diff --git a/predict.py b/predict.py
index 8aca41e..b6cd637 100644
--- a/predict.py
+++ b/predict.py
@@ -6,7 +6,6 @@ from src.config.crop_config import CropConfig
 from src.live_portrait_pipeline import LivePortraitPipeline
 import requests
 
-
 class Predictor(BasePredictor):
     def setup(self) -> None:
         """Load the model into memory to make running multiple predictions efficient"""
@@ -17,18 +16,27 @@ class Predictor(BasePredictor):
 
     def predict(
         self,
-        image: Path = Input(description="Portrait image")
+        input_image_path: Path = Input(description="Portrait image"),
+        input_video_path: Path = Input(description="Driving video"),
+        flag_relative_input: bool = Input(description="relative motion", default=True),
+        flag_do_crop_input: bool = Input(description="We recommend checking the do crop option when facial areas occupy a relatively small portion of your image.", default=True),
+        flag_pasteback: bool = Input(description="paste-back", default=True),
     ) -> Path:
         """Run a single prediction on the model"""
 
+        user_args = ArgumentConfig(
+            flag_relative=flag_relative_input,
+            flag_do_crop=flag_do_crop_input,
+            flag_pasteback=flag_pasteback,
+            source_image=input_image_path,
+            driving_info=str(input_video_path),
+            output_dir="/tmp/"
+        )
+        self.live_portrait_pipeline.cropper.update_config(user_args.__dict__)
+        self.live_portrait_pipeline.live_portrait_wrapper.update_config(user_args.__dict__)
+
         video_path, _ = self.live_portrait_pipeline.execute(
-            ArgumentConfig(
-                source_image=image,
-                driving_info="assets/examples/driving/d0.mp4",
-                output_dir="/tmp/",
-                flag_pasteback=False,
-                flag_do_crop=False,
-            )
+            user_args
         )
 
         return Path(video_path)