BDEggs: A comprehensive image dataset of different types of eggs from birds in Bangladesh

Published: 15 November 2023| Version 1 | DOI: 10.17632/3766fb76w6.1
Arnab Hasin Anon, Sariful Sarkar, Shahzadi Marufa Hakim, Roufin Ahmed, Md. Wahidur Rahman, Mohammad Motiur Rahman


Introducing the dataset “BDEggs”, a distinguishable collection of eight bird egg species commonly found across all of Bangladesh. With a focus on providing comprehensive information, this dataset encompasses eight distinct species of eggs, including: 1. Budgerigar (Melopsittacus undulatus), 2. Domestic pigeon (Columba livia domestica), 3. Domestic duck (Anas platyrhynchos domesticus), 4. Broiler chicken (Gallus gallus domesticus) 5. Country chicken (Gallus gallus domesticus) 6. Quail (Coturnix coturnix), 7. Guinea Fowl (Numididae), 8. China duck (Anas zonorhyncha) Our team has painstakingly gathered a total of 1200 original images. Each original image was diligently captured with natural lighting and an appropriate background, ensuring utmost attention to detail. We dedicated two months, from August 20, 2023, to September 24, 2023, to collect these images from various areas within the Dhaka division. This comprehensive dataset holds immense potential for researchers to leverage advanced machine learning and deep learning techniques in order to drive meaningful advancements in the agricultural sector. As a valuable resource, it paves the way for groundbreaking discoveries in these fields in the future.


Steps to reproduce

The dataset was acquired through several systematic steps. First and foremost, we explored the study of Bangladeshi eggs and the various species that are found in our local Dhaka regions. Then, we went to some cattle stores, local farmer houses, and a local farm in Dhaka District to collect eggs. Subsequently, we diligently collected raw images of these species from various locations. The raw images were collected using the cameras of the Vivo Y21t, the Oppo F17, and the iPhone X. The dataset consists of a total of 1200 raw images. The extensive dataset will greatly assist researchers in contributing to image classification and various machine learning and deep learning techniques.


Uttara University


Agricultural Science, Animal Feed, Animal Feeding, Machine Learning, Dairy Cattle, Poultry, Image Classification, Agricultural Development, Deep Learning, Nutrition Security