Update app.py

app.py

@@ -117,18 +117,18 @@ if uploaded_file is not None:
     col3.subheader("Prediction")
     col5.subheader("Decomposed")
     
-    with col2:
+    with col1:
         # st.markdown("""<style>[data-baseweb="select"] {margin-top: -56px;}</style>""", unsafe_allow_html=True)
         max_scale = int(data.shape[0] // 128)
         # scale = int(st.selectbox('Scale:',[i+1 for i in range(max_scale)], label_visibility="hidden"))
         scale = st.selectbox('Scale:',[f"{(i+1)*128}x{(i+1)*128}" for i in range(max_scale)], label_visibility="hidden")
         scale = int(scale.split("x")[0]) // 128
     
-    with col4:
+    with col3:
         # st.markdown("""<style>[data-baseweb="select"] {margin-top: 16px;}</style>""", unsafe_allow_html=True)
         detect = st.button('Detect')
 
-    with col6:
+    with col5:
         decompose = st.button('Docompose')
         
     # Make two columns for plots
@@ -149,11 +149,12 @@ if uploaded_file is not None:
             pred = np.rot90(pred, -j)
             y_pred += pred / 4
 
-        # Thresholding
-        y_pred = np.where(y_pred > threshold, y_pred, 0)
-
         with colB:
             threshold = st.slider("", 0.0, 1.0, 0.4, 0.05, label_visibility="hidden")
+
+            # Thresholding
+            y_pred = np.where(y_pred > threshold, y_pred, 0)
+            
             plot_prediction(y_pred)
 
         # if decompose: