CherryLeaf-KG: Four-Class Cherry Leaf Disease Image Dataset with Uzbek Labels

This dataset contains 400 cherry tree leaf images collected from active farms in Uch-Korgon village (Kadamzhay District, Batken Region, Kyrgyzstan) using an iPhone 14. Images were captured across three separate farms in July, shortly after the June cherry harvest, from mature trees of at least ten years old. The dataset is organized into four classes, named in Uzbek as used by local growers: Sarik (leaf yellowing / chlorosis, 100 images), Teshik (shot-hole disease with perforations, 100 images), Chirish (brown rot with decaying tissue, 100 images), and Soglom (healthy leaf, 100 images). All images were captured under real outdoor farm conditions, naturally including variations in illumination, leaf orientation, shadows, occlusions, and background clutter. Each image was manually annotated using makesense.ai, with a bounding box drawn around the central leaf. Images were then cropped and standardized into square format at 224x224 pixels. This dataset is designed as a benchmark for evaluating few-shot and zero-shot learning methods in real-world, resource-constrained agricultural settings, and serves as a cross-lingual test case due to its Uzbek-language class labels.