diff --git a/.cproject b/.cproject deleted file mode 100644 index 10b16f91c..000000000 --- a/.cproject +++ /dev/null @@ -1,3563 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 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true - true - true - - - make - -j2 - Pose2SLAMwSPCG_easy.run - true - true - true - - - make - -j5 - UGM_small.run - true - true - true - - - make - -j5 - LocalizationExample.run - true - true - true - - - make - -j5 - OdometryExample.run - true - true - true - - - make - -j5 - RangeISAMExample_plaza2.run - true - true - true - - - make - -j5 - SelfCalibrationExample.run - true - true - true - - - make - -j5 - SFMExample.run - true - true - true - - - make - -j5 - VisualISAMExample.run - true - true - true - - - make - -j5 - VisualISAM2Example.run - true - true - true - - - make - -j5 - Pose2SLAMExample_graphviz.run - true - true - true - - - make - -j5 - Pose2SLAMExample_graph.run - true - true - true - - - make - -j5 - SFMExample_bal.run - true - true - true - - - make - -j5 - Pose2SLAMExample_lago.run - true - true - true - - - make - -j5 - Pose2SLAMExample_g2o.run - true - true - true - - - make - -j5 - SFMExample_SmartFactor.run - true - true - true - - - make - -j4 - Pose2SLAMExampleExpressions.run - true - true - true - - - make - -j4 - SFMExampleExpressions.run - true - true - true - - - make - -j4 - SFMExampleExpressions_bal.run - true - true - true - - - make - -j5 - testLago.run - true - true - true - - - make - -j5 - testLinearContainerFactor.run - true - true - true - - - make - -j5 - testOrdering.run - true - true - true - - - make - -j5 - testValues.run - true - true - true - - - make - -j5 - testWhiteNoiseFactor.run - true - true - true - - - make - -j4 - testExpression.run - true - true - true - - - make - -j4 - testAdaptAutoDiff.run - true - true - true - - - make - -j4 - testCallRecord.run - true - true - true - - - make - -j4 - testExpressionFactor.run - true - true - true - - - make - -j4 - testExecutionTrace.run - true - true - true - - - make - -j4 - testSerializationNonlinear.run - true - true - true - - - make - -j4 - testImuFactor.run - true - true - true - - - make - -j2 - check - true - true - true - - - make - tests/testGaussianISAM2 - true - false - true - - - make - -j5 - timeCalibratedCamera.run - true - true - true - - - make - -j5 - timePinholeCamera.run - true - true - true - - - make - -j5 - timeStereoCamera.run - true - true - true - - - make - -j5 - timeLago.run - true - true - true - - - make - -j5 - timePose3.run - true - true - true - - - make - -j4 - timeAdaptAutoDiff.run - true - true - true - - - make - -j4 - timeCameraExpression.run - true - true - true - - - make - -j4 - timeOneCameraExpression.run - true - true - true - - - make - -j4 - timeSFMExpressions.run - true - true - true - - - make - -j4 - timeIncremental.run - true - true - true - - - make - -j4 - timeSchurFactors.run - true - true - true - - - make - -j4 - timeRot2.run - true - true - true - - - make - -j2 - testRot3.run - true - true - true - - - make - -j2 - testRot2.run - true - true - true - - - make - -j2 - testPose3.run - true - true - true - - - make - -j2 - timeRot3.run - true - true - true - - - make - -j2 - testPose2.run - true - true - true - - - make - -j2 - testCal3_S2.run - true - true - true - - - make - -j2 - testSimpleCamera.run - true - true - true - - - make - -j2 - testHomography2.run - true - true - true - - - make - -j2 - testCalibratedCamera.run - true - true - true - - - make - -j2 - check - true - true - true - - - make - -j2 - clean - true - true - true - - - make - -j2 - testPoint2.run - true - true - true - - - make - -j4 - testBearingFactor.run - true - true - true - - - make - -j4 - testRangeFactor.run - true - true - true - - - make - -j4 - testBearingRangeFactor.run - true - true - true - - - make - -j5 - wrap - true - true - true - - - - diff --git a/.github/workflows/build-linux.yml b/.github/workflows/build-linux.yml index d80a7f4ba..be1da35bb 100644 --- a/.github/workflows/build-linux.yml +++ b/.github/workflows/build-linux.yml @@ -82,4 +82,4 @@ jobs: - name: Build and Test (Linux) if: runner.os == 'Linux' run: | - bash .github/scripts/unix.sh -t \ No newline at end of file + bash .github/scripts/unix.sh -t diff --git a/.github/workflows/build-windows.yml b/.github/workflows/build-windows.yml index 0a55de880..887d41972 100644 --- a/.github/workflows/build-windows.yml +++ b/.github/workflows/build-windows.yml @@ -75,4 +75,4 @@ jobs: cmake --build build --config ${{ matrix.build_type }} --target wrap cmake --build build --config ${{ matrix.build_type }} --target check.base cmake --build build --config ${{ matrix.build_type }} --target check.base_unstable - cmake --build build --config ${{ matrix.build_type }} --target check.linear \ No newline at end of file + cmake --build build --config ${{ matrix.build_type }} --target check.linear diff --git a/CMakeLists.txt b/CMakeLists.txt index 35c487fd3..b19ece0e6 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -34,7 +34,7 @@ include(GtsamTesting) include(GtsamPrinting) # guard against in-source builds -if(${CMAKE_SOURCE_DIR} STREQUAL ${CMAKE_BINARY_DIR}) +if(${GTSAM_SOURCE_DIR} STREQUAL ${GTSAM_BINARY_DIR}) message(FATAL_ERROR "In-source builds not allowed. Please make a new directory (called a build directory) and run CMake from there. You may need to remove CMakeCache.txt. ") endif() @@ -62,6 +62,11 @@ add_subdirectory(CppUnitLite) # This is the new wrapper if(GTSAM_BUILD_PYTHON) + # Need to set this for the wrap package so we don't use the default value. + set(WRAP_PYTHON_VERSION ${GTSAM_PYTHON_VERSION} + CACHE STRING "The Python version to use for wrapping") + + add_subdirectory(wrap) list(APPEND CMAKE_MODULE_PATH "${CMAKE_CURRENT_LIST_DIR}/wrap/cmake") add_subdirectory(python) endif() diff --git a/INSTALL.md b/INSTALL.md index 3dbc3a850..1fddf4df0 100644 --- a/INSTALL.md +++ b/INSTALL.md @@ -70,7 +70,34 @@ execute commands as follows for an out-of-source build: This will build the library and unit tests, run all of the unit tests, and then install the library itself. -## CMake Configuration Options and Details +# Windows Installation + +This section details how to build a GTSAM `.sln` file using Visual Studio. + +### Prerequisites + +- Visual Studio with C++ CMake tools for Windows +- All the other pre-requisites listed above. + +### Steps + +1. Open Visual Studio. +2. Select `Open a local folder` and select the GTSAM source directory. +3. Go to `Project -> CMake Settings`. + - (Optional) Set `Configuration name`. + - (Optional) Set `Configuration type`. + - Set the `Toolset` to `msvc_x64_x64`. If you know what toolset you require, then skip this step. + - Update the `Build root` to `${projectDir}\build\${name}`. + - You can optionally create a new configuration for a `Release` build. + - Set the necessary CMake variables for your use case. + - Click on `Show advanced settings`. + - For `CMake generator`, select a version which matches `Visual Studio Win64`, e.g. `Visual Studio 16 2019 Win64`. + - Save the settings (Ctrl + S). +4. Click on `Project -> Generate Cache`. This will generate the CMake build files (as seen in the Output window). +5. The last step will generate a `GTSAM.sln` file in the `build` directory. At this point, GTSAM can be used as a regular Visual Studio project. + + +# CMake Configuration Options and Details GTSAM has a number of options that can be configured, which is best done with one of the following: @@ -78,7 +105,7 @@ one of the following: - ccmake the curses GUI for cmake - cmake-gui a real GUI for cmake -### Important Options: +## Important Options: #### CMAKE_BUILD_TYPE We support several build configurations for GTSAM (case insensitive) diff --git a/cmake/Config.cmake.in b/cmake/Config.cmake.in index 9bd188037..89627a172 100644 --- a/cmake/Config.cmake.in +++ b/cmake/Config.cmake.in @@ -6,7 +6,7 @@ get_filename_component(OUR_CMAKE_DIR "${CMAKE_CURRENT_LIST_FILE}" PATH) if(EXISTS "${OUR_CMAKE_DIR}/CMakeCache.txt") # In build tree - set(@PACKAGE_NAME@_INCLUDE_DIR @CMAKE_SOURCE_DIR@ CACHE PATH "@PACKAGE_NAME@ include directory") + set(@PACKAGE_NAME@_INCLUDE_DIR @GTSAM_SOURCE_DIR@ CACHE PATH "@PACKAGE_NAME@ include directory") else() # Find installed library set(@PACKAGE_NAME@_INCLUDE_DIR "${OUR_CMAKE_DIR}/@CONF_REL_INCLUDE_DIR@" CACHE PATH "@PACKAGE_NAME@ include directory") @@ -15,7 +15,7 @@ endif() # Find dependencies, required by cmake exported targets: include(CMakeFindDependencyMacro) # Allow using cmake < 3.8 -if(${CMAKE_VERSION} VERSION_LESS "3.8.0") +if(${CMAKE_VERSION} VERSION_LESS "3.8.0") find_package(Boost @BOOST_FIND_MINIMUM_VERSION@ COMPONENTS @BOOST_FIND_MINIMUM_COMPONENTS@) else() find_dependency(Boost @BOOST_FIND_MINIMUM_VERSION@ COMPONENTS @BOOST_FIND_MINIMUM_COMPONENTS@) diff --git a/cmake/GtsamBuildTypes.cmake b/cmake/GtsamBuildTypes.cmake index 3155161be..1262c6935 100644 --- a/cmake/GtsamBuildTypes.cmake +++ b/cmake/GtsamBuildTypes.cmake @@ -204,9 +204,9 @@ endif() # Make common binary output directory when on Windows if(WIN32) - set(RUNTIME_OUTPUT_PATH "${CMAKE_BINARY_DIR}/bin") - set(EXECUTABLE_OUTPUT_PATH "${CMAKE_BINARY_DIR}/bin") - set(LIBRARY_OUTPUT_PATH "${CMAKE_BINARY_DIR}/lib") + set(RUNTIME_OUTPUT_PATH "${GTSAM_BINARY_DIR}/bin") + set(EXECUTABLE_OUTPUT_PATH "${GTSAM_BINARY_DIR}/bin") + set(LIBRARY_OUTPUT_PATH "${GTSAM_BINARY_DIR}/lib") endif() # Set up build type list for cmake-gui diff --git a/cmake/GtsamMatlabWrap.cmake b/cmake/GtsamMatlabWrap.cmake index 4c44d2cb3..2be0c61a8 100644 --- a/cmake/GtsamMatlabWrap.cmake +++ b/cmake/GtsamMatlabWrap.cmake @@ -1,51 +1,64 @@ +# Check / set dependent variables for MATLAB wrapper +if(GTSAM_INSTALL_MATLAB_TOOLBOX) + find_package(Matlab COMPONENTS MEX_COMPILER REQUIRED) + if(NOT Matlab_MEX_COMPILER) + message(FATAL_ERROR "Cannot find MEX compiler binary. Please check your Matlab installation and ensure MEX in installed as well.") + endif() + + if(GTSAM_BUILD_TYPE_POSTFIXES) + set(CURRENT_POSTFIX ${CMAKE_${CMAKE_BUILD_TYPE_UPPER}_POSTFIX}) + endif() + + if(NOT BUILD_SHARED_LIBS) + message(FATAL_ERROR "GTSAM_INSTALL_MATLAB_TOOLBOX and BUILD_SHARED_LIBS=OFF. The MATLAB wrapper cannot be compiled with a static GTSAM library because mex modules are themselves shared libraries. If you want a self-contained mex module, enable GTSAM_MEX_BUILD_STATIC_MODULE instead of BUILD_SHARED_LIBS=OFF.") + endif() +endif() + # Set up cache options option(GTSAM_MEX_BUILD_STATIC_MODULE "Build MATLAB wrapper statically (increases build time)" OFF) set(GTSAM_BUILD_MEX_BINARY_FLAGS "" CACHE STRING "Extra flags for running