Update app.py

app.py

@@ -110,6 +110,7 @@ if uploaded_file is not None:
     with fits.open(uploaded_file) as hdul:
         data = hdul[0].data
         wcs = WCS(hdul[0].header)
+        y_pred = np.zeros((128,128))
     
     # Make four columns for buttons
     _, col1, col2, col3, col4, col5, col6, _ = st.columns([bordersize,0.5,0.5,0.5,0.5,0.5,0.5,bordersize])
@@ -118,7 +119,7 @@ if uploaded_file is not None:
     col5.subheader("Decomposed")
     
     with col1:
-        # st.markdown("""<style>[data-baseweb="select"] {margin-top: -56px;}</style>""", unsafe_allow_html=True)
+        st.markdown("""<style>[data-baseweb="select"] {margin-top: -26px;}</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")
@@ -136,12 +137,11 @@ if uploaded_file is not None:
     
     image = np.log10(data+1)
     with colA:
-        st.markdown("""<style>[data-baseweb="select"] {margin-top: 6px;}</style>""", unsafe_allow_html=True)
         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")
-        y_pred = np.zeros((128,128))
         plot_prediction(y_pred)
     
     if detect: