The Cyprus Seasonal Flora Image Dataset (CSFID)

The dataset comprises a collection of 3,072 labelled training and 768 test images of 27 plant species commonly found in Cyprus. Each image represents a distinct flora class captured under real-world conditions, including herbs, shrubs, trees, and flowering plants. The images vary in lighting, background, and scale, making this dataset suitable for robust training and evaluation of multi-class plant classification models in machine learning and computer vision tasks.
It is designed to facilitate the training of convolutional neural networks (CNNs) and transfer learning architectures by offering naturally captured, high-variance imagery that reflects realistic environmental conditions such as varying lighting, occlusion, and background clutter. This dataset serves as a valuable resource for benchmarking plant classification algorithms and advancing the field of AI-assisted botanical studies.