Nonlinear spike-and-slab sparse coding for interpretable image encoding. PLOS ONE

The data was generated using the Python Image Library (PIL) to draw hundreds of overlapping edges/strokes in a 256 × 256 pixel image: each stroke had an integer intensity between (1, 255), a width between (2, 4) pixels, and a length, starting, and ending position drawn independently from a uniform distribution.

The image was then cut into overlapping D = 9 × 9 patches, each of which contained k ∈ (0, 5) overlapping strokes, for N = 61009. Gaussian noise of σ = 25 and μ = 0 was then independently added to each patch. Additionally, the dataset also contains the corresponding (automatically obtained) labels for each image, indicating the ground-truth number of occluding strokes k ∈ (0, 5) per image.