Update app.py

app.py

@@ -87,7 +87,7 @@ def cut(data0, wcs0, scale=1):
     return data, wcs
 
 # Define function to apply cutting and produce a prediction
-@st.cache
+# @st.cache
 def cut_n_predict(data, wcs, scale):
     data, wcs = cut(data, wcs, scale=scale)
     image = np.log10(data+1)
@@ -102,7 +102,7 @@ def cut_n_predict(data, wcs, scale):
     return y_pred, wcs
 
 # Define function to decompose prediction into individual cavities
-@st.cache
+# @st.cache
 def decompose_cavity(pred, th2=0.7, amin=6):
     X, Y = pred.nonzero()
     data = np.array([X,Y]).reshape(2, -1)
@@ -141,12 +141,12 @@ def decompose_cavity(pred, th2=0.7, amin=6):
     
     return image_decomposed
 
-@st.cache
-def load_file(fname):
-    with fits.open(fname) as hdul:
-        data = hdul[0].data
-        wcs = WCS(hdul[0].header)
-    return data, wcs
+# @st.cache
+# def load_file(fname):
+#     with fits.open(fname) as hdul:
+#         data = hdul[0].data
+#         wcs = WCS(hdul[0].header)
+#     return data, wcs
 
 # def change_scale():
 #     del st.session_state["threshold"]
@@ -207,31 +207,31 @@ if uploaded_file is not None:
         scale = st.selectbox('Scale:',[f"{(i+1)*128}x{(i+1)*128}" for i in range(max_scale)], label_visibility="hidden") #, on_change=change_scale)
         scale = int(scale.split("x")[0]) // 128
     
-    # Detect button
-    with col3: detect = st.button('Detect', key="detect")
+    # # Detect button
+    # with col3: detect = st.button('Detect', key="detect")
     
-    # Threshold slider
-    with col4:
-        st.markdown("")
-        # st.markdown("""<style>[data-baseweb="select"] {margin-top: -36px;}</style>""", unsafe_allow_html=True)
-        threshold = st.slider("Threshold", 0.0, 1.0, 0.0, 0.05, key="threshold") #, label_visibility="hidden")
+    # # Threshold slider
+    # with col4:
+    #     st.markdown("")
+    #     # st.markdown("""<style>[data-baseweb="select"] {margin-top: -36px;}</style>""", unsafe_allow_html=True)
+    #     threshold = st.slider("Threshold", 0.0, 1.0, 0.0, 0.05, key="threshold") #, label_visibility="hidden")
         
-    # Decompose button
-    with col5: decompose = st.button('Decompose', key="decompose")
+    # # Decompose button
+    # with col5: decompose = st.button('Decompose', key="decompose")
         
-    # Make two columns for plots
-    _, colA, colB, colC, _ = st.columns([bordersize,1,1,1,bordersize])
+    # # Make two columns for plots
+    # _, colA, colB, colC, _ = st.columns([bordersize,1,1,1,bordersize])
     
     image = np.log10(data+1)
     plot_image(image, scale)
     
-    if detect or threshold:
-    # if st.session_state.get("detect", True):
-        y_pred, wcs = cut_n_predict(data, wcs, scale)
+    # if detect or threshold:
+    # # if st.session_state.get("detect", True):
+    #     y_pred, wcs = cut_n_predict(data, wcs, scale)
         
-        y_pred_th = np.where(y_pred > threshold, y_pred, 0)
+    #     y_pred_th = np.where(y_pred > threshold, y_pred, 0)
                 
-        plot_prediction(y_pred_th)
+    #     plot_prediction(y_pred_th)
     
     #     if decompose or st.session_state.get("download", False):            
     #         image_decomposed = decompose_cavity(y_pred_th)