Tensor 데이터 유형을 문자열로?

Question

나는 다음과 같은 Tensorflow 코드가 있습니다

import datetime 
import matplotlib.pyplot as plt 
import numpy as np 
import os 
from PIL import Image 
import tensorflow as tf 

image_width = 202 
image_height = 180 
num_channels = 3 

filenames = tf.train.match_filenames_once("./train/Resized/*.jpg") 

def label(label_string): 
    if label_string == 'cat': label = [1,0] 
    if label_string == 'dog': label = [0,1] 

    return label 

def read_image(filename_queue): 
    image_reader = tf.WholeFileReader() 
    key, image_filename = image_reader.read(filename_queue) 
    image = tf.image.decode_jpeg(image_filename) 
    image.set_shape((image_height, image_width, 3)) 

    name = os.path.basename(image_filename) # example "dog.2148.jpg" 
    s = name.split('.') 
    label_string = s[0] 
    label = label(label_string) 

    return image, label 

def input_pipeline(filenames, batch_size, num_epochs=None): 
    filename_queue = tf.train.string_input_producer(filenames, num_epochs=num_epochs, shuffle=True) 
    image, label = read_image(filename_queue) 
    min_after_dequeue = 1000 
    capacity = min_after_dequeue + 3 * batch_size 
    image_batch, label_batch = tf.train.shuffle_batch(
     [image, label], batch_size=batch_size, capacity=capacity, 
     min_after_dequeue=min_after_dequeue) 
    return image_batch, label_batch 

image_batch, label_batch = input_pipeline(filenames, 10) 

마지막 문은 다음과 같은 오류와 함께 실패합니다

--------------------------------------------------------------------------- 
TypeError         Traceback (most recent call last) 
<ipython-input-21-0224ec735c33> in <module>() 
----> 1 image_batch, label_batch = input_pipeline(filenames, 10) 

<ipython-input-20-277e29dc1ae3> in input_pipeline(filenames, batch_size, num_epochs) 
     1 def input_pipeline(filenames, batch_size, num_epochs=None): 
     2  filename_queue = tf.train.string_input_producer(filenames, num_epochs=num_epochs, shuffle=True) 
----> 3  image, label = read_image(filename_queue) 
     4  min_after_dequeue = 1000 
     5  capacity = min_after_dequeue + 3 * batch_size 

<ipython-input-19-ffe4ec8c3e25> in read_image(filename_queue) 
     5  image.set_shape((image_height, image_width, 3)) 
     6 
----> 7  name = os.path.basename(image_filename) # example "dog.2148.jpg" 
     8  s = name.split('.') 
     9  label_string = s[0] 

C:\local\Anaconda3-4.1.1-Windows-x86_64\envs\cntk-py35\lib\ntpath.py in basename(p) 
    230 def basename(p): 
    231  """Returns the final component of a pathname""" 
--> 232  return split(p)[1] 
    233 
    234 

C:\local\Anaconda3-4.1.1-Windows-x86_64\envs\cntk-py35\lib\ntpath.py in split(p) 
    202 
    203  seps = _get_bothseps(p) 
--> 204  d, p = splitdrive(p) 
    205  # set i to index beyond p's last slash 
    206  i = len(p) 

C:\local\Anaconda3-4.1.1-Windows-x86_64\envs\cntk-py35\lib\ntpath.py in splitdrive(p) 
    137 
    138  """ 
--> 139  if len(p) >= 2: 
    140   if isinstance(p, bytes): 
    141    sep = b'\\' 

TypeError: object of type 'Tensor' has no len() 

나는 문제가 문자열 데이터 타입 대 텐서 데이터 타입에 관한 생각을. 어떻게 os.path.basename 함수에 image_filename이 문자열인지 올바르게 표시 할 수 있습니까?

Answer 1

문제는 match_filenames_once가

A variable that is initialized to the list of files matching pattern.

를 반환한다는 것입니다 (여기 참조 : https://www.tensorflow.org/api_docs/python/tf/train/match_filenames_once을).

os.path.basename과 string.split은 텐셔르가 아닌 문자열에서 작동하는 함수입니다.

텐 토플 플로우 파이프 라인 외부로 이미지를로드하는 것이 좋습니다. 이렇게하면 쉽게 레이블링이 가능합니다.