MNIST-READY

A simple and straightforward Ruby library that handles everything related to the MNIST Database. It uses the "don't make me think" approach so you can focus on your revolutionary neural network. You don't even need to download the MNIST Database, everything is included and works out of the box. Just install the mnist-ready gem and be happy.

Installation

gem install mnist-ready

Usage

require 'mnist-ready'

To load all the digits from file to memory:

# Note: this can take a couple of seconds the first time you call it
MNIST = MnistDataset.instance # singleton 

Then have fun!

# 70,000 digits in total
puts MNIST.all_set.size # => 70000

# 60,000 digits for training
puts MNIST.train_set.size # => 60000

# 10,000 digits for testing
puts MNIST.test_set.size # => 10000

digit = MNIST.all_set[0] # first one

# An integer corresponding to the digit of the image
puts digit.label # => 7

# The pixels is an one-dimension array of 784 (28 x 28) pixel values from 0 to 255
puts digit.pixels.size # => 784
puts digit.pixels.inspect # => [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 84, 185, 159, 151, 60, 36, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 222, 254, 254, 254, 254, 241, 198, 198, 198, 198, 198, 198, 198, 198, 170, 52, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 67, 114, 72, 114, 163, 227, 254, 225, 254, 254, 254, 250, 229, 254, 254, 140, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 17, 66, 14, 67, 67, 67, 59, 21, 236, 254, 106, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 83, 253, 209, 18, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 22, 233, 255, 83, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 129, 254, 238, 44, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 59, 249, 254, 62, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 133, 254, 187, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 9, 205, 248, 58, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 126, 254, 182, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 75, 251, 240, 57, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 19, 221, 254, 166, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 203, 254, 219, 35, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 38, 254, 254, 77, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 31, 224, 254, 115, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 133, 254, 254, 52, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 61, 242, 254, 254, 52, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 121, 254, 254, 219, 40, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 121, 254, 207, 18, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]

# To create a Ruby matrix with the pixels, you can simply do:
require 'matrix'
pixels_matrix = Matrix[digit.pixels]
puts pixels_matrix # => Matrix[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 84, 185, 159, 151, 60, 36, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 222, 254, 254, 254, 254, 241, 198, 198, 198, 198, 198, 198, 198, 198, 170, 52, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 67, 114, 72, 114, 163, 227, 254, 225, 254, 254, 254, 250, 229, 254, 254, 140, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 17, 66, 14, 67, 67, 67, 59, 21, 236, 254, 106, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 83, 253, 209, 18, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 22, 233, 255, 83, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 129, 254, 238, 44, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 59, 249, 254, 62, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 133, 254, 187, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 9, 205, 248, 58, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 126, 254, 182, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 75, 251, 240, 57, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 19, 221, 254, 166, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 203, 254, 219, 35, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 38, 254, 254, 77, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 31, 224, 254, 115, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 133, 254, 254, 52, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 61, 242, 254, 254, 52, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 121, 254, 254, 219, 40, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 121, 254, 207, 18, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]
puts pixels_matrix.transpose # => Matrix[[0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [84], [185], [159], [151], [60], [36], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [222], [254], [254], [254], [254], [241], [198], [198], [198], [198], [198], [198], [198], [198], [170], [52], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [67], [114], [72], [114], [163], [227], [254], [225], [254], [254], [254], [250], [229], [254], [254], [140], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [17], [66], [14], [67], [67], [67], [59], [21], [236], [254], [106], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [83], [253], [209], [18], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [22], [233], [255], [83], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [129], [254], [238], [44], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [59], [249], [254], [62], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [133], [254], [187], [5], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [9], [205], [248], [58], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [126], [254], [182], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [75], [251], [240], [57], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [19], [221], [254], [166], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [3], [203], [254], [219], [35], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [38], [254], [254], [77], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [31], [224], [254], [115], [1], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [133], [254], [254], [52], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [61], [242], [254], [254], [52], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [121], [254], [254], [219], [40], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [121], [254], [207], [18], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0], [0]]

And you can see the digits in your terminal, for more fun!

puts digit.ascii_image
 ____________________________ 
|            7               |
|----------------------------|
|                            |
|      }wJY+I                |
|      #$$$$%ddddddddQ>      |
|      -f?fCM$M$$$$W$$c      |
|            _^---~"8$/      |
|                  }$h       |
|                 "&$}       |
|                 n$8!       |
|                ~@$+        |
|                u$w.        |
|               `k@~         |
|               x$m          |
|              ]$%~          |
|              #$L           |
|            .k$*I           |
|            l$$]            |
|           ;#$f             |
|           u$$>             |
|          +%$$>             |
|          r$$*l             |
|          r$h               |
|____________________________|

