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				https://github.com/MarcA711/frigate-rockchip.git
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			437 lines
		
	
	
		
			18 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			437 lines
		
	
	
		
			18 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| import os
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| import signal
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| import sys
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| import traceback
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| import signal
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| import cv2
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| import time
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| import datetime
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| import queue
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| import yaml
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| import threading
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| import multiprocessing as mp
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| import subprocess as sp
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| import numpy as np
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| import logging
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| from flask import Flask, Response, make_response, jsonify, request
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| import paho.mqtt.client as mqtt
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| 
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| from frigate.video import track_camera, get_ffmpeg_input, get_frame_shape, CameraCapture, start_or_restart_ffmpeg
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| from frigate.object_processing import TrackedObjectProcessor
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| from frigate.events import EventProcessor
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| from frigate.util import EventsPerSecond
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| from frigate.edgetpu import EdgeTPUProcess
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| 
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| FRIGATE_VARS = {k: v for k, v in os.environ.items() if k.startswith('FRIGATE_')}
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| 
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| with open('/config/config.yml') as f:
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|     CONFIG = yaml.safe_load(f)
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| 
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| MQTT_HOST = CONFIG['mqtt']['host']
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| MQTT_PORT = CONFIG.get('mqtt', {}).get('port', 1883)
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| MQTT_TOPIC_PREFIX = CONFIG.get('mqtt', {}).get('topic_prefix', 'frigate')
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| MQTT_USER = CONFIG.get('mqtt', {}).get('user')
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| MQTT_PASS = CONFIG.get('mqtt', {}).get('password')
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| if not MQTT_PASS is None:
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|     MQTT_PASS = MQTT_PASS.format(**FRIGATE_VARS)
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| MQTT_CLIENT_ID = CONFIG.get('mqtt', {}).get('client_id', 'frigate')
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| 
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| # Set the default FFmpeg config
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| FFMPEG_CONFIG = CONFIG.get('ffmpeg', {})
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| FFMPEG_DEFAULT_CONFIG = {
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|     'global_args': FFMPEG_CONFIG.get('global_args', 
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|         ['-hide_banner','-loglevel','panic']),
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|     'hwaccel_args': FFMPEG_CONFIG.get('hwaccel_args',
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|         []),
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|     'input_args': FFMPEG_CONFIG.get('input_args',
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|         ['-avoid_negative_ts', 'make_zero',
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|          '-fflags', 'nobuffer',
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|          '-flags', 'low_delay',
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|          '-strict', 'experimental',
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|          '-fflags', '+genpts+discardcorrupt',
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|          '-rtsp_transport', 'tcp',
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|          '-stimeout', '5000000',
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|          '-use_wallclock_as_timestamps', '1']),
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|     'output_args': FFMPEG_CONFIG.get('output_args',
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|         ['-f', 'rawvideo',
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|          '-pix_fmt', 'rgb24'])
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| }
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| 
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| GLOBAL_OBJECT_CONFIG = CONFIG.get('objects', {})
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| 
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| WEB_PORT = CONFIG.get('web_port', 5000)
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| DEBUG = (CONFIG.get('debug', '0') == '1')
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| 
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| def start_plasma_store():
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|     plasma_cmd = ['plasma_store', '-m', '400000000', '-s', '/tmp/plasma']
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|     plasma_process = sp.Popen(plasma_cmd, stdout=sp.DEVNULL, stderr=sp.DEVNULL)
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|     time.sleep(1)
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|     rc = plasma_process.poll()
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|     if rc is not None:
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|         return None
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|     return plasma_process
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| 
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| class CameraWatchdog(threading.Thread):
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|     def __init__(self, camera_processes, config, tflite_process, tracked_objects_queue, plasma_process, stop_event):
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|         threading.Thread.__init__(self)
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|         self.camera_processes = camera_processes
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|         self.config = config
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|         self.tflite_process = tflite_process
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|         self.tracked_objects_queue = tracked_objects_queue
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|         self.plasma_process = plasma_process
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|         self.stop_event = stop_event
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| 
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|     def run(self):
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|         time.sleep(10)
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|         while True:
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|             # wait a bit before checking
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|             time.sleep(10)
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| 
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|             if self.stop_event.is_set():
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|                 print(f"Exiting watchdog...")
