Unripen Papaya Image Dataset for Classification Using Deep Learning

This dataset contains 1,500 images of unripe papaya fruits collected under different lighting conditions, orientations, and backgrounds for deep learning and image processing applications. The images were acquired using a digital camera and organized for classification tasks. The dataset can be used to develop, train, validate, and evaluate machine learning and deep learning models for automated papaya fruit maturity assessment, fruit recognition, and agricultural quality monitoring. The images provide visual information such as color, texture, and shape characteristics of unripe papaya fruits, making the dataset suitable for computer vision research in precision agriculture and postharvest technology.