blocks|key|2629415|text|处理基本的.ppm文件很简单:您有三行文本(P6、"width+height“、255)，然后是3*width*height字节。只要不需要更复杂的.ppm格式变体，就可以分别用5行代码编写一个加载器和一个保存器。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|2629416|entityMap^0|M|2|14|3|1C|E|0^^$0|@$1|2|3|4|5|6|7|H|8|@$9|I|A|J|B|C]|$9|K|A|L|B|C]|$9|M|A|N|B|C]]|D|@]|E|$]]|$1|F|3|-4|5|6|7|O|8|@]|D|@]|E|$]]]|G|$]]

Working with bare-bones .ppm files is trivial: you have three lines of text (<code>P6</code>, "width height", <code>255</code>), and then you have the <code>3*width*height</code> bytes of RGB. As long as you don't need more complicated variants of the .ppm format, you can write a loader and a saver in 5 lines of code each.

blocks|key|2629424|text|您可以像打开文本文件一样打开图像文件。只需适应.png镜像的约定即可。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2629425|对于PNG，请查看https://fr.wikipedia.org/wiki/Portable_Network_Graphics并相应地阅读这些块|offset|length|2629426|entityMap|0|LINK|mutability|MUTABLE|url|https://fr.wikipedia.org/wiki/Portable_Network_Graphics^0|0|9|1J|0|0^^$0|@$1|2|3|4|5|6|7|N|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|O|8|@]|9|@$D|P|E|Q|1|R]]|A|$]]|$1|F|3|-4|5|6|7|S|8|@]|9|@]|A|$]]]|G|$H|$5|I|J|K|A|$L|M]]]]

You can open your image files in the same way you would do for text files. Just adapt to the convention of your .png images.

For PNG look at <a href="https://fr.wikipedia.org/wiki/Portable_Network_Graphics" rel="nofollow noreferrer">https://fr.wikipedia.org/wiki/Portable_Network_Graphics</a> and read the chunks accordingly

blocks|key|2629621|text|你可以在没有OpenCV或numpy或任何讨厌你的东西的情况下编写这样的PPM文件:-|type|unstyled|depth|inlineStyleRanges|offset|length|style|BOLD|CODE|entityRanges|data|2629622|import+array
width,height+=+800,600

PPMheader+=+'P6\n'+%2Bstr(width)+%2B+'+'+%2Bstr(height)+%2B+'\n255\n'

#+Create+and+fill+a+red+PPM+image
image+=+array.array('B',+[255,+0,+0]+*+width+*+height)

#+Save+as+PPM+image
with+open('result.ppm',+'wb')+as+f:
+++f.write(bytearray(PPMheader,+'ascii'))
+++image.tofile(f)|code-block|syntax|javascript|2629623|​|2629624|📷|atomic|2629625|2629626|2629627|我也写了一个非常简单的PPM阅读器-它只读取与上面所写的匹配的24位P6+PPM文件。我猜它可以被充实以处理注释、16位数据和灰度数据，但这是一个开始：|2629628|#!/usr/local/bin/python3
import+array

def+ppmread(filename):
++++with+open(filename,+'rb')+as+f:
++++++++#+Read+first+line+-+expecting+"P6"
++++++++line+=+f.readline().decode('latin-1')
++++++++if+not+line.startswith('P6'):
+++++++++++print("ERROR:+Expected+PPM+file+to+start+with+P6")
+++++++++++return+False

++++++++#+Read+second+line+-+expecting+"width+height"
++++++++line+=+f.readline().decode('latin-1')
++++++++dims+=+line.split()
++++++++width,height=int(dims[0]),int(dims[1])

++++++++#+Read+third+line+-+expecting+"255"
++++++++line+=+f.readline().decode('latin-1')
++++++++if+not+line.startswith('255'):
+++++++++++print("ERROR:+Expected+8-bit+PPM+with+MAXVAL=255")
+++++++++++return+False

