###### datasets

## • Kluth, Zetzsche (2015). Numerosity as a topological invariant.

Here you can find the datasets and the generating script as described in the article

T. Kluth, C. Zetzsche. Numerosity as a topological invariant. In *Journal of Vision*, 16(3):30, 1-39, 2016.

Download numerosity datasets (~200MB).

All datasets contain the numbers N ranging from 1 to 32. The cumulative area A for 100x100 pixel images is split into 8 levels from 288 to 2304 with a step of 288. For each combination (N,A) 200 samples are drawn such that in each number subfolder 1600 images can be found. They are sorted by the level of cumulative area, i.e. images 1-200 have A=288, images 201-400 have A=576, etc. The datasets are distinguished by the shape appearance of the objects:

TR - rectangular shape (training set)

R - rectangular shape

RC - tectangular shape with smoothed corners

C - circular shape

C1 - concave rectangular shape with q=90%q_square

C2 - concave rectangular shape with q=80%q_square

C3 - concave rectangular shape with q=70%q_square

RA - random shapes

RA200 - random shapes 200x200 pixels

RA400 - random shapes 400x400 pixels

All datasets contain images of size 100x100 pixels if not explicitly mentioned. For further information we refer to the related article (see above).