Display data

app.py

@@ -1,4 +1,5 @@
 import streamlit as st
+import pandas as pd
 import sahi.utils.file
 from PIL import Image
 from sahi import AutoDetectionModel
@@ -48,8 +49,17 @@ def download_comparison_images():
 download_comparison_images()
 
 # initialize prediction visual data
-#coco_df = 
-
+coco_df = pd.DataFrame({
+    'category' : ['centrifugal-pump','centrifugal-pump','gate-valve','gate-valve','gate-valve','gate-valve','gate-valve','gate-valve','gate-valve','gate-valve','gate-valve'],
+    'score' : [0.88, 0.85, 0.87, 0.87, 0.86, 0.86, 0.85, 0.84, 0.81, 0.81, 0.76]
+})
+output_df = pd.DataFrame({
+    'category':['ball-valve', 'butterfly-valve', 'centrifugal-pump', 'check-valve', 'gate-valve'],
+    'count':[0, 0, 2, 0, 9],
+    'percentage':[0, 0, 18.2, 0, 81.8] 
+})
+
+# session state
 if "output_1" not in st.session_state:
     img_1 = Image.open('plant_pid.png')
     st.session_state["output_1"] = img_1.resize((4960,3508))
@@ -58,7 +68,11 @@ if "output_2" not in st.session_state:
     img_2 = Image.open('prediction_visual.png')
     st.session_state["output_2"] = img_2.resize((4960,3508))
 
-#if "output_3" not in st.session_state:
+if "output_3" not in st.session_state:
+    st.session_state["output_3"] = coco_df
+    
+if "output_4" not in st.session_state:
+    st.session_state["output_4"] = output_df
     
 
 col1, col2, col3 = st.columns(3, gap='medium')
@@ -160,6 +174,8 @@ if submit:
 
     st.session_state["output_1"] = image
     st.session_state["output_2"] = output_visual
+    st.session_state["output_3"] = coco_df
+    st.session_state["output_4"] = output_df
 
 st.write('##')
 
@@ -167,7 +183,7 @@ col1, col2, col3 = st.columns([1, 5, 1], gap='small')
 with col2:  
     st.markdown(f"#### Object Detection Result")
     with st.container(border = True):
-        tab1, tab2, tab3 = st.tabs(['Original Image','Inference Prediction','Data 📊'])
+        tab1, tab2, tab3, tab4 = st.tabs(['Original Image','Inference Prediction','Data','Insights'])
         with tab1:
             st.image(st.session_state["output_1"])
         with tab2:
@@ -176,7 +192,19 @@ with col2:
             col1,col2,col3 = st.columns([1,2,1])
             with col2:
                 st.dataframe(
-                    output_df.style.hide_columns('percentage'),
+                    st.session_state["output_3"],
+                    column_config = {
+                        'category' : 'Predicted Category',
+                        'score' : 'Confidence',
+                    },
+                    use_container_width = True,
+                    hide_index = True,
+                )
+        with tab4:
+            col1,col2,col3 = st.columns([1,2,1])
+            with col2:
+                st.dataframe(
+                    st.session_state["output_4"],
                     column_config = {
                         'category' : 'Category',
                         'count' : 'Number of Elements',