add example

app.py

@@ -15,13 +15,14 @@ title = "FaceOver - edit face with text 🐨 "
 
 examples = [
     ["examples/jennifer lawrence.jpg", "dark hair smiling woman with glasses", 0.58],
+    ["examples/kim kardashian.jpg", "woman with pink wig",1.15],
     ["examples/kim kardashian.jpg", "beautiful asian woman with short haired ", 0.88],
     ["examples/Arnold Schwarzenegger.jpg", "happy man with long hair and hat", 0.44]
 
 ]
 
 iface = gr.Interface(fn=greet,
-                     inputs=["image", "text", gr.inputs.Slider(0.0, 1.0)],
+                     inputs=["image", "text", gr.inputs.Slider(0.0, 1.5)],
                      outputs="image",
                      title=title,
                      description=description,

help_function.py

@@ -28,12 +28,14 @@ class help_function:
         if not image.shape == torch.Size([3, 224, 224]):
             image = image.reshape(1,3,image.shape[1],image.shape[2])
             image = F.interpolate(image, [224,224], mode='bilinear', align_corners=True)
+
         w_inversion = self.encoder(image.reshape(1,3,224,224)).reshape(1,16,512)
         return w_inversion + self.mean_person
 
     def get_text_delta(self,text_feachers):
         w_delta = self.mapper_clip(text_feachers - self.mean_clip)
         return w_delta
+
     def image_from_text(self,text,image,power = 1.0):
         w_inversion = self.get_image_inversion(image)
         text_embedding = self.get_text_embedding(text)