title: CNN Image Classification: It gives me always the same prediction
body: <p>I'm new on this field, still learning and I'm sorry if it is considered as silly questions.
  So recently I tried to learn image classification using Python and TensorFlow. I followed tutorial on some videos. But I have some problems in my code, because when I tried my model, the validation loss tends to increase, while my validation accuracy keeps fluctuating. When I tried to predict my sample image, it keeps giving me the same prediction. My images in my datasets are 730 images in total.</p>
  
  <p>And here is my code for making the prediction:</p>
  
  <pre><code>import cv2
  import tensorflow as tf
  
  CATEGORIES = ["Bike", "Car"]
  IMAGE_SIZE = 50
  
  def prepare(filepath):
      image_array = cv2.imread(filepath, cv2.IMREAD_GRAYSCALE)
      image_array = image_array/255.0
      new_image_array = cv2.resize(image_array, (IMAGE_SIZE,IMAGE_SIZE))
      return new_image_array.reshape(-1, IMAGE_SIZE, IMAGE_SIZE, 1)
  
  model = tf.keras.models.load_model("prototype.model")
  
  prediction = model.predict([prepare('car.jpg')])
  print( CATEGORIES[int(prediction[0][0])] )
  </code></pre>
  
  <p>Thank you so much.</p>