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将图像(png和jpg)转换为多维列表,然后在python中向后转换

[英]Convert a image (png and jpg) to a multi-dimensional list and backwards in python

I use PIL in order to convert imagse to monochrome and afterwards to a list of lists, but I am not sure how to do so with rgb images. 我使用PIL将图像转换为单色,然后转换为列表列表,但我不知道如何使用rgb图像。

Can someone give me a direction how to convert images to a multi-dimensional list and backwards an python? 有人可以给我一个方向如何将图像转换为多维列表并向后转换python?

Let's start with a known sample image. 让我们从一个已知的样本图像开始。 Here's a small 3x2 one to actually work with and a larger one just so you can see it: 这是一个小的3x2实际工作和一个更大的一个,所以你可以看到它:

Small: 小:

在此输入图像描述

Large: 大:

在此输入图像描述

You can open an image and make it into an efficient, fast numpy multi-dimensional array like this: 你可以打开一个图像,并使其成为一个高效,快捷numpy多维数组是这样的:

#!/usr/local/bin/python3
import numpy as np
from PIL import Image

# Open image from disk
im = Image.open('image.png')
na = np.array(im)

That will look like this: 这将是这样的:

array([[[255,   0,   0],                      # Red
        [  0, 255,   0],                      # Green
        [  0,   0, 255]],                     # Blue

       [[  0,   0,   0],                      # Black
        [255, 255, 255],                      # White
        [126, 126, 126]]], dtype=uint8)       # Mid-grey

And convert it back to a PIL Image and save like this (just append this code to the code above): 并将其转换回PIL图像并像这样保存(只需将此代码附加到上面的代码中):

# Convert array back to Image
resultim = Image.fromarray(na)
resultim.save('result.png')

Some notes : 一些说明

Note 1 注1

If you expect and want an RGB888 image, and you are opening a PNG image, you may get a palettised image which doesn't have RGB values for each pixel, but instead has an index into a palette for each pixel and everything will go wrong! 如果你期望并想要一个RGB888图像,并且你正在打开一个PNG图像,你可能得到一个没有每个像素RGB值的palettised图像,而是每个像素的调色板都有一个索引,一切都会出错!

By way of example, here is the same image as above but when the generating application saved it as a palettised image: 举例来说,这里是与上面相同的图像,但是当生成应用程序将其保存为palettised图像时:

array([[0, 1, 2],
       [3, 4, 5]], dtype=uint8)

And here what is returned from im.getpalette() : 这里是从im.getpalette()返回的im.getpalette()

[255,
 0,
 0,
 0,
 255,
 0,
 0,
 0,
 255,
 0,
 0,
 0,
 255,
 255,
 255,
 126,
 126,
 126,
 ...
 ...

So, the moral of the story is... if you are expecting an RGB888 image, use: 所以,故事的寓意是......如果您期待RGB888图像,请使用:

Image.open('image.png').convert('RGB')

Note 2 笔记2

Likewise, if you open a PNG file that contains transparency, it will have 4 channels, the last being alpha/transparency, and you should call convert('RGB') if you wish to discard the alpha channel. 同样,如果你打开一个包含透明度的PNG文件,它将有4个通道,最后一个是alpha / transparency,如果你想丢弃alpha通道,你应该调用convert('RGB')

Note 3 注3

You can abbreviate the loading and saving into single lines if you don't want the intermediate image: 如果您不想要中间图像,可以将加载和保存缩写为单行:

# Load and make array in one go
na = np.array(Image.open('image.png').convert('RGB'))

# Convert back to PIL Image and save in one go
Image.fromarray(na).save('result.png')

Keywords : Image, image processing, numpy, array, ndarray, PIL, Pillow, Python, Python3, palette, PNG, JPG 关键词 :图像,图像处理,numpy,数组,ndarray,PIL,Pillow,Python,Python3,调色板,PNG,JPG

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