Annotated Banana Ripeness Stage Dataset

This dataset consists of high-resolution images of bananas categorized into three distinct ripeness stages: unripe, ripe, and overripe. Each image contains manual bounding box annotations to support object detection and classification tasks in agricultural computer vision. The project was conducted under the supervision of Md. Abu Raihan, with contributions from the research team regarding data collection and image labeling. This dataset is intended for training machine learning models to automate quality assessment in the food supply chain. Dataset Specifications: Primary Subject: Musa acuminata (Banana) Total Image Count: 819 Classes: Unripe, Ripe, Overripe Annotation Type: Bounding Boxes Dataset Format: YOLO v8 Data Split Ratio: 75% Train | 15% Validation | 15% Test Training Set: 573 images Testing Set: 125 images Validation Set: 121 images