external tests

deepface/DeepFace.py

@@ -48,13 +48,19 @@ if tf_version == 2:
 folder_utils.initialize_folder()
 
 
-def build_model(task: str, model_name: str) -> Any:
+def build_model(model_name: str, task: str = "facial_recognition") -> Any:
     """
-    This function builds a deepface model
+    This function builds a pre-trained model
     Args:
-        model_name (string): face recognition, facial attribute or face detector model
+        model_name (str): model identifier
-            VGG-Face, Facenet, OpenFace, DeepFace, DeepID for face recognition
+            - VGG-Face, Facenet, Facenet512, OpenFace, DeepFace, DeepID, Dlib,
-            Age, Gender, Emotion, Race for facial attributes
+                ArcFace, SFace, GhostFaceNet for face recognition
+            - Age, Gender, Emotion, Race for facial attributes
+            - opencv, mtcnn, ssd, dlib, retinaface, mediapipe, yolov8, yunet,
+                fastmtcnn or centerface for face detectors
+            - Fasnet for spoofing
+        task (str): facial_recognition, facial_attribute, face_detector, spoofing
+            default is facial_recognition
     Returns:
         built_model
     """

deepface/modules/modeling.py

@@ -97,6 +97,6 @@ def build_model(task: str, model_name: str) -> Any:
         if model:
             model_obj[task][model_name] = model()
         else:
-            raise ValueError(f"Invalid model_name passed - {model_name}")
+            raise ValueError(f"Invalid model_name passed - {task}/{model_name}")
 
     return model_obj[task][model_name]

tests/face-recognition-how.py

@@ -16,7 +16,7 @@ logger = Logger()
 
 model_name = "VGG-Face"
 
-model: FacialRecognition = DeepFace.build_model(model_name=model_name)
+model: FacialRecognition = DeepFace.build_model(task="facial_recognition", model_name=model_name)
 
 target_size = model.input_shape