AliceVision and its Meshroom program are an exciting new free and open-source pipeline for photogrammetry processing. Unfortunately, compiling and using either of these programs on Mac OS X is not exactly straightforward. As a result, I’ve compiled a Homebrew tap which includes the necessary formulae, and will use this post to outline how to use them to get up and running. Note that this is intended as a first step for Mac users wishing to experiment with and improve the AliceVision/Meshroom software, and as a result these instructions may become outdated with time.
First off, your Mac will currently need an nVidia GPU with a CUDA compute capability of 2.0 or greater. This is probably a pretty small portion of all Macs sold, but you can check your GPU by looking in “About This Mac” from the Apple icon in the top left corner of the screen, under “Graphics”. If you have an nVidia GPU listed there, you can check its compute capability on the nVidia CUDA GPUs page.
Second, you’re going to need to install the latest CUDA toolkit. As of this writing, that’s CUDA 9.2, which is only officially compatible with OS X 10.13 (High Sierra), so you may also need to upgrade to the latest version of High Sierra if you haven’t already. Alongside this I would also suggest installing the latest nVida CUDA GPU webdriver, which as of this writing is 3126.96.36.199.40.105.
Third, CUDA 9.2 is only compatible with the version of
clang distributed with Xcode 9.2, and will refuse to compile against anything else. You may have an older or newer version of Xcode installed. As of this writing, if you fully update Xcode within a fully updated OS X install, you’ll have Xcode 9.4.1. To get back to Xcode 9.2, what you can do is go to Apple’s Developer Downloads page (for which you’ll need a free Apple developer account), then search for “Xcode 9.2”, then install the Command Line Tools for Xcode 9.2 package for your OS version. After installing, run
sudo xcode-select --switch /Library/Developer/CommandLineTools and then verify that
clang --version shows
Apple LLVM version 9.0.0.
Once you’ve done all this, you can verify a working CUDA install by going to
/Developer/NVIDIA/CUDA-9.2/samples/1_Utilities/deviceQuery and running
sudo make && ./deviceQuery, which should output your GPU information. If it doesn’t build correctly, or
deviceQuery errors or doesn’t list your GPU, you may need to look over the steps above and check that everything is up to date (you can also check the CUDA panel in System Preferences).
The following instructions also assume a working Homebrew install.
If you’ve followed all the above setup instructions and requirements, installing the AliceVision libraries/framework should be as easy as:
brew install ryanfb/alicevision/alicevision
Meshroom Installation & Usage
I haven’t yet created a Homebrew formula for the Meshroom package itself, as it’s all Python and doesn’t seem particularly difficult to install/use once AliceVision is installed and working correctly. Just follow the install instructions there (for my specific Python configuration/installation I used
pip3 instead of
python3 instead of
git clone --recursive git://github.com/alicevision/meshroom cd meshroom pip install -r requirements.txt
One gotcha I ran into is that the CUDA-linked AliceVision binaries invoked by Meshroom don’t automatically find the CUDA libraries on the
DYLD_LIBRARY_PATH, and setting the
DYLD_LIBRARY_PATH from the shell launching Meshroom doesn’t seem to get the variable passed into the shell environment Meshroom uses to spawn commands. Without this, you’ll get an error like:
dyld: Library not loaded: @rpath/libcudart.9.2.dylib Referenced from: /usr/local/bin/aliceVision_depthMapEstimation Reason: image not found
In order to get around this, you can symlink the CUDA libraries into
/usr/local/lib (most of the other workarounds I found for permanently modifying the
DYLD_LIBRARY_PATH seemed more confusing or fragile than this simpler approach):1
for i in /Developer/NVIDIA/CUDA-9.2/lib/*.a /Developer/NVIDIA/CUDA-9.2/lib/*.dylib; do ln -sv "$i" "/usr/local/lib/$(basename "$i")"; done
You can undo/uninstall this with:
for i in /Developer/NVIDIA/CUDA-9.2/lib/*.a /Developer/NVIDIA/CUDA-9.2/lib/*.dylib; do rm -v "/usr/local/lib/$(basename "$i")"; done
You may also want to download the voctree dataset:
curl 'https://gitlab.com/alicevision/trainedVocabularyTreeData/raw/master/vlfeat_K80L3.SIFT.tree' -o /usr/local/Cellar/alicevision/2.0.0/share/aliceVision/vlfeat_K80L3.SIFT.tree
Then launch with:
ALICEVISION_SENSOR_DB=/usr/local/Cellar/alicevision/2.0.0/share/aliceVision/cameraSensors.db ALICEVISION_VOCTREE=/usr/local/Cellar/alicevision/2.0.0/share/aliceVision/vlfeat_K80L3.SIFT.tree PYTHONPATH=$PWD python meshroom/ui
Import some photos, click “Start”, wait a while, and hopefully you should end up with a reconstructed and textured mesh (here’s an example of my own which I uploaded to SketchFab). By default, the output will be in
MeshroomCache/Texturing/ (relative to where you saved the project file).
Previously, I suggested modifying
meshroom/core/desc.pyso that the return value at the end of the
buildCommandLinemethod instead reads:
return 'DYLD_LIBRARY_PATH="/Developer/NVIDIA/CUDA-9.2/lib" ' + cmdPrefix + chunk.node.nodeDesc.commandLine.format(**chunk.node._cmdVars) + cmdSuffix