UniqAI/gaussian-splatting
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README.md
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@ -382,9 +382,24 @@ SIBR has many other functionalities, please see the [documentation](https://sibr
</details>
<br>
## Preprocessing your own Scenes
## Processing your own Scenes
Our rasterization requires a SIMPLE_PINHOLE or PINHOLE camera model for COLMAP data. We provide a converter script ```convert.py```, to extract undistorted images and SfM information. Optionally, you can use ImageMagick to resize the undistorted images. This rescaling is similar to MipNeRF360, i.e., it creates images with 1/2, 1/4 and 1/8 the original resolution in corresponding folders. To use them, please first install a recent version of COLMAP (ideally CUDA-powered) and ImageMagick. Put the images you want to use in a directory ```<location>/input```.
Our COLMAP loaders expect the following dataset structure in the source path location:
```
<location>
|---images
| |---<image 0>
| |---<image 1>
| |---...
|---sparse
|---0
|---cameras.bin | cameras.txt
|---images.bin | images.txt
|---points3D.bin | points3D.txt
```
For rasterization, the camera models must be either a SIMPLE_PINHOLE or PINHOLE camera. We provide a converter script ```convert.py```, to extract undistorted images and SfM information from input images. Optionally, you can use ImageMagick to resize the undistorted images. This rescaling is similar to MipNeRF360, i.e., it creates images with 1/2, 1/4 and 1/8 the original resolution in corresponding folders. To use them, please first install a recent version of COLMAP (ideally CUDA-powered) and ImageMagick. Put the images you want to use in a directory ```<location>/input```.
```
<location>
|---input