Update app.py

app.py

@@ -221,6 +221,8 @@ usefulness = {
     # Add the usefulness or importance for the rest of the flowers
 }
 
+useful = "Ornamental plant with colorful foliage and unique inflorescence"
+
 # Function to add a background image
 def add_bg_from_local(image_path):
     with open(image_path, "rb") as image_file:
@@ -306,8 +308,8 @@ def main():
             <h4 style="color:white"> LEVEL:</br> <b>400L</b></h4>
         """, unsafe_allow_html=True)
 
-    elif selected == "Local Classifier":
-        st.markdown('<h1 style="color:white;">Local Classifier</h1>', unsafe_allow_html=True)
+    elif selected == "Extensive Classifier":
+        st.markdown('<h1 style="color:white;">Extensive Classifier</h1>', unsafe_allow_html=True)
         st.markdown('<h3 style="color:white;">This is a demo of an image classification model trained on the Oxford Flower Dataset.</h3>', unsafe_allow_html=True)
         st.markdown('<h3 style="color:white;">To test the model, upload an image of a flower and click the Run on image button.</h3>', unsafe_allow_html=True)
         
@@ -317,18 +319,29 @@ def main():
         result = st.button('Run on image')
         
         if result and image is not None:
-            st.markdown('**_Calculating results..._**')
+            st.markdown('**_Calculating extensive results..._**')
             flower, closeness, botanical_name, flower_usefulness = predict(model, labels, image)
-            st.markdown(f'<h4 style="color:white;">Flower Type: <span style="color:blue;">{flower}</span></h4>', unsafe_allow_html=True)
-            st.markdown(f'<h4 style="color:white;">Closeness: <span style="color:green;">{closeness}%</span></h4>', unsafe_allow_html=True)
-            st.markdown(f'<h4 style="color:white;">Botanical Name: <span style="color:purple;">{botanical_name}</span></h4>', unsafe_allow_html=True)
-            st.markdown(f'<h4 style="color:white;">Usefulness: <span style="color:orange;">{flower_usefulness}</span></h4>', unsafe_allow_html=True)
+            st.markdown(f'<h4 style="color:white;">Flower Type: <span style="color:orange;">{flower}</span></h4>', unsafe_allow_html=True)
+            st.markdown(f'<h4 style="color:white;">Closeness: <span style="color:orange;">{closeness}%</span></h4>', unsafe_allow_html=True)
+            st.markdown(f'<h4 style="color:white;">Botanical Name: <span style="color:orange;">{botanical_name}</span></h4>', unsafe_allow_html=True)
+            st.markdown(f'<h4 style="color:white;">Usefulness: <span style="color:orange;">{useful}</span></h4>', unsafe_allow_html=True)
 
-    elif selected == "Extensive Classifier":
-        st.markdown('<h1 style="color:white;">Extensive Classifier</h1>', unsafe_allow_html=True)
+    elif selected == "Local Classifier":
+        st.markdown('<h1 style="color:white;">Local Classifier</h1>', unsafe_allow_html=True)
         st.markdown('<h3 style="color:white;">This section will contain extensive classifier details and options.</h3>', unsafe_allow_html=True)
         # Add your extensive classifier code here
 
+        model = load_model()
+        labels = load_labels()
+        image = load_image()
+        result = st.button('Run on image')
+        
+        if result and image is not None:
+            st.markdown('**_Calculating local results..._**')
+            flower, closeness, botanical_name, flower_usefulness = predict(model, labels, image)
+            st.markdown(f'<h5 style="color:white;">Flower Type: <span style="color:orange;">{flower}</span></h4>', unsafe_allow_html=True)
+            st.markdown(f'<h5 style="color:white;">Closeness: <span style="color:orange;">{closeness}%</span></h4>', unsafe_allow_html=True)
+
     elif selected == "Project Details":
         st.markdown('<h1 style="color:white;">Project Details</h1>', unsafe_allow_html=True)
         st.markdown("""