tensorflow版cycleganでエラーが出て困っています。

前提・実現したいこと

tensorflow版cycleganで声質変換を行うAIを作ろうとしているのですが、以下のエラーコードが出て行き詰っています。

発生している問題・エラーメッセージ

 [*] Reading checkpoint...
 [!] Load failed...
Processing image: ./datasets/voice/testA\at.jpg
Traceback (most recent call last):
  File "main.py", line 53, in <module>
    tf.app.run()
  File "C:\Users\mounf\Anaconda3\envs\cycleganvoicechangerproject\lib\site-packages\tensorflow\python\platform\app.py", line 126, in run
    _sys.exit(main(argv))
  File "main.py", line 50, in main
    else model.test(args)
  File "C:\Users\mounf\PycharmProjects\nets\model.py", line 252, in test
    sample_image = [load_test_data(sample_file, args.fine_size)]
  File "C:\Users\mounf\PycharmProjects\nets\utils.py", line 46, in load_test_data
    img = imread(image_path)
  File "C:\Users\mounf\PycharmProjects\nets\utils.py", line 88, in imread
    return _imread(path, mode='RGB').astype(np.float)
  File "C:\Users\mounf\Anaconda3\envs\cycleganvoicechangerproject\lib\site-packages\imageio\core\functions.py", line 260, in imread
    'Invalid keyword argument "mode", ' 'perhaps you mean "pilmode"?'
TypeError: Invalid keyword argument "mode", perhaps you mean "pilmode"?

