Update app.py

app.py

@@ -192,7 +192,7 @@ with col_1:
     uploaded_file = st.file_uploader("Choose a FITS file", type=['fits'], on_change=reset_threshold)
 
 with col_2:
-    st.markdown("<br style='margin:24px 0'>", unsafe_allow_html=True)
+    st.markdown("<br style='margin:18px 0'>", unsafe_allow_html=True)
     example = st.button("Example")
     
     # with col_2:
@@ -212,10 +212,11 @@ with col_2:
 if uploaded_file is not None:
     data, wcs = load_file(uploaded_file)
     os.system(f'mkdir -p {uploaded_file.name.strip(".fits")}')
+    fname = uploaded_file.name.strip(".fits")
 
 if example:
-    uploaded_file.name = "NGC4649_example.fits"
-    data, wcs = load_file("NGC4649_example.fits")
+    fname = "NGC4649_example"
+    data, wcs = load_file(f"{fname}.fits")
 
 if "data" not in locals():
     data = np.zeros((128,128))
@@ -249,7 +250,7 @@ with col5: decompose = st.button('Decompose', key="decompose")
 # Make two columns for plots
 _, colA, colB, colC, _ = st.columns([bordersize,1,1,1,bordersize])
 
-if uploaded_file is not None:
+if (uploaded_file is not None) or example:
     # NORMALIZE IMAGE
     MIN = np.min(np.where(data == 0, 1, data))
     if MIN < 1: data = data / MIN
@@ -258,7 +259,6 @@ if uploaded_file is not None:
     plot_image(image, scale)
     
     if detect or threshold or st.session_state.get("decompose", False):
-        fname = uploaded_file.name.strip(".fits")
 
         y_pred, wcs = cut_n_predict(data, wcs, scale)