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BD Sports-10: A comprehensive video dataset for Bangladeshi sports classification and analysis
Wazih Ullah Tanzim1, Niloy Barua Supta1, Shifatun Nur Shifa1
1Department of Computer Science and Engineering, Premier University, Academic Building #4, 44, Hazari Lane, Kotwali, Chattogram 4000, Bangladesh.
Abstract:
Bangladesh has diverse and vibrant cultural sports, some of which have gained international recognition in recent years. However, there is a lack of standardized datasets for deep learning and computer vision tasks. To address this gap, BD Sports-10 was developed as a comprehensive dataset for Bangladeshi sports. It consists of ten unique sports categories, with a total of 3000 videos, 300 per class, with a resolution of 1920×1080 pixels and 30 frames per second (FPS). Each sport in the dataset features distinct rules, viewing angles, playground setups, and actions, which also depend on players' skills. The dataset captures a diverse range of actions, including jumping, running, tagging, throwing, attempting to hit a clay pot, and capturing an opponent before they cross a designated line. BD Sports-10 includes ten traditional and culturally significant sports: Kabaddi, Nouka Baich, Lathi Khela, Kho Kho, Kanamachi, Toilakto Kolagach Arohon (Kolagach), Hari Vanga, Morog Lorai, Lathim, and Joldanga. This standardized and balanced dataset is not only suitable for classification tasks but also for object detection, player tracking, and automated scoring systems. The dataset supports research in deep learning, machine learning, and computer vision by providing ready-to-use scripts, datasets, and preprocessing pipelines that facilitate diverse AI-based experimental workflows.
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