Orchid2024: A cultivar-level dataset and methodology for fine-grained classification of Chinese Cymbidium Orchids

The authors dedicated over a year to collecting a cultivar image dataset for Chinese Cymbidium orchids named Orchid2024. This dataset contains over 150,000 images spanning 1,275 different categories, involving visits to 20 cities across 12 provincial administrative regions in China to gather pertinent data. Subsequently, we introduced various visual parameter-efficient fine-tuning (PEFT) methods to expedite model development, achieving the highest top-1 accuracy of 86.14% and top-5 accuracy of 95.44%.

本团队历时一年多，采集构建了一款针对中国兰属（Cymbidium）兰花栽培品种的图像数据集，命名为Orchid2024。该数据集共包含超15万张图像，涵盖1275个不同品种类别，采集期间团队先后走访了中国12个省级行政区的20座城市以收集相关数据。随后，本团队引入多种视觉参数高效微调（Parameter-Efficient Fine-Tuning，PEFT）方法以加快模型研发进度，最终取得了最高86.14%的Top-1准确率与95.44%的Top-5准确率。