Context

The goal of this dataset is to classify an image of a handwritten letter into one of 33 categories/letters of Russian alphabet using the deep learning technologies (computer vision).

Content

The dataset includes a folder with the total of 14190 PNG format images.

It also has a file describing each image. This information file contains 4 columns:

• letter (in cyrillic);
• label (a number corresponding to that letter, see below);
• file (the name of a file with this image);
• background (a label corresponding to the background of an image, see below).

Letter Symbols => Letter Labels:

а=>1, б=>2, в=>3, г=>4, д=>5, е=>6, ё=>7, ж=>8, з=>9, и=>10, й=>11, к=>12, л=>13, м=>14, н=>15, о=>16, п=>17, р=>18, с=>19, т=>20, у=>21, ф=>22, х=>23, ц=>24, ч=>25, ш=>26, щ=>27, ъ=>28, ы=>29, ь=>30, э=>31, ю=>32, я=>33

Image Backgrounds => Background Labels:

striped=>0 gridded=>1 no background=>2 graph paper=>3

Acknowledgements

The original dataset has been prepared and uploaded by Olga Belitskaya. This is only a more structured and convenient for beginners version of it. The original dataset was uploaded for unlimited public use, so this dataset inherits that license.