puts digit.pixel_image
 _________________________________________________________________________________________________________________ 
|                                                  7                                                              |
|-----------------------------------------------------------------------------------------------------------------|
|   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0 |
|   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0 |
|   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0 |
|   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0 |
|   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0 |
|   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0 |
|   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0 |
|   0   0   0   0   0   0  84 185 159 151  60  36   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0 |
|   0   0   0   0   0   0 222 254 254 254 254 241 198 198 198 198 198 198 198 198 170  52   0   0   0   0   0   0 |
|   0   0   0   0   0   0  67 114  72 114 163 227 254 225 254 254 254 250 229 254 254 140   0   0   0   0   0   0 |
|   0   0   0   0   0   0   0   0   0   0   0  17  66  14  67  67  67  59  21 236 254 106   0   0   0   0   0   0 |
|   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0  83 253 209  18   0   0   0   0   0   0 |
|   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0  22 233 255  83   0   0   0   0   0   0   0 |
|   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0 129 254 238  44   0   0   0   0   0   0   0 |
|   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0  59 249 254  62   0   0   0   0   0   0   0   0 |
|   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0 133 254 187   5   0   0   0   0   0   0   0   0 |
|   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   9 205 248  58   0   0   0   0   0   0   0   0   0 |
|   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0 126 254 182   0   0   0   0   0   0   0   0   0   0 |
|   0   0   0   0   0   0   0   0   0   0   0   0   0   0  75 251 240  57   0   0   0   0   0   0   0   0   0   0 |
|   0   0   0   0   0   0   0   0   0   0   0   0   0  19 221 254 166   0   0   0   0   0   0   0   0   0   0   0 |
|   0   0   0   0   0   0   0   0   0   0   0   0   3 203 254 219  35   0   0   0   0   0   0   0   0   0   0   0 |
|   0   0   0   0   0   0   0   0   0   0   0   0  38 254 254  77   0   0   0   0   0   0   0   0   0   0   0   0 |
|   0   0   0   0   0   0   0   0   0   0   0  31 224 254 115   1   0   0   0   0   0   0   0   0   0   0   0   0 |
|   0   0   0   0   0   0   0   0   0   0   0 133 254 254  52   0   0   0   0   0   0   0   0   0   0   0   0   0 |
|   0   0   0   0   0   0   0   0   0   0  61 242 254 254  52   0   0   0   0   0   0   0   0   0   0   0   0   0 |
|   0   0   0   0   0   0   0   0   0   0 121 254 254 219  40   0   0   0   0   0   0   0   0   0   0   0   0   0 |
|   0   0   0   0   0   0   0   0   0   0 121 254 207  18   0   0   0   0   0   0   0   0   0   0   0   0   0   0 |
|   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0 |
|_________________________________________________________________________________________________________________|

puts digit.pixel_image(no_zeros = true)
 _________________________________________________________________________________________________________________ 
|                                                  7                                                              |
|-----------------------------------------------------------------------------------------------------------------|
|                                                                                                                 |
|                                                                                                                 |
|                                                                                                                 |
|                                                                                                                 |
|                                                                                                                 |
|                                                                                                                 |
|                                                                                                                 |
|                          84 185 159 151  60  36                                                                 |
|                         222 254 254 254 254 241 198 198 198 198 198 198 198 198 170  52                         |
|                          67 114  72 114 163 227 254 225 254 254 254 250 229 254 254 140                         |
|                                              17  66  14  67  67  67  59  21 236 254 106                         |
|                                                                          83 253 209  18                         |
|                                                                      22 233 255  83                             |
|                                                                     129 254 238  44                             |
|                                                                  59 249 254  62                                 |
|                                                                 133 254 187   5                                 |
|                                                               9 205 248  58                                     |
|                                                             126 254 182                                         |
|                                                          75 251 240  57                                         |
|                                                      19 221 254 166                                             |
|                                                   3 203 254 219  35                                             |
|                                                  38 254 254  77                                                 |
|                                              31 224 254 115   1                                                 |
|                                             133 254 254  52                                                     |
|                                          61 242 254 254  52                                                     |
|                                         121 254 254 219  40                                                     |
|                                         121 254 207  18                                                         |
|                                                                                                                 |
|_________________________________________________________________________________________________________________|

For more information about mnist-ready you can call the info method of MnistDataset:

puts "\n#{MnistDataset.instance.info}"

MNIST-READY 1.1.1 (2023)
Author: Sergio Oliveira Jr
LinkedIn: https://www.linkedin.com/in/soliveira/
URL: https://github.com/saoj/mnist-ready
License: MIT

Total number of digits: 70000
  "0" => 6903
  "1" => 7877
  "2" => 6990
  "3" => 7141
  "4" => 6824
  "5" => 6313
  "6" => 6876
  "7" => 7293
  "8" => 6825
  "9" => 6958

Total number of train digits: 60000
  "0" => 5923
  "1" => 6742
  "2" => 5958
  "3" => 6131
  "4" => 5842
  "5" => 5421
  "6" => 5918
  "7" => 6265
  "8" => 5851
  "9" => 5949

Total number of test digits: 10000
  "0" => 980
  "1" => 1135
  "2" => 1032
  "3" => 1010
  "4" => 982
  "5" => 892
  "6" => 958
  "7" => 1028
  "8" => 974
  "9" => 1009

 ____________________________ 
|            1               |
|----------------------------|
|                            |
|                  ,p$_      |
|                 ^w$$+      |
|                 x$$$+      |
|                -8$$Q'      |
|               +M$$$~       |
|               ($$$p        |
|               o$$$)        |
|              [$$$*i        |
|             ^Z$$*!         |
|             _$$$x          |
|            i&$$%[          |
|           ,#$$%)           |
|           t$$$J            |
|          }B$$a             |
|          p$$aI             |
|         +$$$q              |
|        -M$$$-              |
|        #$$&x^              |
|        #$WL                |
|        #$~                 |
|____________________________|

Showing the Image on the Terminal (iTerm2)

You need to install the imagemagick native library and then the rmagick gem

For Mac:

brew install imagemagick

For Linux (Ubuntu):

sudo apt-get update
sudo apt-get install imagemagick libmagickwand-dev

Then install the gem rmagick

gem install rmagick

Then go ahead and have fun:

Roadmap

• Port it to Python which is a more popular programming language for AI
• DONE => Option for the instance method show_progress so that you can see the progress as the digits are being loaded to memory
• DONE => Option for the instance method just_one so that you can load only one digit for testing instead of the whole thing
• Provide an option to load the digits one by one from disk, instead of loading them all to memory
• Provide a shuffle message to shuffle all arrays: train, test and all (this can be easily done by the user, but we should offer that for convenience)
• DONE => Show the real image on the terminal