重塑图像数组时感到困惑 [英] Confused during reshaping array of image

问题描述

目前，我正在尝试运行ConvNet。每个稍后供入神经网络的图像都存储为一个列表。但是此列表是使用三个for循环创建的。看看：

At the moment I'm trying to run a ConvNet. Each image, which later feeds the neural net, is stored as a list. But the list is at the moment created using three for-loops. Have a look:

im = Image.open(os.path.join(p_input_directory, item))
pix = im.load()

image_representation = []

# Get image into byte array
for color in range(0, 3):
    for x in range(0, 32):
        for y in range(0, 32):
            image_representation.append(pix[x, y][color])

我很确定这不是最好，最有效的方法。因为我必须坚持上面创建的列表的结构，所以我考虑使用 numpy 并提供另一种获取相同结构的方法。

I'm pretty sure that this is not the nicest and most efficient way. Because I have to stick to the structure of the list created above, I thought about using numpy and providing an alternative way to get to the same structure.

from PIL import Image
import numpy as np

image = Image.open(os.path.join(p_input_directory, item))
image.load()
image = np.asarray(image, dtype="uint8")
image = np.reshape(image, 3072)
# Sth is missing here...

但是我不知道如何重塑和连接 image 以获得与上述相同的结构。有人可以帮忙吗？

But I don't know how to reshape and concatenate the image for getting the same structure as above. Can someone help with that?

推荐答案

一种方法是转置轴，这实际上是在 fortran 模式，即反转方式-

One approach would be to transpose the axes, which is essentially flattening in fortran mode i.e. reversed manner -

image = np.asarray(im, dtype="uint8")
image_representation = image.ravel('F').tolist()

近距离查看该函数请查看 numpy.ravel文档。

For a closer look to the function have a look to the numpy.ravel documentation.

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