DESIGN AND IMPLEMENTATION OF A PYTHON-BASED SYSTEM FOR NANYANG HAN DYNASTY STONE RELIEF RESOURCES RESTORATION AND VISUALIZATION

Abstract

The Han dynasty stone reliefs in Nanyang are an important part of China's historical and cultural heritage, with high historical, artistic, and archaeological value. However, due to long-term natural weathering, environmental erosion, and human damage, many of these stone reliefs have problems like cracks, missing parts, dirt, and blurred patterns, which seriously affect their digital preservation and academic research. Currently, the management of Han painting resources generally faces issues such as scattered data, low search efficiency, and a lack of intelligent analysis tools. To address this, we designed and implemented a Python-based system for restoring and visually analyzing Nanyang Han paintings. The system uses a B/S structure, is developed with the Django framework, uses a MySQL database as a central data storage, combines Bootstrap for front-end design, and employs ECharts for multi-dimensional visual analysis. For image restoration, the system introduces a deep learning image repair model that can automatically fill in damaged areas of the stone reliefs and reconstruct patterns. For resource management, it allows adding, deleting, updating, and retrieving Han painting resource information along with categorized management. For visual analysis, it supports multi-dimensional statistical analysis like distribution by era, theme classification, excavation sites, and preservation status, and also provides word cloud analysis, combined searches, and Excel data export. Test results show that the system is stable, user-friendly, and can effectively improve the digital preservation, resource management, and academic research efficiency of the Nanyang Han dynasty stone reliefs.