new_contents: # Code given by Udacity, complete by Andres Guijarro
  # Define a function that takes an image, a color space,
  # and a new image size and returns a feature vector
  
  import cv2
  import matplotlib.pyplot as plt
  import matplotlib.image as mpimg
  
  # Read in an image
  # You can also read cutout2, 3, 4 etc. to see other examples
  image = mpimg.imread('cutout1.jpg')
  
  # Define a function to compute color histogram features
  # Pass the color_space flag as 3-letter all caps string
  # like 'HSV' or 'LUV' etc.
  
  
  def bin_spatial(img, color_space='RGB', size=(32, 32)):
      # Convert image to new color space (if specified)
      small_img = cv2.resize(img, size)
      # Use cv2.resize().ravel() to create the feature vector
      features = small_img.ravel()  # Remove this line!
      # Return the feature vector
      return features
  
  
  def main():
  
      feature_vec = bin_spatial(image, color_space='RGB', size=(32, 32))
  
      # Plot features
      plt.plot(feature_vec)
      plt.title('Spatially Binned Features')
      plt.show()
  
  if __name__ == '__main__':
      main()
  
subject: Add scripts which define a function that takes an image, a color space, and a new image size and returns a feature vector