This project is an attempt to combine data visualization and photography in a simple, intuitive and flexible way. Pictures contain objects of various kinds and shapes, that are positioned in a certain place within the picture's frame. The question, where a specific object is located in a photograph is answered here with a histogram. The histogram is simply the count of the object's pixels in vertical direction, for each pixel column along the photo's horizontal direction.

To be more exact, for each pixel along the x-axis, we look upwards and count the pixels making up the object of interest for that part of the x-axis. The object of interest is thus labelling the y-axis, making the resulting histogram a 1-dimensional representation of its 2-dimensional picture. Colour codes can be used to highlight various objects, that fit the common label chosen for the y-axis, as shown in both examples, where the histogram shows the left and right foot separately (above), or different stereotypes of the Russian culture (below).

For the histogram's creation, a bit of manual work is required at first to outline the shapes of interest. These shapes are turned completely white and the rest of the photograph is recoloured black. Then a small python script is reading these preprocessed pictures, turning every white pixel into a "1", every black pixel into a "0", summing it up along the y-axis and returning the histogram data in csv-format. The csv-file can then be used to draw the histogram's bars and the initial photograph can be combined with the visualization of its data.