Research on 3D Rendering Effect of Marine Bionic Packaging Container Based on Deep Learning and Visualization

Three-dimensional rendering includes the test of system development environment and running environment. Three-dimensional rendering influencing factors test: the number and size of parallel blocks affect the average rendering frame rate of 26.9 when the number is 9600 and the size is 10 × 10, and the average rendering frame rate is 13.7 when the number is 600 and the size is 40 × 40. According to relevant data, it is inferred that the average rendering frame rate is higher when the number of parallel blocks is large and the size of parallel blocks is small, and the number is inversely proportional to the size. The rendering window size also has a relative influence on the rendering frame rate. When the window size is 600 × 400, only the terrain frame rate is 77.3, and when the window size is 1200 × 800, the frame rate is 68.1, which shows that when only the terrain frame rate is rendered, the frame rate decreases with the increase in the window size, and its performance is not high when only CPU is used. However, when CPU is combined with GPU, the performance is greatly improved, reaching the highest of 29.3 and the lowest of 21.5, which is much higher than that when only CPU is used. According to the influence of the number of sampling points on the frame rate, the 5 × 5 sampling method and 2 × 2 sampling method proposed in this paper have better frame rate performance than the traditional template shadow method. Through the above data, we know that the number of parallel blocks, size, window size, sampling method, and other factors have a certain impact on the average rendering frame rate. Marine bionics is a marginal subject between marine biology and technical engineering science. Deep networks have had a huge impact on the field of machine learning research and application, but at the same time, they cannot clearly explain the ins and outs of deep networks. People have been working to understand the complex process more thoroughly. Since humans’ cognition and experience of the world mainly come from vision, good visualization can effectively help people understand the deep network and perform effective optimization and adjustment.