Published: 8 March 2021| Version 1 | DOI: 10.17632/tczzndbprx.1
Samrat Kumar Dey,


Traditional Bangladeshi food image classification has become immensely relevant for a variety of reasons, including restaurant selection, travel destination selection, dietary caloric intake, and cultural awareness. However, this is highly challenging to design an effective and useable traditional labelled (English and Bengali) food dataset of Bangladesh for the research purpose. The ‘DeshiFoodBD’ dataset is presented in this article for traditional Bangladeshi food classification purposes. The food images come from two different sources: 1) web scraping and 2) camera (digital, smartphone). The dataset contains 5425-labelled images of 19 famous Bangladeshi foods such as biriyani, kalavuna, roshgolla, hilsha fish, nehari, and so on. The dataset can be used with a variety of CNN architectures, including ResNet50, YOLO, VGG-16, R-CNN, and DPM.



Military Institute of Science and Technology, Dhaka International University


Image Classification, Recognition, Image Analysis of Food, Traditional Food, Food Application of Computer Vision