SpiceVision: An Image Classification Dataset with a Structured Knowledge Base of Bangladeshi Spices

Published: 2 March 2026| Version 1 | DOI: 10.17632/xpvm6d6k6h.1
Contributors:
Md Mijanur Rahman, Md Nahidul Islam, Tanjim Tabassum Urmi, Mst Nusrat Jahan Liza, Jannatul Ferdous Tuba, Masruful Alam, Aliva Tasnim Oshin Gani

Description

SpiceVision is a curated image dataset designed for image classification, retrieval, and food-related computer vision research with a specific focus on Bangladeshi spices. The dataset consists of 8000+ high-resolution RGB images representing 60 commonly used spices and spice blends in Bangladesh, with each class containing 100+ images to ensure class balance. Images were collected from local markets and household kitchens in Dhaka, Bangladesh, using multiple smartphone cameras under diverse real-world conditions. Variations include different lighting setups (daylight and indoor lighting), backgrounds (white, wooden surfaces, kitchen countertops), viewpoints (top-view, side-view, and close-up), and spice forms (whole, powdered, crushed, and blended). This diversity enhances model robustness and generalization. Each spice class is labeled with a unique class key. containing Bangla and English names, spice category, and common culinary usage. The dataset is organized in a folder-based structure suitable for direct use in machine learning pipelines. SpiceVision supports applications such as spice recognition, educational tools, smart kitchen systems,and retrieval-based food AI research, particularly in low-resource and multilingual contexts.

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Artificial Intelligence, Spice, Image Classification

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