Add multi-texture support to mesh texturing

• store all stages in Interface MVS format by default
• store dense point-cloud as PLY, including all point-views information, etc
• add max-texture-size and multi-texture support to mesh texturing stage
• speedup/improve fix non-manifold mesh algorithm
• unify library/application initialization/destroying
• add python support for reading DMAP and Interface MVS file formats
• account for different pixel center conventions when importing/exporting COLMAP which uses pixel center at (0.5,0.5) instead of (0, 0) as OpenMVS
• add interface to MVSNet, Nerfstudio and RTMV scene formats
• improve interface to Polycam scene format
• speedup PLY load/save
• speedup/improve ray-triangle intersection
• add support for UV coordinates agnostic about orientation
• add support for storing neighbor views information in Interface MVS format
• add support for C++20
• various other fixes

Add Python API

• add Python API
• COLMAP support in MvgMvsPipeline.py
• interface for binary COLMAP
• interface for Polycam scenes
• tower mode #1017
• estimate 3D points scale
• transform scene by a given transform matrix
• unify Docker scripts and add support for GUI
• fix incorrect comparison in BufferedOutputStream #1010
• add lines structure
• compute the focus of attention of a set of cameras
• add image mask support in mesh texturing

Improved densification of textureless areas

• Improve depth-map estimation in textureless areas using multi-resolution
• Add texture sharpening
• Ground plane estimation
• Estimate volume from the reconstructed mesh
• Texture transfer between two meshes
• Automatic Region-Of-Interest estimation
• Simplify build with vcpkg
• Add tests
• Add Continuous Integration action
• Various bug fixes

Various bug-fixes and algorithm fine-tuning

Most important changes:

• fix various bugs and fine-tune Patch-Match CUDA
• update MvgMvsPipeline.py to match the latest OpenMVG and OpenMVS
• add support to rescale a scene, including the images, in InterfaceCOLMAP
• add support to remesh a reconstruction to the mesh cleaning step
• add support to center the scene and set the bounding box to Viewer
• improve view neighbors selection
• generate depth-maps by rendering a given mesh in each view
• simplify view selection in mesh texturing

Faster & more accurate densification

Most important changes:

• new Patch-Match algorithm with improved accuracy and speed (CUDA)
• add geometric-consistency during depth-map estimation
• cluster large scenes to be processed individually (--sub-scene-area)
• Region-Of-Interest (ROI) import and scene trim
• GLTF/GLB exporter

Expose depth-maps

Depth-maps stored as DMAP files can now be exported/imported/visualized. Full changes:

• add DMAP visualization support to Viewer
• expose depth-map file format in Interface.h
• script MvgMvsPipeline.py improvement
• build scripts improvements
• small depth-map estimation improvement
• add option to decimate the input mesh before texturing
• add support for binary COLMAP projects
• add support for Bundle OUT projects (only undistorted cameras)

Implement Semi-Global Matching

Main changes:

• add Semi-Global Matching as a method to estimate a dense point-cloud; this method is still experimental, thus sometimes the speed and completeness might not be as good as the Path-Match approach, though the accuracy could be better; as always any contribution in improving any of these algorithms is welcome

v1.0.1: Merge branch 'develop' into master (#512)

Main changes:

• open depth-map DMAP file format for easy utilization outside OpenMVS (see ExportDepthDataRaw() and ImportDepthDataRaw())
• expose some depth-map functions in SceneDensify.h
• add global ID support to image structure to allow processing large scenes by splitting them into multiple sub-scenes to be processed individually

v1.0

First mature version of OpenMVS.

The quality of the dense point-cloud is much improved. Tested on the two most representative benchmarks in this field, OpenMVS obtains a decent position in the leader-board at only a fraction of run-time compared to the other methods, even though using only a CPU implementation:

• ETH3D Benchmark (created by the COLMAP authors)
• Tanks and Temples Benchmark (created by Intel)

Even better results can be obtained by using also the mesh reconstruction and mesh refinement modules on top of the dense-point cloud and submit a point-cloud sampled from the more accurate mesh.

The support for the OpenMVG SfM solution was extended with an interface to/from the COLMAP solution, supporting both SfM import and dense point-cloud import/export in order for you to experiment with combining different modules at the various stages of the Multi-View Stereo pipeline.

Enjoy!

v0.9

Merge branch 'develop'