Image dataset of Pune city historical places for degradation detection, classification, and restoration

Historical and ancient murals hold clues to life in the past. This depicts the culture, worship styles, and social life of the community. This fascinates researchers and scholars who study historical bindings to showcase the modern world. Over time, most of these historical monuments have not been preserved in their original state. Most of these are affected due to natural climatic conditions, civil wars, and natural disasters. It remains clueless and imaginary about the size, shape, and color of the distorted historical monuments. This results in limitations for historical studies, archeological research, and geographical surveys. In this paper, we have studied the historical places around Pune city. Identified the locations where the monuments have been distorted and reconstructed recently. The construction age, type, color, shape, and size of the monuments are the major parameters of our study. Based on these criteria, we have captured images of these objects through different angles and camera lens. We have collected and categorized these images into folders with the names of historical places. This image dataset contains both captured and augmented images with distinct angles, scales, and directions. It also includes images captured in the daytime and evening with artificial lighting. This image dataset contains a variety of distinct image patterns that are useful as input to train computer-based supervised learning. The machine learning and deep learning algorithms perform efficiently if the input image dataset is large and distinct. Based on the predictive results generated by the machine learning and deep learning models, it is possible to virtually recreate the original monument. This would add a key value to historical research and studies.