Update app.py

app.py

@@ -173,10 +173,15 @@ def analyze_emotion_from_text(text):
 def analyze_emotion_from_image(image):
     try:
         # Ensure the input image is a PIL image
+        print(f"Initial input type: {type(image)}")
         if isinstance(image, dict) and "path" in image:
-            image = Image.open(requests.get(image["path"], stream=True).raw)  # Load image from URL
+            image = Image.open(requests.get(image["path"], stream=True).raw)
+            print("Loaded image from URL.")
         elif isinstance(image, np.ndarray):
-            image = Image.fromarray(image)  # Convert to PIL Image if it's a NumPy array
+            image = Image.fromarray(image)
+            print("Converted image from NumPy array.")
+
+        print(f"Image size: {image.size}, mode: {image.mode}")
 
         # Analyze colors
         dominant_colors = analyze_colors(image)
@@ -184,20 +189,24 @@ def analyze_emotion_from_image(image):
             return "Error analyzing colors"
         
         color_emotions, stress_levels = color_emotion_analysis(dominant_colors)
+        print(f"Color emotions: {color_emotions}, Stress levels: {stress_levels}")
 
         # Analyze patterns
         pattern_analysis, pattern_stress = analyze_patterns(image)
+        print(f"Pattern analysis: {pattern_analysis}, Pattern stress: {pattern_stress}")
 
         # Compute overall result
         overall_result = compute_overall_result(color_emotions, stress_levels, pattern_analysis, pattern_stress)
 
         return overall_result
     except Exception as e:
+        print(f"Error processing image: {str(e)}")
         return f"Error processing image: {str(e)}"
 
 
 
 
+
 # Gradio interface to upload image files and perform analysis
 iface = gr.Interface(fn=analyze_emotion_from_image, inputs="image", outputs="text")