Update app.py

app.py

@@ -22,8 +22,17 @@ def analyze_crack(image):
     
     return edges, crack_lengths, crack_widths
 
+def classify_crack(length, width):
+    if length > 150 or width > 20:
+        return "Major"
+    elif length > 80 or width > 10:
+        return "Moderate"
+    else:
+        return "Minor"
+
 def main():
-    st.set_page_config(page_title='Structural Integrity Analyst', layout='wide')
+    st.set_page_config(page_title='Structural Integrity Analyst', layout='wide', initial_sidebar_state='expanded')
+    
     st.title('🏗️ Structural Integrity Analyst')
     
     st.sidebar.header("Upload Crack Image")
@@ -35,35 +44,46 @@ def main():
         
         edges, crack_lengths, crack_widths = analyze_crack(image)
         
-        st.subheader("Uploaded Image")
-        st.image(uploaded_file, caption="Uploaded Image", use_column_width=True)
+        # Classification
+        classifications = [classify_crack(l, w) for l, w in zip(crack_lengths, crack_widths)]
+        
+        # Organize layout
+        col1, col2 = st.columns(2)
         
-        # Display processed image
-        st.subheader("Processed Crack Detection")
-        fig, ax = plt.subplots()
-        ax.imshow(edges, cmap='gray')
-        ax.axis("off")
-        st.pyplot(fig)
+        with col1:
+            st.subheader("Uploaded Image")
+            st.image(uploaded_file, caption="Uploaded Image", use_column_width=True)
+        
+        with col2:
+            st.subheader("Processed Crack Detection")
+            fig, ax = plt.subplots()
+            ax.imshow(edges, cmap='gray')
+            ax.axis("off")
+            st.pyplot(fig)
         
         # Data Analysis
         data = pd.DataFrame({
             "Crack Length (pixels)": crack_lengths,
-            "Crack Width (pixels)": crack_widths
+            "Crack Width (pixels)": crack_widths,
+            "Severity": classifications
         })
         
-        st.subheader("Crack Metrics")
+        st.subheader("Crack Metrics & Classification")
         st.dataframe(data)
         
+        # Discussion Tab
+        st.subheader("Discussion")
+        st.write("Cracks are classified based on their length and width:")
+        st.write("- **Major:** Cracks exceeding 150 pixels in length or 20 pixels in width indicate severe damage and require immediate attention.")
+        st.write("- **Moderate:** Cracks between 80-150 pixels in length or 10-20 pixels in width are moderate and should be monitored closely.")
+        st.write("- **Minor:** Cracks below 80 pixels in length or 10 pixels in width are minor and may not require immediate intervention but should be observed over time.")
+        
         # Visualization
-        fig1 = px.histogram(data, x="Crack Length (pixels)", title="Crack Length Distribution", nbins=10)
-        fig2 = px.histogram(data, x="Crack Width (pixels)", title="Crack Width Distribution", nbins=10)
+        fig1 = px.histogram(data, x="Crack Length (pixels)", color="Severity", title="Crack Length Distribution", nbins=10)
+        fig2 = px.histogram(data, x="Crack Width (pixels)", color="Severity", title="Crack Width Distribution", nbins=10)
         
         st.plotly_chart(fig1, use_container_width=True)
         st.plotly_chart(fig2, use_container_width=True)
     
 if __name__ == "__main__":
-    main()
-
-
-
-
+    main()