Implementado texto explicativo dinámico que cambia según la selección de la imagen: beneficios para la imagen mejorada y desafíos para la imagen original

utils/preprocessing_ui.py

@@ -105,20 +105,43 @@ def show_preprocessing_ui(image_service, img: np.ndarray) -> Dict[str, Any]:
                 st.markdown("* Brightness decreased by 30%")
                 st.markdown("* Contrast decreased by 30%")
                 
-                # Add explanation of why these improvements help
-                st.markdown("## Why these improvements help facial analysis")
-                
-                # Technical explanation
-                st.markdown("**Technical Benefits:**")
-                st.markdown("* **Balanced contrast:** Enhances the visibility of facial features while reducing shadows and highlights")
-                st.markdown("* **Optimal brightness:** Ensures facial features are clearly distinguishable without over-exposure")
-                st.markdown("* **Proper sizing:** Maintains ideal dimensions for detection algorithms to recognize facial landmarks")
-                
-                # Impact on emotion detection
-                st.markdown("**Impact on Emotion Detection:**")
-                st.markdown("* **More accurate emotion classification:** Cleaner input images lead to more reliable emotion detection")
-                st.markdown("* **Better feature extraction:** Facial features like eyes, mouth, and eyebrows are more clearly defined")
-                st.markdown("* **Reduced noise and artifacts:** Minimizes false detections and improves confidence scores")
+                # Dynamic explanation based on selected mode
+                if st.session_state["selected_image_mode"] == "improved":
+                    # Show explanation about improvements benefits
+                    st.markdown("## Why these improvements help facial analysis")
+                    
+                    # Technical explanation
+                    st.markdown("**Technical Benefits:**")
+                    st.markdown("* **Balanced contrast:** Enhances the visibility of facial features while reducing shadows and highlights")
+                    st.markdown("* **Optimal brightness:** Ensures facial features are clearly distinguishable without over-exposure")
+                    st.markdown("* **Proper sizing:** Maintains ideal dimensions for detection algorithms to recognize facial landmarks")
+                    
+                    # Impact on emotion detection
+                    st.markdown("**Impact on Emotion Detection:**")
+                    st.markdown("* **More accurate emotion classification:** Cleaner input images lead to more reliable emotion detection")
+                    st.markdown("* **Better feature extraction:** Facial features like eyes, mouth, and eyebrows are more clearly defined")
+                    st.markdown("* **Reduced noise and artifacts:** Minimizes false detections and improves confidence scores")
+                else:
+                    # Show explanation about potential challenges with original images
+                    st.markdown("## Potential challenges with original images")
+                    
+                    # Technical explanation
+                    st.markdown("**Common issues with unprocessed images:**")
+                    st.markdown("* **Variable lighting conditions:** Original images may have shadows or highlights that obscure facial features")
+                    st.markdown("* **Inconsistent contrast:** Low contrast can make facial features harder to detect accurately")
+                    st.markdown("* **Background noise:** Unprocessed images often contain visual elements that can distract detection algorithms")
+                    
+                    # Impact on detection
+                    st.markdown("**Potential impact on detection quality:**")
+                    st.markdown("* **Lower detection confidence:** Original images may result in less confident emotion classifications")
+                    st.markdown("* **Feature detection challenges:** Some facial features might be missed or misidentified")
+                    st.markdown("* **Increased false readings:** Environmental factors in the original image could lead to misinterpretations")
+                    
+                    # When to use original images
+                    st.markdown("**When to use original images:**")
+                    st.markdown("* When the original lighting and contrast are already optimal")
+                    st.markdown("* When you want to analyze the image exactly as captured")
+                    st.markdown("* For comparison with processed results")
                 
             except Exception as e:
                 # Log detailed error information