Annotated Banana Ripeness Stage Dataset

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Authors: Natiq-Ul-Haque Rohit, Abu Raihan, Afia Sarkar, Fahima Tabassum, Aziza Haque
Cited by: 0

Abstract

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: 673 Classes: Unripe, Ripe, Overripe Annotation Type: Bounding Boxes Dataset Format: YOLO v8 Data Split Ratio: 80% Train | 10% Validation | 10% Test Training Set: 538 images Testing Set: 68 images Validation Set: 67 images

Fields of Study & Subjects

Smart Agriculture and AI Advanced Neural Network Applications Industrial Vision Systems and Defect Detection

Publication details

Journal / source
Mendeley Data
Publication date
3 March 2026
Language
EN
Document type
Dataset