Text detection
SYPHAXAR dataset is a dataset for Arabic text detection in the wild. It was collected from Tunisia in “Sfax” city, the second largest Tunisian city after the capital. A total of 3078 images were gathered through manual collection one by one, with each image energizing text detection challenges in nature according to real existing complexity of 15 different routes along with ring roads, intersections and roundabouts. These annotated images consist of more than 31000 objects, each of which is enclosed within a bounding box.
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SYPHAX dataset was collected from Tunisia in “Sfax” city, the second largest Tunisian city after the capital. A total of 2008 images were gathered through manual collection one by one, with each image energizing text detection challenges in nature according to real existing complexity of 15 different routes (downtown, Nasryia, Sidi Mansour, Sakiet Ezziet, Sakiet Eddayer, Mahdia road, Tunis main road, Chehia, Taniour, Lafran, Elayn, Gremda, Manzel Chaker, Matar route, Gabes road) along with ring roads, intersections and roundabouts.
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In recent years, it has become more difficult to identify road traffic signage and panel guide material. Few studies have been made to solve these two issues at the same time, especially in the Arabic language. Additionally, the limited number of datasets for traffic signs and panel guide content makes the investigation more interesting. the Tunisian research groups in intelligent machines of the University of Sfax (REGIM laboratory of Sfax) will provide the NaSTSArLaT dataset free to researchers in traffic detection signs and traffic road scene text detection.
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Today, the cameras are fixed everywhere, in streets, in vehicles, and in any public area. However, Analysis and extraction of information from images are required. Particularly, in autonomous vehicles and in smart applications that are developed to guide tourists. So, a large dataset of scene text images is an important and difficult factor in the extraction of textual information in natural images. It is the input to any computer vision system.
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