6. Second COLMAP step : matching. For less than 1000 images, you can use exhaustive matching (this will take around 2hours). If there is too much images, you can use either spatial matching or vocab tree matching
This will create a model file in the folder `output/sparse` (or `output/sparse/0`), in the form of 3 files
```
└── sparse
└── 0
├── cameras.bin
├── images.bin
├── points3D.bin
└── project.ini
```
8. Third COLMAP step : [georeferencing](https://colmap.github.io/faq.html#geo-registration)
* Create an `images.txt` with the image name and their XYZ position, relative to the centered Lidar Point using the file `cloud_centroid.txt`created at step 4