title: model.predict() returns classes and not probabilities
body: <p><strong>Hello!</strong></p>
  
  <p>I am using Keras for first time. 
  I trained and saved a model. <em>(as a json file and its weights too)</em>
  The model it is intended to classify an image among 3 classes.
  My compile method :</p>
  
  <pre><code>model.compile(loss='categorical_crossentropy',
                optimizer='adam',
                metrics=['accuracy'])
  </code></pre>
  
  <p>After that, I load the model and its weights and i try to make a prediction for a random image</p>
  
  <pre><code># Predicting images
  img =image.load_img('/path/to/image/index.jpeg', target_size=(224, 224))
  x = image.img_to_array(img)
  #normilize the array output
  x *= (255.0/x.max())
  image = np.expand_dims(x, axis = 0)
  image = preprocess(image)
  preds = loaded_model.predict(image,)
  pred_classes = np.argmax(preds)
  print(preds)
  print(pred_classes)
  </code></pre>
  
  <p>How to i get a list with the probabilities? 
  For example <code>[75% 15% 10%]</code>
  Currently i get as an output </p>
  
  <pre><code>[[5.571262e-21 0.000000e+00 1.000000e+00]]
  2
  </code></pre>
  
  <p>This is the model summary <code>print(loaded_model.summary())</code>
  Model successfully loaded from disk! </p>
  
  <pre><code>_________________________________________________________________
  Layer (type)                 Output Shape              Param #  
  =================================================================
  conv2d_1 (Conv2D)            (None, 222, 222, 64)      1792      
  _________________________________________________________________
  activation_1 (Activation)    (None, 222, 222, 64)      0        
  _________________________________________________________________
  max_pooling2d_1 (MaxPooling2 (None, 111, 111, 64)      0        
  _________________________________________________________________
  conv2d_2 (Conv2D)            (None, 109, 109, 64)      36928    
  _________________________________________________________________
  activation_2 (Activation)    (None, 109, 109, 64)      0        
  _________________________________________________________________
  max_pooling2d_2 (MaxPooling2 (None, 54, 54, 64)        0        
  _________________________________________________________________
  conv2d_3 (Conv2D)            (None, 52, 52, 128)       73856    
  _________________________________________________________________
  activation_3 (Activation)    (None, 52, 52, 128)       0        
  _________________________________________________________________
  max_pooling2d_3 (MaxPooling2 (None, 26, 26, 128)       0        
  _________________________________________________________________
  conv2d_4 (Conv2D)            (None, 24, 24, 256)       295168    
  _________________________________________________________________
  activation_4 (Activation)    (None, 24, 24, 256)       0        
  _________________________________________________________________
  max_pooling2d_4 (MaxPooling2 (None, 12, 12, 256)       0        
  _________________________________________________________________
  conv2d_5 (Conv2D)            (None, 10, 10, 512)       1180160  
  _________________________________________________________________
  activation_5 (Activation)    (None, 10, 10, 512)       0        
  _________________________________________________________________
  max_pooling2d_5 (MaxPooling2 (None, 5, 5, 512)         0        
  _________________________________________________________________
  flatten_1 (Flatten)          (None, 12800)             0        
  _________________________________________________________________
  dense_1 (Dense)              (None, 512)               6554112  
  _________________________________________________________________
  activation_6 (Activation)    (None, 512)               0        
  _________________________________________________________________
  dropout_1 (Dropout)          (None, 512)               0        
  _________________________________________________________________
  dense_2 (Dense)              (None, 3)                 1539      
  _________________________________________________________________
  activation_7 (Activation)    (None, 3)                 0        
  =================================================================
  Total params: 8,143,555
  Trainable params: 8,143,555
  Non-trainable params: 0
  </code></pre>