From 6653d481a69898eb6d758b7b74c7acd913bfa562 Mon Sep 17 00:00:00 2001
From: Geralt_of_Rivia <87054407+guanjunwu@users.noreply.github.com>
Date: Mon, 11 Dec 2023 13:32:30 +0800
Subject: [PATCH] Update README.md

---
 README.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index 5936a58..6b5d39c 100644
--- a/README.md
+++ b/README.md
@@ -122,21 +122,21 @@ merge your trained 4dgs.
 usage:
 ```python
 export exp_name="dynerf"
-python merge_many_4dgs.py --model_path output/$exp_name/flame_salmon_1
+python merge_many_4dgs.py --model_path output/$exp_name/sear_steak
 ```
 
 `colmap.sh`:
 generate point clouds from input data
 ```bash
 bash colmap.sh data/hypernerf/virg/vrig-chicken hypernerf 
-bash colmap.sh data/dynerf/flame_salmon_1 llff
+bash colmap.sh data/dynerf/sear_steak llff
 ```
 
 **Blender** format seems doesn't work. Welcome to raise a pull request to fix it.
 
 `downsample_point.py` :downsample generated point clouds by sfm.
 ```python
-python scripts/downsample_point.py data/dynerf/sear_steak/points3D_downsample.ply data/dynerf/sear_steak/points3D_downsample2.ply
+python scripts/downsample_point.py data/dynerf/sear_steak/colmap/dense/workspace/fused.ply data/dynerf/sear_steak/points3D_downsample2.ply
 ```
 In my paper, I always use `colmap.sh` to generate dense point clouds and downsample it to less than 40000 points.