title: sys.argv[1]) IndexError: list index out of range
body: <p>I just begin to learn about python. When I execute the code below, I get an error. It tells that 
  Traceback (most recent call last):
    File "predict_1.py", line 87, in 
      main(sys.argv[1])
  IndexError: list index out of range</p>
  
  <p>Any help is greatly appreciated. Thank for your reading!</p>
  
  <pre><code>#import modules
  import sys
  import tensorflow as tf
  from PIL import Image,ImageFilter
  
  def predictint(imvalue):
    """
    This function returns the predicted integer.
    The imput is the pixel values from the imageprepare() function.
    """
  
    # Define the model (same as when creating the model file)
    x = tf.placeholder(tf.float32, [None, 784])
    W = tf.Variable(tf.zeros([784, 10]))
    b = tf.Variable(tf.zeros([10]))
    y = tf.nn.softmax(tf.matmul(x, W) + b)
  
    init_op = tf.initialize_all_variables()
    saver = tf.train.Saver()
  
    """
    Load the model.ckpt file
    file is stored in the same directory as this python script is started
    Use the model to predict the integer. Integer is returend as list.
  
    Based on the documentatoin at
    https://www.tensorflow.org/versions/master/how_tos/variables/index.html
    """
    with tf.Session() as sess:
        sess.run(init_op)
        new_saver = tf.train.import_meta_graph('model.ckpt.meta')
    new_saver.restore(sess, "model.ckpt")
        #print ("Model restored.")
  
        prediction=tf.argmax(y,1)
        return prediction.eval(feed_dict={x: [imvalue]}, session=sess)
  
  
  def imageprepare(argv):
    """
    This function returns the pixel values.
    The imput is a png file location.
    """
    im = Image.open(argv).convert('L')
    width = float(im.size[0])
    height = float(im.size[1])
    newImage = Image.new('L', (28, 28), (255)) #creates white canvas of 28x28 pixels
  
    if width &gt; height: #check which dimension is bigger
        #Width is bigger. Width becomes 20 pixels.
        nheight = int(round((20.0/width*height),0)) #resize height according to ratio width
        if (nheigth == 0): #rare case but minimum is 1 pixel
            nheigth = 1  
        # resize and sharpen
        img = im.resize((20,nheight), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)
        wtop = int(round(((28 - nheight)/2),0)) #caculate horizontal pozition
        newImage.paste(img, (4, wtop)) #paste resized image on white canvas
    else:
        #Height is bigger. Heigth becomes 20 pixels. 
        nwidth = int(round((20.0/height*width),0)) #resize width according to ratio height
        if (nwidth == 0): #rare case but minimum is 1 pixel
            nwidth = 1
         # resize and sharpen
        img = im.resize((nwidth,20), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)
        wleft = int(round(((28 - nwidth)/2),0)) #caculate vertical pozition
        newImage.paste(img, (wleft, 4)) #paste resized image on white canvas
  
    #newImage.save("sample.png")
  
    tv = list(newImage.getdata()) #get pixel values
  
    #normalize pixels to 0 and 1. 0 is pure white, 1 is pure black.
    tva = [ (255-x)*1.0/255.0 for x in tv] 
    return tva
    #print(tva)
  
  def main(argv):
    """
    Main function.
    """
    imvalue = imageprepare(argv)
    predint = predictint(imvalue)
    print (predint[0]) #first value in list
  
    if __name__ == "__main__":
    main(sys.argv[1])
  </code></pre>