blakeblackshear.frigate/detect_objects.py
2020-08-01 18:20:44 -05:00

388 lines
16 KiB
Python

import os
import sys
import traceback
import signal
import cv2
import time
import datetime
import queue
import yaml
import threading
import multiprocessing as mp
import subprocess as sp
import numpy as np
import logging
from flask import Flask, Response, make_response, jsonify, request
import paho.mqtt.client as mqtt
from frigate.video import track_camera, get_ffmpeg_input, get_frame_shape, CameraCapture, start_or_restart_ffmpeg
from frigate.object_processing import TrackedObjectProcessor
from frigate.events import EventProcessor
from frigate.util import EventsPerSecond
from frigate.edgetpu import EdgeTPUProcess
FRIGATE_VARS = {k: v for k, v in os.environ.items() if k.startswith('FRIGATE_')}
with open('/config/config.yml') as f:
CONFIG = yaml.safe_load(f)
MQTT_HOST = CONFIG['mqtt']['host']
MQTT_PORT = CONFIG.get('mqtt', {}).get('port', 1883)
MQTT_TOPIC_PREFIX = CONFIG.get('mqtt', {}).get('topic_prefix', 'frigate')
MQTT_USER = CONFIG.get('mqtt', {}).get('user')
MQTT_PASS = CONFIG.get('mqtt', {}).get('password')
if not MQTT_PASS is None:
MQTT_PASS = MQTT_PASS.format(**FRIGATE_VARS)
MQTT_CLIENT_ID = CONFIG.get('mqtt', {}).get('client_id', 'frigate')
# Set the default FFmpeg config
FFMPEG_CONFIG = CONFIG.get('ffmpeg', {})
FFMPEG_DEFAULT_CONFIG = {
'global_args': FFMPEG_CONFIG.get('global_args',
['-hide_banner','-loglevel','panic']),
'hwaccel_args': FFMPEG_CONFIG.get('hwaccel_args',
[]),
'input_args': FFMPEG_CONFIG.get('input_args',
['-avoid_negative_ts', 'make_zero',
'-fflags', 'nobuffer',
'-flags', 'low_delay',
'-strict', 'experimental',
'-fflags', '+genpts+discardcorrupt',
'-vsync', 'drop',
'-rtsp_transport', 'tcp',
'-stimeout', '5000000',
'-use_wallclock_as_timestamps', '1']),
'output_args': FFMPEG_CONFIG.get('output_args',
['-f', 'rawvideo',
'-pix_fmt', 'rgb24'])
}
GLOBAL_OBJECT_CONFIG = CONFIG.get('objects', {})
WEB_PORT = CONFIG.get('web_port', 5000)
DEBUG = (CONFIG.get('debug', '0') == '1')
def start_plasma_store():
plasma_cmd = ['plasma_store', '-m', '400000000', '-s', '/tmp/plasma']
plasma_process = sp.Popen(plasma_cmd, stdout=sp.DEVNULL, stderr=sp.DEVNULL)
time.sleep(1)
rc = plasma_process.poll()
if rc is not None:
return None
return plasma_process
class CameraWatchdog(threading.Thread):
def __init__(self, camera_processes, config, tflite_process, tracked_objects_queue, plasma_process):
threading.Thread.__init__(self)
self.camera_processes = camera_processes
self.config = config
self.tflite_process = tflite_process
self.tracked_objects_queue = tracked_objects_queue
self.plasma_process = plasma_process
def run(self):
time.sleep(10)
while True:
# wait a bit before checking
time.sleep(10)
now = datetime.datetime.now().timestamp()
# check the plasma process
rc = self.plasma_process.poll()
if rc != None:
print(f"plasma_process exited unexpectedly with {rc}")
self.plasma_process = start_plasma_store()
# check the detection process
detection_start = self.tflite_process.detection_start.value
if (detection_start > 0.0 and
now - detection_start > 10):
print("Detection appears to be stuck. Restarting detection process")
self.tflite_process.start_or_restart()
elif not self.tflite_process.detect_process.is_alive():
print("Detection appears to have stopped. Restarting detection process")
self.tflite_process.start_or_restart()
# check the camera processes
for name, camera_process in self.camera_processes.items():
process = camera_process['process']
if not process.is_alive():
print(f"Track process for {name} is not alive. Starting again...")
