These images were generated using UnityEyes simulator, after including essential eyeball physiology elements and modeling binocular vision dynamics. The images are annotated with head pose and gaze direction information, besides 2D and 3D landmarks of eye's most important features. Additionally, the images are distributed into two classes denoting the status of the eye (Open for open eyes, Closed for closed eyes). This dataset was used to train a DNN model for detecting drowsiness status of a driver. The dataset contains 1,704 training images, 4,232 testing images and additional 4,103 images for improvements.