Updated line 25 with: preprocess_image function -> Validates whether image is a PIL image -> if not then it converts the image utilizing Image.fromarray

app.py

@@ -23,10 +23,11 @@ preprocess = T.Compose([
 
 # Function to preprocess the image
 def preprocess_image(img_pil):
-    img_pil = img_pil.convert('RGB') # Convert to RGB if necessary
-    img_tensor = preprocess(img_pil) 
-    img_tensor = img_tensor.unsqueeze(0) # Add batch dimension
-    return img_tensor
+    # Ensure img_pil is a PIL Image object
+    if not isinstance(img_pil, Image.Image):
+        img_pil = Image.fromarray(img_pil)  # Convert NumPy array to PIL Image
+    inputs = feature_extractor(images=img_pil, return_tensors="pt")
+    return inputs
 
 # Function to predict the class of the image
 def predict_classification(img_pil):