ColMap OpenMVS workflow

Through a lot of reading about those doc and issue

I wanna write a tutorial for fresh people.

This is prepare for linux server (means no desktop)

And I have compile the latest version colmap and openmvs

Step 1

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

• here --SiftExtraction.use_gpu is using for linux server only, you can comment it out if you have desktop.
• --ImageReader.camera_model PINHOLE, you could choice other one, check the list camera model
• For using InterfaceCOLMAP, you must specify PINHOLE model

Step 2

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

• here --SiftMatching.use_gpu 0 has same effect with SiftExtraction.use_gpu

Step 3

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

Step 4

• 去除图片的畸变(undistort)

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

• 把相机内存转化为txt格式方便openmvs读取

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

• At this step, you will see three txt file will be created at sparse dir.
  • cameras.txt, images.txt, point3D.txt
  • And PINHOLE is in cameras.txt you will see

Step 5

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

Step 6

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

Step 7

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

Step 8

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

Step 9

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

FINAL

• You will get model.mtl model.obj and the texure model_material_0_map_Kd.jpg
• Open obj with software you like, I’ll recommend MAYA

Code

• ucas script - ipynb