Missing Eggs on Tray Dataset For Empty Slots Detection

Abstract

This dataset is designed for computer vision–based detection of missing eggs on egg trays. It supports research and development of automated inspection systems in poultry farming and smart agriculture. The dataset contains annotated images of missing eggs in trays, where eggs may be missing, enabling object detection models to identify missing positions accurately. It is suitable for training and evaluating deep learning models such as YOLOv5, YOLOv8, Faster R-CNN, and SSD. The dataset aims to facilitate automated egg tray inspection, missing eggs detection, and the development of real-time egg theft control systems. The dataset contains two compressed files of egg images and corresponding labels. The images folder contains the raw visual data in .jpg format used for training and validating the object detection model. These images capture egg trays under different conditions, including trays with many missing eggs and trays with almost complete egg placement. Each image shows an egg tray captured from a top or near-top view, with variations in egg arrangements, camera distance, and angle. The dataset is also available on Kaggle Public repository as Missing_Egg Dataset.