face detect test

vtoonify/style_transfer.py

@@ -76,16 +76,6 @@ if __name__ == "__main__":
         open(modelname, 'wb').write(data) 
     landmarkpredictor = dlib.shape_predictor(modelname)
 
-    cnn_model_path = './checkpoint/mmod_human_face_detector.dat'
-    if not os.path.exists(cnn_model_path):
-        import wget, bz2
-
-        wget.download('http://dlib.net/files/mmod_human_face_detector.dat.bz2', cnn_model_path + '.bz2')
-        zipfile = bz2.BZ2File(cnn_model_path + '.bz2')
-        data = zipfile.read()
-        open(cnn_model_path, 'wb').write(data)
-    cnn_face_detector = dlib.shape_predictor(cnn_model_path)
-
     pspencoder = load_psp_standalone(args.style_encoder_path, device)    
 
     if args.backbone == 'dualstylegan':

vtoonify_model.py

@@ -19,7 +19,7 @@ import gc
 import huggingface_hub
 import os
 
-MODEL_REPO = 'PKUWilliamYang/VToonify'
+MODEL_REPO = 'saimemrekanat/vmodels'
 
 class Model():
     def __init__(self, device):
@@ -69,6 +69,10 @@ class Model():
     def _create_dlib_landmark_model():
         return dlib.shape_predictor(huggingface_hub.hf_hub_download(MODEL_REPO,
                                                     'models/shape_predictor_68_face_landmarks.dat'))
+
+    def _create_dlib_landmark_cnn_model():
+        return dlib.shape_predictor(huggingface_hub.hf_hub_download(MODEL_REPO,
+                                                    'models/mmod_human_face_detector.dat'))
     
     def _create_parsing_model(self):
         parsingpredictor = BiSeNet(n_classes=19)