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|                 break
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| 
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|             now = datetime.datetime.now().timestamp()
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|             
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|             # check the plasma process
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|             rc = self.plasma_process.poll()
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|             if rc != None:
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|                 print(f"plasma_process exited unexpectedly with {rc}")
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|                 self.plasma_process = start_plasma_store()
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| 
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|             # check the detection process
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|             detection_start = self.tflite_process.detection_start.value
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|             if (detection_start > 0.0 and 
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|                 now - detection_start > 10):
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|                 print("Detection appears to be stuck. Restarting detection process")
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|                 self.tflite_process.start_or_restart()
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|             elif not self.tflite_process.detect_process.is_alive():
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|                 print("Detection appears to have stopped. Restarting detection process")
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|                 self.tflite_process.start_or_restart()
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| 
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|             # check the camera processes
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|             for name, camera_process in self.camera_processes.items():
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|                 process = camera_process['process']
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|                 if not process.is_alive():
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|                     print(f"Track process for {name} is not alive. Starting again...")
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|                     camera_process['process_fps'].value = 0.0
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|                     camera_process['detection_fps'].value = 0.0
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|                     camera_process['read_start'].value = 0.0
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|                     process = mp.Process(target=track_camera, args=(name, self.config[name], GLOBAL_OBJECT_CONFIG, camera_process['frame_queue'],
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|                         camera_process['frame_shape'], self.tflite_process.detection_queue, self.tracked_objects_queue, 
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|                         camera_process['process_fps'], camera_process['detection_fps'],
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|                         camera_process['read_start'], camera_process['detection_frame']))
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|                     process.daemon = True
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|                     camera_process['process'] = process
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|                     process.start()
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|                     print(f"Track process started for {name}: {process.pid}")
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|                 
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|                 if not camera_process['capture_thread'].is_alive():
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|                     frame_shape = camera_process['frame_shape']
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|                     frame_size = frame_shape[0] * frame_shape[1] * frame_shape[2]
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|                     ffmpeg_process = start_or_restart_ffmpeg(camera_process['ffmpeg_cmd'], frame_size)
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|                     camera_capture = CameraCapture(name, ffmpeg_process, frame_shape, camera_process['frame_queue'], 
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|                         camera_process['take_frame'], camera_process['camera_fps'], camera_process['detection_frame'], self.stop_event)
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|                     camera_capture.start()
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|                     camera_process['ffmpeg_process'] = ffmpeg_process
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|                     camera_process['capture_thread'] = camera_capture
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|                 elif now - camera_process['capture_thread'].current_frame > 5:
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|                     print(f"No frames received from {name} in 5 seconds. Exiting ffmpeg...")
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|                     ffmpeg_process = camera_process['ffmpeg_process']
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|                     ffmpeg_process.terminate()
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|                     try:
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|                         print("Waiting for ffmpeg to exit gracefully...")
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|                         ffmpeg_process.communicate(timeout=30)
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|                     except sp.TimeoutExpired:
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|                         print("FFmpeg didnt exit. Force killing...")
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|                         ffmpeg_process.kill()
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|                         ffmpeg_process.communicate()
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| 
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| def main():
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|     stop_event = threading.Event()
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|     # connect to mqtt and setup last will
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|     def on_connect(client, userdata, flags, rc):
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|         print("On connect called")
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|         if rc != 0:
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|             if rc == 3:
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|                 print ("MQTT Server unavailable")
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|             elif rc == 4:
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|                 print ("MQTT Bad username or password")
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|             elif rc == 5:
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|                 print ("MQTT Not authorized")
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|             else:
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|                 print ("Unable to connect to MQTT: Connection refused. Error code: " + str(rc))
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|         # publish a message to signal that the service is running
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|         client.publish(MQTT_TOPIC_PREFIX+'/available', 'online', retain=True)
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|     client = mqtt.Client(client_id=MQTT_CLIENT_ID)
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|     client.on_connect = on_connect
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|     client.will_set(MQTT_TOPIC_PREFIX+'/available', payload='offline', qos=1, retain=True)
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|     if not MQTT_USER is None:
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|         client.username_pw_set(MQTT_USER, password=MQTT_PASS)
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|     client.connect(MQTT_HOST, MQTT_PORT, 60)
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|     client.loop_start()
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| 
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|     plasma_process = start_plasma_store()
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| 
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|     ##
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|     # Setup config defaults for cameras
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|     ##
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|     for name, config in CONFIG['cameras'].items():
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|         config['snapshots'] = {
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|             'show_timestamp': config.get('snapshots', {}).get('show_timestamp', True),
