Update app.py

app.py

@@ -11,7 +11,7 @@ from PIL import Image
 # Function to extract features from the image
 def extract_features(image):
     # Convert PIL image to NumPy array
-    image = np.array(image)
+    image = np.array(image) 
 
     # Extract RGB means
     meanr = np.mean(image[:, :, 0])  # Red channel
@@ -73,11 +73,11 @@ def extract_features(image):
     }
 
 # Function to check if the image is a valid file format
-def check_image_format(image):
+def check_image_format(filepath):
     try:
         # Try opening the image using PIL
-        img = Image.open(image)
-        img.verify()  # Verify if it's a valid image file
+        with Image.open(filepath) as img:
+            img.verify()  # Verify if it's a valid image file
         return True
     except Exception as e:
         print(f"Error opening image: {e}")
@@ -87,14 +87,14 @@ def check_image_format(image):
 def predict_hemoglobin(age, gender, image):
     try:
         # Check if the image file is valid
-        if not check_image_format(image):
+        if not check_image_format(image.name):
             return "Error: The uploaded image file is not recognized or is corrupt. Please upload an image in JPG, PNG, BMP, or GIF format."
 
         # Extract features from the image
         features = extract_features(image)
 
         # Ensure gender is encoded correctly (0 for female, 1 for male)
-        features['Gender'] = 1 if gender.lower() == 'M' else 0
+        features['Gender'] = 1 if gender.lower() == 'male' else 0
         features['Age'] = age
 
         # Create a DataFrame for features (do not include Hgb, as it's the predicted value)