如何修正jupyter笔记本中的错误:图像数据不能转换为浮点？

Question

我需要别人的帮助。

我还尝试了以下代码并得到了一个错误(这是关于pix2pix的，结果在本节中没有显示任何照片)：

import tensorflow as tf

import os
import time
import numpy as np
from matplotlib import pyplot as plt
from IPython import display

PATH = os.path.join('datasets/','facades/', 'train/')

BUFFER_SIZE = 400
BATCH_SIZE = 1
IMG_WIDTH = 256
IMG_HEIGHT = 256

inp, re = load(PATH+'train/100.jpg')

plt.figure()
plt.imshow(inp/255.0)
plt.figure()
plt.imshow(re/255.0)

这是错误

  TypeError                                 Traceback (most recent call last)
<ipython-input-16-0ddde1d49d08> in <module>
      2 
      3 plt.figure()
----> 4 plt.imshow(inp/255.0)
      5 plt.figure()
      6 plt.imshow(re/255.0)

C:\ProgramData\Anaconda3\envs\generative\lib\site-packages\matplotlib\pyplot.py in imshow(X, cmap, norm, aspect, interpolation, alpha, vmin, vmax, origin, extent, shape, filternorm, filterrad, imlim, resample, url, data, **kwargs)
   2699         filternorm=filternorm, filterrad=filterrad, imlim=imlim,
   2700         resample=resample, url=url, **({"data": data} if data is not
-> 2701         None else {}), **kwargs)
   2702     sci(__ret)
   2703     return __ret

C:\ProgramData\Anaconda3\envs\generative\lib\site-packages\matplotlib\__init__.py in inner(ax, data, *args, **kwargs)
   1808                         "the Matplotlib list!)" % (label_namer, func.__name__),
   1809                         RuntimeWarning, stacklevel=2)
-> 1810             return func(ax, *args, **kwargs)
   1811 
   1812         inner.__doc__ = _add_data_doc(inner.__doc__,

C:\ProgramData\Anaconda3\envs\generative\lib\site-packages\matplotlib\axes\_axes.py in imshow(self, X, cmap, norm, aspect, interpolation, alpha, vmin, vmax, origin, extent, shape, filternorm, filterrad, imlim, resample, url, **kwargs)
   5492                               resample=resample, **kwargs)
   5493 
-> 5494         im.set_data(X)
   5495         im.set_alpha(alpha)
   5496         if im.get_clip_path() is None:

C:\ProgramData\Anaconda3\envs\generative\lib\site-packages\matplotlib\image.py in set_data(self, A)
    640         if (self._A.dtype != np.uint8 and
    641                 not np.can_cast(self._A.dtype, float, "same_kind")):
--> 642             raise TypeError("Image data cannot be converted to float")
    643 
    644         if not (self._A.ndim == 2

TypeError: Image data cannot be converted to float

我也对path进行了尝试，但是得到了相同的错误

 _URL = 'https://people.eecs.berkeley.edu/~tinghuiz/projects/pix2pix/datasets/facades.tar.gz'

path_to_zip = tf.keras.utils.get_file('facades.tar.gz',
                                      origin=_URL,
                                      extract=True)

PATH = os.path.join(os.path.dirname(path_to_zip), 'facades/')

Answer 1

此错误通常意味着您没有正确读取图像中的内容。

我已经尝试过在Colab中执行pix2pix代码，并且成功地运行了。请您试一试下面的代码，并让我们知道您是否面临任何问题。

import tensorflow as tf
print(tf.__version__)
import os
import time
import numpy as np
from matplotlib import pyplot as plt
from IPython import display

_URL = 'https://people.eecs.berkeley.edu/~tinghuiz/projects/pix2pix/datasets/facades.tar.gz'

path_to_zip = tf.keras.utils.get_file('facades.tar.gz',
                                      origin=_URL,
                                      extract=True)

PATH = os.path.join(os.path.dirname(path_to_zip), 'facades/')

BUFFER_SIZE = 400
BATCH_SIZE = 1
IMG_WIDTH = 256
IMG_HEIGHT = 256

def load(image_file):
  image = tf.io.read_file(image_file)
  image = tf.image.decode_jpeg(image)

  w = tf.shape(image)[1]

  w = w // 2
  real_image = image[:, :w, :]
  input_image = image[:, w:, :]

  input_image = tf.cast(input_image, tf.float32)
  real_image = tf.cast(real_image, tf.float32)

  return input_image, real_image
  
inp, re = load(PATH+'train/100.jpg')

plt.figure()
plt.imshow(inp/255.0)
plt.figure()
plt.imshow(re/255.0)

只有在当前工作目录中有datasets时，才可以按下面的方式设置路径。

PATH = os.path.join('datasets/','facades/')
inp, re = load(PATH+'train/100.jpg')

或

PATH = os.path.join('datasets/','facades/', 'train/')
inp, re = load(PATH+'100.jpg')