Image Dataset for Disease Detection in Sponge Gourd (Luffa aegyptiaca) Leaves

Dataset Purpose: Annotated images of sponge gourd (Luffa aegyptiaca) leaves for disease detection and classification.

Location: Collected from multiple regions in Bangladesh.

Leaf Categories: Five distinct disease categories, each with specific characteristics:
Fresh Leaf: Healthy, non-diseased leaves.
Mosaic Leaf: Leaves with mosaic patterns caused by viral infections.
Insect Disease Leaf: Leaves damaged and discolored by insect infestations.
Downy Mildew: Fungal infection marked by pale yellow spots and powdery growth.
Bacterial Leaf Spot Disease: Necrotic spots on leaves due to bacterial infections.

Applications: Supports the development and evaluation of machine learning models for disease detection in sponge gourd cultivation.

Audience: Useful for researchers and practitioners in agriculture, plant pathology, and computer vision.

Dataset Features: Images are annotated and labeled, providing a comprehensive resource for automated disease classification in plants.

数据集目的：本数据集收录了丝瓜（Luffa aegyptiaca）叶片的标注图像，旨在用于疾病检测与分类。采集地点：图像数据来源于孟加拉国多个区域。叶片类别：包含五种独特的疾病类别，每种类别具有特定的特征：新鲜叶片：健康、无病害的叶片；花叶：由病毒感染引起的花斑状叶片；虫害叶片：昆虫侵害导致的叶片损伤和变色；白粉病：以淡黄色斑点及粉末状生长物为特征的真菌感染；细菌性叶斑病：由细菌感染引起的叶片坏死斑点。应用：本数据集支持机器学习模型在丝瓜栽培中的疾病检测开发与评估。受众：对农业、植物病理学和计算机视觉领域的科研人员和从业者具有实用价值。数据集特性：图像已进行标注和标签化，为植物自动疾病分类提供了全面资源。