UniqAI/gaussian-splatting
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@ -305,7 +305,11 @@ The SIBR interface provides several methods of navigating the scene. By default,
### Running the Network Viewer ### Running the Network Viewer
https://github.com/graphdeco-inria/gaussian-splatting/assets/40643808/9fe09f3b-32a7-4889-ae4e-227c999298cf
https://github.com/graphdeco-inria/gaussian-splatting/assets/40643808/90a2e4d3-cf2e-4633-b35f-bfe284e28ff7
After extracting or installing the viewers, you may run the compiled ```SIBR_remoteGaussian_app[_config]``` app in ```<SIBR install dir>/bin```, e.g.: After extracting or installing the viewers, you may run the compiled ```SIBR_remoteGaussian_app[_config]``` app in ```<SIBR install dir>/bin```, e.g.:
```shell ```shell
@ -333,7 +337,11 @@ The network viewer allows you to connect to a running training process on the sa
### Running the Real-Time Viewer ### Running the Real-Time Viewer
https://github.com/graphdeco-inria/gaussian-splatting/assets/40643808/9aa239af-67f9-4f9e-ba5b-d0132ccc06a0
https://github.com/graphdeco-inria/gaussian-splatting/assets/40643808/0940547f-1d82-4c2f-a616-44eabbf0f816
After extracting or installing the viewers, you may run the compiled ```SIBR_gaussianViewer_app[_config]``` app in ```<SIBR install dir>/bin```, e.g.: After extracting or installing the viewers, you may run the compiled ```SIBR_gaussianViewer_app[_config]``` app in ```<SIBR install dir>/bin```, e.g.:
@ -382,4 +390,4 @@ Alternatively, you can use the optional parameters ```--colmap_executable``` and
- *How can I use the differentiable Gaussian rasterizer for my own project?* Easy, it is included in this repo as a submodule ```diff-gaussian-rasterization```. Feel free to check out and install the package. It's not really documented, but using it from the Python side is very straightforward (cf. ```gaussian_renderer/__init__.py```). - *How can I use the differentiable Gaussian rasterizer for my own project?* Easy, it is included in this repo as a submodule ```diff-gaussian-rasterization```. Feel free to check out and install the package. It's not really documented, but using it from the Python side is very straightforward (cf. ```gaussian_renderer/__init__.py```).
- *Something is broken, how did this happen?* We tried hard to provide a solid and comprehensible basis to make use of the paper's method. We have refactored the code quite a bit, but we have limited capacity to test all possible usage scenarios. Thus, if part of the website, the code or the performance is lacking, please create an issue. If we find the time, we will do our best to address it. - *Something is broken, how did this happen?* We tried hard to provide a solid and comprehensible basis to make use of the paper's method. We have refactored the code quite a bit, but we have limited capacity to test all possible usage scenarios. Thus, if part of the website, the code or the performance is lacking, please create an issue. If we find the time, we will do our best to address it.