Matlab MEX compilation") set(GTSAM_TOOLBOX_INSTALL_PATH "" CACHE PATH "Matlab toolbox destination, blank defaults to CMAKE_INSTALL_PREFIX/gtsam_toolbox") if(NOT GTSAM_TOOLBOX_INSTALL_PATH) - set(GTSAM_TOOLBOX_INSTALL_PATH "${CMAKE_INSTALL_PREFIX}/gtsam_toolbox") + set(GTSAM_TOOLBOX_INSTALL_PATH "${CMAKE_INSTALL_PREFIX}/gtsam_toolbox") endif() # GTSAM_MEX_BUILD_STATIC_MODULE is not for Windows - on Windows any static # are already compiled into the library by the linker if(GTSAM_MEX_BUILD_STATIC_MODULE AND WIN32) - message(FATAL_ERROR "GTSAM_MEX_BUILD_STATIC_MODULE should not be set on Windows - the linker already automatically compiles in any dependent static libraries. To create a standalone toolbox pacakge, simply ensure that CMake finds the static versions of all dependent libraries (Boost, etc).") + message(FATAL_ERROR "GTSAM_MEX_BUILD_STATIC_MODULE should not be set on Windows - the linker already automatically compiles in any dependent static libraries. To create a standalone toolbox pacakge, simply ensure that CMake finds the static versions of all dependent libraries (Boost, etc).") endif() -# Try to automatically configure mex path -if(APPLE) - file(GLOB matlab_bin_directories "/Applications/MATLAB*/bin") - set(mex_program_name "mex") -elseif(WIN32) - file(GLOB matlab_bin_directories "C:/Program Files*/MATLAB/*/bin") - set(mex_program_name "mex.bat") -else() - file(GLOB matlab_bin_directories "/usr/local/MATLAB/*/bin") - set(mex_program_name "mex") -endif() +set(MEX_COMMAND ${Matlab_MEX_COMPILER} CACHE PATH "Path to MATLAB MEX compiler") +set(MATLAB_ROOT ${Matlab_ROOT_DIR} CACHE PATH "Path to MATLAB installation root (e.g. /usr/local/MATLAB/R2012a)") +# Try to automatically configure mex path from provided custom `bin` path. if(GTSAM_CUSTOM_MATLAB_PATH) - set(matlab_bin_directories ${GTSAM_CUSTOM_MATLAB_PATH}) -endif() + set(matlab_bin_directory ${GTSAM_CUSTOM_MATLAB_PATH}) -# Run find_program explicitly putting $PATH after our predefined program -# directories using 'ENV PATH' and 'NO_SYSTEM_ENVIRONMENT_PATH' - this prevents -# finding the LaTeX mex program (totally unrelated to MATLAB Mex) when LaTeX is -# on the system path. -list(REVERSE matlab_bin_directories) # Reverse list so the highest version (sorted alphabetically) is preferred -find_program(MEX_COMMAND ${mex_program_name} - PATHS ${matlab_bin_directories} ENV PATH - NO_DEFAULT_PATH) -mark_as_advanced(FORCE MEX_COMMAND) -# Now that we have mex, trace back to find the Matlab installation root -get_filename_component(MEX_COMMAND "${MEX_COMMAND}" REALPATH) -get_filename_component(mex_path "${MEX_COMMAND}" PATH) -if(mex_path MATCHES ".*/win64$") - get_filename_component(MATLAB_ROOT "${mex_path}/../.." ABSOLUTE) -else() - get_filename_component(MATLAB_ROOT "${mex_path}/.." ABSOLUTE) + if(WIN32) + set(mex_program_name "mex.bat") + else() + set(mex_program_name "mex") + endif() + + # Run find_program explicitly putting $PATH after our predefined program + # directories using 'ENV PATH' and 'NO_SYSTEM_ENVIRONMENT_PATH' - this prevents + # finding the LaTeX mex program (totally unrelated to MATLAB Mex) when LaTeX is + # on the system path. + find_program(MEX_COMMAND ${mex_program_name} + PATHS ${matlab_bin_directory} ENV PATH + NO_DEFAULT_PATH) + + mark_as_advanced(FORCE MEX_COMMAND) + # Now that we have mex, trace back to find the Matlab installation root + get_filename_component(MEX_COMMAND "${MEX_COMMAND}" REALPATH) + get_filename_component(mex_path "${MEX_COMMAND}" PATH) + if(mex_path MATCHES ".*/win64$") + get_filename_component(MATLAB_ROOT "${mex_path}/../.." ABSOLUTE) + else() + get_filename_component(MATLAB_ROOT "${mex_path}/.." ABSOLUTE) + endif() endif() -set(MATLAB_ROOT "${MATLAB_ROOT}" CACHE PATH "Path to MATLAB installation root (e.g. /usr/local/MATLAB/R2012a)") # User-friendly wrapping function. Builds a mex module from the provided @@ -133,7 +146,7 @@ function(wrap_library_internal interfaceHeader linkLibraries extraIncludeDirs ex endif() endif() endforeach() - + ## CHRIS: Temporary fix. On my system the get_target_property above returned Not-found for gtsam module ## This needs to be fixed!! if(UNIX AND NOT APPLE) @@ -146,7 +159,7 @@ function(wrap_library_internal interfaceHeader linkLibraries extraIncludeDirs ex endif() endif() endif() - + #message("AUTOMATIC DEPENDENCIES: ${automaticDependencies}") ## CHRIS: End temporary fix @@ -200,7 +213,7 @@ function(wrap_library_internal interfaceHeader linkLibraries extraIncludeDirs ex endif() endif() endforeach() - + # Check libraries for conflicting versions built-in to MATLAB set(dependentLibraries "") if(NOT "${otherLibraryTargets}" STREQUAL "") @@ -227,12 +240,16 @@ function(wrap_library_internal interfaceHeader linkLibraries extraIncludeDirs ex set(_ignore gtsam::Point2 gtsam::Point3) - add_custom_command( + + # set the matlab wrapping script variable + set(MATLAB_WRAP_SCRIPT "${GTSAM_SOURCE_DIR}/wrap/scripts/matlab_wrap.py") + + add_custom_command( OUTPUT ${generated_cpp_file} DEPENDS ${interfaceHeader} ${module_library_target} ${otherLibraryTargets} ${otherSourcesAndObjects} COMMAND ${PYTHON_EXECUTABLE} - ${CMAKE_SOURCE_DIR}/wrap/matlab_wrapper.py + ${MATLAB_WRAP_SCRIPT} --src ${interfaceHeader} --module_name ${moduleName} --out ${generated_files_path} @@ -240,7 +257,7 @@ function(wrap_library_internal interfaceHeader linkLibraries extraIncludeDirs ex --ignore ${_ignore} VERBATIM WORKING_DIRECTORY ${generated_files_path}) - + # Set up building of mex module string(REPLACE ";" " " extraMexFlagsSpaced "${extraMexFlags}") string(REPLACE ";" " " mexFlagsSpaced "${GTSAM_BUILD_MEX_BINARY_FLAGS}") @@ -278,8 +295,8 @@ function(wrap_library_internal interfaceHeader linkLibraries extraIncludeDirs ex endif() # Hacking around output issue with custom command - # Deletes generated build folder - add_custom_target(wrap_${moduleName}_matlab_distclean + # Deletes generated build folder + add_custom_target(wrap_${moduleName}_matlab_distclean COMMAND cmake -E remove_directory ${generated_files_path} COMMAND cmake -E remove_directory ${compiled_mex_modules_root}) endfunction() @@ -330,17 +347,17 @@ function(check_conflicting_libraries_internal libraries) set(mxLibPath "${MATLAB_ROOT}/bin/glnx86") endif() endif() - + # List matlab's built-in libraries file(GLOB matlabLibs RELATIVE "${mxLibPath}" "${mxLibPath}/lib*") - + # Convert to base names set(matlabLibNames "") foreach(lib ${matlabLibs}) get_filename_component(libName "${lib}" NAME_WE) list(APPEND matlabLibNames "${libName}") endforeach() - + # Get names of link libraries set(linkLibNames "") foreach(lib ${libraries}) @@ -362,10 +379,10 @@ function(check_conflicting_libraries_internal libraries) endif() endif() endforeach() - + # Remove duplicates list(REMOVE_DUPLICATES linkLibNames) - + set(conflictingLibs "") foreach(lib ${linkLibNames}) list(FIND matlabLibNames "${lib}" libPos) @@ -376,7 +393,7 @@ function(check_conflicting_libraries_internal libraries) set(conflictingLibs "${conflictingLibs}${lib}") endif() endforeach() - + if(NOT "${conflictingLibs}" STREQUAL "") message(WARNING "GTSAM links to the libraries [ ${conflictingLibs} ] on your system, but " "MATLAB is distributed with its own versions of these libraries which may conflict. " @@ -418,4 +435,3 @@ function(install_matlab_scripts source_directory patterns) endif() endfunction() - diff --git a/cmake/GtsamTesting.cmake b/cmake/GtsamTesting.cmake index 3b42ffa21..573fb696a 100644 --- a/cmake/GtsamTesting.cmake +++ b/cmake/GtsamTesting.cmake @@ -88,36 +88,36 @@ enable_testing() option(GTSAM_BUILD_TESTS "Enable/Disable building of tests" ON) option(GTSAM_BUILD_EXAMPLES_ALWAYS "Build examples with 'make all' (build with 'make examples' if not)" ON) - option(GTSAM_BUILD_TIMING_ALWAYS "Build timing scripts with 'make all' (build with 'make timing' if not" OFF) +option(GTSAM_BUILD_TIMING_ALWAYS "Build timing scripts with 'make all' (build with 'make timing' if not" OFF) - # Add option for combining unit tests - if(MSVC OR XCODE_VERSION) - option(GTSAM_SINGLE_TEST_EXE "Combine unit tests into single executable (faster compile)" ON) - else() - option(GTSAM_SINGLE_TEST_EXE "Combine unit tests into single executable (faster compile)" OFF) - endif() - mark_as_advanced(GTSAM_SINGLE_TEST_EXE) +# Add option for combining unit tests +if(MSVC OR XCODE_VERSION) + option(GTSAM_SINGLE_TEST_EXE "Combine unit tests into single executable (faster compile)" ON) +else() + option(GTSAM_SINGLE_TEST_EXE "Combine unit tests into single executable (faster compile)" OFF) +endif() +mark_as_advanced(GTSAM_SINGLE_TEST_EXE) - # Enable make check (http://www.cmake.org/Wiki/CMakeEmulateMakeCheck) - if(GTSAM_BUILD_TESTS) - add_custom_target(check COMMAND ${CMAKE_CTEST_COMMAND} -C $ --output-on-failure) - # Also add alternative checks using valgrind. - # We don't look for valgrind being installed in the system, since these - # targets are not invoked unless directly instructed by the user. - if (UNIX) - # Run all tests using valgrind: - add_custom_target(check_valgrind) - endif() +# Enable make check (http://www.cmake.org/Wiki/CMakeEmulateMakeCheck) +if(GTSAM_BUILD_TESTS) + add_custom_target(check COMMAND ${CMAKE_CTEST_COMMAND} -C $ --output-on-failure) + # Also add alternative checks using valgrind. + # We don't look for valgrind being installed in the system, since these + # targets are not invoked unless directly instructed by the user. + if (UNIX) + # Run all tests using valgrind: + add_custom_target(check_valgrind) + endif() - # Add target to build tests without running - add_custom_target(all.tests) - endif() + # Add target to build tests without running + add_custom_target(all.tests) +endif() - # Add examples target - add_custom_target(examples) +# Add examples target +add_custom_target(examples) - # Add timing target - add_custom_target(timing) +# Add timing target +add_custom_target(timing) # Implementations of this file's macros: diff --git a/cmake/HandleEigen.cmake b/cmake/HandleEigen.cmake index fda441907..b21d16885 100644 --- a/cmake/HandleEigen.cmake +++ b/cmake/HandleEigen.cmake @@ -42,7 +42,7 @@ else() set(GTSAM_EIGEN_INCLUDE_FOR_INSTALL "include/gtsam/3rdparty/Eigen/") # The actual include directory (for BUILD cmake target interface): - set(GTSAM_EIGEN_INCLUDE_FOR_BUILD "${CMAKE_SOURCE_DIR}/gtsam/3rdparty/Eigen/") + set(GTSAM_EIGEN_INCLUDE_FOR_BUILD "${GTSAM_SOURCE_DIR}/gtsam/3rdparty/Eigen/") endif() # Detect Eigen version: diff --git a/cmake/HandleGeneralOptions.cmake b/cmake/HandleGeneralOptions.cmake index 85a529e49..ee86066a2 100644 --- a/cmake/HandleGeneralOptions.cmake +++ b/cmake/HandleGeneralOptions.cmake @@ -24,6 +24,7 @@ option(GTSAM_WITH_EIGEN_MKL "Eigen will use Intel MKL if available" option(GTSAM_WITH_EIGEN_MKL_OPENMP "Eigen, when using Intel MKL, will also use OpenMP for multithreading if available" OFF) option(GTSAM_THROW_CHEIRALITY_EXCEPTION "Throw exception when a triangulated point is behind a camera" ON) option(GTSAM_BUILD_PYTHON "Enable/Disable building & installation of Python module with pybind11" OFF) +option(GTSAM_INSTALL_MATLAB_TOOLBOX "Enable/Disable installation of matlab toolbox" OFF) option(GTSAM_ALLOW_DEPRECATED_SINCE_V41 "Allow use of methods/functions deprecated in GTSAM 4.1" ON) option(GTSAM_SUPPORT_NESTED_DISSECTION "Support Metis-based nested dissection" ON) option(GTSAM_TANGENT_PREINTEGRATION "Use new ImuFactor with integration on tangent space" ON) @@ -40,16 +41,5 @@ elseif(GTSAM_ROT3_EXPMAP) set(GTSAM_POSE3_EXPMAP 1 CACHE BOOL "" FORCE) endif() -# Options relating to MATLAB wrapper -# TODO: Check for matlab mex binary before handling building of binaries -option(GTSAM_INSTALL_MATLAB_TOOLBOX "Enable/Disable installation of matlab toolbox" OFF) +# Set the default Python version. This is later updated in HandlePython.cmake. set(GTSAM_PYTHON_VERSION "Default" CACHE STRING "The version of Python to build the wrappers against.") - -# Check / set dependent variables for MATLAB wrapper -if(GTSAM_INSTALL_MATLAB_TOOLBOX AND GTSAM_BUILD_TYPE_POSTFIXES) - set(CURRENT_POSTFIX ${CMAKE_${CMAKE_BUILD_TYPE_UPPER}_POSTFIX}) -endif() - -if(GTSAM_INSTALL_MATLAB_TOOLBOX AND NOT BUILD_SHARED_LIBS) - message(FATAL_ERROR "GTSAM_INSTALL_MATLAB_TOOLBOX and BUILD_SHARED_LIBS=OFF. The MATLAB wrapper cannot be compiled with a static GTSAM library because mex modules are themselves shared libraries. If you want a self-contained mex module, enable GTSAM_MEX_BUILD_STATIC_MODULE instead of BUILD_SHARED_LIBS=OFF.") -endif() diff --git a/cmake/HandlePython.cmake b/cmake/HandlePython.cmake index e5d55b451..0c24824bc 100644 --- a/cmake/HandlePython.cmake +++ b/cmake/HandlePython.cmake @@ -1,22 +1,48 @@ # Set Python version if either Python or MATLAB wrapper is requested. if(GTSAM_BUILD_PYTHON OR GTSAM_INSTALL_MATLAB_TOOLBOX) - if(${GTSAM_PYTHON_VERSION} STREQUAL "Default") - # Get info about the Python3 interpreter - # https://cmake.org/cmake/help/latest/module/FindPython3.html#module:FindPython3 - find_package(Python3 COMPONENTS Interpreter Development) + if(${GTSAM_PYTHON_VERSION} STREQUAL "Default") - if(NOT ${Python3_FOUND}) - message(FATAL_ERROR "Cannot find Python3 interpreter. Please install Python >= 3.6.") - endif() + if(${CMAKE_VERSION} VERSION_LESS "3.12.0") + # Use older version of cmake's find_python + find_package(PythonInterp) + + if(NOT ${PYTHONINTERP_FOUND}) + message( + FATAL_ERROR + "Cannot find Python interpreter. Please install Python >= 3.6.") + endif() + + find_package(PythonLibs ${PYTHON_VERSION_STRING}) + + set(Python_VERSION_MAJOR ${PYTHON_VERSION_MAJOR}) + set(Python_VERSION_MINOR ${PYTHON_VERSION_MINOR}) + set(Python_EXECUTABLE ${PYTHON_EXECUTABLE}) + + else() + # Get info about the Python3 interpreter + # https://cmake.org/cmake/help/latest/module/FindPython3.html#module:FindPython3 + find_package(Python3 COMPONENTS Interpreter Development) + + if(NOT ${Python3_FOUND}) + message( + FATAL_ERROR + "Cannot find Python3 interpreter. Please install Python >= 3.6.") + endif() + + set(Python_VERSION_MAJOR ${Python3_VERSION_MAJOR}) + set(Python_VERSION_MINOR ${Python3_VERSION_MINOR}) - set(GTSAM_PYTHON_VERSION "${Python3_VERSION_MAJOR}.${Python3_VERSION_MINOR}" - CACHE - STRING - "The version of Python to build the wrappers against." - FORCE) endif() + + set(GTSAM_PYTHON_VERSION + "${Python_VERSION_MAJOR}.${Python_VERSION_MINOR}" + CACHE STRING "The version of Python to build the wrappers against." + FORCE) + + endif() endif() +# Check for build of Unstable modules if(GTSAM_BUILD_PYTHON) if(GTSAM_UNSTABLE_BUILD_PYTHON) if (NOT GTSAM_BUILD_UNSTABLE) diff --git a/examples/Data/quadraped_imu_data.csv b/examples/Data/quadraped_imu_data.csv new file mode 100644 index 000000000..d324066d8 --- /dev/null +++ b/examples/Data/quadraped_imu_data.csv @@ -0,0 +1,2636 @@ +%time,field.header.seq,field.header.stamp,field.header.frame_id,field.orientation.x,field.orientation.y,field.orientation.z,field.orientation.w,field.orientation_covariance0,field.orientation_covariance1,field.orientation_covariance2,field.orientation_covariance3,field.orientation_covariance4,field.orientation_covariance5,field.orientation_covariance6,field.orientation_covariance7,field.orientation_covariance8,field.angular_velocity.x,field.angular_velocity.y,field.angular_velocity.z,field.angular_velocity_covariance0,field.angular_velocity_covariance1,field.angular_velocity_covariance2,field.angular_velocity_covariance3,field.angular_velocity_covariance4,field.angular_velocity_covariance5,field.angular_velocity_covariance6,field.angular_velocity_covariance7,field.angular_velocity_covariance8,field.linear_acceleration.x,field.linear_acceleration.y,field.linear_acceleration.z,field.linear_acceleration_covariance0,field.linear_acceleration_covariance1,field.linear_acceleration_covariance2,field.linear_acceleration_covariance3,field.linear_acceleration_covariance4,field.linear_acceleration_covariance5,field.linear_acceleration_covariance6,field.linear_acceleration_covariance7,field.linear_acceleration_covariance8 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+124320250000,13682,124320250000,RH_EXTIMU,1.54441756041e-05,3.33331097357e-05,-0.702979677557,0.711209934964,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-0.00398784999429,0.00900697382457,-7.46660532534e-05,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.154699949727,0.0598659055842,9.97228429688,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 diff --git a/examples/ImuFactorsExample.cpp b/examples/ImuFactorsExample.cpp index a8a9715e0..793927d7e 100644 --- a/examples/ImuFactorsExample.cpp +++ b/examples/ImuFactorsExample.cpp @@ -125,7 +125,7 @@ int main(int argc, char* argv[]) { output_filename = var_map["output_filename"].as(); use_isam = var_map["use_isam"].as(); - ISAM2* isam2; + ISAM2* isam2 = 0; if (use_isam) { printf("Using ISAM2\n"); ISAM2Params parameters; diff --git a/examples/Pose3Localization.cpp b/examples/Pose3Localization.cpp index 1667b43d9..c18a9e9ce 100644 --- a/examples/Pose3Localization.cpp +++ b/examples/Pose3Localization.cpp @@ -43,7 +43,7 @@ int main(const int argc, const char* argv[]) { auto priorModel = noiseModel::Diagonal::Variances( (Vector(6) << 1e-6, 1e-6, 1e-6, 1e-4, 1e-4, 1e-4).finished()); Key firstKey = 0; - for (const Values::ConstKeyValuePair& key_value : *initial) { + for (const auto key_value : *initial) { std::cout << "Adding prior to g2o file " << std::endl; firstKey = key_value.key; graph->addPrior(firstKey, Pose3(), priorModel); @@ -74,7 +74,7 @@ int main(const int argc, const char* argv[]) { // Calculate and print marginal covariances for all variables Marginals marginals(*graph, result); - for (const auto& key_value : result) { + for (const auto key_value : result) { auto p = dynamic_cast*>(&key_value.value); if (!p) continue; std::cout << marginals.marginalCovariance(key_value.key) << endl; diff --git a/examples/Pose3SLAMExample_changeKeys.cpp b/examples/Pose3SLAMExample_changeKeys.cpp index abadce975..5d4ed6657 100644 --- a/examples/Pose3SLAMExample_changeKeys.cpp +++ b/examples/Pose3SLAMExample_changeKeys.cpp @@ -55,7 +55,7 @@ int main(const int argc, const char *argv[]) { std::cout << "Rewriting input to file: " << inputFileRewritten << std::endl; // Additional: rewrite input with simplified keys 0,1,... Values simpleInitial; - for(const Values::ConstKeyValuePair& key_value: *initial) { + for(const auto key_value: *initial) { Key key; if(add) key = key_value.key + firstKey; diff --git a/examples/Pose3SLAMExample_g2o.cpp b/examples/Pose3SLAMExample_g2o.cpp index 1cca92f59..367964307 100644 --- a/examples/Pose3SLAMExample_g2o.cpp +++ b/examples/Pose3SLAMExample_g2o.cpp @@ -42,7 +42,7 @@ int main(const int argc, const char* argv[]) { auto priorModel = noiseModel::Diagonal::Variances( (Vector(6) << 1e-6, 1e-6, 1e-6, 1e-4, 1e-4, 1e-4).finished()); Key firstKey = 0; - for (const Values::ConstKeyValuePair& key_value : *initial) { + for (const auto key_value : *initial) { std::cout << "Adding prior to g2o file " << std::endl; firstKey = key_value.key; graph->addPrior(firstKey, Pose3(), priorModel); diff --git a/examples/Pose3SLAMExample_initializePose3Chordal.cpp b/examples/Pose3SLAMExample_initializePose3Chordal.cpp index 00a546bb2..992750fed 100644 --- a/examples/Pose3SLAMExample_initializePose3Chordal.cpp +++ b/examples/Pose3SLAMExample_initializePose3Chordal.cpp @@ -42,7 +42,7 @@ int main(const int argc, const char* argv[]) { auto priorModel = noiseModel::Diagonal::Variances( (Vector(6) << 1e-6, 1e-6, 1e-6, 1e-4, 1e-4, 1e-4).finished()); Key firstKey = 0; - for (const Values::ConstKeyValuePair& key_value : *initial) { + for (const auto key_value : *initial) { std::cout << "Adding prior to g2o file " << std::endl; firstKey = key_value.key; graph->addPrior(firstKey, Pose3(), priorModel); diff --git a/examples/Pose3SLAMExample_initializePose3Gradient.cpp b/examples/Pose3SLAMExample_initializePose3Gradient.cpp index 2f92afb9e..384f290a1 100644 --- a/examples/Pose3SLAMExample_initializePose3Gradient.cpp +++ b/examples/Pose3SLAMExample_initializePose3Gradient.cpp @@ -42,7 +42,7 @@ int main(const int argc, const char* argv[]) { auto priorModel = noiseModel::Diagonal::Variances( (Vector(6) << 1e-6, 1e-6, 1e-6, 1e-4, 1e-4, 1e-4).finished()); Key firstKey = 0; - for (const Values::ConstKeyValuePair& key_value : *initial) { + for (const auto key_value : *initial) { std::cout << "Adding prior to g2o file " << std::endl; firstKey = key_value.key; graph->addPrior(firstKey, Pose3(), priorModel); diff --git a/examples/ShonanAveragingCLI.cpp b/examples/ShonanAveragingCLI.cpp index 09221fda2..c72a32017 100644 --- a/examples/ShonanAveragingCLI.cpp +++ b/examples/ShonanAveragingCLI.cpp @@ -25,6 +25,9 @@ * Read 3D dataset sphere25000.txt and output to shonan.g2o (default) * ./ShonanAveragingCLI -i spere2500.txt * + * If you prefer using a robust Huber loss, you can add the option "-h true", + * for instance + * ./ShonanAveragingCLI -i spere2500.txt -h true */ #include @@ -43,7 +46,8 @@ int main(int argc, char* argv[]) { string datasetName; string inputFile; string outputFile; - int d, seed; + int d, seed, pMin; + bool useHuberLoss; po::options_description desc( "Shonan Rotation Averaging CLI reads a *pose* graph, extracts the " "rotation constraints, and runs the Shonan algorithm."); @@ -58,6 +62,10 @@ int main(int argc, char* argv[]) { "Write solution to the specified file")( "dimension,d", po::value(&d)->default_value(3), "Optimize over 2D or 3D rotations")( + "useHuberLoss,h", po::value(&useHuberLoss)->default_value(false), + "set True to use Huber loss")("pMin,p", + po::value(&pMin)->default_value(3), + "set to use desired rank pMin")( "seed,s", po::value(&seed)->default_value(42), "Random seed for initial estimate"); po::variables_map vm; @@ -85,11 +93,14 @@ int main(int argc, char* argv[]) { NonlinearFactorGraph::shared_ptr inputGraph; Values::shared_ptr posesInFile; Values poses; + auto lmParams = LevenbergMarquardtParams::CeresDefaults(); if (d == 2) { cout << "Running Shonan averaging for SO(2) on " << inputFile << endl; - ShonanAveraging2 shonan(inputFile); + ShonanAveraging2::Parameters parameters(lmParams); + parameters.setUseHuber(useHuberLoss); + ShonanAveraging2 shonan(inputFile, parameters); auto initial = shonan.initializeRandomly(rng); - auto result = shonan.run(initial); + auto result = shonan.run(initial, pMin); // Parse file again to set up translation problem, adding a prior boost::tie(inputGraph, posesInFile) = load2D(inputFile); @@ -101,9 +112,11 @@ int main(int argc, char* argv[]) { poses = initialize::computePoses(result.first, &poseGraph); } else if (d == 3) { cout << "Running Shonan averaging for SO(3) on " << inputFile << endl; - ShonanAveraging3 shonan(inputFile); + ShonanAveraging3::Parameters parameters(lmParams); + parameters.setUseHuber(useHuberLoss); + ShonanAveraging3 shonan(inputFile, parameters); auto initial = shonan.initializeRandomly(rng); - auto result = shonan.run(initial); + auto result = shonan.run(initial, pMin); // Parse file again to set up translation problem, adding a prior boost::tie(inputGraph, posesInFile) = load3D(inputFile); @@ -118,7 +131,7 @@ int main(int argc, char* argv[]) { return 1; } cout << "Writing result to " << outputFile << endl; - writeG2o(NonlinearFactorGraph(), poses, outputFile); + writeG2o(*inputGraph, poses, outputFile); return 0; } diff --git a/examples/SolverComparer.cpp b/examples/SolverComparer.cpp index 718ae6286..7bae41403 100644 --- a/examples/SolverComparer.cpp +++ b/examples/SolverComparer.cpp @@ -559,7 +559,7 @@ void runPerturb() // Perturb values VectorValues noise; - for(const Values::KeyValuePair& key_val: initial) + for(const Values::KeyValuePair key_val: initial) { Vector noisev(key_val.value.dim()); for(Vector::Index i = 0; i < noisev.size(); ++i) diff --git a/gtsam/3rdparty/metis/CMakeLists.txt b/gtsam/3rdparty/metis/CMakeLists.txt index de46165ff..dc26aecb2 100644 --- a/gtsam/3rdparty/metis/CMakeLists.txt +++ b/gtsam/3rdparty/metis/CMakeLists.txt @@ -1,4 +1,4 @@ -cmake_minimum_required(VERSION 2.8) +cmake_minimum_required(VERSION 3.0) project(METIS) # Add flags for currect directory and below diff --git a/gtsam/3rdparty/metis/libmetis/CMakeLists.txt b/gtsam/3rdparty/metis/libmetis/CMakeLists.txt index 330e989fa..92f931b98 100644 --- a/gtsam/3rdparty/metis/libmetis/CMakeLists.txt +++ b/gtsam/3rdparty/metis/libmetis/CMakeLists.txt @@ -12,6 +12,7 @@ endif() if(WIN32) set_target_properties(metis-gtsam PROPERTIES PREFIX "" + COMPILE_FLAGS /w RUNTIME_OUTPUT_DIRECTORY "${PROJECT_BINARY_DIR}/../../../bin") endif() diff --git a/gtsam/CMakeLists.txt b/gtsam/CMakeLists.txt index 37c4a1f88..11ae113b9 100644 --- a/gtsam/CMakeLists.txt +++ b/gtsam/CMakeLists.txt @@ -134,15 +134,15 @@ endif() # of any previously installed GTSAM headers. target_include_directories(gtsam BEFORE PUBLIC # main gtsam includes: - $ + $ $ # config.h - $ + $ # unit tests: - $ + $ ) # 3rdparty libraries: use the "system" flag so they are included via "-isystem" -# and warnings (and warnings-considered-errors) in those headers are not +# and warnings (and warnings-considered-errors) in those headers are not # reported as warnings/errors in our targets: target_include_directories(gtsam SYSTEM BEFORE PUBLIC # SuiteSparse_config @@ -156,9 +156,9 @@ target_include_directories(gtsam SYSTEM BEFORE PUBLIC ) if(GTSAM_SUPPORT_NESTED_DISSECTION) target_include_directories(gtsam BEFORE PUBLIC - $ - $ - $ + $ + $ + $ $ ) endif() @@ -199,7 +199,7 @@ if(WIN32) else() if("${CMAKE_BUILD_TYPE}" STREQUAL "Release") # Suppress all warnings from 3rd party sources. - set_source_files_properties(${3rdparty_srcs} PROPERTIES COMPILE_FLAGS "-w") + set_source_files_properties(${3rdparty_srcs} PROPERTIES COMPILE_FLAGS "-w -Wno-everything") else() set_source_files_properties(${3rdparty_srcs} PROPERTIES COMPILE_FLAGS "-Wno-error") endif() diff --git a/gtsam/base/Matrix.cpp b/gtsam/base/Matrix.cpp index 551bdac10..41a80629b 100644 --- a/gtsam/base/Matrix.cpp +++ b/gtsam/base/Matrix.cpp @@ -153,7 +153,7 @@ const Eigen::IOFormat& matlabFormat() { /* ************************************************************************* */ //3 argument call void print(const Matrix& A, const string &s, ostream& stream) { - cout << s << A.format(matlabFormat()) << endl; + stream << s << A.format(matlabFormat()) << endl; } /* ************************************************************************* */ diff --git a/gtsam/base/Matrix.h b/gtsam/base/Matrix.h index 071c33fca..a3a14c6c3 100644 --- a/gtsam/base/Matrix.h +++ b/gtsam/base/Matrix.h @@ -90,7 +90,7 @@ bool equal_with_abs_tol(const Eigen::DenseBase& A, const Eigen::DenseBas for(size_t i=0; i #include -#include +#include +#include #include #define GTSAM_PRINT(x)((x).print(#x)) @@ -72,10 +72,10 @@ namespace gtsam { }; // \ Testable inline void print(float v, const std::string& s = "") { - printf("%s%f\n",s.c_str(),v); + std::cout << (s == "" ? s : s + " ") << v << std::endl; } inline void print(double v, const std::string& s = "") { - printf("%s%lf\n",s.c_str(),v); + std::cout << (s == "" ? s : s + " ") << v << std::endl; } /** Call equal on the object */ diff --git a/gtsam/base/Vector.cpp b/gtsam/base/Vector.cpp index beec030ba..658ab9a0d 100644 --- a/gtsam/base/Vector.cpp +++ b/gtsam/base/Vector.cpp @@ -39,7 +39,7 @@ namespace gtsam { * 1. https://randomascii.wordpress.com/2012/02/25/comparing-floating-point-numbers-2012-edition/ * 2. https://floating-point-gui.de/errors/comparison/ * ************************************************************************* */ -bool fpEqual(double a, double b, double tol) { +bool fpEqual(double a, double b, double tol, bool check_relative_also) { using std::abs; using std::isnan; using std::isinf; @@ -48,7 +48,7 @@ bool fpEqual(double a, double b, double tol) { double larger = (abs(b) > abs(a)) ? abs(b) : abs(a); // handle NaNs - if(std::isnan(a) || isnan(b)) { + if(isnan(a) || isnan(b)) { return isnan(a) && isnan(b); } // handle inf @@ -60,13 +60,15 @@ bool fpEqual(double a, double b, double tol) { else if(a == 0 || b == 0 || (abs(a) + abs(b)) < DOUBLE_MIN_NORMAL) { return abs(a-b) <= tol * DOUBLE_MIN_NORMAL; } - // Check if the numbers are really close - // Needed when comparing numbers near zero or tol is in vicinity - else if(abs(a-b) <= tol) { + // Check if the numbers are really close. + // Needed when comparing numbers near zero or tol is in vicinity. + else if (abs(a - b) <= tol) { return true; } - // Use relative error - else if(abs(a-b) <= tol * min(larger, std::numeric_limits::max())) { + // Check for relative error + else if (abs(a - b) <= + tol * min(larger, std::numeric_limits::max()) && + check_relative_also) { return true; } diff --git a/gtsam/base/Vector.h b/gtsam/base/Vector.h index 319ad6ee6..ed90a7126 100644 --- a/gtsam/base/Vector.h +++ b/gtsam/base/Vector.h @@ -85,9 +85,15 @@ static_assert( * respectively for the comparison to be true. * If one is NaN/Inf and the other is not, returns false. * + * @param check_relative_also is a flag which toggles additional checking for + * relative error. This means that if either the absolute error or the relative + * error is within the tolerance, the result will be true. + * By default, the flag is true. + * * Return true if two numbers are close wrt tol. */ -GTSAM_EXPORT bool fpEqual(double a, double b, double tol); +GTSAM_EXPORT bool fpEqual(double a, double b, double tol, + bool check_relative_also = true); /** * print without optional string, must specify cout yourself diff --git a/gtsam/base/tests/testMatrix.cpp b/gtsam/base/tests/testMatrix.cpp index 468e842f2..a7c218705 100644 --- a/gtsam/base/tests/testMatrix.cpp +++ b/gtsam/base/tests/testMatrix.cpp @@ -1163,6 +1163,19 @@ TEST(Matrix , IsVectorSpace) { BOOST_CONCEPT_ASSERT((IsVectorSpace)); } +TEST(Matrix, AbsoluteError) { + double a = 2000, b = 1997, tol = 1e-1; + bool isEqual; + + // Test only absolute error + isEqual = fpEqual(a, b, tol, false); + EXPECT(!isEqual); + + // Test relative error as well + isEqual = fpEqual(a, b, tol); + EXPECT(isEqual); +} + /* ************************************************************************* */ int main() { TestResult tr; diff --git a/gtsam/geometry/Cal3.cpp b/gtsam/geometry/Cal3.cpp new file mode 100644 index 000000000..41de47f46 --- /dev/null +++ b/gtsam/geometry/Cal3.cpp @@ -0,0 +1,75 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file Cal3.cpp + * @brief Common code for all calibration models. + * @author Frank Dellaert + */ + +#include + +#include +#include +#include + +namespace gtsam { + +/* ************************************************************************* */ +Cal3::Cal3(double fov, int w, int h) + : s_(0), u0_((double)w / 2.0), v0_((double)h / 2.0) { + double a = fov * M_PI / 360.0; // fov/2 in radians + fx_ = double(w) / (2.0 * tan(a)); + fy_ = fx_; +} + +/* ************************************************************************* */ +Cal3::Cal3(const std::string& path) { + const auto buffer = path + std::string("/calibration_info.txt"); + std::ifstream infile(buffer, std::ios::in); + + if (infile && !infile.eof()) { + infile >> fx_ >> fy_ >> s_ >> u0_ >> v0_; + } else { + throw std::runtime_error("Cal3: Unable to load the calibration"); + } + + infile.close(); +} + +/* ************************************************************************* */ +std::ostream& operator<<(std::ostream& os, const Cal3& cal) { + os << "fx: " << cal.fx() << ", fy: " << cal.fy() << ", s: " << cal.skew() + << ", px: " << cal.px() << ", py: " << cal.py(); + return os; +} + +/* ************************************************************************* */ +void Cal3::print(const std::string& s) const { gtsam::print((Matrix)K(), s); } + +/* ************************************************************************* */ +bool Cal3::equals(const Cal3& K, double tol) const { + return (std::fabs(fx_ - K.fx_) < tol && std::fabs(fy_ - K.fy_) < tol && + std::fabs(s_ - K.s_) < tol && std::fabs(u0_ - K.u0_) < tol && + std::fabs(v0_ - K.v0_) < tol); +} + +Matrix3 Cal3::inverse() const { + const double fxy = fx_ * fy_, sv0 = s_ * v0_, fyu0 = fy_ * u0_; + Matrix3 K_inverse; + K_inverse << 1.0 / fx_, -s_ / fxy, (sv0 - fyu0) / fxy, 0.0, 1.0 / fy_, + -v0_ / fy_, 0.0, 0.0, 1.0; + return K_inverse; +} + +/* ************************************************************************* */ + +} // \ namespace gtsam diff --git a/gtsam/geometry/Cal3.h b/gtsam/geometry/Cal3.h new file mode 100644 index 000000000..08ce4c1e6 --- /dev/null +++ b/gtsam/geometry/Cal3.h @@ -0,0 +1,206 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file Cal3.h + * @brief Common code for all Calibration models. + * @author Varun Agrawal + */ + +/** + * @addtogroup geometry + */ + +#pragma once + +#include + +namespace gtsam { + +/** + * Function which makes use of the Implicit Function Theorem to compute the + * Jacobians of `calibrate` using `uncalibrate`. + * This is useful when there are iterative operations in the `calibrate` + * function which make computing jacobians difficult. + * + * Given f(pi, pn) = uncalibrate(pn) - pi, and g(pi) = calibrate, we can + * easily compute the Jacobians: + * df/pi = -I (pn and pi are independent args) + * Dp = -inv(H_uncal_pn) * df/pi = -inv(H_uncal_pn) * (-I) = inv(H_uncal_pn) + * Dcal = -inv(H_uncal_pn) * df/K = -inv(H_uncal_pn) * H_uncal_K + * + * @tparam Cal Calibration model. + * @tparam Dim The number of parameters in the calibration model. + * @param p Calibrated point. + * @param Dcal optional 2*p Jacobian wrpt `p` Cal3DS2 parameters. + * @param Dp optional 2*2 Jacobian wrpt intrinsic coordinates. + */ +template +void calibrateJacobians(const Cal& calibration, const Point2& pn, + OptionalJacobian<2, Dim> Dcal = boost::none, + OptionalJacobian<2, 2> Dp = boost::none) { + if (Dcal || Dp) { + Eigen::Matrix H_uncal_K; + Matrix22 H_uncal_pn, H_uncal_pn_inv; + + // Compute uncalibrate Jacobians + calibration.uncalibrate(pn, Dcal ? &H_uncal_K : nullptr, H_uncal_pn); + + H_uncal_pn_inv = H_uncal_pn.inverse(); + + if (Dp) *Dp = H_uncal_pn_inv; + if (Dcal) *Dcal = -H_uncal_pn_inv * H_uncal_K; + } +} + +/** + * @brief Common base class for all calibration models. + * @addtogroup geometry + * \nosubgrouping + */ +class GTSAM_EXPORT Cal3 { + protected: + double fx_ = 1.0f, fy_ = 1.0f; ///< focal length + double s_ = 0.0f; ///< skew + double u0_ = 0.0f, v0_ = 0.0f; ///< principal point + + public: + enum { dimension = 5 }; + ///< shared pointer to calibration object + using shared_ptr = boost::shared_ptr; + + /// @name Standard Constructors + /// @{ + + /// Create a default calibration that leaves coordinates unchanged + Cal3() = default; + + /// constructor from doubles + Cal3(double fx, double fy, double s, double u0, double v0) + : fx_(fx), fy_(fy), s_(s), u0_(u0), v0_(v0) {} + + /// constructor from vector + Cal3(const Vector5& d) + : fx_(d(0)), fy_(d(1)), s_(d(2)), u0_(d(3)), v0_(d(4)) {} + + /** + * Easy constructor, takes fov in degrees, asssumes zero skew, unit aspect + * @param fov field of view in degrees + * @param w image width + * @param h image height + */ + Cal3(double fov, int w, int h); + + /// Virtual destructor + virtual ~Cal3() {} + + /// @} + /// @name Advanced Constructors + /// @{ + + /** + * Load calibration parameters from `calibration_info.txt` file located in + * `path` directory. + * + * The contents of calibration file should be the 5 parameters in order: + * `fx, fy, s, u0, v0` + * + * @param path path to directory containing `calibration_info.txt`. + */ + Cal3(const std::string& path); + + /// @} + /// @name Testable + /// @{ + + /// Output stream operator + GTSAM_EXPORT friend std::ostream& operator<<(std::ostream& os, + const Cal3& cal); + + /// print with optional string + virtual void print(const std::string& s = "") const; + + /// Check if equal up to specified tolerance + bool equals(const Cal3& K, double tol = 10e-9) const; + + /// @} + /// @name Standard Interface + /// @{ + + /// focal length x + inline double fx() const { return fx_; } + + /// focal length y + inline double fy() const { return fy_; } + + /// aspect ratio + inline double aspectRatio() const { return fx_ / fy_; } + + /// skew + inline double skew() const { return s_; } + + /// image center in x + inline double px() const { return u0_; } + + /// image center in y + inline double py() const { return v0_; } + + /// return the principal point + Point2 principalPoint() const { return Point2(u0_, v0_); } + + /// vectorized form (column-wise) + Vector5 vector() const { + Vector5 v; + v << fx_, fy_, s_, u0_, v0_; + return v; + } + + /// return calibration matrix K + virtual Matrix3 K() const { + Matrix3 K; + K << fx_, s_, u0_, 0.0, fy_, v0_, 0.0, 0.0, 1.0; + return K; + } + +#ifdef GTSAM_ALLOW_DEPRECATED_SINCE_V41 + /** @deprecated The following function has been deprecated, use K above */ + Matrix3 matrix() const { return K(); } +#endif + + /// Return inverted calibration matrix inv(K) + Matrix3 inverse() const; + + /// return DOF, dimensionality of tangent space + inline virtual size_t dim() const { return Dim(); } + + /// return DOF, dimensionality of tangent space + inline static size_t Dim() { return dimension; } + + /// @} + /// @name Advanced Interface + /// @{ + + private: + /// Serialization function + friend class boost::serialization::access; + template + void serialize(Archive& ar, const unsigned int /*version*/) { + ar& BOOST_SERIALIZATION_NVP(fx_); + ar& BOOST_SERIALIZATION_NVP(fy_); + ar& BOOST_SERIALIZATION_NVP(s_); + ar& BOOST_SERIALIZATION_NVP(u0_); + ar& BOOST_SERIALIZATION_NVP(v0_); + } + + /// @} +}; + +} // \ namespace gtsam diff --git a/gtsam/geometry/Cal3Bundler.cpp b/gtsam/geometry/Cal3Bundler.cpp index b198643b0..e03562452 100644 --- a/gtsam/geometry/Cal3Bundler.cpp +++ b/gtsam/geometry/Cal3Bundler.cpp @@ -15,28 +15,19 @@ * @author ydjian */ -#include #include +#include +#include #include #include -#include namespace gtsam { -/* ************************************************************************* */ -Cal3Bundler::Cal3Bundler() : - f_(1), k1_(0), k2_(0), u0_(0), v0_(0), tol_(1e-5) { -} - -/* ************************************************************************* */ -Cal3Bundler::Cal3Bundler(double f, double k1, double k2, double u0, double v0, - double tol) - : f_(f), k1_(k1), k2_(k2), u0_(u0), v0_(v0), tol_(tol) {} - /* ************************************************************************* */ Matrix3 Cal3Bundler::K() const { + // This function is needed to ensure skew = 0; Matrix3 K; - K << f_, 0, u0_, 0, f_, v0_, 0, 0, 1; + K << fx_, 0, u0_, 0, fy_, v0_, 0, 0, 1.0; return K; } @@ -48,35 +39,42 @@ Vector4 Cal3Bundler::k() const { } /* ************************************************************************* */ -Vector3 Cal3Bundler::vector() const { - return Vector3(f_, k1_, k2_); +Vector3 Cal3Bundler::vector() const { return Vector3(fx_, k1_, k2_); } + +/* ************************************************************************* */ +std::ostream& operator<<(std::ostream& os, const Cal3Bundler& cal) { + os << "f: " << cal.fx() << ", k1: " << cal.k1() << ", k2: " << cal.k2() + << ", px: " << cal.px() << ", py: " << cal.py(); + return os; } /* ************************************************************************* */ void Cal3Bundler::print(const std::string& s) const { - gtsam::print((Vector)(Vector(5) << f_, k1_, k2_, u0_, v0_).finished(), s + ".K"); + gtsam::print((Vector)(Vector(5) << fx_, k1_, k2_, u0_, v0_).finished(), + s + ".K"); } /* ************************************************************************* */ bool Cal3Bundler::equals(const Cal3Bundler& K, double tol) const { - if (std::abs(f_ - K.f_) > tol || std::abs(k1_ - K.k1_) > tol - || std::abs(k2_ - K.k2_) > tol || std::abs(u0_ - K.u0_) > tol - || std::abs(v0_ - K.v0_) > tol) - return false; - return true; + const Cal3* base = dynamic_cast(&K); + return (Cal3::equals(*base, tol) && std::fabs(k1_ - K.k1_) < tol && + std::fabs(k2_ - K.k2_) < tol && std::fabs(u0_ - K.u0_) < tol && + std::fabs(v0_ - K.v0_) < tol); } /* ************************************************************************* */ -Point2 Cal3Bundler::uncalibrate(const Point2& p, // - OptionalJacobian<2, 3> Dcal, OptionalJacobian<2, 2> Dp) const { - // r = x^2 + y^2; - // g = (1 + k(1)*r + k(2)*r^2); +Point2 Cal3Bundler::uncalibrate(const Point2& p, OptionalJacobian<2, 3> Dcal, + OptionalJacobian<2, 2> Dp) const { + // r = x² + y²; + // g = (1 + k(1)*r + k(2)*r²); // pi(:,i) = g * pn(:,i) const double x = p.x(), y = p.y(); const double r = x * x + y * y; const double g = 1. + (k1_ + k2_ * r) * r; const double u = g * x, v = g * y; + const double f_ = fx_; + // Derivatives make use of intermediate variables above if (Dcal) { double rx = r * x, ry = r * y; @@ -94,23 +92,22 @@ Point2 Cal3Bundler::uncalibrate(const Point2& p, // } /* ************************************************************************* */ -Point2 Cal3Bundler::calibrate(const Point2& pi, - OptionalJacobian<2, 3> Dcal, +Point2 Cal3Bundler::calibrate(const Point2& pi, OptionalJacobian<2, 3> Dcal, OptionalJacobian<2, 2> Dp) const { - // Copied from Cal3DS2 :-( - // but specialized with k1,k2 non-zero only and fx=fy and s=0 - double x = (pi.x() - u0_)/f_, y = (pi.y() - v0_)/f_; + // Copied from Cal3DS2 + // but specialized with k1, k2 non-zero only and fx=fy and s=0 + double x = (pi.x() - u0_) / fx_, y = (pi.y() - v0_) / fx_; const Point2 invKPi(x, y); - // initialize by ignoring the distortion at all, might be problematic for pixels around boundary + // initialize by ignoring the distortion at all, might be problematic for + // pixels around boundary Point2 pn(x, y); // iterate until the uncalibrate is close to the actual pixel coordinate const int maxIterations = 10; int iteration; for (iteration = 0; iteration < maxIterations; ++iteration) { - if (distance2(uncalibrate(pn), pi) <= tol_) - break; + if (distance2(uncalibrate(pn), pi) <= tol_) break; const double px = pn.x(), py = pn.y(), xx = px * px, yy = py * py; const double rr = xx + yy; const double g = (1 + k1_ * rr + k2_ * rr * rr); @@ -119,26 +116,10 @@ Point2 Cal3Bundler::calibrate(const Point2& pi, if (iteration >= maxIterations) throw std::runtime_error( - "Cal3Bundler::calibrate fails to converge. need a better initialization"); + "Cal3Bundler::calibrate fails to converge. need a better " + "initialization"); - // We make use of the Implicit Function Theorem to compute the Jacobians from uncalibrate - // Given f(pi, pn) = uncalibrate(pn) - pi, and g(pi) = calibrate, we can easily compute the