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|             'draw_zones': config.get('snapshots', {}).get('draw_zones', False)
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|         }
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| 
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|     # Queue for cameras to push tracked objects to
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|     tracked_objects_queue = mp.Queue()
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| 
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|     # Queue for clip processing
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|     event_queue = mp.Queue()
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|     
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|     # Start the shared tflite process
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|     tflite_process = EdgeTPUProcess()
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| 
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|     # start the camera processes
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|     camera_processes = {}
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|     for name, config in CONFIG['cameras'].items():
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|         # Merge the ffmpeg config with the global config
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|         ffmpeg = config.get('ffmpeg', {})
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|         ffmpeg_input = get_ffmpeg_input(ffmpeg['input'])
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|         ffmpeg_global_args = ffmpeg.get('global_args', FFMPEG_DEFAULT_CONFIG['global_args'])
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|         ffmpeg_hwaccel_args = ffmpeg.get('hwaccel_args', FFMPEG_DEFAULT_CONFIG['hwaccel_args'])
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|         ffmpeg_input_args = ffmpeg.get('input_args', FFMPEG_DEFAULT_CONFIG['input_args'])
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|         ffmpeg_output_args = ffmpeg.get('output_args', FFMPEG_DEFAULT_CONFIG['output_args'])
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|         if config.get('save_clips', {}).get('enabled', False):
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|             ffmpeg_output_args = [
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|                 "-f",
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|                 "segment",
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|                 "-segment_time",
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|                 "10",
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|                 "-segment_format",
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|                 "mp4",
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|                 "-reset_timestamps",
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|                 "1",
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|                 "-strftime",
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|                 "1",
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|                 "-c",
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|                 "copy",
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|                 "-an",
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|                 "-map",
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|                 "0",
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|                 f"/cache/{name}-%Y%m%d%H%M%S.mp4"
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|             ] + ffmpeg_output_args
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|         ffmpeg_cmd = (['ffmpeg'] +
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|                 ffmpeg_global_args +
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|                 ffmpeg_hwaccel_args +
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|                 ffmpeg_input_args +
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|                 ['-i', ffmpeg_input] +
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|                 ffmpeg_output_args +
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|                 ['pipe:'])
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|         
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|         if 'width' in config and 'height' in config:
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|             frame_shape = (config['height'], config['width'], 3)
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|         else:
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|             frame_shape = get_frame_shape(ffmpeg_input)
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| 
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|         frame_size = frame_shape[0] * frame_shape[1] * frame_shape[2]
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|         take_frame = config.get('take_frame', 1)
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| 
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|         detection_frame = mp.Value('d', 0.0)
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| 
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|         ffmpeg_process = start_or_restart_ffmpeg(ffmpeg_cmd, frame_size)
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|         frame_queue = mp.Queue()
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|         camera_fps = EventsPerSecond()
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|         camera_fps.start()
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|         camera_capture = CameraCapture(name, ffmpeg_process, frame_shape, frame_queue, take_frame, camera_fps, detection_frame, stop_event)
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|         camera_capture.start()
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| 
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|         camera_processes[name] = {
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|             'camera_fps': camera_fps,
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|             'take_frame': take_frame,
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|             'process_fps': mp.Value('d', 0.0),
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|             'detection_fps': mp.Value('d', 0.0),
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|             'detection_frame': detection_frame,
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|             'read_start': mp.Value('d', 0.0),
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|             'ffmpeg_process': ffmpeg_process,
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|             'ffmpeg_cmd': ffmpeg_cmd,
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|             'frame_queue': frame_queue,
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|             'frame_shape': frame_shape,
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|             'capture_thread': camera_capture
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|         }
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| 
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|         camera_process = mp.Process(target=track_camera, args=(name, config, GLOBAL_OBJECT_CONFIG, frame_queue, frame_shape,
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|             tflite_process.detection_queue, tracked_objects_queue, camera_processes[name]['process_fps'], 
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|             camera_processes[name]['detection_fps'], 
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|             camera_processes[name]['read_start'], camera_processes[name]['detection_frame'], stop_event))
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|         camera_process.daemon = True
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|         camera_processes[name]['process'] = camera_process
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| 
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|     for name, camera_process in camera_processes.items():
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|         camera_process['process'].start()
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|         print(f"Camera_process started for {name}: {camera_process['process'].pid}")
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| 
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|     event_processor = EventProcessor(CONFIG['cameras'], camera_processes, '/cache', '/clips', event_queue, stop_event)
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|     event_processor.start()
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|     
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|     object_processor = TrackedObjectProcessor(CONFIG['cameras'], CONFIG.get('zones', {}), client, MQTT_TOPIC_PREFIX, tracked_objects_queue, event_queue,stop_event)
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|     object_processor.start()
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|     
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|     camera_watchdog = CameraWatchdog(camera_processes, CONFIG['cameras'], tflite_process, tracked_objects_queue, plasma_process, stop_event)
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|     camera_watchdog.start()
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| 
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|     def receiveSignal(signalNumber, frame):
