updates to app.py

app.py

@@ -117,4 +117,34 @@ if archivo_imagen is not None:
         st.subheader("Segmentación:")
         st.write(output.shape)
         st.image(output, width=850)
-        
+
+
+    ## This will provide a dashboard
+        st.subheader("Diagnostic metrics overview")
+                
+                conteo_dientes = len(cnts)
+                area_total = np.sum(mask > 0)
+                area_promedio = area_total / conteo_dientes if conteo_dientes > 0 else 0
+                
+                col_m1, col_m2, col_m3 = st.columns(3)
+                col_m1.metric("Tooth count", conteo_dientes)
+                col_m2.metric("Total dental area (px)", f"{area_total:,}")
+                col_m3.metric("Average tooth area (px)", f"{int(area_promedio):,}")
+                
+                st.markdown("### Detected instances data")
+                
+                datos_dientes = []
+                for i, c in enumerate(cnts):
+                    area = cv2.contourArea(c)
+                    x, y, w, h = cv2.boundingRect(c)
+                    datos_dientes.append({
+                        "ID": i + 1,
+                        "Area (px)": area,
+                        "Width (px)": w,
+                        "Height (px)": h
+                    })
+                    
+                import pandas as pd
+                df_dientes = pd.DataFrame(datos_dientes)
+                st.dataframe(df_dientes, use_container_width=True)
+                

requirements.txt

@@ -1,4 +1,5 @@
 streamlit
 huggingface_hub==0.21.4
 tensorflow==2.15.0
-opencv-python-headless
+opencv-python-headless
+pandas