add num_threads fixes #322

README.md

@@ -200,6 +200,9 @@ detectors:
     type: edgetpu
     # Optional: device name as defined here: https://coral.ai/docs/edgetpu/multiple-edgetpu/#using-the-tensorflow-lite-python-api
     device: usb
+    # Optional: num_threads value passed to the tflite.Interpreter (default: shown below)
+    # This value is only used for CPU types
+    num_threads: 3
 
 # Optional: model configuration
 model:

frigate/app.py

@@ -125,9 +125,9 @@ class FrigateApp():
 
         for name, detector in self.config.detectors.items():
             if detector.type == 'cpu':
-                self.detectors[name] = EdgeTPUProcess(name, self.detection_queue, self.detection_out_events, model_shape, tf_device='cpu')
+                self.detectors[name] = EdgeTPUProcess(name, self.detection_queue, self.detection_out_events, model_shape, 'cpu', detector.num_threads)
             if detector.type == 'edgetpu':
-                self.detectors[name] = EdgeTPUProcess(name, self.detection_queue, self.detection_out_events, model_shape, tf_device=detector.device)
+                self.detectors[name] = EdgeTPUProcess(name, self.detection_queue, self.detection_out_events, model_shape, detector.device, detector.num_threads)
 
     def start_detected_frames_processor(self):
         self.detected_frames_processor = TrackedObjectProcessor(self.config, self.mqtt_client, self.config.mqtt.topic_prefix, 

frigate/config.py

@@ -15,7 +15,8 @@ DETECTORS_SCHEMA = vol.Schema(
     {
         vol.Required(str): {
             vol.Required('type', default='edgetpu'): vol.In(['cpu', 'edgetpu']), 
-            vol.Optional('device', default='usb'): str
+            vol.Optional('device', default='usb'): str,
+            vol.Optional('num_threads', default=3): int
         }
     }
 )
@@ -264,6 +265,7 @@ class DetectorConfig():
     def __init__(self, config):
         self._type = config['type']
         self._device = config['device']
+        self._num_threads = config['num_threads']
     
     @property
     def type(self):
@@ -273,10 +275,15 @@ class DetectorConfig():
     def device(self):
         return self._device
     
+    @property
+    def num_threads(self):
+        return self._num_threads
+    
     def to_dict(self):
         return {
             'type': self.type,
-            'device': self.device
+            'device': self.device,
+            'num_threads': self.num_threads
         }
 
 class LoggerConfig():

frigate/edgetpu.py

@@ -43,7 +43,7 @@ class ObjectDetector(ABC):
         pass
 
 class LocalObjectDetector(ObjectDetector):
-    def __init__(self, tf_device=None, labels=None):
+    def __init__(self, tf_device=None, num_threads=3, labels=None):
         self.fps = EventsPerSecond()
         if labels is None:
             self.labels = {}
@@ -66,7 +66,7 @@ class LocalObjectDetector(ObjectDetector):
         
         if edge_tpu_delegate is None:
             self.interpreter = tflite.Interpreter(
-                model_path='/cpu_model.tflite')
+                model_path='/cpu_model.tflite', num_threads=num_threads)
         else:
             self.interpreter = tflite.Interpreter(
                 model_path='/edgetpu_model.tflite',
@@ -106,7 +106,7 @@ class LocalObjectDetector(ObjectDetector):
         
         return detections
 
-def run_detector(name: str, detection_queue: mp.Queue, out_events: Dict[str, mp.Event], avg_speed, start, model_shape, tf_device):
+def run_detector(name: str, detection_queue: mp.Queue, out_events: Dict[str, mp.Event], avg_speed, start, model_shape, tf_device, num_threads):
     threading.current_thread().name = f"detector:{name}"
     logger = logging.getLogger(f"detector.{name}")
     logger.info(f"Starting detection process: {os.getpid()}")
@@ -120,7 +120,7 @@ def run_detector(name: str, detection_queue: mp.Queue, out_events: Dict[str, mp.
     signal.signal(signal.SIGINT, receiveSignal)
 
     frame_manager = SharedMemoryFrameManager()
-    object_detector = LocalObjectDetector(tf_device=tf_device)
+    object_detector = LocalObjectDetector(tf_device=tf_device, num_threads=num_threads)
 
     outputs = {}
     for name in out_events.keys():
@@ -155,7 +155,7 @@ def run_detector(name: str, detection_queue: mp.Queue, out_events: Dict[str, mp.
         avg_speed.value = (avg_speed.value*9 + duration)/10
         
 class EdgeTPUProcess():
-    def __init__(self, name, detection_queue, out_events, model_shape, tf_device=None):
+    def __init__(self, name, detection_queue, out_events, model_shape, tf_device=None, num_threads=3):
         self.name = name
         self.out_events = out_events
         self.detection_queue = detection_queue
@@ -164,6 +164,7 @@ class EdgeTPUProcess():
         self.detect_process = None
         self.model_shape = model_shape
         self.tf_device = tf_device
+        self.num_threads = num_threads
         self.start_or_restart()
     
     def stop(self):
@@ -179,7 +180,7 @@ class EdgeTPUProcess():
         self.detection_start.value = 0.0
         if (not self.detect_process is None) and self.detect_process.is_alive():
             self.stop()
-        self.detect_process = mp.Process(target=run_detector, name=f"detector:{self.name}", args=(self.name, self.detection_queue, self.out_events, self.avg_inference_speed, self.detection_start, self.model_shape, self.tf_device))
+        self.detect_process = mp.Process(target=run_detector, name=f"detector:{self.name}", args=(self.name, self.detection_queue, self.out_events, self.avg_inference_speed, self.detection_start, self.model_shape, self.tf_device, self.num_threads))
         self.detect_process.daemon = True
         self.detect_process.start()