Step1 特征提取

colmap feature_extractor \
--SiftExtraction.use_gpu 0 \
--database_path $PROJECT/database.db\
--image_path $DATA_ROOT/$PROJECT/images

Step2 特征匹配

colmap exhaustive_matcher\
--SiftMatching.use_gpu 0\
--database_path $PROJECT/database.db

Step2 特征匹配

colmap exhaustive_matcher\
--SiftMatching.use_gpu 0\
--database_path $PROJECT/database.db

Step3 空三

colmap mapper\
--database_path $PROJECT/database.db \
--image_path $DATA_ROOT/$PROJECT/images \
--output_path $PROJECT/sparse 

Step4 影像去畸变

colmap image_undistorter \
--image_path $DATA_ROOT/$PROJECT/images \
--input_path $PROJECT/sparse/0 \
--output_path $PROJECT/dense \
--output_type COLMAP \

• here --output_type, you could find the usage at colmap

Step5 模型转换

colmap model_converter \
--input_path $PROJECT/dense/sparse \
--output_path $PROJECT/dense/sparse  \
--output_type TXT

• Under this step, you will see three txt file will be created at $PROJECT/dense/sparse dir.
• cameras.txt, images.txt, point3D.txt
• But you could choice another place to save them.
• And PINHOLE is in cameras.txt you will see.

Step6 格式转换

InterfaceCOLMAP \
--working-folder $(pwd)/$PROJECT/ \
--input-file $(pwd)/$PROJECT/ \
--output-file $(pwd)/$PROJECT/model_colmap.mvs

Step7 密集重建

DensifyPointCloud \
--input-file $(pwd)/$PROJECT/model_colmap.mvs \
--working-folder $(pwd)/$PROJECT/ \
--output-file $(pwd)/$PROJECT/model_dense.mvs \
--archive-type -1 \

• Here --archive-type -1 must be set

Step8 构网

ReconstructMesh --input-file $(pwd)/$PROJECT/model_dense.mvs \
--working-folder $(pwd)/$PROJECT/ \
--output-file $(pwd)/$PROJECT/model_dense_mesh.mvs

Step9 网格精化

RefineMesh \
--resolution-level 1 \
--input-file $(pwd)/$PROJECT/model_dense_mesh.mvs \
--working-folder $(pwd)/$PROJECT/ \
--output-file $(pwd)/$PROJECT/model_dense_mesh_refine.mvs

Step10 纹理映射

TextureMesh \
--export-type obj \
--output-file $(pwd)/$PROJECT/model.obj \
--working-folder $(pwd)/$PROJECT/ \
--input-file $(pwd)/$PROJECT/model_dense_mesh_refine.mvs