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improve watchdog and coral fps tracking

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Blake Blackshear
2020-02-21 20:44:53 -06:00
parent 66eeb8b5cb
commit b507a73d79
4 changed files with 47 additions and 22 deletions
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45
detect_objects.py
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@@ -1,5 +1,6 @@
import cv2
import time
import datetime
import queue
import yaml
import threading
@@ -53,12 +54,13 @@ WEB_PORT = CONFIG.get('web_port', 5000)
DEBUG = (CONFIG.get('debug', '0') == '1')
class CameraWatchdog(threading.Thread):
def __init__(self, camera_processes, config, tflite_process, tracked_objects_queue):
def __init__(self, camera_processes, config, tflite_process, tracked_objects_queue, object_processor):
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.object_processor = object_processor
def run(self):
time.sleep(10)
@@ -68,6 +70,17 @@ class CameraWatchdog(threading.Thread):
for name, camera_process in self.camera_processes.items():
process = camera_process['process']
if (datetime.datetime.now().timestamp() - self.object_processor.get_current_frame_time(name)) > 30:
print(f"Last frame for {name} is more than 30 seconds old...")
if process.is_alive():
process.terminate()
try:
print("Waiting for process to exit gracefully...")
process.wait(timeout=30)
except sp.TimeoutExpired:
print("Process didnt exit. Force killing...")
process.kill()
process.wait()
if not process.is_alive():
print(f"Process for {name} is not alive. Starting again...")
camera_process['fps'].value = float(self.config[name]['fps'])
@@ -131,11 +144,13 @@ def main():
for name, config in CONFIG['cameras'].items():
camera_processes[name] = {
'fps': mp.Value('d', float(config['fps'])),
'skipped_fps': mp.Value('d', 0.0)
'skipped_fps': mp.Value('d', 0.0),
'detection_fps': mp.Value('d', 0.0),
'last_frame': datetime.datetime.now().timestamp()
}
camera_process = mp.Process(target=track_camera, args=(name, config, FFMPEG_DEFAULT_CONFIG, GLOBAL_OBJECT_CONFIG,
tflite_process.detect_lock, tflite_process.detect_ready, tflite_process.frame_ready, tracked_objects_queue,
camera_processes[name]['fps'], camera_processes[name]['skipped_fps']))
camera_processes[name]['fps'], camera_processes[name]['skipped_fps'], camera_processes[name]['detection_fps']))
camera_process.daemon = True
camera_processes[name]['process'] = camera_process
@@ -143,11 +158,11 @@ def main():
camera_process['process'].start()
print(f"Camera_process started for {name}: {camera_process['process'].pid}")
camera_watchdog = CameraWatchdog(camera_processes, CONFIG['cameras'], tflite_process, tracked_objects_queue)
camera_watchdog.start()
object_processor = TrackedObjectProcessor(CONFIG['cameras'], client, MQTT_TOPIC_PREFIX, tracked_objects_queue)
object_processor.start()
camera_watchdog = CameraWatchdog(camera_processes, CONFIG['cameras'], tflite_process, tracked_objects_queue, object_processor)
camera_watchdog.start()
# create a flask app that encodes frames a mjpeg on demand
app = Flask(__name__)
@@ -161,18 +176,22 @@ def main():
@app.route('/debug/stats')
def stats():
stats = {
'coral': {
'fps': tflite_process.fps.value,
'inference_speed': round(tflite_process.avg_inference_speed.value*1000, 2)
}
}
stats = {}
total_detection_fps = 0
for name, camera_stats in camera_processes.items():
total_detection_fps += camera_stats['detection_fps'].value
stats[name] = {
'fps': camera_stats['fps'].value,
'skipped_fps': camera_stats['skipped_fps'].value
'skipped_fps': camera_stats['skipped_fps'].value,
'detection_fps': camera_stats['detection_fps'].value
}
stats['coral'] = {
'fps': total_detection_fps,
'inference_speed': round(tflite_process.avg_inference_speed.value*1000, 2)
}
return jsonify(stats)