We regret not having results for the texturing process here, but that will be rectified in the future. Support for AMD GPUs has been requested by the community, but are not supported at this time. an NVIDIA card made in the last few years. The mesh process, along with texturing and shading, all require a CUDA GPU, i.e. With non-CUDA GPUs, Realit圜apture will generate a sparse point cloud, which is basically image alignment and feature detection on the images projected into 3D. NVIDIA Quadro RTX 4000 (8GB, Quadro 441.66)Īs the graphics card list above hints, Realit圜apture is suited for those with NVIDIA graphics cards, as it has crucial operations that require CUDA. NVIDIA GeForce GTX 1660 Ti (6GB, GeForce 441.66) NVIDIA GeForce GTX 1080 Ti (11GB, GeForce 441.66) NVIDIA GeForce RTX 2060 (6GB, GeForce 441.66) NVIDIA GeForce RTX 2060 SUPER (8GB, GeForce 441.66) NVIDIA GeForce RTX 2070 SUPER (8GB, GeForce 441.66) NVIDIA GeForce RTX 2080 SUPER (8GB, GeForce 441.66) NVIDIA GeForce RTX 2080 Ti (11GB, GeForce 441.66) With that preamble out-of-the-way, here’s a look at the test system used: That will be included in the future, along with CPU performance in the next article. One thing we goofed on is not having also tested texture generation performance, as we had not configured the settings correctly. This isn’t a perfectly shot project, but that doesn’t impact the test in any way. That produces similar to what you see above. In our test, we drop 123 photos that Techgage Senior Editor Jamie Fletcher took of an ATX motherboard and CPU cooler into the software, and hit start.
Given the lack of CPU performance here, we feel like this article is a bit lacking, but it’s a start, and will improve the next time we do a full round of testing.
Instead, the proper way to see accurate times is with the report option in the software itself. RC stores a log file around the file system that we thought would give us an accurate result inside, but it doesn’t. The reason we’re kicking off our look at Realit圜apture with only GPUs in focus is because our original CPU-based testing was flawed, so we don’t currently have useful data to share.