  Significant number of researches have been developed recently around
intelligent system for traffic management, especially, OCR based license plate
recognition, as it is considered as a main step for any automatic traffic
management system. Good quality data sets are increasingly needed and produced
by the research community to improve the performance of those algorithms.
Furthermore, a special need of data is noted for countries having special
characters on their licence plates, like Morocco, where Arabic Alphabet is
used. In this work, we present a labeled open data set of circulation plates
taken in Morocco, for different type of vehicles, namely cars, trucks and
motorcycles. This data was collected manually and consists of 705 unique and
different images. Furthermore this data was labeled for plate segmentation and
for matriculation number OCR. Also, As we show in this paper, the data can be
enriched using data augmentation techniques to create training sets with few
thousands of images for different machine leaning and AI applications. We
present and compare a set of models built on this data. Also, we publish this
data as an open access data to encourage innovation and applications in the
field of OCR and image processing for traffic control and other applications
for transportation and heterogeneous vehicle management.
