allow setting specific edgetpu in config

config/config.example.yml

@@ -1,5 +1,11 @@
 web_port: 5000
 
+################
+## Tell frigate to look for a specific EdgeTPU device. Useful if you want to run multiple instances of frigate
+## on the same machine with multiple EdgeTPUs. https://coral.ai/docs/edgetpu/multiple-edgetpu/#using-the-tensorflow-lite-python-api
+################
+tensorflow_device: usb
+
 mqtt:
  host: mqtt.server.com
  topic_prefix: frigate

detect_objects.py

@@ -61,6 +61,7 @@
 
 WEB_PORT = CONFIG.get('web_port', 5000)
 DEBUG = (CONFIG.get('debug', '0') == '1')
+TENSORFLOW_DEVICE = CONFIG.get('tensorflow_device')
 
 def start_plasma_store():
  plasma_cmd = ['plasma_store', '-m', '400000000', '-s', '/tmp/plasma']
@@ -190,7 +191,7 @@ def on_connect(client, userdata, flags, rc):
  event_queue = mp.Queue()
 
  # Start the shared tflite process
- tflite_process = EdgeTPUProcess()
+ tflite_process = EdgeTPUProcess(TENSORFLOW_DEVICE)
 
  # start the camera processes
  camera_processes = {}

frigate/edgetpu.py

@@ -34,18 +34,24 @@ def detect(self, tensor_input, threshold = .4):
  pass
 
 class LocalObjectDetector(ObjectDetector):
- def __init__(self, labels=None):
+ def __init__(self, tf_device=None, labels=None):
  if labels is None:
  self.labels = {}
  else:
  self.labels = load_labels(labels)
 
+ device_config = {"device": "usb"}
+ if not tf_device is None:
+ device_config = {"device": tf_device}
+
  edge_tpu_delegate = None
  try:
- edge_tpu_delegate = load_delegate('libedgetpu.so.1.0', {"device": "usb"})
- print("USB TPU found")
+ print(f"Attempting to load TPU as {device_config['device']}")
+ edge_tpu_delegate = load_delegate('libedgetpu.so.1.0', device_config)
+ print("TPU found")
  except ValueError:
  try:
+ print(f"Attempting to load TPU as pci:0")
  edge_tpu_delegate = load_delegate('libedgetpu.so.1.0', {"device": "pci:0"})
  print("PCIe TPU found")
  except ValueError:
@@ -92,11 +98,11 @@ def detect_raw(self, tensor_input):
 
  return detections
 
-def run_detector(detection_queue, avg_speed, start):
+def run_detector(detection_queue, avg_speed, start, tf_device):
  print(f"Starting detection process: {os.getpid()}")
  listen()
  plasma_client = plasma.connect("/tmp/plasma")
- object_detector = LocalObjectDetector()
+ object_detector = LocalObjectDetector(tf_device=tf_device)
 
  while True:
  object_id_str = detection_queue.get()
@@ -117,11 +123,12 @@ def run_detector(detection_queue, avg_speed, start):
  avg_speed.value = (avg_speed.value*9 + duration)/10
 
 class EdgeTPUProcess():
- def __init__(self):
+ def __init__(self, tf_device=None):
  self.detection_queue = mp.Queue()
  self.avg_inference_speed = mp.Value('d', 0.01)
  self.detection_start = mp.Value('d', 0.0)
  self.detect_process = None
+ self.tf_device = tf_device
  self.start_or_restart()
 
  def start_or_restart(self):
@@ -134,7 +141,7 @@ def start_or_restart(self):
  print("Detection process didnt exit. Force killing...")
  self.detect_process.kill()
  self.detect_process.join()
- self.detect_process = mp.Process(target=run_detector, args=(self.detection_queue, self.avg_inference_speed, self.detection_start))
+ self.detect_process = mp.Process(target=run_detector, args=(self.detection_queue, self.avg_inference_speed, self.detection_start, self.tf_device))
  self.detect_process.daemon = True
  self.detect_process.start()