Fixed errors

app.py

@@ -44,10 +44,10 @@ def predict(image):
     try:
         # The input image is already a 2D numpy array (grayscale)
         # Ensure it's the right size and normalize it
-        if image.shape != (28, 28):
-            pil_image = Image.fromarray(image.squeeze().astype('uint8'))
-            pil_image = pil_image.resize((28, 28))
-            image = np.array(pil_image)
+        
+        pil_image = Image.fromarray(image.squeeze().astype('uint8'))
+        pil_image = pil_image.resize((28, 28))
+        image = np.array(pil_image)
         
         # Convert to tensor and add batch and channel dimensions
         tensor_image = torch.tensor(image, dtype=torch.float32).unsqueeze(0).unsqueeze(0)