«Ошибка OSE: невозможно идентифицировать файл изображения» не может быть решена

Question

Я новичок в углубленном изучении.Я работаю над двумя ноутбуками Jupyter.С одним из них работает код, а другой выдает сообщение об ошибке.Может быть, кто-то может мне помочь.

Я уже попробовал все решения, показанные здесь.К сожалению, ни одно решение не решило мою проблему.

from PIL import Image
import os
import tensorflow as tf
config = tf.ConfigProto()
config.gpu_options.allow_growth = True
sess = tf.Session(config=config)
import keras
keras.__version__

import os
import numpy as np
from keras.preprocessing.image import ImageDataGenerator

base_dir = 'path'

train_dir = os.path.join(base_dir, 'train')
validation_dir = os.path.join(base_dir, 'validation')
test_dir = os.path.join(base_dir, 'test')

datagen = ImageDataGenerator(rescale=1./255)
batch_size = 20

def extract_features(directory, sample_count):
    features = np.zeros(shape=(sample_count, 7, 7, 1280))
    labels = np.zeros(shape=(sample_count))
    generator = datagen.flow_from_directory(
        directory,
        target_size=(224, 224),
        batch_size=batch_size,
        class_mode='binary')
    i = 0
    for inputs_batch, labels_batch in generator:
        features_batch = conv_base.predict(inputs_batch)
        features[i * batch_size : (i + 1) * batch_size] = features_batch
        labels[i * batch_size : (i + 1) * batch_size] = labels_batch
        i += 1
        if i * batch_size >= sample_count:
            # Note that since generators yield data indefinitely in a loop,
            # we must `break` after every image has been seen once.
            break
    return features, labels

train_features, train_labels = extract_features(train_dir, 2000)
validation_features, validation_labels = extract_features(validation_dir, 1000)
test_features, test_labels = extract_features(test_dir, 1000)

Локально код выполняется нормально.На работе я получаю следующее сообщение об ошибке.

---------------------------------------------------------------------------
OSError                                   Traceback (most recent call last)
<ipython-input-9-e489372cb3cc> in <module>()
----> 1 train_features, train_labels = extract_features(train_dir, 2000)
      2 validation_features, validation_labels = extract_features(validation_dir, 1000)
      3 test_features, test_labels = extract_features(test_dir, 1000)

<ipython-input-8-12cf5e6b2065> in extract_features(directory, sample_count)
     22         class_mode='binary')
     23     i = 0
---> 24     for inputs_batch, labels_batch in generator:
     25         features_batch = conv_base.predict(inputs_batch)
     26         features[i * batch_size : (i + 1) * batch_size] = features_batch

/usr/local/lib/python3.5/dist-packages/keras_preprocessing/image/iterator.py in __next__(self, *args, **kwargs)
     98 
     99     def __next__(self, *args, **kwargs):
--> 100         return self.next(*args, **kwargs)
    101 
    102     def next(self):

/usr/local/lib/python3.5/dist-packages/keras_preprocessing/image/iterator.py in next(self)
    110         # The transformation of images is not under thread lock
    111         # so it can be done in parallel
--> 112         return self._get_batches_of_transformed_samples(index_array)
    113 
    114     def _get_batches_of_transformed_samples(self, index_array):

/usr/local/lib/python3.5/dist-packages/keras_preprocessing/image/iterator.py in _get_batches_of_transformed_samples(self, index_array)
    224                            color_mode=self.color_mode,
    225                            target_size=self.target_size,
--> 226                            interpolation=self.interpolation)
    227             x = img_to_array(img, data_format=self.data_format)
    228             # Pillow images should be closed after `load_img`,

/usr/local/lib/python3.5/dist-packages/keras_preprocessing/image/utils.py in load_img(path, grayscale, color_mode, target_size, interpolation)
    102         raise ImportError('Could not import PIL.Image. '
    103                           'The use of `array_to_img` requires PIL.')
--> 104     img = pil_image.open(path)
    105     if color_mode == 'grayscale':
    106         if img.mode != 'L':

~/.local/lib/python3.5/site-packages/PIL/Image.py in open(fp, mode)
   2685         warnings.warn(message)
   2686     raise IOError("cannot identify image file %r"
-> 2687                   % (filename if filename else fp))
   2688 
   2689 #

OSError: cannot identify image file 'somepath'