Update app.py

app.py

@@ -169,7 +169,7 @@ os.system("rm -R -- */")
 with col:
     with st.container():
         # Create heading and description
-        st.markdown("<h1 align='center'>Cavity Detection Tool <a href='https://github.com/tomasplsek/CADET'>(CADET)</a></h1>", unsafe_allow_html=True)    
+        st.markdown("<h1 align='center'>Cavity Detection Tool (CADET)</h1>", unsafe_allow_html=True)    
         # st.markdown("Cavity Detection Tool (CADET) is a machine learning pipeline trained to detect X-ray cavities from noisy Chandra images of early-type galaxies.")
         # st.markdown("To use this tool: upload your image, select the scale of interest, make a prediction, and decompose it into individual cavities!")
         # st.markdown("Input images should be FITS files in units of counts, centred at the galaxy center, and point sources should be filled with surrounding background ([dmfilth](https://cxc.cfa.harvard.edu/ciao/ahelp/dmfilth.html)).")
@@ -177,10 +177,10 @@ with col:
 
         # #F3F4F6
         st.markdown("<div style='border-radius:5px;padding-top:8px;padding-bottom:8px;padding-left:14px;padding-right:14px;line-height:140%;font-size:120%;background-color:#FFFFFF;'>\
-Cavity Detection Tool (CADET) is a machine learning pipeline trained to detect X-ray cavities from <em>Chandra</em> images of early-type galaxies, groups, and clusters.\
+Cavity Detection Tool <a href='https://github.com/tomasplsek/CADET'>(CADET)</a> is a machine learning pipeline trained to detect X-ray cavities from <em>Chandra</em> images of early-type galaxies, groups, and clusters.\
 <br style='margin-bottom: 6px'>To use this tool:<br><b>1)</b> upload your FITS file<br><b>2)</b> select the scale of interest<br><b>3)</b> make a prediction<br><b>4)</b> decompose into individual cavities\
 <br style='margin-bottom: 6px'>If you use this tool in your research, please cite <a href='https://arxiv.org/abs/2304.05457'>Plšek et al. 2023</a>.\
-</div><br>", unsafe_allow_html=True)
+</div>", unsafe_allow_html=True)
 
 # Input images should be FITS files in units of counts, centred at the galaxy center, and point sources should be filled with surrounding background \
 # (<a href='https://cxc.cfa.harvard.edu/ciao/ahelp/dmfilth.html'>dmfilth</a>). <br><br>\
@@ -242,9 +242,13 @@ with col5: decompose = st.button('Decompose', key="decompose")
 _, colA, colB, colC, _ = st.columns([bordersize,1,1,1,bordersize])
 
 if uploaded_file is not None:
+    # NORMALIZE IMAGE
+    MIN = np.min(np.where(image == 0, 1, image))
+    if MIN < 1: image = image / MIN
+    
     image = np.log10(data+1)
     plot_image(image, scale)
-
+    
     if detect or threshold or st.session_state.get("decompose", False):
         fname = uploaded_file.name.strip(".fits")