RaspberryJalisco: A multi-class dataset on the phenological stages of Rubus idaeus with YOLOv8 annotations

We present an multi-class annotated image dataset of raspberry (Rubus idaeus) fruits at distinct phenological stages. The images were field-collected, captured in a commercial orchard located in the municipality of Jocotepec, Jalisco, Mexico, during the months of November and December 2025.The dataset has in total 11,884 images with 174,763 bounding-box annotations. These are distributed across two complementary labeling schemes. The first one is a fine-grained 5-class configuration: Bud, BrightRed C4, DarkRed C5, Green, and Orange (red dot). The second one is a coarser 3-class configuration: Immature, BrightRed C4, and Orange (red dot). The dataset is oriented towards yield-prediction tasks.The images were acquired with a DSLR camera under natural midday illumination and manually annotated by a team of three domain-expert annotators using LabelImg. Then they were curated nd split via Roboflow into training (70 %), validation (20 %), and test (10 %) subsets.All annotations follow the YOLO normalized format and are provided as plain-text files alongside a descriptor in yaml format.This dataset is the first publicly available annotated one of raspberry orchards under Mexican tropical growing conditions. This resource provides a valuable benchmark for precision-agriculture researchers, plant phenotyping specialists, and machine-learning practitioners working on fruit detection, counting, and harvest-volume estimation. The directory is organized as follows RaspberryJalisco: train: (8318 photographs with annotations) images labels valid: (2378 photographs with annotations) images labels test: (1188 photographs with annotations) images labels data_3classes.yaml data_5classes.yaml The "images" folders contain the photographs in JPEG format, with a resolution of 2000x1500 pixels. The "labels" folders contain the annotations in the format expected by YOLOv8 (<class_id> <x_center> <y_center> <width> <height>), in plain text (.txt) files. The YAML files have the class classifications and names.