SeasVeg: An Image Dataset of Bangladeshi Seasonal Vegetables

This dataset introduces a newly developed dataset named "SeasVeg," which includes Ten different types of seasonal vegetables from various regions in Pabna and Dhaka, Bangladesh. The ten different categories are Carica Papaya, Momordica dioica, Abelmoschus esculentus, Lablab purpureus, Trichosanthes cucumerina, Trichosanthes dioica, Solanum Iycopersicum, Brassica oleracea, Momordica charantia, Raphanus sativus. The dataset contains a total of 1,500 original images, along with an additional 3000 augmented images. We meticulously captured each original image under natural lighting conditions with an appropriate background. This comprehensive dataset holds immense potential for researchers in utilizing various ML and DL methods to advance the healthcare sector significantly. It is a valuable resource for future investigations, laying the foundation for crucial developments in these domains.本次介绍的是一款全新开发的蔬菜数据集——"SeasVeg"，其涵盖了来自孟加拉国巴布纳（Pabna）与达卡（Dhaka）不同区域的十种季节性蔬菜。这十个蔬菜类别分别为：番木瓜（Carica Papaya）、齿叶苦瓜（Momordica dioica）、秋葵（Abelmoschus esculentus）、扁豆（Lablab purpureus）、蛇瓜（Trichosanthes cucumerina）、印度栝楼（Trichosanthes dioica）、番茄（Solanum lycopersicum）、甘蓝（Brassica oleracea）、苦瓜（Momordica charantia）以及萝卜（Raphanus sativus）。该数据集共包含1500张原始图像，以及额外3000张增强图像。研究团队在自然光照条件下搭配适宜背景，对每张原始图像进行了精细化拍摄。这款完备的数据集具备极高的应用潜力，可支持机器学习（Machine Learning, ML）与深度学习（Deep Learning, DL）领域的研究者运用各类方法，显著推动医疗保健行业的发展。它是支撑未来相关研究的宝贵资源，为该领域的关键技术突破奠定了坚实基础。