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.面向图像分割的多类杂草数据集包含两类杂草：裸柱菊（Soliva Sessilis，Field Burrweed）与遏蓝菜（Thlaspi Arvense L.，Field Pennycress）。该数据集的杂草图像采集于印度北方邦戈勒克布尔市一处茄子农场的田间环境，拍摄对象为处于早期生长阶段的杂草。数据集共包含7872张增强图像及其对应的分割掩码。图像通过多款智能手机相机拍摄，以RGB色彩格式存储，文件格式为JPEG。采集到的原始图像通过LabelMe标注工具（labelme）进行标注，以生成分割掩码。随后对原始数据集进行数据增强，得到最终的数据集。