progress bar

deepface/DeepFace.py

@@ -66,8 +66,15 @@ def verify(img1_path, img2_path=''
 	threshold = functions.findThreshold(model_name, distance_metric)
 
 	#------------------------------
+	pbar = tqdm(range(0,len(img_list)), desc='Verification')
+	
 	resp_objects = []
-	for instance in img_list:
+	
+	#for instance in img_list:
+	for index in pbar:
+	
+		instance = img_list[index]
+		
 		if type(instance) == list and len(instance) >= 2:
 			img1_path = instance[0]
 			img2_path = instance[1]
@@ -198,7 +205,12 @@ def analyze(img_path, actions = [], models = {}, enforce_detection = True):
 	#---------------------------------
 
 	resp_objects = []
-	for img_path in img_paths:
+	
+	global_pbar = tqdm(range(0,len(img_paths)), desc='Analyzing')
+	
+	#for img_path in img_paths:
+	for j in global_pbar:
+		img_path = img_paths[j]
 
 		resp_obj = "{"
 

setup.py

@@ -5,7 +5,7 @@ with open("README.md", "r", encoding="utf-8") as fh:
 
 setuptools.setup(
     name="deepface",  
-    version="0.0.21",
+    version="0.0.22",
     author="Sefik Ilkin Serengil",
     author_email="serengil@gmail.com",
     description="Deep Face Analysis Framework for Face Recognition and Demography",

tests/unit_tests.py

@@ -153,4 +153,4 @@ facial_attribute_models["age"] = age_model
 facial_attribute_models["gender"] = gender_model
 facial_attribute_models["race"] = race_model
 
-resp_obj = DeepFace.analyze("dataset/img1.jpg", models=facial_attribute_models)
+resp_obj = DeepFace.analyze("dataset/img1.jpg", models=facial_attribute_models)