Edible Oil Seed Dataset
Description
Edible Oil Seed Dataset :- The Oil seed classification plays a critical role in the agricultural and industrial sectors, aiding in quality control, sorting, and automation of processing systems. With the rise of machine learning and deep learning technologies, there is a growing need for high-quality, labeled datasets that can support the development and testing of classification models. This paper introduces the Edible Oil Seed Dataset, a carefully curated collection of 10,111 images across six widely cultivated oil seed types: Black Sesame, Groundnut, Mustard, Soybean, Sunflower, and White Sesame. Captured using a high-resolution mobile imaging system with burst-shot capabilities, each image has undergone preprocessing steps such as resizing, normalization, and labeling to ensure suitability for machine learning applications. The dataset provides a solid foundation for tasks involving computer vision in agriculture, such as real-time seed sorting, quality assessment, and educational demonstrations of classification algorithms. Representing six categories:- 1. Black Sesame Seeds - 1850 2. Groundnuts - 3000 3. Mustard Seeds - 1500 4. Soybean Seeds - 1531 5. Sunflower Seeds -1569 6. White Sesame Seeds - 661 Total Images= 10,111 Device Specifications:- - Primary Camera: Device Model: Xiaomi Redmi 10C - 50 MP sensor, f/1.8 aperture, 26mm (wide), PDAF - Secondary Camera: Device Model: Xiaomi Redmi Note 7S - 48 MP sensor, f/1.8 aperture, 1/2.0" sensor size, 0.8µm pixel size, PDAF - Features: Dual - LED flash, HDR - Modes Used: Burst Shot Mode (capturing 20+ frames for optimal image selection) This dataset is intended to bridge the gap between theoretical research and real-world application, making it a valuable resource for developers, researchers, and educators aiming to implement or explore seed classification using artificial intelligence techniques. Its versatility supports diverse use cases from research and development to practical deployment in smart agricultural systems.