Jacobians - // df/pi = -I (pn and pi are independent args) - // Dcal = -inv(H_uncal_pn) * df/pi = -inv(H_uncal_pn) * (-I) = inv(H_uncal_pn) - // Dp = -inv(H_uncal_pn) * df/K = -inv(H_uncal_pn) * H_uncal_K - Matrix23 H_uncal_K; - Matrix22 H_uncal_pn, H_uncal_pn_inv; - - if (Dcal || Dp) { - // Compute uncalibrate Jacobians - uncalibrate(pn, Dcal ? &H_uncal_K : nullptr, H_uncal_pn); - - H_uncal_pn_inv = H_uncal_pn.inverse(); - - if (Dp) *Dp = H_uncal_pn_inv; - if (Dcal) *Dcal = -H_uncal_pn_inv * H_uncal_K; - - } + calibrateJacobians(*this, pn, Dcal, Dp); return pn; } @@ -167,14 +148,4 @@ Matrix25 Cal3Bundler::D2d_intrinsic_calibration(const Point2& p) const { return H; } -/* ************************************************************************* */ -Cal3Bundler Cal3Bundler::retract(const Vector& d) const { - return Cal3Bundler(f_ + d(0), k1_ + d(1), k2_ + d(2), u0_, v0_); -} - -/* ************************************************************************* */ -Vector3 Cal3Bundler::localCoordinates(const Cal3Bundler& T2) const { - return T2.vector() - vector(); -} - -} +} // \ namespace gtsam diff --git a/gtsam/geometry/Cal3Bundler.h b/gtsam/geometry/Cal3Bundler.h index 2e3fab002..0016ded2d 100644 --- a/gtsam/geometry/Cal3Bundler.h +++ b/gtsam/geometry/Cal3Bundler.h @@ -14,10 +14,12 @@ * @brief Calibration used by Bundler * @date Sep 25, 2010 * @author Yong Dian Jian + * @author Varun Agrawal */ #pragma once +#include #include namespace gtsam { @@ -27,23 +29,23 @@ namespace gtsam { * @addtogroup geometry * \nosubgrouping */ -class GTSAM_EXPORT Cal3Bundler { +class GTSAM_EXPORT Cal3Bundler : public Cal3 { + private: + double k1_ = 0.0f, k2_ = 0.0f; ///< radial distortion + double tol_ = 1e-5; ///< tolerance value when calibrating -private: - double f_; ///< focal length - double k1_, k2_; ///< radial distortion - double u0_, v0_; ///< image center, not a parameter to be optimized but a constant - double tol_; ///< tolerance value when calibrating - -public: + // NOTE: We use the base class fx to represent the common focal length. + // Also, image center parameters (u0, v0) are not optimized + // but are treated as constants. + public: enum { dimension = 3 }; /// @name Standard Constructors /// @{ /// Default constructor - Cal3Bundler(); + Cal3Bundler() = default; /** * Constructor @@ -55,7 +57,8 @@ public: * @param tol optional calibration tolerance value */ Cal3Bundler(double f, double k1, double k2, double u0 = 0, double v0 = 0, - double tol = 1e-5); + double tol = 1e-5) + : Cal3(f, f, 0, u0, v0), k1_(k1), k2_(k2), tol_(tol) {} virtual ~Cal3Bundler() {} @@ -63,8 +66,12 @@ public: /// @name Testable /// @{ + /// Output stream operator + GTSAM_EXPORT friend std::ostream& operator<<(std::ostream& os, + const Cal3Bundler& cal); + /// print with optional string - void print(const std::string& s = "") const; + void print(const std::string& s = "") const override; /// assert equality up to a tolerance bool equals(const Cal3Bundler& K, double tol = 10e-9) const; @@ -73,64 +80,41 @@ public: /// @name Standard Interface /// @{ - Matrix3 K() const; ///< Standard 3*3 calibration matrix - Vector4 k() const; ///< Radial distortion parameters (4 of them, 2 0) + /// distorsion parameter k1 + inline double k1() const { return k1_; } + + /// distorsion parameter k2 + inline double k2() const { return k2_; } + + /// image center in x + inline double px() const { return u0_; } + + /// image center in y + inline double py() const { return v0_; } + + Matrix3 K() const override; ///< Standard 3*3 calibration matrix + Vector4 k() const; ///< Radial distortion parameters (4 of them, 2 0) Vector3 vector() const; - /// focal length x - inline double fx() const { - return f_; - } - - /// focal length y - inline double fy() const { - return f_; - } - - /// distorsion parameter k1 - inline double k1() const { - return k1_; - } - - /// distorsion parameter k2 - inline double k2() const { - return k2_; - } - - /// image center in x - inline double px() const { - return u0_; - } - - /// image center in y - inline double py() const { - return v0_; - } - #ifdef GTSAM_ALLOW_DEPRECATED_SINCE_V41 /// get parameter u0 - inline double u0() const { - return u0_; - } + inline double u0() const { return u0_; } /// get parameter v0 - inline double v0() const { - return v0_; - } + inline double v0() const { return v0_; } #endif - /** * @brief: convert intrinsic coordinates xy to image coordinates uv * Version of uncalibrate with derivatives * @param p point in intrinsic coordinates - * @param Dcal optional 2*3 Jacobian wrpt CalBundler parameters + * @param Dcal optional 2*3 Jacobian wrpt Cal3Bundler parameters * @param Dp optional 2*2 Jacobian wrpt intrinsic coordinates * @return point in image coordinates */ Point2 uncalibrate(const Point2& p, OptionalJacobian<2, 3> Dcal = boost::none, - OptionalJacobian<2, 2> Dp = boost::none) const; + OptionalJacobian<2, 2> Dp = boost::none) const; /** * Convert a pixel coordinate to ideal coordinate xy @@ -140,8 +124,7 @@ public: * @param Dp optional 2*2 Jacobian wrpt intrinsic coordinates * @return point in intrinsic coordinates */ - Point2 calibrate(const Point2& pi, - OptionalJacobian<2, 3> Dcal = boost::none, + Point2 calibrate(const Point2& pi, OptionalJacobian<2, 3> Dcal = boost::none, OptionalJacobian<2, 2> Dp = boost::none) const; /// @deprecated might be removed in next release, use uncalibrate @@ -157,48 +140,45 @@ public: /// @name Manifold /// @{ + /// return DOF, dimensionality of tangent space + virtual size_t dim() const override { return Dim(); } + + /// return DOF, dimensionality of tangent space + inline static size_t Dim() { return dimension; } + /// Update calibration with tangent space delta - Cal3Bundler retract(const Vector& d) const; + inline Cal3Bundler retract(const Vector& d) const { + return Cal3Bundler(fx_ + d(0), k1_ + d(1), k2_ + d(2), u0_, v0_); + } /// Calculate local coordinates to another calibration - Vector3 localCoordinates(const Cal3Bundler& T2) const; - - /// dimensionality - virtual size_t dim() const { - return 3; + Vector3 localCoordinates(const Cal3Bundler& T2) const { + return T2.vector() - vector(); } - /// dimensionality - static size_t Dim() { - return 3; - } - -private: - + private: /// @} /// @name Advanced Interface /// @{ /** Serialization function */ friend class boost::serialization::access; - template - void serialize(Archive & ar, const unsigned int /*version*/) { - ar & BOOST_SERIALIZATION_NVP(f_); - ar & BOOST_SERIALIZATION_NVP(k1_); - ar & BOOST_SERIALIZATION_NVP(k2_); - ar & BOOST_SERIALIZATION_NVP(u0_); - ar & BOOST_SERIALIZATION_NVP(v0_); - ar & BOOST_SERIALIZATION_NVP(tol_); + template + void serialize(Archive& ar, const unsigned int /*version*/) { + ar& boost::serialization::make_nvp( + "Cal3Bundler", boost::serialization::base_object(*this)); + ar& BOOST_SERIALIZATION_NVP(k1_); + ar& BOOST_SERIALIZATION_NVP(k2_); + ar& BOOST_SERIALIZATION_NVP(tol_); } /// @} - }; -template<> +template <> struct traits : public internal::Manifold {}; -template<> +template <> struct traits : public internal::Manifold {}; -} // namespace gtsam +} // namespace gtsam diff --git a/gtsam/geometry/Cal3DS2.cpp b/gtsam/geometry/Cal3DS2.cpp index 070d16c6c..f93386ea7 100644 --- a/gtsam/geometry/Cal3DS2.cpp +++ b/gtsam/geometry/Cal3DS2.cpp @@ -13,28 +13,30 @@ * @file Cal3DS2.cpp * @date Feb 28, 2010 * @author ydjian + * @author Varun Agrawal */ -#include #include +#include +#include #include #include -#include namespace gtsam { /* ************************************************************************* */ -void Cal3DS2::print(const std::string& s_) const { - Base::print(s_); +std::ostream& operator<<(std::ostream& os, const Cal3DS2& cal) { + os << (Cal3DS2_Base&)cal; + return os; } +/* ************************************************************************* */ +void Cal3DS2::print(const std::string& s_) const { Base::print(s_); } + /* ************************************************************************* */ bool Cal3DS2::equals(const Cal3DS2& K, double tol) const { - if (std::abs(fx_ - K.fx_) > tol || std::abs(fy_ - K.fy_) > tol || std::abs(s_ - K.s_) > tol || - std::abs(u0_ - K.u0_) > tol || std::abs(v0_ - K.v0_) > tol || std::abs(k1_ - K.k1_) > tol || - std::abs(k2_ - K.k2_) > tol || std::abs(p1_ - K.p1_) > tol || std::abs(p2_ - K.p2_) > tol) - return false; - return true; + const Cal3DS2_Base* base = dynamic_cast(&K); + return Cal3DS2_Base::equals(*base, tol); } /* ************************************************************************* */ @@ -46,8 +48,5 @@ Cal3DS2 Cal3DS2::retract(const Vector& d) const { Vector Cal3DS2::localCoordinates(const Cal3DS2& T2) const { return T2.vector() - vector(); } - } /* ************************************************************************* */ - - diff --git a/gtsam/geometry/Cal3DS2.h b/gtsam/geometry/Cal3DS2.h index 7fd453d45..58d35c2ec 100644 --- a/gtsam/geometry/Cal3DS2.h +++ b/gtsam/geometry/Cal3DS2.h @@ -11,9 +11,11 @@ /** * @file Cal3DS2.h - * @brief Calibration of a camera with radial distortion, calculations in base class Cal3DS2_Base + * @brief Calibration of a camera with radial distortion, calculations in base + * class Cal3DS2_Base * @date Feb 28, 2010 * @author ydjian + * @autho Varun Agrawal */ #pragma once @@ -30,22 +32,20 @@ namespace gtsam { * \nosubgrouping */ class GTSAM_EXPORT Cal3DS2 : public Cal3DS2_Base { + using Base = Cal3DS2_Base; - typedef Cal3DS2_Base Base; - -public: - + public: enum { dimension = 9 }; /// @name Standard Constructors /// @{ /// Default Constructor with only unit focal length - Cal3DS2() : Base() {} + Cal3DS2() = default; - Cal3DS2(double fx, double fy, double s, double u0, double v0, - double k1, double k2, double p1 = 0.0, double p2 = 0.0) : - Base(fx, fy, s, u0, v0, k1, k2, p1, p2) {} + Cal3DS2(double fx, double fy, double s, double u0, double v0, double k1, + double k2, double p1 = 0.0, double p2 = 0.0, double tol = 1e-5) + : Base(fx, fy, s, u0, v0, k1, k2, p1, p2, tol) {} virtual ~Cal3DS2() {} @@ -53,12 +53,16 @@ public: /// @name Advanced Constructors /// @{ - Cal3DS2(const Vector &v) : Base(v) {} + Cal3DS2(const Vector9& v) : Base(v) {} /// @} /// @name Testable /// @{ + /// Output stream operator + GTSAM_EXPORT friend std::ostream& operator<<(std::ostream& os, + const Cal3DS2& cal); + /// print with optional string void print(const std::string& s = "") const override; @@ -70,16 +74,16 @@ public: /// @{ /// Given delta vector, update calibration - Cal3DS2 retract(const Vector& d) const ; + Cal3DS2 retract(const Vector& d) const; /// Given a different calibration, calculate update to obtain it - Vector