Creating a good public health environment can improve the public’s environmental health literacy level. Therefore, we propose a street art image retrieval system to address the problems of artists’ single creation method and the exhaustion of creative inspiration in the process of creating street art images in a public health environment. The system can retrieve the relevant image categories and cultural backgrounds, according to the street art images to be drawn, which reduces the artists’ creation burden and helps the public to better appreciate and understand art. In the image classification module, a ResNet34 street art image classification network with a nonlocal attention mechanism is proposed by combining the characteristics of street art images. The experimental results show that the method can achieve accurate classification of art images and can accurately retrieve relevant images based on the input art images, helping artists to better create and improve the public health environment.