Update app.py

app.py

@@ -105,12 +105,53 @@ def analyze_patterns(image):
         num_edges = np.sum(edges > 0)
 
         if num_edges > 10000:  # Arbitrary threshold for "chaos"
-            return "Chaotic patterns - possibly distress"
+            return "Chaotic patterns - possibly distress", 0.8  # Assigning 0.8 stress for chaotic patterns
         else:
-            return "Orderly patterns - possibly calm"
+            return "Orderly patterns - possibly calm", 0.2  # Assigning 0.2 stress for calm patterns
     except Exception as e:
         print(f"Error in analyze_patterns: {e}")
-        return "Error analyzing patterns"
+        return "Error analyzing patterns", 0.5  # Assigning neutral weight for errors
+
+
+# Function to compute overall results by combining color and pattern analyses
+def compute_overall_result(color_emotions, stress_levels, pattern_analysis, pattern_stress):
+    try:
+        # Assigning weightage to different factors
+        color_emotion_weight = 0.7  # 70% for color-based emotions and stress
+        pattern_weight = 0.3  # 30% for pattern analysis
+
+        # Determine the most common emotion from colors
+        dominant_emotion = max(set(color_emotions), key=color_emotions.count)
+        
+        # Average stress level from color analysis (converting text stress levels to numeric)
+        stress_mapping = {
+            "No Stress": 0.1,
+            "Very Low Stress": 0.3,
+            "Low Stress": 0.5,
+            "Moderate Stress": 0.7,
+            "Moderate-High Stress": 0.9,
+        }
+        color_stress_numeric = [stress_mapping[stress] for stress in stress_levels if stress in stress_mapping]
+        avg_color_stress = np.mean(color_stress_numeric) if color_stress_numeric else 0.5  # Default to 0.5 if no valid data
+        
+        # Compute the overall stress by combining color stress and pattern stress
+        overall_stress = (avg_color_stress * color_emotion_weight) + (pattern_stress * pattern_weight)
+        
+        # Determine overall result based on combined factors
+        if overall_stress < 0.3:
+            overall_emotion = "Calm and Relaxed"
+        elif 0.3 <= overall_stress < 0.6:
+            overall_emotion = "Neutral Mood"
+        elif 0.6 <= overall_stress < 0.8:
+            overall_emotion = "Slightly Stressed"
+        else:
+            overall_emotion = "Highly Stressed"
+        
+        return f"Overall emotion: {overall_emotion} (Dominant Color Emotion: {dominant_emotion}, Pattern Analysis: {pattern_analysis})"
+    
+    except Exception as e:
+        return f"Error computing overall result: {str(e)}"
+
 
 # Main function to process image and analyze emotional expression
 def analyze_emotion_from_image(image):
@@ -127,9 +168,12 @@ def analyze_emotion_from_image(image):
         color_emotions, stress_levels = color_emotion_analysis(dominant_colors)
 
         # Analyze patterns
-        pattern_analysis = analyze_patterns(image)
+        pattern_analysis, pattern_stress = analyze_patterns(image)
+
+        # Compute overall result
+        overall_result = compute_overall_result(color_emotions, stress_levels, pattern_analysis, pattern_stress)
 
-        return f"Color-based emotions: {color_emotions}\nStress levels: {stress_levels}\nPattern analysis: {pattern_analysis}"
+        return overall_result
     except Exception as e:
         return f"Error processing image: {str(e)}"