如何将灰度图像转换为像素值列表？

我正在尝试创建一个 python 程序，它采用灰度、24*24 像素图像文件（我尚未决定类型，因此欢迎提出建议）并将其转换为从 0（白色）到 255 的像素值列表（黑色的）。

我计划使用这个数组来创建一个MNIST http://yann.lecun.com/exdb/mnist/-类似于图片的字节文件，可以被Tensor-Flow手写识别算法识别。

我已经找到了枕头库 http://pillow.readthedocs.io/通过迭代每个像素并将其值附加到数组中，成为此任务中最有用的

from PIL import Image

img = Image.open('eggs.png').convert('1')
rawData = img.load()
data = []
for y in range(24):
    for x in range(24):
        data.append(rawData[x,y])

然而这个解决方案有两个问题：

1. 像素值不是存储为整数，而是存储为像素对象，无法进一步进行数学操作，因此无用。
2. Even the Pillow docs https://pillow.readthedocs.io/en/latest/reference/PixelAccess.html#pixelaccess-class state that:

   访问单个像素相当慢。如果您要循环遍历图像中的所有像素，则可能有一种使用 Pillow API 的其他部分更快的方法。

您可以将图像数据转换为 Python 列表（或列表列表），如下所示：

from PIL import Image

img = Image.open('eggs.png').convert('L')  # convert image to 8-bit grayscale
WIDTH, HEIGHT = img.size

data = list(img.getdata()) # convert image data to a list of integers
# convert that to 2D list (list of lists of integers)
data = [data[offset:offset+WIDTH] for offset in range(0, WIDTH*HEIGHT, WIDTH)]

# At this point the image's pixels are all in memory and can be accessed
# individually using data[row][col].

# For example:
for row in data:
    print(' '.join('{:3}'.format(value) for value in row))

# Here's another more compact representation.
chars = '@%#*+=-:. '  # Change as desired.
scale = (len(chars)-1)/255.
print()
for row in data:
    print(' '.join(chars[int(value*scale)] for value in row))

这是小型 24x24 RGB 的放大版本eggs.png https://i.stack.imgur.com/uEojM.png我用于测试的图像：

这是第一个访问示例的输出：

这是第二个示例的输出：

@ @ % * @ @ @ @ % - . * @ @ @ @ @ @ @ @ @ @ @ @
@ @ .   . + @ # .     = @ @ @ @ @ @ @ @ @ @ @ @
@ *             . .   * @ @ @ @ @ @ @ @ @ @ @ @
@ #     . .   . .     + % % @ @ @ @ # = @ @ @ @
@ %       . : - - - :       % @ % :     # @ @ @
@ #     . = = - - - = - . . = =         % @ @ @
@ =     - = : - - : - = . .     . : .   % @ @ @
%     . = - - - - : - = .   . - = = =   - @ @ @
=   .   - = - : : = + - : . - = - : - =   : * %
-   .   . - = + = - .   . - = : - - - = .     -
=   . : : . - - .       : = - - - - - = .   . %
%   : : .     . : - - . : = - - - : = :     # @
@ # :   .   . = = - - = . = + - - = - .   . @ @
@ @ #     . - = : - : = - . - = = : . .     # @
@ @ %     : = - - - : = -     : -   . . .   - @
@ @ *     : = : - - - = .   . - .   .     . + @
@ #       . = - : - = :     : :   .   - % @ @ @
*     . . . : = = - : . .   - .     - @ @ @ @ @
*   . .       . : .   . .   - = . = @ @ @ @ @ @
@ :     - -       . . . .     # @ @ @ @ @ @ @ @
@ @ = # @ @ *     . .     . - @ @ @ @ @ @ @ @ @
@ @ @ @ @ @ @ .   .   . # @ @ @ @ @ @ @ @ @ @ @
@ @ @ @ @ @ @ -     . % @ @ @ @ @ @ @ @ @ @ @ @
@ @ @ @ @ @ @ # . : % @ @ @ @ @ @ @ @ @ @ @ @ @

现在访问像素数据应该比使用对象更快img.load()返回（并且值将是 0..255 范围内的整数）。