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|         print('Received:', signalNumber)
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|         stop_event.set()
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|         event_processor.join()
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|         object_processor.join()
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|         camera_watchdog.join()
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|         for name, camera_process in camera_processes.items():
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|             camera_process['capture_thread'].join()
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|         rc = camera_watchdog.plasma_process.poll()
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|         if rc == None:
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|             camera_watchdog.plasma_process.terminate()
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|         sys.exit()
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|     
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|     signal.signal(signal.SIGTERM, receiveSignal)
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|     signal.signal(signal.SIGINT, receiveSignal)
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| 
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|     # create a flask app that encodes frames a mjpeg on demand
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|     app = Flask(__name__)
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|     log = logging.getLogger('werkzeug')
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|     log.setLevel(logging.ERROR)
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| 
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|     @app.route('/')
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|     def ishealthy():
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|         # return a healh
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|         return "Frigate is running. Alive and healthy!"
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| 
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|     @app.route('/debug/stack')
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|     def processor_stack():
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|         frame = sys._current_frames().get(object_processor.ident, None)
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|         if frame:
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|             return "<br>".join(traceback.format_stack(frame)), 200
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|         else:
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|             return "no frame found", 200
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| 
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|     @app.route('/debug/print_stack')
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|     def print_stack():
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|         pid = int(request.args.get('pid', 0))
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|         if pid == 0:
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|             return "missing pid", 200
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|         else:
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|             os.kill(pid, signal.SIGUSR1)
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|             return "check logs", 200
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| 
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|     @app.route('/debug/stats')
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|     def stats():
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|         stats = {}
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| 
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|         total_detection_fps = 0
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| 
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|         for name, camera_stats in camera_processes.items():
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|             total_detection_fps += camera_stats['detection_fps'].value
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|             capture_thread = camera_stats['capture_thread']
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|             stats[name] = {
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|                 'camera_fps': round(capture_thread.fps.eps(), 2),
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|                 'process_fps': round(camera_stats['process_fps'].value, 2),
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|                 'skipped_fps': round(capture_thread.skipped_fps.eps(), 2),
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|                 'detection_fps': round(camera_stats['detection_fps'].value, 2),
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|                 'read_start': camera_stats['read_start'].value,
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|                 'pid': camera_stats['process'].pid,
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|                 'ffmpeg_pid': camera_stats['ffmpeg_process'].pid,
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|                 'frame_info': {
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|                     'read': capture_thread.current_frame,
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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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|         
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|         stats['coral'] = {
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|             'fps': round(total_detection_fps, 2),
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|             'inference_speed': round(tflite_process.avg_inference_speed.value*1000, 2),
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|             'detection_start': tflite_process.detection_start.value,
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|             'pid': tflite_process.detect_process.pid
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|         }
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| 
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|         rc = camera_watchdog.plasma_process.poll()
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|         stats['plasma_store_rc'] = rc
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| 
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|         return jsonify(stats)
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| 
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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_frame = object_processor.get_best(camera_name, label)
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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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| 
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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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| 
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|             best_frame = cv2.resize(best_frame, dsize=(width, height), interpolation=cv2.INTER_AREA)
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|             best_frame = cv2.cvtColor(best_frame, cv2.COLOR_RGB2BGR)
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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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| 
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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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|     
 | |
|     @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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| 
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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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| 
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|             frame = cv2.resize(frame, dsize=(width, height), interpolation=cv2.INTER_AREA)
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|             frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
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| 
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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)
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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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| 
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|             width = int(height*frame.shape[1]/frame.shape[0])
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| 
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|             frame = cv2.resize(frame, dsize=(width, height), interpolation=cv2.INTER_LINEAR)
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|             frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
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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)
 | |
| 
 | |
|     object_processor.join()
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|     
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|     plasma_process.terminate()
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| 
 | |
| if __name__ == '__main__':
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|     main()
 | 
