test mobile

app.py

@@ -42,9 +42,9 @@ def main():
             return
 
         with prediction_result_placeholder.container():
-            with st.expander("Show result of prediction"):
-                with st.spinner('Waiting for result display...'):
-                    display_options(st.session_state.crop_image, st.session_state.score_threshold, is_mobile, screen_width)
+            #with st.expander("Show result of prediction"):
+                #with st.spinner('Waiting for result display...'):
+            display_options(st.session_state.crop_image, st.session_state.score_threshold, is_mobile, int(5/6*screen_width))
 
         if not is_mobile:
             with additional_options_placeholder.container():

modules/streamlit_utils.py

@@ -37,24 +37,6 @@ def clear_memory():
     st.session_state.clear()
     gc.collect()
 
-def sidebar():# Sidebar content
-    st.sidebar.header("This BPMN AI model recognition is proposed by: \n ELCA in collaboration with EPFL.")
-    st.sidebar.subheader("Instructions:")
-    st.sidebar.text("1. Upload you image")
-    st.sidebar.text("2. Crop the image \n  (try to put the BPMN diagram \n   in the center of the image)")
-    st.sidebar.text("3. Set the score threshold \n   for prediction (default is 0.5)")
-    st.sidebar.text("4. Click on 'Launch Prediction'")
-    st.sidebar.text("5. You can now see the annotation \n   and the BPMN XML result")
-    st.sidebar.text("6. You can change the scale for \n   the XML file (default is 1.0)")
-    st.sidebar.text("7. You can modify and download \n   the result in right format")
-
-    st.sidebar.subheader("If there is an error, try to:")
-    st.sidebar.text("1. Change the score threshold")
-    st.sidebar.text("2. Re-crop the image by placing\n   the BPMN diagram in the center\n   of the image")
-    st.sidebar.text("3. Re-Launch the prediction")
-
-    st.sidebar.subheader("You can close this sidebar")
-
 
 # Function to read XML content from a file
 def read_xml_file(filepath):
@@ -218,7 +200,23 @@ def display_title(is_mobile):
     st.title(title)
 
 def display_sidebar():
-    sidebar()
+    st.sidebar.header("This BPMN AI model recognition is proposed by: \n ELCA in collaboration with EPFL.")
+    st.sidebar.subheader("Instructions:")
+    st.sidebar.text("1. Upload you image")
+    st.sidebar.text("2. Crop the image \n  (try to put the BPMN diagram \n   in the center of the image)")
+    st.sidebar.text("3. Set the score threshold \n   for prediction (default is 0.5)")
+    st.sidebar.text("4. Click on 'Launch Prediction'")
+    st.sidebar.text("5. You can now see the annotation \n   and the BPMN XML result")
+    st.sidebar.text("6. You can modify the result \n   by clicking on 'Modify Results'")
+    st.sidebar.text("7. You can change the scale for \n   the XML file (default is 1.0)")
+    st.sidebar.text("8. You can modify with the modeler \n   and download the result in right format")
+
+    st.sidebar.subheader("If there is an error, try to:")
+    st.sidebar.text("1. Change the score threshold")
+    st.sidebar.text("2. Re-crop the image by placing\n   the BPMN diagram in the center\n   of the image")
+    st.sidebar.text("3. Re-Launch the prediction")
+
+    st.sidebar.subheader("You can close this sidebar")
 
 def initialize_session_state():
     if 'pool_bboxes' not in st.session_state:
@@ -288,7 +286,7 @@ def crop_image(resized_image, original_image):
 def get_score_threshold(is_mobile):
     col1, col2 = st.columns(2)
     with col1:
-        st.session_state.score_threshold = st.slider("Set score threshold for prediction", min_value=0.0, max_value=1.0, value=0.5 if not is_mobile else 0.6, step=0.05) 
+        st.session_state.score_threshold = st.slider("Set score threshold for prediction", min_value=0.0, max_value=1.0, value=0.5, step=0.05) 
 
 def launch_prediction(cropped_image, score_threshold, is_mobile, screen_width):
     st.session_state.crop_image = cropped_image