Edible Oil Seed Dataset

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.食用油籽数据集（Edible Oil Seed Dataset）： 油籽分类在农业与工业领域均具有关键作用，可为质量管控、物料分拣及加工系统自动化提供重要支撑。随着机器学习与深度学习技术的发展，业界对高质量带标注数据集的需求日益增长，以支撑分类模型的开发与测试工作。本文介绍了食用油籽数据集（Edible Oil Seed Dataset），该数据集经精心整理，涵盖6种广泛种植的油籽品类，共计10111张图像，分别为黑芝麻、花生、芥子、大豆、向日葵籽与白芝麻。 本数据集采用具备连拍功能的高分辨率移动成像系统采集，所有图像均经过尺寸调整、归一化与标注等预处理步骤，以适配机器学习应用场景。该数据集可为农业计算机视觉相关任务提供坚实基础，包括实时籽类分拣、品质评估以及分类算法教学演示等。 本次数据集涵盖六大类别： 1. 黑芝麻籽：1850张 2. 花生：3000张 3. 芥子：1500张 4. 大豆籽：1531张 5. 向日葵籽：1569张 6. 白芝麻籽：661张 图像总数量：10111张 设备规格： - 主摄像头： 设备型号：小米Redmi 10C，搭载5000万像素传感器，光圈f/1.8，焦距26mm（广角），支持相位检测自动对焦（PDAF） - 副摄像头： 设备型号：小米Redmi Note 7S，搭载4800万像素传感器，光圈f/1.8，传感器尺寸1/2.0英寸，像素尺寸0.8μm，支持相位检测自动对焦（PDAF） - 附加功能：双LED闪光灯、高动态范围成像（HDR） - 拍摄模式：连拍模式（单次拍摄20帧以上，以挑选最优图像） 本数据集旨在填补理论研究与实际应用之间的鸿沟，可为开发者、研究者与教育工作者开展基于人工智能技术的籽类分类研究或落地应用提供宝贵资源。其通用性可覆盖从研发到智能农业系统实际部署等多样化应用场景。