Just remembered that I have an example notebook for reading MNIST into NumPy 
arrays, maybe that helps:

http://nbviewer.jupyter.org/github/rasbt/pattern_classification/blob/master/data_collecting/reading_mnist.ipynb

> On Jan 24, 2016, at 8:59 AM, Abder-Rahman Ali <abder.rahman....@gmail.com> 
> wrote:
> 
> Hi,
> 
> 
> 
> I have read the images from my local directory as follows:
> 
> from PIL import Image
> import
>  os
> 
> root 
> = '/Users/xyz/Desktop/data'
> 
> 
> 
> for path, subdirs, files in os.walk(root):
> 
>     
> for name in files:
> 
>         img_path 
> = os.path.join(path,name)
> I have two subdirectories: category-1 and category-2, each of which contains 
> image files (.jpg) that belong to each category.
> 
> How can I use those images and two categories with the train_test_split() 
> function in Scikit-Learn? In other words, to arrange the training and testing 
> data?
> 
> Thanks.
> 
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