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
Any help is greatly appreciated. Thank for your reading!
#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 > 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])
 
     
     
    