Question

在加载图像时，我试图通过在pyplot中将其打印出来，以确保正确加载了图像，但是我遇到了问题。如何将这些图像加载到Tensorflow中，并使用pyplot的imshow()（或其他方式）进行检查？

图像数据是单通道（黑白）jpeg。最初将其加载为具有未知形状和uint8 dtype的Tensor。我已经尝试确保将Tensor重塑为正确的形状并将其铸造为float32。我还尝试确保将值从0.0-1.0缩放为浮点数，并使用imshow()函数中的Gray映射。

import tensorflow as tf
import matplotlib.pyplot as plt

def load_and_preprocess_jpeg(imagepath):
    img = tf.read_file(imagepath)
    img_tensor = tf.image.decode_jpeg(img)
    img_tensor.set_shape([792,1224,1])
    img_tensor = tf.reshape(img_tensor, [792,1224])
    img_tensor = tf.cast(img_tensor, tf.float32, name='ImageCast')
    #img_tensor /= 255.0 #Tried with and without
    return img_tensor

def read_data(all_filenames):
    path_Dataset = tf.data.Dataset.from_tensor_slices(all_filenames)
    image_Dataset = path_Dataset.map(load_and_preprocess_jpeg)
    plt.figure(figsize=(8,8))
    temp_DS = image_Dataset.take(4)
    itera = temp_DS.make_one_shot_iterator()
    for n in range(4):
        image = itera.get_next()
        plt.subplot(2,2,n+1)
        plt.imshow(image)
        plt.grid(False)
        plt.xticks([])
        plt.yticks([])

我的堆栈跟踪：

File "<stdin>", line 1, in <module>
line 34, in read_data
  plt.imshow(image)
matplotlib\pyplot.py, line 3205, in imshow
  **kwargs)
matplotlib\__init__.py, line 1855, in inner
  return func(ax, *args, **kwargs)
matplotlib\axes\_axes.py, line 5487, in imshow
  im.set_data(X)
matplotlib\image.py, line 649, in set_data
  raise TypeError("Image data cannot be converted to float")

Answer 1

您正在尝试绘制张量。为了绘制图像，您必须首先运行会话。尝试以下代码：

import tensorflow as tf
import matplotlib.pyplot as plt

def load_and_preprocess_jpeg(imagepath):
    img = tf.read_file(imagepath)
    img_tensor = tf.image.decode_jpeg(img)
    img_tensor = tf.image.resize_images(img_tensor, [img_size,img_size])
    img_tensor = tf.cast(img_tensor, tf.float32, name='ImageCast')
    img_tensor /= 255.0 
    return img_tensor

path_Dataset = tf.data.Dataset.from_tensor_slices(all_filenames)
image_Dataset = path_Dataset.map(load_and_preprocess_jpeg)
temp_DS = image_Dataset.take(4)
itera = temp_DS.make_one_shot_iterator()
image = itera.get_next()

with tf.Session() as sess:
    sess.run(tf.global_variables_initializer())
    while True:
        try:
            image_to_plot = sess.run(image)
            plt.figure(figsize=(8,8))
            plt.subplot(2,2,n+1)
            plt.imshow(image_to_plot)
            plt.grid(False)
            plt.xticks([])
            plt.yticks([])

        except tf.errors.OutOfRangeError:
            break

为什么收到TypeError“图像数据无法转换为浮点型”？

1 个答案: