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@@ -99,8 +99,7 @@ After that, you'll need to copy manually (for now), the folder to `images`, for
Examples
```
ns-process-data lantern --data ./data/lab_ground_floor/trimmed_videos_smart_subset --mask-dir ./data/lab_ground_floor/trimmed_videos_masks --output-dir ./data/lab_ground_floor/colmap_out_smart --skip-image-processing --camera-type equirectangular --images-per
-equirect 8 --skip-colmap --skip-perspective-transform
ns-process-data lantern --data ./data/lab_ground_floor/trimmed_videos_smart_subset --mask-dir ./data/lab_ground_floor/trimmed_videos_masks --output-dir ./data/lab_ground_floor/colmap_out_smart --skip-image-processing --camera-type equirectangular --images-per-equirect 8 --skip-colmap --skip-perspective-transform
```
## 2. Pre-training NeRF
@@ -120,7 +119,7 @@ If you need to use less frames, add this argument: `--pipeline.datamanager.train
Examples
```
ns-train lantern-nerfacto --data data/lab_ground_floor/colmap_out_smart --pipeline.datamanager.train-num-images-to-sample-from 200 --pipeline.datamanager.eval-num-images-to-sample-from 30
ns-train lantern-nerfacto --data data/lab_ground_floor/colmap_out_smart --pipeline.datamanager.eval-num-images-to-sample-from 0
```
## 3. Running MomoNet