camera_process['process_fps'].value = 0.0
camera_process['detection_fps'].value = 0.0
camera_process['read_start'].value = 0.0
process = mp.Process(target=track_camera, args=(name, self.config[name], GLOBAL_OBJECT_CONFIG, camera_process['frame_queue'],
camera_process['frame_shape'], self.tflite_process.detection_queue, self.tracked_objects_queue,
camera_process['process_fps'], camera_process['detection_fps'],
camera_process['read_start'], camera_process['detection_frame']))
process.daemon = True
camera_process['process'] = process
process.start()
print(f"Track process started for {name}: {process.pid}")
if not camera_process['capture_thread'].is_alive():
frame_shape = camera_process['frame_shape']
frame_size = frame_shape[0] * frame_shape[1] * frame_shape[2]
ffmpeg_process = start_or_restart_ffmpeg(camera_process['ffmpeg_cmd'], frame_size)
camera_capture = CameraCapture(name, ffmpeg_process, frame_shape, camera_process['frame_queue'],
camera_process['take_frame'], camera_process['camera_fps'], camera_process['detection_frame'])
camera_capture.start()
camera_process['ffmpeg_process'] = ffmpeg_process
camera_process['capture_thread'] = camera_capture
elif now - camera_process['capture_thread'].current_frame > 5:
print(f"No frames received from {name} in 5 seconds. Exiting ffmpeg...")
ffmpeg_process = camera_process['ffmpeg_process']
ffmpeg_process.terminate()
try:
print("Waiting for ffmpeg to exit gracefully...")
ffmpeg_process.communicate(timeout=30)
except sp.TimeoutExpired:
print("FFmpeg didnt exit. Force killing...")
ffmpeg_process.kill()
ffmpeg_process.communicate()
def main():
# connect to mqtt and setup last will
def on_connect(client, userdata, flags, rc):
print("On connect called")
if rc != 0:
if rc == 3:
print ("MQTT Server unavailable")
elif rc == 4:
print ("MQTT Bad username or password")
elif rc == 5:
print ("MQTT Not authorized")
else:
print ("Unable to connect to MQTT: Connection refused. Error code: " + str(rc))
# publish a message to signal that the service is running
client.publish(MQTT_TOPIC_PREFIX+'/available', 'online', retain=True)
client = mqtt.Client(client_id=MQTT_CLIENT_ID)
client.on_connect = on_connect
client.will_set(MQTT_TOPIC_PREFIX+'/available', payload='offline', qos=1, retain=True)
if not MQTT_USER is None:
client.username_pw_set(MQTT_USER, password=MQTT_PASS)
client.connect(MQTT_HOST, MQTT_PORT, 60)
client.loop_start()
plasma_process = start_plasma_store()
##
# Setup config defaults for cameras
##
for name, config in CONFIG['cameras'].items():
config['snapshots'] = {
'show_timestamp': config.get('snapshots', {}).get('show_timestamp', True)
}
# Queue for cameras to push tracked objects to
tracked_objects_queue = mp.SimpleQueue()
# Queue for clip processing
event_queue = mp.Queue()
# Start the shared tflite process
tflite_process = EdgeTPUProcess()
# start the camera processes
camera_processes = {}
for name, config in CONFIG['cameras'].items():
# Merge the ffmpeg config with the global config
ffmpeg = config.get('ffmpeg', {})
ffmpeg_input = get_ffmpeg_input(ffmpeg['input'])
ffmpeg_global_args = ffmpeg.get('global_args', FFMPEG_DEFAULT_CONFIG['global_args'])
ffmpeg_hwaccel_args = ffmpeg.get('hwaccel_args', FFMPEG_DEFAULT_CONFIG['hwaccel_args'])
ffmpeg_input_args = ffmpeg.get('input_args', FFMPEG_DEFAULT_CONFIG['input_args'])
ffmpeg_output_args = ffmpeg.get('output_args', FFMPEG_DEFAULT_CONFIG['output_args'])
if config.get('save_clips', False):
ffmpeg_output_args = [
"-f",
"segment",
"-segment_time",
"10",
"-segment_format",
"mp4",
"-reset_timestamps",
"1",
"-strftime",
"1",
"-c",
"copy",
"-an",
"-map",
"0",
f"/cache/{name}-%Y%m%d%H%M%S.mp4"
] + ffmpeg_output_args
ffmpeg_cmd = (['ffmpeg'] +
ffmpeg_global_args +
ffmpeg_hwaccel_args +
ffmpeg_input_args +
['-i', ffmpeg_input] +
ffmpeg_output_args +
['pipe:'])
if 'width' in config and 'height' in config:
frame_shape = (config['height'], config['width'], 3)
else:
frame_shape = get_frame_shape(ffmpeg_input)
frame_size = frame_shape[0] * frame_shape[1] * frame_shape[2]
take_frame = config.get('take_frame', 1)
detection_frame = mp.Value('d', 0.0)
