectors, self.detected_frames_processor)
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def init_mqtt(self):
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# TODO: create config class
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@ -176,12 +176,12 @@ class FrigateApp():
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self.init_config()
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self.init_queues()
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self.init_database()
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self.init_web_server()
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self.init_mqtt()
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self.start_detectors()
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self.start_detected_frames_processor()
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self.start_camera_processors()
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self.start_camera_capture_processes()
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self.init_web_server()
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self.start_event_processor()
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self.start_watchdog()
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self.flask_app.run(host='0.0.0.0', port=self.config['web_port'], debug=False)
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186
frigate/http.py
186
frigate/http.py
@ -1,7 +1,11 @@
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import os
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import time
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import cv2
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import numpy as np
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from flask import (
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Flask, Blueprint, jsonify
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Flask, Blueprint, jsonify, request, Response, current_app, make_response
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)
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from peewee import SqliteDatabase
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from playhouse.shortcuts import model_to_dict
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@ -10,7 +14,7 @@ from frigate.models import Event
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bp = Blueprint('frigate', __name__)
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def create_app(database: SqliteDatabase):
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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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@ -22,6 +26,11 @@ def create_app(database: SqliteDatabase):
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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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@ -35,108 +44,103 @@ def events():
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events = Event.select()
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return jsonify([model_to_dict(e) for e in events])
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# @app.route('/debug/stats')
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# def stats():
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# stats = {}
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@bp.route('/debug/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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total_detection_fps = 0
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# for name, camera_stats in camera_process_info.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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# 'frame_info': {
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# 'detect': camera_stats['detection_frame'].value,
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# 'process': object_processor.camera_data[name]['current_frame_time']
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# }
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# }
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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 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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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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return jsonify(stats)
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# @app.route('/<camera_name>/<label>/best.jpg')
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# def best(camera_name, label):
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# if camera_name in CONFIG['cameras']:
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# best_object = object_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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@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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# region = best_object.get('region', [0,0,300,300])
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# best_frame = best_frame[region[1]:region[3], region[0]:region[2]]
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crop = bool(request.args.get('crop', 0, type=int))
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if crop:
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region = best_object.get('region', [0,0,300,300])
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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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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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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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# @app.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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# if camera_name in CONFIG['cameras']:
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# # return a multipart response
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# return Response(imagestream(camera_name, fps, height),
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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>')
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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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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),
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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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# @app.route('/<camera_name>/latest.jpg')
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# def latest_frame(camera_name):
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# if camera_name in CONFIG['cameras']:
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# # max out at specified FPS
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# frame = object_processor.get_current_frame(camera_name)
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# if frame is None:
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# frame = np.zeros((720,1280,3), np.uint8)
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@bp.route('/<camera_name>/latest.jpg')
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def latest_frame(camera_name):
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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)
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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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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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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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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(camera_name, fps, height):
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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 = object_processor.get_current_frame(camera_name, draw=True)
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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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def imagestream(detected_frames_processor, camera_name, fps, height):
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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=True)
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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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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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# app.run(host='0.0.0.0', port=WEB_PORT, debug=False)
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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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