Merge pull request #17 from uriafranko/uria-franko

passing already built models to analyze function as well

Contributors.md

@@ -0,0 +1 @@
+uriafranko

deepface/DeepFace.py

@@ -20,6 +20,7 @@ from deepface.basemodels import VGGFace, OpenFace, Facenet, FbDeepFace
 from deepface.extendedmodels import Age, Gender, Race, Emotion
 from deepface.commons import functions, realtime, distance as dst
 
+
 def verify(img1_path, img2_path=''
 	, model_name ='VGG-Face', distance_metric = 'cosine', model = None):
 
@@ -148,7 +149,8 @@ def verify(img1_path, img2_path=''
 		return resp_obj
 		#return resp_objects
 
-def analyze(img_path, actions= []):
+
+def analyze(img_path, actions= [], models= {}):
 
 	if type(img_path) == list:
 		img_paths = img_path.copy()
@@ -168,15 +170,27 @@ def analyze(img_path, actions= []):
 	#---------------------------------
 
 	if 'emotion' in actions:
+		if 'emotion' in models:
+			emotion_model = models['emotion']
+		else:
 			emotion_model = Emotion.loadModel()
 
 	if 'age' in actions:
+		if 'age' in models:
+			age_model = models['age']
+		else:
 			age_model = Age.loadModel()
 
 	if 'gender' in actions:
+		if 'gender' in models:
+			gender_model = models['gender']
+		else:
 			gender_model = Gender.loadModel()
 
 	if 'race' in actions:
+		if 'race' in models:
+			race_model = models['race']
+		else:
 			race_model = Race.loadModel()
 	#---------------------------------
 
@@ -289,13 +303,16 @@ def analyze(img_path, actions= []):
 		return resp_obj
 		#return resp_objects
 
+
 def detectFace(img_path):
 	img = functions.detectFace(img_path)[0] #detectFace returns (1, 224, 224, 3)
 	return img[:, :, ::-1] #bgr to rgb
 
+
 def stream(db_path, model_name ='VGG-Face', distance_metric = 'cosine', enable_face_analysis = True):
 	realtime.analysis(db_path, model_name, distance_metric, enable_face_analysis)
 
+
 #---------------------------
 
 functions.initializeFolder()