該当のソースコード

python
1♯utils.py
2from __future__ import division
3import math
4import pprint
5import scipy.misc
6import numpy as np
7import copy
8try:
9    _imread = scipy.misc.imread
10except AttributeError:
11    from imageio import imread as _imread
12
13pp = pprint.PrettyPrinter()
14
15get_stddev = lambda x, k_h, k_w: 1/math.sqrt(k_w*k_h*x.get_shape()[-1])
16
17♯new added functions for cyclegan
18class ImagePool(object):
19    def __init__(self, maxsize=50):
20        self.maxsize = maxsize
21        self.num_img = 0
22        self.images = []
23
24    def __call__(self, image):
25        if self.maxsize <= 0:
26            return image
27        if self.num_img < self.maxsize:
28            self.images.append(image)
29            self.num_img += 1
30            return image
31        if np.random.rand() > 0.5:
32            idx = int(np.random.rand()*self.maxsize)
33            tmp1 = copy.copy(self.images[idx])[0]
34            self.images[idx][0] = image[0]
35            idx = int(np.random.rand()*self.maxsize)
36            tmp2 = copy.copy(self.images[idx])[1]
37            self.images[idx][1] = image[1]
38            return [tmp1, tmp2]
39        else:
40            return image
41
42def load_test_data(image_path, fine_size=256):
43    img = imread(image_path)
44    img = scipy.misc.imresize(img, [fine_size, fine_size])
45    img = img/127.5 - 1
46    return img
47
48def load_train_data(image_path, load_size=286, fine_size=256, is_testing=False):
49    img_A = imread(image_path[0])
50    img_B = imread(image_path[1])
51    if not is_testing:
52        img_A = scipy.misc.imresize(img_A, [load_size, load_size])
53        img_B = scipy.misc.imresize(img_B, [load_size, load_size])
54        h1 = int(np.ceil(np.random.uniform(1e-2, load_size-fine_size)))
55        w1 = int(np.ceil(np.random.uniform(1e-2, load_size-fine_size)))
56        img_A = img_A[h1:h1+fine_size, w1:w1+fine_size]
57        img_B = img_B[h1:h1+fine_size, w1:w1+fine_size]
58
59        if np.random.random() > 0.5:
60            img_A = np.fliplr(img_A)
61            img_B = np.fliplr(img_B)
62    else:
63        img_A = scipy.misc.imresize(img_A, [fine_size, fine_size])
64        img_B = scipy.misc.imresize(img_B, [fine_size, fine_size])
65
66    img_A = img_A/127.5 - 1.
67    img_B = img_B/127.5 - 1.
68
69    img_AB = np.concatenate((img_A, img_B), axis=2)
70    # img_AB shape: (fine_size, fine_size, input_c_dim + output_c_dim)
71    return img_AB
72
73-----------------------------
74
75def get_image(image_path, image_size, is_crop=True, resize_w=64, is_grayscale = False):
76    return transform(imread(image_path, is_grayscale), image_size, is_crop, resize_w)
77
78def save_images(images, size, image_path):
79    return imsave(inverse_transform(images), size, image_path)
80
81def imread(path, is_grayscale = False):
82    if (is_grayscale):
83        return _imread(path, flatten=True).astype(np.float)
84    else:
85        return _imread(path, mode='RGB').astype(np.float)
86
87def merge_images(images, size):
88    return inverse_transform(images)
89
90def merge(images, size):
91    h, w = images.shape[1], images.shape[2]
92    img = np.zeros((h * size[0], w * size[1], 3))
93    for idx, image in enumerate(images):
94        i = idx % size[1]
95        j = idx // size[1]
96        img[j*h:j*h+h, i*w:i*w+w, :] = image
97
98    return img
99
100def imsave(images, size, path):
101    return scipy.misc.imsave(path, merge(images, size))
102
103def center_crop(x, crop_h, crop_w,
104                resize_h=64, resize_w=64):
105  if crop_w is None:
106    crop_w = crop_h
107  h, w = x.shape[:2]
108  j = int(round((h - crop_h)/2.))
109  i = int(round((w - crop_w)/2.))
110  return scipy.misc.imresize(
111      x[j:j+crop_h, i:i+crop_w], [resize_h, resize_w])
112
113def transform(image, npx=64, is_crop=True, resize_w=64):
114    # npx : # of pixels width/height of image
115    if is_crop:
116        cropped_image = center_crop(image, npx, resize_w=resize_w)
117    else:
118        cropped_image = image
119    return np.array(cropped_image)/127.5 - 1.
120
121def inverse_transform(images):
122    return (images+1.)/2.
123
124
125♯---ここからfunction.py
126♯Images
127
128
129def imread(uri, format=None, **kwargs):
130    """ imread(uri, format=None, **kwargs)
131
132    Reads an image from the specified file. Returns a numpy array, which
133    comes with a dict of meta data at its 'meta' attribute.
134
135    Note that the image data is returned as-is, and may not always have
136    a dtype of uint8 (and thus may differ from what e.g. PIL returns).
137
138    Parameters
139    ♯----------
140    uri : {str, pathlib.Path, bytes, file}
141        The resource to load the image from, e.g. a filename, pathlib.Path,
142        http address or file object, see the docs for more info.
143    format : str
144        The format to use to read the file. By default imageio selects
145        the appropriate for you based on the filename and its contents.
146    kwargs : ...
147        Further keyword arguments are passed to the reader. See :func:`.help`
148        to see what arguments are available for a particular format.
149    """
150
151    if "mode" in kwargs:
152        raise TypeError(
153            'Invalid keyword argument "mode", ' 'perhaps you mean "pilmode"?'
154        )
155
156    ♯Get reader and read first
157    reader = read(uri, format, "i", **kwargs)
158    with reader:
159        return reader.get_data(0)
160
161### 試したこと
162
163ネットで調べましたが、情報が少なく、有効な解決手段が見つかりませんでした。
164### 補足情報（FW/ツールのバージョンなど）
165現在使っている環境です。
166absl-py==0.8.1
167astor==0.8.0
168bleach==1.5.0
169certifi==2019.9.11
170gast==0.3.2
171grpcio==1.24.1
172html5lib==0.9999999
173imageio==2.6.1
174Markdown==3.1.1
175numpy==1.17.3
176Pillow==6.2.0
177protobuf==3.10.0
178scipy==1.3.1
179six==1.12.0
180tensorboard==1.8.0
181tensorflow-gpu==1.8.0
182termcolor==1.1.0
183Werkzeug==0.16.0
184wincertstore==0.2

ryuii

2019/10/19 01:45 編集

imageio.imreadのソースコード部分でエラーが出ているよう思われるので、このエラーログでは、imageio.imreadの第3引数の配列に、"mode"が含まれていてエラーが出ているとしか判断ができません。imageio.imread付近のエラーログとソースコードかあると解決につながりやすくなりますので、差し支えない範囲で、記載できますでしょうか。解釈が間違えていたら、おっしゃってください。