Add Pixi project files#3
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Add instructions to use pixi project Use pytorch build with support for sm_120 Build ceres-solver with support for cuDSS Fix ceres-solver with cuDSS detection Fix usage of kornia method Fix mast3r model load call to account for changes in pytorch
S-o-T
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May 31, 2026
| target_compile_definitions(pygluemap PRIVATE cxx_std_17) | ||
| if (TARGET Ceres::ceres_cuda_kernels) | ||
| get_target_property(CERES_INTERFACE_LINK_LIBRARIES Ceres::ceres INTERFACE_LINK_LIBRARIES) | ||
| string(FIND "${CERES_INTERFACE_LINK_LIBRARIES}" "cudss" CERES_HAS_CUDA) |
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ceres-solver can be compiled with support for cuda implementation of dense linear solvers (this would imply Ceres::ceres_cuda_kernels), but enabling cuda implementation of sparse linear solvers requires cuDSS (thus, checking for Ceres::ceres_cuda_kernels is not enough).
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I've just used this branch to get an environement setup 👍 Hit a couple of snags, you're missing ninja and cmake: (and maybe a cxx compiler): Also I had to pass Might be worth adding another pixi task to download the model checkpoints too. |
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I have failed to run a demo on Blackwell gpu, also the detection of/dispatch into ceres-solver with cuDSS seems to be broken. I had no prior experience with Pixi and this issue appeared as a good opportunity 😄 .
I have checked this changes using gluemap-demo on my own dataset and results seems to be valid (i have not assessed if using the cuDSS does indeed leads to any speedups). Sharing it as a draft for those who might find it useful. If there is an interest to merge this, i can decompose into separate PRs (if necessary)