Update app.py

app.py

@@ -39,26 +39,24 @@ def get_prediction(img):
     return predictions[0,:]
 
 models = ['DDPM', 'Glide', 'Latent Diffusion', 'Palette', 'Stable Diffusion', 'VQ Diffusion', 'real', 'unseen_fake']
-variant = None 
+
 
 st.title("Fake Detection")
 st.divider()
 
+st.subheader("Modelvariant")
+variant = st.selectbox(
+    "Choose the model",
+    ("ResNet50v2-Basemodel", "ResNet50v2-Finetuned"),
+    index=None,
+)
+st.write("You selected model: ", variant)
+st.divider()
 
-while(variant == None):
-    st.subheader("Modelvariant")
-    variant = st.selectbox(
-        "Choose the model",
-        ("ResNet50v2-Basemodel", "ResNet50v2-Finetuned"),
-        index=None,
-    )
-    st.write("You selected model: ", variant)
-    st.divider()
-    
-    if variant == "ResNet50v2-Basemodel":
-        local_model_path = snapshot_download(repo_id="ElBeh/ma_basemodel")
-    else:
-        local_model_path = snapshot_download(repo_id="ElBeh/ma_finetuned_model")
+if variant == "ResNet50v2-Basemodel":
+    local_model_path = snapshot_download(repo_id="ElBeh/ma_basemodel")
+else:
+    local_model_path = snapshot_download(repo_id="ElBeh/ma_finetuned_model")
 
 
 model = keras.models.load_model(local_model_path)