Update app.py

app.py

@@ -37,35 +37,28 @@ def classify_crack(length, width):
 
 def generate_description(severity):
     if "Major" in severity:
-        return "🚨 This crack is classified as **Major**, indicating significant structural distress. Major cracks can compromise the integrity of the structure and require **immediate intervention**. These are typically caused by foundation settlement, excessive load, or material failure. **Professional assessment is advised.**"
+        return "🚨 This crack is classified as **Major**, indicating significant structural distress. Immediate intervention is required."
     elif "Moderate" in severity:
-        return "⚠️ This crack is classified as **Moderate**. While not immediately critical, it suggests progressive structural movement or material fatigue. **Monitoring and remedial measures**, such as crack sealing or reinforcement, should be considered."
+        return "⚠️ This crack is classified as **Moderate**. Monitoring and remedial measures should be considered."
     else:
-        return "✅ This crack is **Minor** and likely due to **surface shrinkage or thermal expansion**. While not structurally concerning, periodic monitoring is recommended to ensure it does not propagate further."
+        return "✅ This crack is **Minor** and likely due to surface shrinkage or thermal expansion. Periodic monitoring is recommended."
+
+def determine_structure_safety(crack_data):
+    if not crack_data:
+        return "✅ Structure is Safe", "green"
+    
+    major_count = sum(1 for crack in crack_data if "Major" in crack["Severity"])
+    moderate_count = sum(1 for crack in crack_data if "Moderate" in crack["Severity"])
+    
+    if major_count > 0 or moderate_count > 3:
+        return "🚨 Structure is NOT Safe", "red"
+    
+    return "⚠️ Structure Needs Monitoring", "orange"
 
 def main():
     st.set_page_config(page_title='🏗️ Structural Integrity Analyst', layout='wide', initial_sidebar_state='expanded')
     
-    # Custom Styling
-    st.markdown(
-        """
-        <style>
-            .title {
-                text-align: center;
-                font-size: 36px;
-                font-weight: bold;
-                color: #003366;
-            }
-            .subheader {
-                font-size: 24px;
-                font-weight: bold;
-                color: #00509E;
-            }
-        </style>
-        """, unsafe_allow_html=True
-    )
-    
-    st.markdown("<h1 class='title'>🏗️ Structural Integrity Analyst</h1>", unsafe_allow_html=True)
+    st.markdown("<h1 style='text-align: center; color: #003366;'>🏗️ Structural Integrity Analyst</h1>", unsafe_allow_html=True)
     
     st.sidebar.header("📂 Upload Crack Image")
     uploaded_file = st.sidebar.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
@@ -76,15 +69,19 @@ def main():
         
         edges, crack_data = analyze_crack(image)
         
+        # Determine Structural Safety
+        structure_status, status_color = determine_structure_safety(crack_data)
+        st.markdown(f"<h2 style='text-align: center; color: {status_color};'>{structure_status}</h2>", unsafe_allow_html=True)
+        
         # Organize layout
         col1, col2 = st.columns(2)
         
         with col1:
-            st.markdown("<h2 class='subheader'>📸 Uploaded Image</h2>", unsafe_allow_html=True)
+            st.subheader("📸 Uploaded Image")
             st.image(uploaded_file, caption="Uploaded Image", use_column_width=True)
         
         with col2:
-            st.markdown("<h2 class='subheader'>🔍 Processed Crack Detection</h2>", unsafe_allow_html=True)
+            st.subheader("🔍 Processed Crack Detection")
             fig, ax = plt.subplots()
             ax.imshow(edges, cmap='gray')
             ax.axis("off")
@@ -93,26 +90,21 @@ def main():
         # Data Analysis
         data = pd.DataFrame(crack_data)
         
-        st.markdown("<h2 class='subheader'>📊 Crack Metrics & Classification</h2>", unsafe_allow_html=True)
-        st.dataframe(data.style.applymap(lambda val: 'background-color: #FFDDC1' if 'Major' in str(val) else ('background-color: #FFF3CD' if 'Moderate' in str(val) else 'background-color: #D4EDDA')))
-        
-        # Description of Cracks
-        st.markdown("<h2 class='subheader'>📝 Crack Analysis & Recommendations</h2>", unsafe_allow_html=True)
-        for _, row in data.iterrows():
-            st.markdown(f"**Crack at (X: {row['X']}, Y: {row['Y']})** - {generate_description(row['Severity'])}")
-        
-        # Discussion
-        st.markdown("<h2 class='subheader'>💡 Discussion on Crack Severity</h2>", unsafe_allow_html=True)
-        st.write("- 🔴 **Major:** Significant structural impact, requires **immediate repair and engineering assessment.**")
-        st.write("- 🟠 **Moderate:** Moderate concern, monitoring required, may need **localized reinforcement.**")
-        st.write("- 🟢 **Minor:** Surface-level cracks, **not structurally critical** but should be observed over time.")
-        
-        # Visualization
-        fig1 = px.histogram(data, x="Length", color="Severity", title="📏 Crack Length Distribution", nbins=10, color_discrete_map={"🔴 Major": "red", "🟠 Moderate": "orange", "🟢 Minor": "green"})
-        fig2 = px.histogram(data, x="Width", color="Severity", title="📐 Crack Width Distribution", nbins=10, color_discrete_map={"🔴 Major": "red", "🟠 Moderate": "orange", "🟢 Minor": "green"})
-        
-        st.plotly_chart(fig1, use_container_width=True)
-        st.plotly_chart(fig2, use_container_width=True)
+        if not data.empty:
+            st.subheader("📊 Crack Metrics & Classification")
+            st.dataframe(data.style.applymap(lambda val: 'background-color: #FFDDC1' if 'Major' in str(val) else ('background-color: #FFF3CD' if 'Moderate' in str(val) else 'background-color: #D4EDDA')))
+            
+            # Description of Cracks
+            st.subheader("📝 Crack Analysis & Recommendations")
+            for _, row in data.iterrows():
+                st.markdown(f"**Crack at (X: {row['X']}, Y: {row['Y']})** - {generate_description(row['Severity'])}")
+            
+            # Visualization
+            fig1 = px.histogram(data, x="Length", color="Severity", title="📏 Crack Length Distribution", nbins=10, color_discrete_map={"🔴 Major": "red", "🟠 Moderate": "orange", "🟢 Minor": "green"})
+            fig2 = px.histogram(data, x="Width", color="Severity", title="📐 Crack Width Distribution", nbins=10, color_discrete_map={"🔴 Major": "red", "🟠 Moderate": "orange", "🟢 Minor": "green"})
+            
+            st.plotly_chart(fig1, use_container_width=True)
+            st.plotly_chart(fig2, use_container_width=True)
     
 if __name__ == "__main__":
-    main()
+    main()