title: How to handle RGB images in Keras
body: <p>I'm trying to train a simple neural net with manually-curated dataset of images and associated labels.</p>
  
  <p>I've created a numpy to create the labels called facey_label.</p>
  
  <p>I've used matplotlib's imread function to turn each of 811 images into an array of shape (255, 255, 3) and then planned to use the np.array function to create a tensor img_array of shape (811, 255, 255, 3) </p>
  
  <pre><code>model = keras.Sequential([
      keras.layers.Flatten(input_shape=(811, 255, 255, 3)),
      keras.layers.Dense(128, activation=tf.nn.relu),
      keras.layers.Dense(10, activation=tf.nn.softmax)
  ])
  model.compile(optimizer='adam', 
                loss='sparse_categorical_crossentropy',
                metrics=['accuracy'])
  model.fit(img_array, facey_label, epochs=5)
  </code></pre>
  
  <p>However, I receive the error:</p>
  
  <pre><code>ValueError: Error when checking input: expected flatten_1_input to have 5 dimensions, but got array with shape (811, 250, 250, 3)
  </code></pre>
  
  <p>What have I got wrong?</p>