Update app.py

app.py

@@ -85,9 +85,9 @@ def generate_annotation(img, overlap=False, hand_encoding=False):
     # STEP 5: Process the classification result. In this case, visualize it.
     annotated_image = draw_landmarks_on_image(image.numpy_view(), detection_result, overlap=overlap, hand_encoding=hand_encoding)
     return annotated_image
-with gr.Row():
-    model_type = gr.Radio(["Standard", "Hand Encoding"], label="Model preprocessing", info="We developed two models, one with standard mediapipe landmarks, and one with different (but similar) coloring on palm landmards to distinguish left and right")
 
+model_type = gr.Radio(["Standard", "Hand Encoding"], label="Model preprocessing", info="We developed two models, one with standard mediapipe landmarks, and one with different (but similar) coloring on palm landmards to distinguish left and right")
+model_type="Standard"
 if model_type=="Standard":
     args = Namespace(
         pretrained_model_name_or_path="runwayml/stable-diffusion-v1-5",