Update app.py

app.py

@@ -138,11 +138,6 @@ if uploaded_file is not None:
     image = np.log10(data+1)
     with colA:
         plot_image(image, scale)
-
-    with colB:
-        st.markdown("""<style>[data-baseweb="select"] {margin-top: -36px;}</style>""", unsafe_allow_html=True)
-        threshold = st.slider("", 0.0, 1.0, 0.4, 0.05, label_visibility="hidden")
-        # plot_prediction(y_pred)
     
     if detect:
         data, wcs = cut(data, wcs, scale=scale)
@@ -155,10 +150,17 @@ if uploaded_file is not None:
             pred = np.rot90(pred, -j)
             y_pred += pred / 4
 
+        with colB:
+            st.markdown("""<style>[data-baseweb="select"] {margin-top: -36px;}</style>""", unsafe_allow_html=True)
+            threshold = st.slider("", 0.0, 1.0, 0.4, 0.05, label_visibility="hidden")
+        
         y_pred = np.where(y_pred > threshold, y_pred, 0)
 
         plot_prediction(y_pred)
 
+    with colC:
+        st.markdown("""<style>[data-baseweb="select"] {margin-top: -36px;}</style>""", unsafe_allow_html=True)
+
         # if decompose:
         #     cavs = decompose_cavity(y_pred, )