Comments (5)
it is hard to debug ths with just ths info, is it possible to replicate this failure?
can you tell us more about your build/run environment?
@DmitriyKorchemkin any idea what maybe going on here?
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Hi @sandwichmaker ,
Thank you for the reply!
Yes, the build environment is just COLMAP build environment:
colmap installation
I installed ceres-solver 2.2.0 and verified the version by running simple_bundle_adjustment test.
When building this problem_
, we have 60006 images and about 13 millions points.
We want to jointly optimize the image poses and map points using ceres::solve()
with :
- solver_options.linear_solver_type = ceres::DENSE_SCHUR
- solver_options.dense_linear_algebra_library_type= ceres::DenseLinearAlgebraLibraryType::CUDA;
However, we got this aborted error every time.
If we change the linear_solver_type to ceres::ITERATIVE_SCHUR or ceres::SPARSE_SCHUR it won't abort and can finish the process.
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@sandwichmaker I see. Thanks for the reply.
After I changed the solver to ceres::ITERATIVE_SCHUR
it won't abort anymore.
Since we want to leverage CUDA acceleration and that only supports either DENSE_SCHUR
or DENSE_QR
solvers,
is there any way we can do it while avoiding aborted error?
Thank you!
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Currently there is no way to use CUDA for such large problems.
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Related Issues (20)
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- Add absl/log/vlog_is_on.h as an explicit included header HOT 1
- Change GradientProblem related APIs to use std::unique_ptr HOT 1
- Will the pointer be automatically deleted by Ceres HOT 2
- undefined reference to `ceres::Problem::AddResidualBlock(ceres::CostFunction*, ceres::LossFunction*, double*)' HOT 3
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- "libceres.a(problem.cc.o) is referenced by DSO" HOT 8
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