From 8458e107c73a6487f88485a2567598db6ad5fb5c Mon Sep 17 00:00:00 2001
From: Sefik Ilkin Serengil <serengil@gmail.com>
Date: Thu, 24 Jun 2021 00:35:47 +0300
Subject: [PATCH] no need to use initialize_detector function anymore

---
 deepface/DeepFace.py          | 14 ++++----------
 deepface/commons/functions.py | 12 ++++--------
 tests/unit_tests.py           | 11 +----------
 3 files changed, 9 insertions(+), 28 deletions(-)

diff --git a/deepface/DeepFace.py b/deepface/DeepFace.py
index d69e07b..6723185 100644
--- a/deepface/DeepFace.py
+++ b/deepface/DeepFace.py
@@ -48,7 +48,8 @@ def build_model(model_name):
 		'Emotion': Emotion.loadModel,
 		'Age': Age.loadModel,
 		'Gender': Gender.loadModel,
-		'Race': Race.loadModel
+		'Race': Race.loadModel,
+		'Ensemble': Boosting.loadModel
 	}
 
 	if not "model_obj" in globals() or model_label != model_name:
@@ -105,7 +106,6 @@ def verify(img1_path, img2_path = '', model_name = 'VGG-Face', distance_metric =
 	tic = time.time()
 
 	img_list, bulkProcess = functions.initialize_input(img1_path, img2_path)
-	functions.initialize_detector(detector_backend = detector_backend)
 
 	resp_objects = []
 
@@ -123,7 +123,7 @@ def verify(img1_path, img2_path = '', model_name = 'VGG-Face', distance_metric =
 
 	if model == None:
 		if model_name == 'Ensemble':
-			models = Boosting.loadModel()
+			models = build_model(model_name)
 		else:
 			model = build_model(model_name)
 			models = {}
@@ -310,7 +310,6 @@ def analyze(img_path, actions = ['emotion', 'age', 'gender', 'race'] , models =
 	"""
 
 	img_paths, bulkProcess = functions.initialize_input(img_path)
-	functions.initialize_detector(detector_backend = detector_backend)
 
 	#---------------------------------
 
@@ -494,7 +493,6 @@ def find(img_path, db_path, model_name ='VGG-Face', distance_metric = 'cosine',
 	tic = time.time()
 
 	img_paths, bulkProcess = functions.initialize_input(img_path)
-	functions.initialize_detector(detector_backend = detector_backend)
 
 	#-------------------------------
 
@@ -504,7 +502,7 @@ def find(img_path, db_path, model_name ='VGG-Face', distance_metric = 'cosine',
 
 			if model_name == 'Ensemble':
 				print("Ensemble learning enabled")
-				models = Boosting.loadModel()
+				models = build_model(model_name)
 
 			else: #model is not ensemble
 				model = build_model(model_name)
@@ -735,8 +733,6 @@ def represent(img_path, model_name = 'VGG-Face', model = None, enforce_detection
 	if model is None:
 		model = build_model(model_name)
 
-	functions.initialize_detector(detector_backend = detector_backend)
-
 	#---------------------------------
 
 	#decide input shape
@@ -782,8 +778,6 @@ def stream(db_path = '', model_name ='VGG-Face', distance_metric = 'cosine', ena
 	if frame_threshold < 1:
 		raise ValueError("frame_threshold must be greater than the value 1 but you passed "+str(frame_threshold))
 
-	functions.initialize_detector(detector_backend = 'opencv') #stream uses opencv by default!
-
 	realtime.analysis(db_path, model_name, distance_metric, enable_face_analysis
 						, source = source, time_threshold = time_threshold, frame_threshold = frame_threshold)
 
diff --git a/deepface/commons/functions.py b/deepface/commons/functions.py
index 39eab5d..4ed5de3 100644
--- a/deepface/commons/functions.py
+++ b/deepface/commons/functions.py
@@ -41,11 +41,6 @@ def initialize_input(img1_path, img2_path = None):
 
 	return img_list, bulkProcess
 
-def initialize_detector(detector_backend):
-
-	global face_detector
-	face_detector = FaceDetector.build_model(detector_backend)
-
 def initializeFolder():
 
 	home = str(Path.home())
@@ -91,9 +86,10 @@ def detect_face(img, detector_backend = 'opencv', grayscale = False, enforce_det
 
 	img_region = [0, 0, img.shape[0], img.shape[1]]
 
-	#if functions.preproces_face is called directly, then face_detector global variable might not been initialized.
-	if not "face_detector" in globals():
-		initialize_detector(detector_backend = detector_backend)
+	#detector stored in a global variable in FaceDetector object.
+	#this call should be completed very fast because it will return found in memory
+	#it will not build face detector model in each call (consider for loops)
+	face_detector = FaceDetector.build_model(detector_backend)
 
 	detected_face, img_region = FaceDetector.detect_face(face_detector, detector_backend, img, align)
 
diff --git a/tests/unit_tests.py b/tests/unit_tests.py
index 176154a..bd6c699 100644
--- a/tests/unit_tests.py
+++ b/tests/unit_tests.py
@@ -279,16 +279,7 @@ print("Pre-trained ensemble method - find")
 from deepface import DeepFace
 from deepface.basemodels import VGGFace, OpenFace, Facenet, FbDeepFace
 
-model = {}
-model["VGG-Face"] = VGGFace.loadModel()
-print("VGG loaded")
-model["Facenet"] = Facenet.loadModel()
-print("Facenet loaded")
-model["OpenFace"] = OpenFace.loadModel()
-print("OpenFace loaded")
-model["DeepFace"] = FbDeepFace.loadModel()
-print("DeepFace loaded")
-
+model = DeepFace.build_model("Ensemble")
 df = DeepFace.find("dataset/img1.jpg", db_path = "dataset", model_name = 'Ensemble', model = model, enforce_detection=False)
 
 print(df)