如何使用imageio调整图像大小? [英] How to resize an image using imageio?

问题描述

考虑类型为 imageio.core.util.Array 的图像 img .

img 的形状为(256，256，3).我想将其调整为(128，128，3).

The shape of img is (256, 256, 3). I want to resize it to (128, 128, 3).

我至少尝试了以下三个:

I tried at least the following three:

img.resize(img_res, pilmode="RGB")

img.resize(img_res)

img = cv2.resize(img, self.img_res)

此处 img_res =(128，128).

没有一个人运作良好.如何将图像调整为所需的大小?

None of them worked well. How can I resize my image to the desired size?

推荐答案

根据 imageio.core.util.Array 上的文档， Array 是" np.ndarray [...]".因此，在某些类型为 Array 的 img 上调用 resize 时，实际的调用将转到 np.resize ！这很重要.

According to the documentation on imageio.core.util.Array, Array is "a subclass of np.ndarray [...]". Thus, when calling resize on some img of type Array, the actual call goes to np.ndarray.resize – which IS NOT np.resize! That's important here.

摘自 np.ndarray.resize 上的文档:

提高:

ValueError

如果 a 不拥有自己的数据[...]

If a does not own its own data [...]

这就是为什么，像这样的一些代码

That's why, some code like

import imageio

img = imageio.imread('path/to/your/image.png')
img.resize((128, 128))

将以这种方式失败:

Traceback (most recent call last):
    img.resize((128, 128))
ValueError: cannot resize this array: it does not own its data

该错误似乎与 Array 类绑定，因为以下代码也因相同的错误消息而失败:

That error seems to be bound to the Array class, because the following code also fails with the same error message:

from imageio.core.util import Array
import numpy as np

img = Array(np.zeros((200, 200, 3), np.uint8))
img.resize((128, 128))

很明显， Array 类仅将视图存储到一些无法直接访问的NumPy数组，也许是一些内部内存缓冲区！?

Obviously, the Array class only stores a view to some not directly accessible NumPy array, maybe some internal memory buffer!?

现在，让我们看看可能的解决方法:

Now, let's see possible workarounds:

实际上，像

那样使用 np.resize

import imageio
import numpy as np

img = imageio.imread('path/to/your/image.png')
img = np.resize(img, (128, 128, 3))

不是一个好选择，因为 np.resize 并非旨在正确调整图像大小.因此，结果会失真.

is not a good choice, because np.resize is not designed to properly resize images. So, the result is distorted.

使用OpenCV对我来说很好:

Using OpenCV works fine for me:

import cv2
import imageio

img = imageio.imread('path/to/your/image.png')
img = cv2.resize(img, (128, 128))

请记住，OpenCV使用BGR排序，而imageio使用RGB排序-例如，在还使用 cv2.imshow 时，这一点很重要.

Keep in mind, that OpenCV uses BGR ordering, while imageio uses RGB ordering – that's important when also using cv2.imshow for example.

使用枕头也可以正常工作:

Using Pillow also works without problems:

import imageio
from PIL import Image

img = imageio.imread('path/to/your/image.png')
img = Image.fromarray(img).resize((128, 128))

最后，还有 skimage.transform.resize :

import imageio
from skimage.transform import resize

img = imageio.imread('path/tp/your/image.png')
img = resize(img, (128, 128))

选择最适合您的需求！

----------------------------------------
System information
----------------------------------------
Platform:      Windows-10-10.0.16299-SP0
Python:        3.8.5
imageio:       2.9.0
NumPy:         1.19.5
OpenCV:        4.5.1
Pillow:        8.1.0
scikit-image:  0.18.1
----------------------------------------

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