Update model/model.py

model/model.py

@@ -5,14 +5,14 @@ import numpy as np
 import os
 import tensorflow as tf
 
-os.environ["KERAS_BACKEND"] = "tensorflow"
-model = keras.saving.load_model("hf://sensei-ml/Brain_Tumors_Classificator_CNN_Keras_Model")
+os.environ['KERAS_BACKEND'] = 'tensorflow'
+model = keras.saving.load_model('hf://sensei-ml/Brain_Tumors_Classificator_CNN_Keras_Model')
 
 
 def predict(image_path):
     image = Image.fromarray(image_path)
-    image = image.convert('L')
-    image = image.resize((150, 150))  # Resize to match your model's input size
+    image = image.convert('L')  # Use grayscale images
+    image = image.resize((150, 150))  # Resize to 150 x 150 px.
     img_array = np.array(image) / 255.0  # Normalize pixel values
     img_array = np.expand_dims(img_array, axis=0)  # Add batch dimension
     prediction = model.predict(img_array)