The De La Salle University – Outdoor Mirrors and Reflective Surfaces (DLSU-OMRS) dataset contains 454 images of outdoor mirrors and reflective surfaces, along with their corresponding ground-truth masks for segmentation. The images were scraped from Shutterstock using the key phrases outdoor mirror and street mirror and manually filtered to remove duplicates and heavily manipulated photos. Ground-truth masks were produced through manual segmentation. The images have their respective licenses, and the ground-truth masks are licensed under the BSD 3-Clause "New" or "Revised" License. The use of this dataset is restricted to noncommercial purposes only. More details can be found in the paper "Designing a Lightweight Edge-Guided Convolutional Neural Network for Segmenting Mirrors and Reflective Surfaces," which was accepted for full paper presentation at the 2023 International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision (WSCG 2023). The project page is https://github.com/memgonzales/mirror-segmentation. The paper is published in Computer Science Research Notes: http://wscg.zcu.cz/WSCG2023/full/E59-full.pdf.