++++++++image=+f.read(width*height*3)

ppmread('test.ppm')|2629629|2629630|在终端中使用ImageMagick将PPM转换为PNG或JPEG：|2629631|convert+result.ppm+-auto-level+image.png|2629632|或者：|2629633|convert+result.ppm+-resize+1024x768+image.jpg|2629634|同样，在终端中使用ImageMagick将JPEG转换为PPM：|2629635|convert+image.jpg+-depth+8+image.ppm|2629636|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/9bc45ee990ffb05678723db17b78157d.jpeg|imageAlt^0|6|6|D|5|10|3|0|0|0|0|1|0|0|0|0|0|0|0|6|B|0|0|0|0|9|B|0|0^^$0|@$1|2|3|4|5|6|7|1I|8|@$9|1J|A|1K|B|C]|$9|1L|A|1M|B|C]|$9|1N|A|1O|B|D]]|E|@]|F|$]]|$1|G|3|H|5|I|7|1P|8|@]|E|@]|F|$J|K]]|$1|L|3|M|5|6|7|1Q|8|@]|E|@]|F|$]]|$1|N|3|O|5|P|7|1R|8|@]|E|@$9|1S|A|1T|1|1U]]|F|$]]|$1|Q|3|M|5|6|7|1V|8|@]|E|@]|F|$]]|$1|R|3|-4|5|6|7|1W|8|@]|E|@]|F|$]]|$1|S|3|T|5|6|7|1X|8|@]|E|@]|F|$]]|$1|U|3|V|5|I|7|1Y|8|@]|E|@]|F|$J|K]]|$1|W|3|-4|5|6|7|1Z|8|@]|E|@]|F|$]]|$1|X|3|Y|5|6|7|20|8|@$9|21|A|22|B|C]]|E|@]|F|$]]|$1|Z|3|10|5|I|7|23|8|@]|E|@]|F|$J|K]]|$1|11|3|12|5|6|7|24|8|@]|E|@]|F|$]]|$1|13|3|14|5|I|7|25|8|@]|E|@]|F|$J|K]]|$1|15|3|16|5|6|7|26|8|@$9|27|A|28|B|C]]|E|@]|F|$]]|$1|17|3|18|5|I|7|29|8|@]|E|@]|F|$J|K]]|$1|19|3|-4|5|6|7|2A|8|@]|E|@]|F|$]]]|1A|$1B|$5|1C|1D|1E|F|$1F|1G|1H|-4]]]]

You can write a <code>PPM</code> file like this without OpenCV or numpy or anything that hates you :-

<pre><code>import array
width,height = 800,600

PPMheader = 'P6\n' +str(width) + ' ' +str(height) + '\n255\n'

# Create and fill a red PPM image
image = array.array('B', [255, 0, 0] * width * height)

# Save as PPM image
with open('result.ppm', 'wb') as f:
 f.write(bytearray(PPMheader, 'ascii'))
 image.tofile(f)
</code></pre>

<a href="https://i.stack.imgur.com/lhJaJ.jpg" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/lhJaJ.jpg" alt="enter image description here"></a>

<hr>

I wrote a really simplistic PPM reader too - it only reads 24-bit P6 PPM files matching the ones written above. I guess it could be fleshed out to handle comments, 16-bit data and greyscale data, but it's a start:

<pre><code>#!/usr/local/bin/python3
import array

def ppmread(filename):
 with open(filename, 'rb') as f:
 # Read first line - expecting "P6"
 line = f.readline().decode('latin-1')
 if not line.startswith('P6'):
 print("ERROR: Expected PPM file to start with P6")
 return False

 # Read second line - expecting "width height"
 line = f.readline().decode('latin-1')
 dims = line.split()
 width,height=int(dims[0]),int(dims[1])

 # Read third line - expecting "255"
 line = f.readline().decode('latin-1')
 if not line.startswith('255'):
 print("ERROR: Expected 8-bit PPM with MAXVAL=255")
 return False

 image= f.read(width*height*3)

ppmread('test.ppm')
</code></pre>

<hr>

Convert PPM to PNG or JPEG with ImageMagick in Terminal:

<pre><code>convert result.ppm -auto-level image.png
</code></pre>

Or:

<pre><code>convert result.ppm -resize 1024x768 image.jpg
</code></pre>

Likewise, convert JPEG to PPM with ImageMagick in Terminal:

