This support was broken due to the TrustRegionMinimizer refactoring.
It is now enabled again, with the responsibilty for dumping the
problem shifted to the individual TrustRegionStrategy.
There is however one wrinkle, which is perhaps an indication of
poor design to start with. The LinearLeastSquaresProblemProto
carries in it num_eliminate_blocks, something which does not
exist anymore. More importantly, the TrustRegionStrategy does not
have access to this quantity anymore.
Dealing with this will be the subject of a future change.
Change-Id: I358adf6a2e386f4940b617bf950d6c7e87d2635d
CreateJacobianBlockSparsityTranspose starts with a conservative
estimate of the size of the block sparsity pattern of the Jacobian.
When the Jacobian has more non-zeros than that, the TripletSparseMatrix
being used to store the sparsity has a Reallocate method which
allows one to resize the matrix and IF num_nonzeros is set, then the
existing values in the array are also copied into the newly allocated
memory.
Unfortunately the pattern we follow in ceres code is to call
set_num_nonzeros after one is done populating the sparsity pattern
of a matrix. This does not mix well with Reallocate and results
in the matrix having uninitialized memory.
This patch fixes this problem and adds a test that verifies the fix.
Thanks to Yuliy Schwartzburg for reporting this bug and providing
code to reproduce it.
Change-Id: I58583714ffaebd880d85af16e3685b2d6ee053e8
1. Multithread the inversion of J'J.
2. Simplify the dense rank truncation loop.
3. Minor correction to building documentation.
Change-Id: Ide932811c0f28dc6c253809339fb2caa083865b5
1. Further tightening of the Covariance documentation.
2. Documented minimizer progress output.
3. Lint cleanup from William Rucklidge.
4. Updated version history.
Change-Id: I8bc28484675d4edf89a7c050b6379dbac6c39e91
1. Sparse covariance estimation now uses cholmod_rcond to
detect singular Jacobians.
2. Dense covariance estimation now uses relative magnitude
of singular/eigen values to compute the pseudoinverse.
3. Truncation logic is now unified with Solver::Options::null_space_rank.
Change-Id: I095bd737510c836b4251255926190a7f31d64bce
Add example application which is based on bundle
adjustment code from Libmv library, which is heavily
used in Blender.
Apart from bundle adjustment code this commit also
contains real-life optimization problems from VFX
pipeline. This files are created from production
files of Tears of Steel movie.
New code is placed to examples, and could be used
either as an example implementation of BA or for
timing investigation of problems appearing in VFX.
Problems for this application are placed to
data/libmv-ba-problems.
Usage:
./libmv_bundle_adjuster --input=/path/to/problem_file.bin
There's also optional flag --refine_intrinsics which
declares explicitly whether intrinscis shall be
refined or not. If this flag is not passed, refinement
will happen for problems stored in image space.
Structure of problem files is described in header
comment of libmv_bundle_adjuster.cc.
Change-Id: I51202848c75dcd7612b707609e5ff3708e01b625
Apparently, TR1 symbols are defined in different namespace
comparing to MSVC 2010, which lead to compilation error when
using MSVC 2008.
Change-Id: I4fa3ceae4b4e2c6e7a46b1fb5b498640e7b18b74
- In C you're not allowed to define variables in the middle
of the block. This was violated in curve_fitting.c by
calling ceres_init() in the beginning of main() and declaring
variables later.
- Also ifdef-ed suitesparse stuff in covariance estimation module.
This solves compilation error when you don't have suitesparse
compiled/installed.
Change-Id: I22b543c09ea01f55e127079daade99a0b781f789
Also
1. Remove an inadvertent LOG(INFO) from trust_region_minimizer.cc
2. Refactor some of the code in FullReport to reduce duplication
across line search and trust region minimizers.
3. Consistent capitalization.
Change-Id: I9078b1704efab23d2858530636f524e60c7d9016
Remove the Eigen temporary by revealing the columnwise nature
of the computation. This also allows us to get rid of the
special case for nrow = 1.
On problem-356-226730-pre.txt with -robustify evaluation times
change from:
Before:
Residual Evaluations 1.015
Jacobian Evaluations 18.313
After:
Residual Evaluations 1.005
Jacobian Evaluations 8.382
To give a sense of the overhead reduction, compare these numbers
when loss functions are disabled.