ffmpeg_process = start_or_restart_ffmpeg(ffmpeg_cmd, frame_size)
frame_queue = mp.SimpleQueue()
camera_fps = EventsPerSecond()
camera_fps.start()
camera_capture = CameraCapture(name, ffmpeg_process, frame_shape, frame_queue, take_frame, camera_fps, detection_frame)
camera_capture.start()
camera_processes[name] = {
'camera_fps': camera_fps,
'take_frame': take_frame,
'process_fps': mp.Value('d', 0.0),
'detection_fps': mp.Value('d', 0.0),
'detection_frame': detection_frame,
'read_start': mp.Value('d', 0.0),
'ffmpeg_process': ffmpeg_process,
'ffmpeg_cmd': ffmpeg_cmd,
'frame_queue': frame_queue,
'frame_shape': frame_shape,
'capture_thread': camera_capture
}
camera_process = mp.Process(target=track_camera, args=(name, config, GLOBAL_OBJECT_CONFIG, frame_queue, frame_shape,
tflite_process.detection_queue, tracked_objects_queue, camera_processes[name]['process_fps'],
camera_processes[name]['detection_fps'],
camera_processes[name]['read_start'], camera_processes[name]['detection_frame']))
camera_process.daemon = True
camera_processes[name]['process'] = camera_process
for name, camera_process in camera_processes.items():
camera_process['process'].start()
print(f"Camera_process started for {name}: {camera_process['process'].pid}")
event_processor = EventProcessor(CONFIG['cameras'], camera_processes, '/cache', '/clips', event_queue)
event_processor.start()
object_processor = TrackedObjectProcessor(CONFIG['cameras'], client, MQTT_TOPIC_PREFIX, tracked_objects_queue, event_queue)
object_processor.start()
camera_watchdog = CameraWatchdog(camera_processes, CONFIG['cameras'], tflite_process, tracked_objects_queue, plasma_process)
camera_watchdog.start()
# create a flask app that encodes frames a mjpeg on demand
app = Flask(__name__)
log = logging.getLogger('werkzeug')
log.setLevel(logging.ERROR)
@app.route('/')
def ishealthy():
# return a healh
return "Frigate is running. Alive and healthy!"
@app.route('/debug/stack')
def processor_stack():
frame = sys._current_frames().get(object_processor.ident, None)
if frame:
return "<br>".join(traceback.format_stack(frame)), 200
else:
return "no frame found", 200
@app.route('/debug/print_stack')
def print_stack():
pid = int(request.args.get('pid', 0))
if pid == 0:
return "missing pid", 200
else:
os.kill(pid, signal.SIGUSR1)
return "check logs", 200
@app.route('/debug/stats')
def stats():
stats = {}
total_detection_fps = 0
for name, camera_stats in camera_processes.items():
total_detection_fps += camera_stats['detection_fps'].value
capture_thread = camera_stats['capture_thread']
stats[name] = {
'camera_fps': round(capture_thread.fps.eps(), 2),
'process_fps': round(camera_stats['process_fps'].value, 2),
'skipped_fps': round(capture_thread.skipped_fps.eps(), 2),
'detection_fps': round(camera_stats['detection_fps'].value, 2),
'read_start': camera_stats['read_start'].value,
'pid': camera_stats['process'].pid,
'ffmpeg_pid': camera_stats['ffmpeg_process'].pid,
'frame_info': {
'read': capture_thread.current_frame,
'detect': camera_stats['detection_frame'].value,
'process': object_processor.camera_data[name]['current_frame_time']
}
}
stats['coral'] = {
'fps': round(total_detection_fps, 2),
'inference_speed': round(tflite_process.avg_inference_speed.value*1000, 2),
'detection_start': tflite_process.detection_start.value,
'pid': tflite_process.detect_process.pid
}
rc = camera_watchdog.plasma_process.poll()
stats['plasma_store_rc'] = rc
return jsonify(stats)
@app.route('/<camera_name>/<label>/best.jpg')
def best(camera_name, label):
if camera_name in CONFIG['cameras']:
best_frame = object_processor.get_best(camera_name, label)
if best_frame is None:
best_frame = np.zeros((720,1280,3), np.uint8)
best_frame = cv2.cvtColor(best_frame, cv2.COLOR_RGB2BGR)
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
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)
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)
frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
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)
object_processor.join()
plasma_process.terminate()
if __name__ == '__main__':
main()