Update model/model.py

model/model.py

@@ -12,7 +12,7 @@ def predict(image_path):
     image = image.convert('L')
     image = image.resize((150, 150))  # Resize to match your model's input size
     img_array = np.array(image) / 255.0  # Normalize pixel values
-    img_array = np.expand_dims(image_array, axis=0)  # Add batch dimension
+    img_array = np.expand_dims(img_array, axis=0)  # Add batch dimension
     prediction = model.predict(img_array)
     predicted_class_index = np.argmax(prediction)
     labels = ['Glioma', 'Meningioma', 'No tumor', 'Pituitary']