Residual Evaluations 0.955
Jacobian Evaluations 7.772
So, this is a 17.5x speedup!
The one dimensional specialization was motivated by denoising.cc.
The evaluation times there are essentially unchanged.
Before:
Residual Evaluations 2.774
Jacobian Evaluations 20.178
After:
Residual Evaluations 2.588
Jacobian Evaluations 19.781
Change-Id: Ic0efbaed75fe4489635039f17189ae24b97802c8
This allows CovarianceImpl to be forward declared without
scoped_ptr freaking out.
Thanks to Nima Keivan for reporting this.
Change-Id: Icd5aa766b3aab70246055225231a4b971c6b7b90
Add a Covariance object to the API.
Given a Problem object and a set of parameter block pairs the
Covariance object computes a sparse covariance matrix corresponding
to those block pairs and provides random access to them.
Constant parameter blocks and parameter blocks with local parameterizations
are correctly handled.
Sparse and dense implementations are provided. With the dense implementation
rank deficient Jacobians can also be handled.
Parts of the code are threaded using OpenMP if available.
Change-Id: I5b49583b3d79579df3e0f334c22567acb23ed4ad
This introduces a simple C API for a subset of Ceres. This opens the door to
using languages like Python to call Ceres, since it is much easier to bind to C
than it is to bind to C++. It will mean giving up the native Ceres autodiff.
The implementation in this patch does not attempt to do everything but is only
just enough to get started. Subsequent patches will increase the surface area
of Ceres that is covered by the C API.
Change-Id: Ic51804bac6865e1a2e476553248aabc91dff3409
The schur ordering is used to construct an elimination
ordering for Schur type solvers when the user has not
supplied an elimination ordering.
The ordering algorithm does an ordered traversal of the
sparsity graph of the Hessian. The order in which this is
done used to be determined by the degree of the parameter
blocks with ties broken arbitrarily using the memory address
of the parameter blocks.
This introduced non-determinism in the solver, causing subtle
numerical differences in the value of the solution everytime
the solve was run.
This change introduces ComputeStableSchurOrdering which utilizes
a new function StableIndependentSetOrdering. The latter takes
as input an ordering of the vertices of the graph which is used
to break ties when ordering the vertice by degree. The former
constructs such an ordering by using the order in which the
parameter blocks were added to the Problem.
In this way, as long as the construction of the problem is
deterministic, the schur ordering will always be deterministic
too.
I have chosen not to delete the existing unstable implementations
of these functions as they are used by the inner iteration
minimizer.
Sometime in the near future I will clean up some of the duplicate
code and see if we can move all the code to using a stable ordering.
Change-Id: I8fbfa240d7307a2c3fe9b135f6968aa410d78780
- The -O4 option requires the linker to have bitcode support, currently for
clang this means using the gold linker and the LLVM-gold plugin:
http://llvm.org/docs/GoldPlugin.html.
- Otherwise you get (confusing) 'file format not recognised' errors ala:
http://llvm.org/bugs/show_bug.cgi?id=9897.
- Adding explicit check for LTO support as at least some package installs of
clang on linux do not use the gold linker by default.
Change-Id: I2a4c670e470d9b48da2a15b7e91a59fb4ad3e8ad
1. Bug fix in NumericDiffCostFunction (Thanks to Nicolas Brodu).
2. Minor documentation update in solver.h
3. Version history update.
4. Bump the version and ABI version.
Change-Id: I951574ddd0b2c4c03b9c79ff33eb9bea549071e7
1. CX_SPARSE supports pre-ordering of the jacobian.
2. Add support for constrained approximate minimum degree ordering
for SuiteSparse versions >= 4.2.0
3. Using 2, support for pre-ordering for SPARSE_SCHUR when used
with SUITE_SPARSE.
4. Using 2, support for user orderings in SPARSE_NORMAL_CHOLESKY.
5. Minor cleanups in documentation and code all around.
6. Test update and refactoring.
Change-Id: Ibfe3ac95d59d54ab14d1d60a07f767688070f29f
Sameer Agarwal