Multiclass Weeds Dataset for Image Segmentation

The Multiclass Weeds Dataset for Image Segmentation comprises two species of weeds: Soliva Sessilis (Field Burrweed) and Thlaspi Arvense L. (Field Pennycress). Weed images were acquired during the early growth stage under field conditions in a brinjal farm located in Gorakhpur, Uttar Pradesh, India. The dataset contains 7872 augmented images and corresponding masks. Images were captured using various smartphone cameras and stored in RGB color format in JPEG format. The captured images were labeled using the labelme tool to generate segmented masks. Subsequently, the dataset was augmented to generate the final dataset.

搜集汇总

背景与挑战

背景概述

该数据集包含7872张增强图像及对应掩码，涵盖两种杂草（Soliva Sessilis和Thlaspi Arvense L.）在茄子田早期生长阶段的图像，用于图像分割和深度学习研究。图像使用智能手机拍摄，并通过labelme工具标注，适用于农业工程和作物保护领域。