This data article describes a dataset of images of common Chinese deities. The dataset is divided into five categories according to the types of deities, and a total of 1314 orig-inal images were captured by smart phones from Chinese temples and through Google search engine. Each category were split into training, validation and test subsets in a ratio of 70:20:10. We rotated the pictures by 30 & DEG;, 60 & DEG;, 90 & DEG;, 120 & DEG;, 150 & DEG;, and 180 & DEG;; and zoomed in and out to augment the im-ages for training and validation sets. After data enhancement, the total number of images reaches 10,786. Two models, EfficientNet-B0 and MobileNetV2, are used to identify five kinds of god images. After data augmentation, the accuracy, precision, recall, specificity and F1-score of EfficientNet-B0 were 96.15%, 96.44%, 96.18%, 96.16% and 97.60%, respectively; the accuracy, precision recall, specificity and F1-score of Mo-bileNetV2 were 92.31%, 92.89%, 92.37%, 92.33% and 95.19%, respectively. This dataset can be used as a reference for tra-ditional Chinese god statue images, and can also be used for object detection and image classification through machine learning and deep learning methods.(c) 2022 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ )