The dataset is split between train, test and val folders.

Files consist of 60 seconds recordings that were cut from longer recording sessions. Cuts from a single recording session are all in the same training split.

Each dat file is a binary file in which events are encoded using 4 bytes (unsigned int32) for the timestamps and 4 bytes (unsigned int32) for the data, encoding is little-endian ordering.

The data is composed of 14 bits for the x position, 14 bits for the y position and 1 bit for the polarity (encoded as -1/1).

Annotations use the numpy format and can simply be loaded form python using numpy boxes = np.load(path)

Boxes have the following fields:

• x abscissa of the top left corner in pixels
• y ordinate of the top left corner in pixels
• w width of the boxes in pixel
• h height of the boxes in pixel
• ts timestamp of the box in the sequence in microseconds
• class_id 0 for pedestrians, 1 for two wheelers, 2 for cars, 3 for trucks, 4 for buses, 5 for traffic signs, 6 for traffic lights