SegNetプログラムの実行

前提・実現したいこと

こちらのサイトに掲載されているSegNetのプログラムを拝借して実行したところ、datasetプログラムで下記のようなエラーが発生するようになってしまいました。
これはTensorFlowがインポートできていないということなのでしょうか？原因がわからないので、解決策を教えていただきたいです。

発生している問題・エラーメッセージ

runfile('C:/Users/ユーザ名/.spyder-py3/dataset.py', wdir='C:/Users/t.k/.spyder-py3')
Using TensorFlow backend.
Traceback (most recent call last):

  File "<ipython-input-6-ef8e060fac88>", line 1, in <module>
    runfile('C:/Users/ユーザ名/.spyder-py3/dataset.py', wdir='C:/Users/t.k/.spyder-py3')

  File "C:\Users\ユーザ名\Anaconda3\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 668, in runfile
    execfile(filename, namespace)

  File "C:\Users\ユーザ名\Anaconda3\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 108, in execfile
    exec(compile(f.read(), filename, 'exec'), namespace)

  File "C:/Users/ユーザ名/.spyder-py3/dataset.py", line 11, in <module>
    from keras.applications import imagenet_utils

  File "C:\Users\ユーザ名\Anaconda3\lib\site-packages\keras\__init__.py", line 3, in <module>
    from . import utils

  File "C:\Users\ユーザ名\Anaconda3\lib\site-packages\keras\utils\__init__.py", line 6, in <module>
    from . import conv_utils

  File "C:\Users\ユーザ名\Anaconda3\lib\site-packages\keras\utils\conv_utils.py", line 9, in <module>
    from .. import backend as K

  File "C:\Users\ユーザ名\Anaconda3\lib\site-packages\keras\backend\__init__.py", line 89, in <module>
    from .tensorflow_backend import *

  File "C:\Users\ユーザ名\Anaconda3\lib\site-packages\keras\backend\tensorflow_backend.py", line 5, in <module>
    import tensorflow as tf

  File "C:\Users\ユーザ名\Anaconda3\lib\site-packages\tensorflow\__init__.py", line 24, in <module>
    from tensorflow.python import pywrap_tensorflow  # pylint: disable=unused-import

  File "C:\Users\ユーザ名\Anaconda3\lib\site-packages\tensorflow\python\__init__.py", line 49, in <module>
    from tensorflow.python import pywrap_tensorflow

  File "C:\Users\ユーザ名\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 74, in <module>
    raise ImportError(msg)

ImportError: Traceback (most recent call last):
  File "C:\Users\ユーザ名\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 58, in <module>
    from tensorflow.python.pywrap_tensorflow_internal import *
  File "C:\Users\ユーザ名\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 28, in <module>
    _pywrap_tensorflow_internal = swig_import_helper()
  File "C:\Users\ユーザ名\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 24, in swig_import_helper
    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
  File "C:\Users\ユーザ名\Anaconda3\lib\imp.py", line 243, in load_module
    return load_dynamic(name, filename, file)
  File "C:\Users\ユーザ名\Anaconda3\lib\imp.py", line 343, in load_dynamic
    return _load(spec)
ImportError: DLL load failed: 指定されたモジュールが見つかりません。


Failed to load the native TensorFlow runtime.

See https://www.tensorflow.org/install/install_sources#common_installation_problems

for some common reasons and solutions.  Include the entire stack trace
above this error message when asking for help.

該当のソースコード

# -*- coding: utf-8 -*-

import cv2
import numpy as np

from keras.applications import imagenet_utils

import os

DataPath = './CamVid/'
data_shape = 360*480

class Dataset:
    def __init__(self, classes=12, train_file='train.txt', test_file='test.txt'):
        self.train_file = train_file
        self.test_file = test_file
        self.data_shape = 360*480
        self.classes = classes

    def normalized(self, rgb):
        #return rgb/255.0
        norm=np.zeros((rgb.shape[0], rgb.shape[1], 3),np.float32)

        b=rgb[:,:,0]
        g=rgb[:,:,1]
        r=rgb[:,:,2]

        norm[:,:,0]=cv2.equalizeHist(b)
        norm[:,:,1]=cv2.equalizeHist(g)
        norm[:,:,2]=cv2.equalizeHist(r)

        return norm

    def one_hot_it(self, labels):
        x = np.zeros([360,480,12])
        for i in range(360):
            for j in range(480):
                x[i,j,labels[i][j]] = 1
        return x

    def load_data(self, mode='train'):
        data = []
        label = []
        if (mode == 'train'):
            filename = self.train_file
        else:
            filename = self.test_file

        with open(DataPath + filename) as f:
            txt = f.readlines()
            txt = [line.split(' ') for line in txt]

        for i in range(len(txt)):
            data.append(self.normalized(cv2.imread(os.getcwd() + txt[i][0][7:])))
            label.append(self.one_hot_it(cv2.imread(os.getcwd() + txt[i][1][7:][:-1])[:,:,0]))
            print('.',end='')
        #print("train data file", os.getcwd() + txt[i][0][7:])
        #print("label data raw", cv2.imread(os.getcwd() + '/CamVid/trainannot/0001TP_006690.png'))
        return np.array(data), np.array(label)


    def preprocess_inputs(self, X):
    ### @ https://github.com/fchollet/keras/blob/master/keras/applications/imagenet_utils.py
        """Preprocesses a tensor encoding a batch of images.
        # Arguments
            x: input Numpy tensor, 4D.
            data_format: data format of the image tensor.
            mode: One of "caffe", "tf".
                - caffe: will convert the images from RGB to BGR,
                    then will zero-center each color channel with
                    respect to the ImageNet dataset,
                    without scaling.
                - tf: will scale pixels between -1 and 1,
                    sample-wise.
        # Returns
            Preprocessed tensor.
        """
        return imagenet_utils.preprocess_input(X)

    def reshape_labels(self, y):
        return np.reshape(y, (len(y), self.data_shape, self.classes))