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    <p>It seems that there is <em>misunderstanding</em> in what you are going to do with image files. The following shows the two possible cases based on you question.</p> <p>To read a <code>JPG</code> file into <code>TXT</code> file <strong>without</strong> analyzing image data i.e., no decompressing etc. Use this (what would be the use for this, we are not sure!, BTW). </p> <pre><code>import os from scipy.misc import imread import numpy as np imagePath = 'c:/your jpgs/' savepath = imagePath #save as text no decompressing for filename in os.listdir(imagePath): if filename!='.DS_Store' and filename[-3:]=='jpg': with open(filename,'rb') as fin: b = fin.read() fin.close() out = ','.join(b)+'\n' with open(savepath+'trainMatrix1.txt','a') as fut: fut.write(out) fut.close() </code></pre> <p>output is as: </p> <pre><code>ÿ,Ø,ÿ,à, ,,J,F,I,F, ,,,, ,d, ,d, , ,ÿ,á, </code></pre> <p>To read a <code>JPG</code> file into <code>TXT</code> file <strong>with</strong> analyzing image data i.e., <strong>decompressing</strong> etc. Use this which utilises <code>imread</code> to decompress image data. You will need remember <code>JPG</code> is a heavily compressed image format, so after decompressing, it will be huge text file. You are appending all, so the output will be huge! </p> <pre><code>#save as text decompressed image into bytes for filename in os.listdir(imagePath): if filename!='.DS_Store' and filename[-3:]=='jpg': b = imread(filename,flatten=0).flatten() print b.shape out = ','.join('%d'%i for i in b)+'\n' print len(out) with open(savepath+'trainMatrix2.txt','a') as fut: fut.write(out) fut.close() </code></pre> <p>output is as (color data):</p> <pre><code>255,255,255,245,245,245,125,125,125,72,72,72,17,17,17,2,2,2,15 </code></pre>
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    1. POconvert JPG to txt causes change in file size in python
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    1. COThank you very much. Well, I'm very new to this material but one use of storing it into a txt format is that I can later on use them to train a neural network. The libraries for neural networks usually take in an M*N matrix ( in this case M=number of images, N is the equivalent length of the images when converted to a row vector).
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    2. CO@user2639876 Why don't you store them directly in a MAT file? Then it would be more easy to manipulate them. I would recommend preprocessing the data using unsupervised learning (i.e: RBM, Autoencoders, CNN)
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      1. USEdgar Andrés Margffoy Tuay
    3. CO@user2639876 Note that a pixel in an image contains three values for `Red`, `Green` and `Blue` components. It may contain `Alpha` component. So a pixel is not a single value. If you use `gray scale` images with no alpha then a pixel can be represented by a single value. Based on your comment, the second solution helps you in which decompression happens.Check [Color RGB](http://en.wikipedia.org/wiki/RGB_color_model), and [RGB to Gray](http://stackoverflow.com/questions/687261/converting-rgb-to-grayscale-intensity). Happy with answer please accept it.
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