Update app.py

app.py

@@ -12,45 +12,41 @@ from scipy.ndimage import gaussian_filter
 from tensorflow.keras.models import load_model
 from options.swap_options import SwapOptions
 
-print("hello")
-
-token = os.environ['model_fetch']
+# .
+# token = os.environ['model_fetch']
 
 opt = SwapOptions().parse()
+token = os.environ['token']
 
 retina_repo = Repository(local_dir="retina_models", clone_from="felixrosberg/RetinaFace")
 
-print("cloned")
-
 from retinaface.models import *
 
-print("imported")
-
-RetinaFace = load_model("retina_model/RetinaFace-Res50.h5",
+RetinaFace = load_model("retina_models/RetinaFace-Res50.h5",
                         custom_objects={"FPN": FPN,
                                         "SSH": SSH,
                                         "BboxHead": BboxHead,
                                         "LandmarkHead": LandmarkHead,
-                                        "ClassHead": ClassHead})
-
-print("loading model")
+                                        "ClassHead": ClassHead}
+                        )
 
 arc_repo = Repository(local_dir="arcface_model", clone_from="felixrosberg/ArcFace")
 ArcFace = load_model("arcface_model/ArcFace-Res50.h5")
 ArcFaceE = load_model("arcface_model/ArcFacePerceptual-Res50.h5")
 
-
 g_repo = Repository(local_dir="g_model_c_hq", clone_from="felixrosberg/FaceDancer",use_auth_token=token)
 G = load_model("g_model_c_hq/FaceDancer_config_c_HQ.h5", custom_objects={"AdaIN": AdaIN,
                                                                  "AdaptiveAttention": AdaptiveAttention,
                                                                  "InstanceNormalization": InstanceNormalization})
 
-# r_repo = Repository(local_dir="reconstruction_attack", clone_from="felixrosberg/reconstruction_attack", use_auth_token=token)
+# r_repo = Repository(local_dir="reconstruction_attack", clone_from="felixrosberg/reconstruction_attack",
+#                     private=True, use_auth_token=token)
 # R = load_model("reconstruction_attack/reconstructor_42.h5", custom_objects={"AdaIN": AdaIN,
 #                                                                             "AdaptiveAttention": AdaptiveAttention,
 #                                                                             "InstanceNormalization": InstanceNormalization})
 
-# permuter_repo = Repository(local_dir="identity_permuter", clone_from="felixrosberg/identitypermuter", use_auth_token=token, git_user="felixrosberg")
+# permuter_repo = Repository(local_dir="identity_permuter", clone_from="felixrosberg/identitypermuter",
+#                            private=True, use_auth_token=token, git_user="felixrosberg")
 
 # from identity_permuter.id_permuter import identity_permuter
 
@@ -128,7 +124,7 @@ def run_inference(target, source, slider, adv_slider, settings):
                 slider_weight = slider / 100
 
                 target_z = ArcFace.predict(np.expand_dims(tf.image.resize(im_aligned, [112, 112]) * 0.5 + 0.5, axis=0))
-                source_z = IDP.predict(target_z)
+                # source_z = IDP.predict(target_z)
 
                 source_z = slider_weight * source_z + (1 - slider_weight) * target_z