.

.idea/AFFA-face-swap.iml

@@ -2,7 +2,7 @@
 <module type="PYTHON_MODULE" version="4">
   <component name="NewModuleRootManager">
     <content url="file://$MODULE_DIR$" />
-    <orderEntry type="jdk" jdkName="Python 3.8 (py38)" jdkType="Python SDK" />
+    <orderEntry type="jdk" jdkName="Python 3.10" jdkType="Python SDK" />
     <orderEntry type="sourceFolder" forTests="false" />
   </component>
   <component name="PyDocumentationSettings">

.idea/misc.xml

@@ -1,4 +1,4 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <project version="4">
-  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.8 (py38)" project-jdk-type="Python SDK" />
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.10" project-jdk-type="Python SDK" />
 </project>

.idea/other.xml

@@ -0,0 +1,7 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="PySciProjectComponent">
+    <option name="PY_SCI_VIEW" value="true" />
+    <option name="PY_SCI_VIEW_SUGGESTED" value="true" />
+  </component>
+</project>

app.py

@@ -14,7 +14,7 @@ from utils.utils import (estimate_norm, get_lm, inverse_estimate_norm,
                          norm_crop, transform_landmark_points)
 
 # .
-token = os.environ['model_fetch']
+# token = os.environ['model_fetch']
 
 opt = SwapOptions().parse()
 
@@ -49,8 +49,8 @@ G = load_model("g_model_c_hq/FaceDancer_config_c_HQ.h5", custom_objects={"AdaIN"
 
 # from identity_permuter.id_permuter import identity_permuter
 
-IDP = identity_permuter(emb_size=32, min_arg=False)
-IDP.load_weights("identity_permuter/id_permuter.h5")
+# IDP = identity_permuter(emb_size=32, min_arg=False)
+# IDP.load_weights("identity_permuter/id_permuter.h5")
 
 blend_mask_base = np.zeros(shape=(256, 256, 1))
 blend_mask_base[80:244, 32:224] = 1
@@ -123,7 +123,7 @@ 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