Update app.py

app.py

@@ -171,33 +171,37 @@ def analyze_emotion_from_text(text):
 
 # Main function to process image and analyze emotional expression
 def analyze_emotion_from_image(image):
-    print(f"Color emotions: abc")
     try:
-        # Ensure the input image is a PIL image
         print(f"Initial input type: {type(image)}")
-        
-        # Check if the input is a URL (string)
-        if isinstance(image, str):
+
+        # Check if the input is a URL string
+        if isinstance(image, str) and image.startswith('http'):
             print(f"Loading image from URL: {image}")
             response = requests.get(image, stream=True)
             response.raise_for_status()  # Raise an error for bad responses
-            image = Image.open(response.raw).convert("RGB")  # Convert to RGB
+            image = Image.open(BytesIO(response.content)).convert("RGB")  # Load from URL response content
             print("Loaded image from URL.")
         
-        # Check if the input is a dictionary (for blob data)
+        # Check if the input is a local file path string
+        elif isinstance(image, str):
+            print(f"Loading image from file path: {image}")
+            image = Image.open(image).convert("RGB")  # Load from file path
+            print("Loaded image from local file.")
+
+        # Check if the input is Blob data (file-like object)
         elif isinstance(image, dict) and "blob" in image:
             blob_data = image["blob"]
-            image = Image.open(blob_data).convert("RGB")  # Convert to RGB
+            image = Image.open(blob_data).convert("RGB")  # Load from Blob data
             print("Loaded image from Blob data.")
         
         # Check if the input is a NumPy array
         elif isinstance(image, np.ndarray):
-            image = Image.fromarray(image).convert("RGB")  # Convert to RGB
+            image = Image.fromarray(image).convert("RGB")  # Convert NumPy array to image
             print("Converted image from NumPy array.")
 
         print(f"Image size: {image.size}, mode: {image.mode}")
 
-        # Analyze colors
+        # Analyze colors (stubbed function)
         dominant_colors = analyze_colors(image)
         if dominant_colors is None:
             return "Error analyzing colors"
@@ -205,11 +209,11 @@ def analyze_emotion_from_image(image):
         color_emotions, stress_levels = color_emotion_analysis(dominant_colors)
         print(f"Color emotions: {color_emotions}, Stress levels: {stress_levels}")
 
-        # Analyze patterns
+        # Analyze patterns (stubbed function)
         pattern_analysis, pattern_stress = analyze_patterns(image)
         print(f"Pattern analysis: {pattern_analysis}, Pattern stress: {pattern_stress}")
 
-        # Compute overall result
+        # Compute overall result (stubbed function)
         overall_result = compute_overall_result(color_emotions, stress_levels, pattern_analysis, pattern_stress)
 
         return overall_result