initialize recognizers in threads instead of camera init

src/compare.py

@@ -62,10 +62,7 @@ if not encodings:
 # Add the time needed to start the script
 timings['st'] = time.time() - timings['st']
 
-video_capture = None
+timings['ic'] = time.time()
-
-def initialize_cam():
-	global video_capture
 
 # Start video capture on the IR camera
 video_capture = cv2.VideoCapture(config.get("video", "device_path"))
@@ -88,9 +85,8 @@ def initialize_cam():
 # This will let the camera adjust its light levels while we're importing for faster scanning
 video_capture.grab()
 
-timings['ic'] = time.time()
+# Note the time it took to open the camera
-init_thread = Thread(target=initialize_cam)
+timings['ic'] = time.time() - timings['ic']
-init_thread.start()
 
 timings['ll'] = time.time()
 
@@ -98,6 +94,9 @@ timings['ll'] = time.time()
 import dlib
 import numpy as np
 
+pose_predictor = None
+face_encoder = None
+
 use_cnn = config.getboolean('core', 'use_cnn', fallback=False)
 if use_cnn:
 	face_detector = dlib.cnn_face_detection_model_v1(
@@ -106,20 +105,28 @@ if use_cnn:
 else:
 	face_detector = dlib.get_frontal_face_detector()
 
+def init_predictor():
+	global pose_predictor
 	pose_predictor = dlib.shape_predictor(
 		PATH + '/dlib-data/shape_predictor_5_face_landmarks.dat'
 	)
+
+def init_encoder():
+	global face_encoder
 	face_encoder = dlib.face_recognition_model_v1(
 		PATH + '/dlib-data/dlib_face_recognition_resnet_model_v1.dat'
 	)
 
-timings['ll'] = time.time() - timings['ll']
 
-# wait for camera initialization to finish
+init_thread1 = Thread(target=init_encoder)
-init_thread.join()
+init_thread2 = Thread(target=init_predictor)
-del init_thread
+init_thread1.start()
-# Note the time it took to open the camera
+init_thread2.start()
-timings['ic'] = time.time() - timings['ic']
+
+init_thread2.join()
+init_thread1.join()
+del init_thread1, init_thread2
+timings['ll'] = time.time() - timings['ll']
 
 # Fetch the max frame height
 max_height = config.getfloat("video", "max_height", fallback=0.0)