A dataset of medicinal plant leaves from Bangladesh

This dataset contains a collection of 1,094 original JPG images of medicinal leaves, captured in natural conditions from the rural jungle area of Guadanga village, Phulpur, Mymensingh, Bangladesh. The images are organized into six folders, each representing a distinct and commonly found medicinal plant species: • Centella Asiatica • Coccinia Grandis • Eclipta Prostrata • Mikania Micrantha • Murraya Koenigii • Stephania Japonica The original leaf images were captured using two high-resolution smartphone cameras — Google Pixel 5 and Google Pixel 6a — to ensure clear and detailed visuals suitable for a variety of machine learning and image processing tasks. All images are unprocessed, making the dataset ideal for researchers who wish to work with real-world, raw image data. To support the development of deeper and more robust deep learning models, this dataset also includes 2,188 augmented JPG images, generated from the original set using standard image augmentation techniques. These augmentations help improve generalization and model performance on complex leaf classification tasks. Dataset Summary: Total Images: Original: 1,094 JPG images Augmented: 2,188 JPG images Plant Classes: 6 distinct medicinal plant species Image Format: JPG Image Organization: Organized into 6 folders named after plant species Capture Devices: Google Pixel 5 and Google Pixel 6a Source Location: Jungle of Guadanga, Phulpur, Mymensingh, Bangladesh Purpose: Suitable for tasks such as medicinal plant classification, leaf recognition, image segmentation, and deep learning-based botanical analysis. This dataset provides a rich and realistic foundation for researchers and practitioners working in domains such as plant pathology, botany, herbal medicine identification, and AI-driven agriculture.本数据集收录1094张原始JPG（Joint Photographic Experts Group，联合图像专家组）格式药用叶片图像，所有图像均采集自孟加拉国迈门辛县普尔布尔区瓜丹加村的乡村丛林自然环境。图像被划分为6个文件夹，每个文件夹对应一种独特且常见的药用植物物种： • 积雪草（Centella Asiatica） • 红瓜（Coccinia Grandis） • 鳢肠（Eclipta Prostrata） • 微甘菊（Mikania Micrantha） • 九里香（Murraya Koenigii） • 千金藤（Stephania Japonica） 原始叶片图像采用谷歌Pixel 5与谷歌Pixel 6a两款高分辨率智能手机拍摄，以确保画面清晰、细节丰富，可适配各类机器学习与图像处理任务。所有图像均未经过后期处理，非常适合希望使用真实原生图像数据开展研究的科研人员。 为支持开发更深层、更鲁棒的深度学习模型，本数据集还包含2188张增强版JPG格式图像，这些图像由原始数据集通过标准图像增强技术生成，可提升复杂叶片分类任务中的模型泛化能力与性能表现。 数据集概况： 总图像量： 原始图像：1094张JPG格式图像 增强图像：2188张JPG格式图像 植物类别：6种独特的药用植物物种 图像格式：JPG格式 图像组织方式：按植物物种名称分为6个文件夹 拍摄设备：谷歌Pixel 5与谷歌Pixel 6a 采集地点：孟加拉国迈门辛县普尔布尔区瓜丹加村丛林 适用任务：适用于药用植物分类、叶片识别、图像分割以及基于深度学习的植物学分析等任务。 本数据集为植物病理学、植物学、草药鉴定以及人工智能驱动农业等领域的研究人员与从业者提供了丰富且贴合真实场景的研究基础。