<pre><code>convert image.jpg -depth 8 image.ppm
</code></pre>

blocks|key|2419140|text|基于各种输入(感谢Mark+Setchell的代码片段)，现在我可以读取RGB值，然后逐个像素地处理它们，然后写入一个新的图像文件，所有这些都不需要使用任何外部库。当我开始这一切的时候，我使用了带有OpenCV和Numpy的CPython，运行时间不少于60分钟。然后，我没有使用Numpy或OpenCV重写代码，并使用Pypy运行它:它只用了两分钟就完成了！这是尽管与原始jpg相比，ppm文件的大小非常大。write-ppm部分由Mark处理。他还建议了一种自动处理可变头部的方法(对我来说是奢侈的……)。这描述了我的过程，只显示了read-ppm部分(我相信它可以进一步清理)：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2419141|#+have+image+file+as+png,+bmp,+jpg+etc.+and+open+in+GIMP.
#+from+GIMP,+export+the+image+file+as+myPicture.ppm+(use+ASCII+option,+not+RAW).
#+examine+the+header+of+the+ppm+file+to+find+the+exact+locations+of+the+width,+height+and+maxvalue.+Used+Notepad.

#+Python+code
#+BEGIN+read+the+ppm+image
h_ind=9;+w_ind=8;+mval_ind=10+#indexes+for+height,+width,+maxval+in+the+ppm+header
with+open('myPicture.ppm','r')+as+ppm:+#+open+the+ppm+file
++++data=ppm.read()
values=data.split()
for+i+in+range(mval_ind,len(values)):
++++values[i]=int(values[i])+#+convert+rgb+data+from+string+to+int+for+later+numeric+processing
height=int(values[h_ind]);+width=int(values[w_ind]);+mval=int(values[mval_ind])+#+read+height,+width,+maxvalue
rgb0+=+[tuple(values[i:i%2B3])+for+i+in+range(mval_ind%2B1,+len(values),+3)]+#+contains+all+rgb+values+as+integers
#+END+read+the+ppm+image|code-block|syntax|javascript|2419142|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

Based on various input (kudos to Mark Setchell for his code snippets), now I was able both to read the rgb values, then process them pixel by pixel, then write a new image file, all without using any external libraries. When I started all this I used CPython with OpenCV and Numpy and the runtime was no less than 60 minutes. Then I re-wrote the code without Numpy or OpenCV and ran it using Pypy: it took only two minutes to finish! This is despite the very large size of the ppm file as compared to the original jpg. The write-ppm part was addressed by Mark. He also suggests an automatic way of dealing with variable headers (luxury for me...). This describes my process, showing only the read-ppm part (I am sure it can be cleaned up further): 

<pre><code># have image file as png, bmp, jpg etc. and open in GIMP.
# from GIMP, export the image file as myPicture.ppm (use ASCII option, not RAW).
# examine the header of the ppm file to find the exact locations of the width, height and maxvalue. Used Notepad.

# Python code
# BEGIN read the ppm image
h_ind=9; w_ind=8; mval_ind=10 #indexes for height, width, maxval in the ppm header
with open('myPicture.ppm','r') as ppm: # open the ppm file
 data=ppm.read()
values=data.split()
for i in range(mval_ind,len(values)):
 values[i]=int(values[i]) # convert rgb data from string to int for later numeric processing
height=int(values[h_ind]); width=int(values[w_ind]); mval=int(values[mval_ind]) # read height, width, maxvalue
rgb0 = [tuple(values[i:i+3]) for i in range(mval_ind+1, len(values), 3)] # contains all rgb values as integers
# END read the ppm image
</code></pre>

I have a python script which opens an image file (.png or .ppm) using OpenCV, then loads all the RGB values into a multidimensional Python array (or list), performs some pixel by pixel calculations solely on the Python array (OpenCV is not used at all for this stage), then uses the newly created array (containing new RGB values) to write a new image file (.png here) using OpenCV again. Numpy is not used at all in this script. The program works fine.

The question is how to do this without using any external libraries, regardless whether they are for image processing or not (e.g. OpenCV, Numpy, Scipy, Pillow etc.). To summarize, I need to use bare bones Python's internal modules to: 1. open image and read the RGB values and 2. write a new image from pre-calculated RGB values. I will use Pypy instead of CPython for this purpose, to speed things up.
Note: I use Windows 10, if that matters.

How to open/create images in Python without using external modules

图像处理

Python

我有一个python脚本，它使用OpenCV打开一个图像文件(.png或.ppm)，然后将所有RGB值加载到一个多维Python数组(或列表)中，单独在Python数组上执行一些逐像素计算(在这个阶段根本不使用OpenCV )，然后使用新创建的数组(包含新的RGB值)再次使用OpenCV编写新的图像文件(这里是.png...

问如何在不使用外部模块的情况下使用Python打开/创建图像
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