如何刪除CMD指令，以便可以在IDE控制台（Python）中運行程序？

Question

我有一個代碼（如下），僅當它從CMD執行時才運行。 我需要對其進行修改，並且它必須在IDE控制台（Eclipse）中運行。

當我嘗試在Eclipse中執行此操作時，出現以下錯誤：

Traceback (most recent call last):
  File "C:\Users\User\workspace\TF\TF\predict_2.py", line 138, in <module>
    main(sys.argv[1])
IndexError: list index out of range

需要做什么？

我正在閱讀有關__main__和sys.argv但我不太了解...

"""Predict a handwritten integer (MNIST expert).

Script requires
1) saved model (model2.ckpt file) in the same location as the script is run from.
(requried a model created in the MNIST expert tutorial)
2) one argument (png file location of a handwritten integer)

Documentation at:
http://niektemme.com/ @@to do
"""

#import modules
import sys
import tensorflow as tf
from PIL import Image, ImageFilter
import os
from datetime import datetime

def predictint(imvalue):
    """
    This function returns the predicted integer.
    The input 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]))

    def weight_variable(shape):
      initial = tf.truncated_normal(shape, stddev=0.1)
      return tf.Variable(initial)

    def bias_variable(shape):
      initial = tf.constant(0.1, shape=shape)
      return tf.Variable(initial)

    def conv2d(x, W):
      return tf.nn.conv2d(x, W, strides=[1, 1, 1, 1], padding='SAME')

    def max_pool_2x2(x):
      return tf.nn.max_pool(x, ksize=[1, 2, 2, 1], strides=[1, 2, 2, 1], padding='SAME')   

    W_conv1 = weight_variable([5, 5, 1, 32])
    b_conv1 = bias_variable([32])

    x_image = tf.reshape(x, [-1,28,28,1])
    h_conv1 = tf.nn.relu(conv2d(x_image, W_conv1) + b_conv1)
    h_pool1 = max_pool_2x2(h_conv1)

    W_conv2 = weight_variable([5, 5, 32, 64])
    b_conv2 = bias_variable([64])

    h_conv2 = tf.nn.relu(conv2d(h_pool1, W_conv2) + b_conv2)
    h_pool2 = max_pool_2x2(h_conv2)

    W_fc1 = weight_variable([7 * 7 * 64, 1024])
    b_fc1 = bias_variable([1024])

    h_pool2_flat = tf.reshape(h_pool2, [-1, 7*7*64])
    h_fc1 = tf.nn.relu(tf.matmul(h_pool2_flat, W_fc1) + b_fc1)

    keep_prob = tf.placeholder(tf.float32)
    h_fc1_drop = tf.nn.dropout(h_fc1, keep_prob)

    W_fc2 = weight_variable([1024, 10])
    b_fc2 = bias_variable([10])

    y_conv=tf.nn.softmax(tf.matmul(h_fc1_drop, W_fc2) + b_fc2)

    init_op = tf.initialize_all_variables()
    saver = tf.train.Saver()

    """
    Load the model2.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)
        saver.restore(sess, "model2.ckpt")
        #print ("Model restored.")

        prediction=tf.argmax(y_conv,1)

        return prediction.eval(feed_dict={x: [imvalue],keep_prob: 1.0}, session=sess)

def imageprepare(argv):
    """
    This function returns the pixel values.
    The input 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 (nheight == 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])

Answer 1

就像@JCooke所說的那樣，必須通過刪除/插入“其他”在main(sys.argv[1])修改代碼。

就我而言，我必須在IDE控制台中查看圖像的處理。 在CMD中，我必須提出一個論點，該論點必須是圖像本身的路徑。 在代碼中，我使用圖像的路徑更改了sys.argv[1] 。