Dataset INCAFO - Grapevine variety identification using leaves
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This dataset contains multiple samples of grapevine leaves for variety identification. The data identified the most common grapevine varieties in Portugal and some of the most common in Europe. The current dataset was designed for image classification in a Tree Folder Structure Data characterization The data is composed of digitalized images in multiple forms. The leaves were digitalized with a neutral background for easier differentiation. The original images were resized for a workable size: (512 x 428) px. The peduncle is removed for each leaf, and the leaf is flattened. Most of the images have to be preprocessed for label removal. Dataset characterization The dataset has 37 classes: Alfrocheiro Alicante Bouschet Alvarinho Antão Vaz Aragonez Arinto Arinto dos Açores Baga Bical Boal Espinho Cabernet Sauvignon Castelão Cercial Chardonnay Encruzado Fernão Pires Gouveio Jaen Loureiro Malvasia Fina Moreto Negra Mole Rufete Sercial Síria Syrah Terrantez do Pico Tinta Barroca Tinta Negra Tinto Cão Touriga Franca Touriga Nacional Trajadura Trincadeira Verdelho Vinhão Viosinho The dataset follows an Image Tree Folder structure, such as train class 1 img.jpg ... ... test class 1 img.jpg ... ... val class 1 img.jpg ... ...
本数据集包含多份用于葡萄品种识别的葡萄叶片样本，涵盖葡萄牙本土最常见的葡萄品种，以及部分欧洲主流栽培品种。 本数据集专为图像分类任务设计，采用树形文件夹结构进行组织。 ### 数据特征 本数据集由多种形式的数字化图像构成。所有叶片均以中性背景拍摄，便于后续区分识别。原始图像已被统一调整至可用尺寸：(512 × 428) 像素。 每片叶片均已移除叶柄，并进行展平处理。多数图像需进行标签移除预处理。 ### 数据集特征 本数据集共包含37个分类类别，具体如下： Alfrocheiro Alicante Bouschet Alvarinho Antão Vaz Aragonez Arinto Arinto dos Açores Baga Bical Boal Espinho Cabernet Sauvignon Castelão Cercial Chardonnay Encruzado Fernão Pires Gouveio Jaen Loureiro Malvasia Fina Moreto Negra Mole Rufete Sercial Síria Syrah Terrantez do Pico Tinta Barroca Tinta Negra Tinto Cão Touriga Franca Touriga Nacional Trajadura Trincadeira Verdelho Vinhão Viosinho 本数据集遵循图像树形文件夹结构，示例如下： train ├── 类别1 │ ├── img.jpg │ └── ... └── ... test ├── 类别1 │ ├── img.jpg │ └── ... └── ... val ├── 类别1 │ ├── img.jpg │ └── ... └── ...