localCoordinates(const Cal3DS2& T2) const ; + Vector localCoordinates(const Cal3DS2& T2) const; /// Return dimensions of calibration manifold object - virtual size_t dim() const { return dimension ; } + virtual size_t dim() const override { return Dim(); } /// Return dimensions of calibration manifold object - static size_t Dim() { return dimension; } + inline static size_t Dim() { return dimension; } /// @} /// @name Clone @@ -92,30 +96,24 @@ public: /// @} - -private: - + private: /// @name Advanced Interface /// @{ /** Serialization function */ friend class boost::serialization::access; - template - void serialize(Archive & ar, const unsigned int /*version*/) - { - ar & boost::serialization::make_nvp("Cal3DS2", - boost::serialization::base_object(*this)); + template + void serialize(Archive& ar, const unsigned int /*version*/) { + ar& boost::serialization::make_nvp( + "Cal3DS2", boost::serialization::base_object(*this)); } /// @} - }; -template<> +template <> struct traits : public internal::Manifold {}; -template<> +template <> struct traits : public internal::Manifold {}; - } - diff --git a/gtsam/geometry/Cal3DS2_Base.cpp b/gtsam/geometry/Cal3DS2_Base.cpp index 6c03883ce..a3f7026b9 100644 --- a/gtsam/geometry/Cal3DS2_Base.cpp +++ b/gtsam/geometry/Cal3DS2_Base.cpp @@ -13,27 +13,17 @@ * @file Cal3DS2_Base.cpp * @date Feb 28, 2010 * @author ydjian + * @author Varun Agrawal */ -#include #include +#include +#include #include #include -#include namespace gtsam { -/* ************************************************************************* */ -Cal3DS2_Base::Cal3DS2_Base(const Vector &v): - fx_(v[0]), fy_(v[1]), s_(v[2]), u0_(v[3]), v0_(v[4]), k1_(v[5]), k2_(v[6]), p1_(v[7]), p2_(v[8]){} - -/* ************************************************************************* */ -Matrix3 Cal3DS2_Base::K() const { - Matrix3 K; - K << fx_, s_, u0_, 0.0, fy_, v0_, 0.0, 0.0, 1.0; - return K; -} - /* ************************************************************************* */ Vector9 Cal3DS2_Base::vector() const { Vector9 v; @@ -41,6 +31,14 @@ Vector9 Cal3DS2_Base::vector() const { return v; } +/* ************************************************************************* */ +std::ostream& operator<<(std::ostream& os, const Cal3DS2_Base& cal) { + os << (Cal3&)cal; + os << ", k1: " << cal.k1() << ", k2: " << cal.k2() << ", p1: " << cal.p1() + << ", p2: " << cal.p2(); + return os; +} + /* ************************************************************************* */ void Cal3DS2_Base::print(const std::string& s_) const { gtsam::print((Matrix)K(), s_ + ".K"); @@ -49,31 +47,30 @@ void Cal3DS2_Base::print(const std::string& s_) const { /* ************************************************************************* */ bool Cal3DS2_Base::equals(const Cal3DS2_Base& K, double tol) const { - if (std::abs(fx_ - K.fx_) > tol || std::abs(fy_ - K.fy_) > tol || std::abs(s_ - K.s_) > tol || - std::abs(u0_ - K.u0_) > tol || std::abs(v0_ - K.v0_) > tol || std::abs(k1_ - K.k1_) > tol || - std::abs(k2_ - K.k2_) > tol || std::abs(p1_ - K.p1_) > tol || std::abs(p2_ - K.p2_) > tol) - return false; - return true; + const Cal3* base = dynamic_cast(&K); + return Cal3::equals(*base, tol) && std::fabs(k1_ - K.k1_) < tol && + std::fabs(k2_ - K.k2_) < tol && std::fabs(p1_ - K.p1_) < tol && + std::fabs(p2_ - K.p2_) < tol; } /* ************************************************************************* */ -static Matrix29 D2dcalibration(double x, double y, double xx, - double yy, double xy, double rr, double r4, double pnx, double pny, - const Matrix2& DK) { +static Matrix29 D2dcalibration(double x, double y, double xx, double yy, + double xy, double rr, double r4, double pnx, + double pny, const Matrix2& DK) { Matrix25 DR1; DR1 << pnx, 0.0, pny, 1.0, 0.0, 0.0, pny, 0.0, 0.0, 1.0; Matrix24 DR2; - DR2 << x * rr, x * r4, 2 * xy, rr + 2 * xx, // - y * rr, y * r4, rr + 2 * yy, 2 * xy; + DR2 << x * rr, x * r4, 2 * xy, rr + 2 * xx, // + y * rr, y * r4, rr + 2 * yy, 2 * xy; Matrix29 D; D << DR1, DK * DR2; return D; } /* ************************************************************************* */ -static Matrix2 D2dintrinsic(double x, double y, double rr, - double g, double k1, double k2, double p1, double p2, - const Matrix2& DK) { +static Matrix2 D2dintrinsic(double x, double y, double rr, double g, double k1, + double k2, double p1, double p2, + const Matrix2& DK) { const double drdx = 2. * x; const double drdy = 2. * y; const double dgdx = k1 * drdx + k2 * 2. * rr * drdx; @@ -87,24 +84,23 @@ static Matrix2 D2dintrinsic(double x, double y, double rr, const double dDydy = 2. * p2 * x + p1 * (drdy + 4. * y); Matrix2 DR; - DR << g + x * dgdx + dDxdx, x * dgdy + dDxdy, // - y * dgdx + dDydx, g + y * dgdy + dDydy; + DR << g + x * dgdx + dDxdx, x * dgdy + dDxdy, // + y * dgdx + dDydx, g + y * dgdy + dDydy; return DK * DR; } /* ************************************************************************* */ -Point2 Cal3DS2_Base::uncalibrate(const Point2& p, - OptionalJacobian<2,9> H1, OptionalJacobian<2,2> H2) const { - - // rr = x^2 + y^2; - // g = (1 + k(1)*rr + k(2)*rr^2); - // dp = [2*k(3)*x*y + k(4)*(rr + 2*x^2); 2*k(4)*x*y + k(3)*(rr + 2*y^2)]; +Point2 Cal3DS2_Base::uncalibrate(const Point2& p, OptionalJacobian<2, 9> Dcal, + OptionalJacobian<2, 2> Dp) const { + // r² = x² + y²; + // g = (1 + k(1)*r² + k(2)*r⁴); + // dp = [2*k(3)*x*y + k(4)*(r² + 2*x²); 2*k(4)*x*y + k(3)*(r² + 2*y²)]; // pi(:,i) = g * pn(:,i) + dp; const double x = p.x(), y = p.y(), xy = x * y, xx = x * x, yy = y * y; const double rr = xx + yy; const double r4 = rr * rr; - const double g = 1. + k1_ * rr + k2_ * r4; // scaling factor + const double g = 1. + k1_ * rr + k2_ * r4; // scaling factor // tangential component const double dx = 2. * p1_ * xy + p2_ * (rr + 2. * xx); @@ -115,37 +111,44 @@ Point2 Cal3DS2_Base::uncalibrate(const Point2& p, const double pny = g * y + dy; Matrix2 DK; - if (H1 || H2) DK << fx_, s_, 0.0, fy_; + if (Dcal || Dp) { + DK << fx_, s_, 0.0, fy_; + } // Derivative for calibration - if (H1) - *H1 = D2dcalibration(x, y, xx, yy, xy, rr, r4, pnx, pny, DK); + if (Dcal) { + *Dcal = D2dcalibration(x, y, xx, yy, xy, rr, r4, pnx, pny, DK); + } // Derivative for points - if (H2) - *H2 = D2dintrinsic(x, y, rr, g, k1_, k2_, p1_, p2_, DK); + if (Dp) { + *Dp = D2dintrinsic(x, y, rr, g, k1_, k2_, p1_, p2_, DK); + } // Regular uncalibrate after distortion return Point2(fx_ * pnx + s_ * pny + u0_, fy_ * pny + v0_); } /* ************************************************************************* */ -Point2 Cal3DS2_Base::calibrate(const Point2& pi, const double tol) const { +Point2 Cal3DS2_Base::calibrate(const Point2& pi, OptionalJacobian<2, 9> Dcal, + OptionalJacobian<2, 2> Dp) const { // Use the following fixed point iteration to invert the radial distortion. // pn_{t+1} = (inv(K)*pi - dp(pn_{t})) / g(pn_{t}) - const Point2 invKPi ((1 / fx_) * (pi.x() - u0_ - (s_ / fy_) * (pi.y() - v0_)), - (1 / fy_) * (pi.y() - v0_)); + const Point2 invKPi((1 / fx_) * (pi.x() - u0_ - (s_ / fy_) * (pi.y() - v0_)), + (1 / fy_) * (pi.y() - v0_)); - // initialize by ignoring the distortion at all, might be problematic for pixels around boundary + // initialize by ignoring the distortion at all, might be problematic for + // pixels around boundary Point2 pn = invKPi; // iterate until the uncalibrate is close to the actual pixel coordinate const int maxIterations = 10; int iteration; for (iteration = 0; iteration < maxIterations; ++iteration) { - if (distance2(uncalibrate(pn), pi) <= tol) break; - const double x = pn.x(), y = pn.y(), xy = x * y, xx = x * x, yy = y * y; + if (distance2(uncalibrate(pn), pi) <= tol_) break; + const double px = pn.x(), py = pn.y(), xy = px * py, xx = px * px, + yy = py * py; const double rr = xx + yy; const double g = (1 + k1_ * rr + k2_ * rr * rr); const double dx = 2 * p1_ * xy + p2_ * (rr + 2 * xx); @@ -153,8 +156,11 @@ Point2 Cal3DS2_Base::calibrate(const Point2& pi, const double tol) const { pn = (invKPi - Point2(dx, dy)) / g; } - if ( iteration >= maxIterations ) - throw std::runtime_error("Cal3DS2::calibrate fails to converge. need a better initialization"); + if (iteration >= maxIterations) + throw std::runtime_error( + "Cal3DS2::calibrate fails to converge. need a better initialization"); + + calibrateJacobians(*this, pn, Dcal, Dp); return pn; } @@ -184,8 +190,5 @@ Matrix29 Cal3DS2_Base::D2d_calibration(const Point2& p) const { DK << fx_, s_, 0.0, fy_; return D2dcalibration(x, y, xx, yy, xy, rr, r4, pnx, pny, DK); } - } /* ************************************************************************* */ - - diff --git a/gtsam/geometry/Cal3DS2_Base.h b/gtsam/geometry/Cal3DS2_Base.h index a0ece8bdb..23e138838 100644 --- a/gtsam/geometry/Cal3DS2_Base.h +++ b/gtsam/geometry/Cal3DS2_Base.h @@ -14,10 +14,12 @@ * @brief Calibration of a camera with radial distortion * @date Feb 28, 2010 * @author ydjian + * @author Varun Agrawal */ #pragma once +#include #include namespace gtsam { @@ -31,30 +33,34 @@ namespace gtsam { * http://docs.opencv.org/modules/calib3d/doc/camera_calibration_and_3d_reconstruction.html * but using only k1,k2,p1, and p2 coefficients. * K = [ fx s u0 ; 0 fy v0 ; 0 0 1 ] - * rr = Pn.x^2 + Pn.y^2 - * \hat{Pn} = (1 + k1*rr + k2*rr^2 ) Pn + [ 2*p1 Pn.x Pn.y + p2 (rr + 2 Pn.x^2) ; - * p1 (rr + 2 Pn.y^2) + 2*p2 Pn.x Pn.y ] - * pi = K*Pn + * r² = P.x² + P.y² + * P̂ = (1 + k1*r² + k2*r⁴) P + [ (2*p1 P.x P.y) + p2 (r² + 2 Pn.x²) + * p1 (r² + 2 Pn.y²) + (2*p2 Pn.x Pn.y) ] + * pi = K*P̂ */ -class GTSAM_EXPORT Cal3DS2_Base { +class GTSAM_EXPORT Cal3DS2_Base : public Cal3 { + protected: + double k1_ = 0.0f, k2_ = 0.0f; ///< radial 2nd-order and 4th-order + double p1_ = 0.0f, p2_ = 0.0f; ///< tangential distortion + double tol_ = 1e-5; ///< tolerance value when calibrating -protected: - - double fx_, fy_, s_, u0_, v0_ ; // focal length, skew and principal point - double k1_, k2_ ; // radial 2nd-order and 4th-order - double p1_, p2_ ; // tangential distortion - -public: + public: + enum { dimension = 9 }; /// @name Standard Constructors /// @{ /// Default Constructor with only unit focal length - Cal3DS2_Base() : fx_(1), fy_(1), s_(0), u0_(0), v0_(0), k1_(0), k2_(0), p1_(0), p2_(0) {} + Cal3DS2_Base() = default; - Cal3DS2_Base(double fx, double fy, double s, double u0, double v0, - double k1, double k2, double p1 = 0.0, double p2 = 0.0) : - fx_(fx), fy_(fy), s_(s), u0_(u0), v0_(v0), k1_(k1), k2_(k2), p1_(p1), p2_(p2) {} + Cal3DS2_Base(double fx, double fy, double s, double u0, double v0, double k1, + double k2, double p1 = 0.0, double p2 = 0.0, double tol = 1e-5) + : Cal3(fx, fy, s, u0, v0), + k1_(k1), + k2_(k2), + p1_(p1), + p2_(p2), + tol_(tol) {} virtual ~Cal3DS2_Base() {} @@ -62,51 +68,42 @@ public: /// @name Advanced Constructors /// @{ - Cal3DS2_Base(const Vector &v) ; + Cal3DS2_Base(const Vector9& v) + : Cal3(v(0), v(1), v(2), v(3), v(4)), + k1_(v(5)), + k2_(v(6)), + p1_(v(7)), + p2_(v(8)) {} /// @} /// @name Testable /// @{ + /// Output stream operator + GTSAM_EXPORT friend std::ostream& operator<<(std::ostream& os, + const Cal3DS2_Base& cal); + /// print with optional string - virtual void print(const std::string& s = "") const; + void print(const std::string& s = "") const override; /// assert equality up to a tolerance - bool equals(const Cal3DS2_Base& K, double tol = 10e-9) const; + bool equals(const Cal3DS2_Base& K, double tol = 1e-8) const; /// @} /// @name Standard Interface /// @{ - /// focal length x - inline double fx() const { return fx_;} - - /// focal length x - inline double fy() const { return fy_;} - - /// skew - inline double skew() const { return s_;} - - /// image center in x - inline double px() const { return u0_;} - - /// image center in y - inline double py() const { return v0_;} - /// First distortion coefficient - inline double k1() const { return k1_;} + inline double k1() const { return k1_; } /// Second distortion coefficient - inline double k2() const { return k2_;} + inline double k2() const { return k2_; } /// First tangential distortion coefficient - inline double p1() const { return p1_;} + inline double p1() const { return p1_; } /// Second tangential distortion coefficient - inline double p2() const { return p2_;} - - /// return calibration matrix -- not really applicable - Matrix3 K() const; + inline double p2() const { return p2_; } /// return distortion parameter vector Vector4 k() const { return Vector4(k1_, k2_, p1_, p2_); } @@ -121,18 +118,24 @@ public: * @param Dp optional 2*2 Jacobian wrpt intrinsic coordinates * @return point in (distorted) image coordinates */ - Point2 uncalibrate(const Point2& p, - OptionalJacobian<2,9> Dcal = boost::none, - OptionalJacobian<2,2> Dp = boost::none) const ; + Point2 uncalibrate(const Point2& p, OptionalJacobian<2, 9> Dcal = boost::none, + OptionalJacobian<2, 2> Dp = boost::none) const; /// Convert (distorted) image coordinates uv to intrinsic coordinates xy - Point2 calibrate(const Point2& p, const double tol=1e-5) const; + Point2 calibrate(const Point2& p, OptionalJacobian<2, 9> Dcal = boost::none, + OptionalJacobian<2, 2> Dp = boost::none) const; /// Derivative of uncalibrate wrpt intrinsic coordinates - Matrix2 D2d_intrinsic(const Point2& p) const ; + Matrix2 D2d_intrinsic(const Point2& p) const; /// Derivative of uncalibrate wrpt the calibration parameters - Matrix29 D2d_calibration(const Point2& p) const ; + Matrix29 D2d_calibration(const Point2& p) const; + + /// return DOF, dimensionality of tangent space + virtual size_t dim() const override { return Dim(); } + + /// return DOF, dimensionality of tangent space + inline static size_t Dim() { return dimension; } /// @} /// @name Clone @@ -145,30 +148,23 @@ public: /// @} -private: - + private: /// @name Advanced Interface /// @{ /** Serialization function */ friend class boost::serialization::access; - template - void serialize(Archive & ar, const unsigned int /*version*/) - { - ar & BOOST_SERIALIZATION_NVP(fx_); - ar & BOOST_SERIALIZATION_NVP(fy_); - ar & BOOST_SERIALIZATION_NVP(s_); - ar & BOOST_SERIALIZATION_NVP(u0_); - ar & BOOST_SERIALIZATION_NVP(v0_); - ar & BOOST_SERIALIZATION_NVP(k1_); - ar & BOOST_SERIALIZATION_NVP(k2_); - ar & BOOST_SERIALIZATION_NVP(p1_); - ar & BOOST_SERIALIZATION_NVP(p2_); + template + void serialize(Archive& ar, const unsigned int /*version*/) { + ar& boost::serialization::make_nvp( + "Cal3DS2_Base", boost::serialization::base_object(*this)); + ar& BOOST_SERIALIZATION_NVP(k1_); + ar& BOOST_SERIALIZATION_NVP(k2_); + ar& BOOST_SERIALIZATION_NVP(p1_); + ar& BOOST_SERIALIZATION_NVP(p2_); + ar& BOOST_SERIALIZATION_NVP(tol_); } /// @} - }; - } - diff --git a/gtsam/geometry/Cal3Fisheye.cpp b/gtsam/geometry/Cal3Fisheye.cpp index f7794fafb..b9e60acee 100644 --- a/gtsam/geometry/Cal3Fisheye.cpp +++ b/gtsam/geometry/Cal3Fisheye.cpp @@ -13,6 +13,7 @@ * @file Cal3Fisheye.cpp * @date Apr 8, 2020 * @author ghaggin + * @author Varun Agrawal */ #include @@ -23,18 +24,6 @@ namespace gtsam { -/* ************************************************************************* */ -Cal3Fisheye::Cal3Fisheye(const Vector9& v) - : fx_(v[0]), - fy_(v[1]), - s_(v[2]), - u0_(v[3]), - v0_(v[4]), - k1_(v[5]), - k2_(v[6]), - k3_(v[7]), - k4_(v[8]) {} - /* ************************************************************************* */ Vector9 Cal3Fisheye::vector() const { Vector9 v; @@ -42,13 +31,6 @@ Vector9 Cal3Fisheye::vector() const { return v; } -/* ************************************************************************* */ -Matrix3 Cal3Fisheye::K() const { - Matrix3 K; - K << fx_, s_, u0_, 0.0, fy_, v0_, 0.0, 0.0, 1.0; - return K; -} - /* ************************************************************************* */ double Cal3Fisheye::Scaling(double r) { static constexpr double threshold = 1e-8; @@ -122,14 +104,15 @@ Point2 Cal3Fisheye::uncalibrate(const Point2& p, OptionalJacobian<2, 9> H1, } /* ************************************************************************* */ -Point2 Cal3Fisheye::calibrate(const Point2& uv, const double tol) const { +Point2 Cal3Fisheye::calibrate(const Point2& uv, OptionalJacobian<2, 9> Dcal, + OptionalJacobian<2, 2> Dp) const { // initial gues just inverts the pinhole model const double u = uv.x(), v = uv.y(); const double yd = (v - v0_) / fy_; const double xd = (u - s_ * yd - u0_) / fx_; Point2 pi(xd, yd); - // Perform newtons method, break when solution converges past tol, + // Perform newtons method, break when solution converges past tol_, // throw exception if max iterations are reached const int maxIterations = 10; int iteration; @@ -140,7 +123,7 @@ Point2 Cal3Fisheye::calibrate(const Point2& uv, const double tol) const { const Point2 uv_hat = uncalibrate(pi, boost::none, jac); // Test convergence - if ((uv_hat - uv).norm() < tol) break; + if ((uv_hat - uv).norm() < tol_) break; // Newton's method update step pi = pi - jac.inverse() * (uv_hat - uv); @@ -151,9 +134,19 @@ Point2 Cal3Fisheye::calibrate(const Point2& uv, const double tol) const { "Cal3Fisheye::calibrate fails to converge. need a better " "initialization"); + calibrateJacobians(*this, pi, Dcal, Dp); + return pi; } +/* ************************************************************************* */ +std::ostream& operator<<(std::ostream& os, const Cal3Fisheye& cal) { + os << (Cal3&)cal; + os << ", k1: " << cal.k1() << ", k2: " << cal.k2() << ", k3: " << cal.k3() + << ", k4: " << cal.k4(); + return os; +} + /* ************************************************************************* */ void Cal3Fisheye::print(const std::string& s_) const { gtsam::print((Matrix)K(), s_ + ".K"); @@ -162,24 +155,12 @@ void Cal3Fisheye::print(const std::string& s_) const { /* ************************************************************************* */ bool Cal3Fisheye::equals(const Cal3Fisheye& K, double tol) const { - if (std::abs(fx_ - K.fx_) > tol || std::abs(fy_ - K.fy_) > tol || - std::abs(s_ - K.s_) > tol || std::abs(u0_ - K.u0_) > tol || - std::abs(v0_ - K.v0_) > tol || std::abs(k1_ - K.k1_) > tol || - std::abs(k2_ - K.k2_) > tol || std::abs(k3_ - K.k3_) > tol || - std::abs(k4_ - K.k4_) > tol) - return false; - return true; + const Cal3* base = dynamic_cast(&K); + return Cal3::equals(*base, tol) && std::fabs(k1_ - K.k1_) < tol && + std::fabs(k2_ - K.k2_) < tol && std::fabs(k3_ - K.k3_) < tol && + std::fabs(k4_ - K.k4_) < tol; } /* ************************************************************************* */ -Cal3Fisheye Cal3Fisheye::retract(const Vector& d) const { - return Cal3Fisheye(vector() + d); -} -/* ************************************************************************* */ -Vector Cal3Fisheye::localCoordinates(const Cal3Fisheye& T2) const { - return T2.vector() - vector(); -} - -} // namespace gtsam -/* ************************************************************************* */ +} // \ namespace gtsam diff --git a/gtsam/geometry/Cal3Fisheye.h b/gtsam/geometry/Cal3Fisheye.h index e24fe074f..a394d2000 100644 --- a/gtsam/geometry/Cal3Fisheye.h +++ b/gtsam/geometry/Cal3Fisheye.h @@ -14,10 +14,12 @@ * @brief Calibration of a fisheye camera * @date Apr 8, 2020 * @author ghaggin + * @author Varun Agrawal */ #pragma once +#include #include #include @@ -36,43 +38,40 @@ namespace gtsam { * Intrinsic coordinates: * [x_i;y_i] = [x/z; y/z] * Distorted coordinates: - * r^2 = (x_i)^2 + (y_i)^2 + * r² = (x_i)² + (y_i)² * th = atan(r) - * th_d = th(1 + k1*th^2 + k2*th^4 + k3*th^6 + k4*th^8) + * th_d = th(1 + k1*th² + k2*th⁴ + k3*th⁶ + k4*th⁸) * [x_d; y_d] = (th_d / r)*[x_i; y_i] * Pixel coordinates: * K = [fx s u0; 0 fy v0 ;0 0 1] * [u; v; 1] = K*[x_d; y_d; 1] */ -class GTSAM_EXPORT Cal3Fisheye { +class GTSAM_EXPORT Cal3Fisheye : public Cal3 { private: - double fx_, fy_, s_, u0_, v0_; // focal length, skew and principal point - double k1_, k2_, k3_, k4_; // fisheye distortion coefficients + double k1_ = 0.0f, k2_ = 0.0f; ///< fisheye distortion coefficients + double k3_ = 0.0f, k4_ = 0.0f; ///< fisheye distortion coefficients + double tol_ = 1e-5; ///< tolerance value when calibrating public: enum { dimension = 9 }; - typedef boost::shared_ptr - shared_ptr; ///< shared pointer to fisheye calibration object + ///< shared pointer to fisheye calibration object + using shared_ptr = boost::shared_ptr; /// @name Standard Constructors /// @{ /// Default Constructor with only unit focal length - Cal3Fisheye() - : fx_(1), fy_(1), s_(0), u0_(0), v0_(0), k1_(0), k2_(0), k3_(0), k4_(0) {} + Cal3Fisheye() = default; Cal3Fisheye(const double fx, const double fy, const double s, const double u0, const double v0, const double k1, const double k2, - const double k3, const double k4) - : fx_(fx), - fy_(fy), - s_(s), - u0_(u0), - v0_(v0), + const double k3, const double k4, double tol = 1e-5) + : Cal3(fx, fy, s, u0, v0), k1_(k1), k2_(k2), k3_(k3), - k4_(k4) {} + k4_(k4), + tol_(tol) {} virtual ~Cal3Fisheye() {} @@ -80,27 +79,17 @@ class GTSAM_EXPORT Cal3Fisheye { /// @name Advanced Constructors /// @{ - explicit Cal3Fisheye(const Vector9& v); + explicit Cal3Fisheye(const Vector9& v) + : Cal3(v(0), v(1), v(2), v(3), v(4)), + k1_(v(5)), + k2_(v(6)), + k3_(v(7)), + k4_(v(8)) {} /// @} /// @name Standard Interface /// @{ - /// focal length x - inline double fx() const { return fx_; } - - /// focal length x - inline double fy() const { return fy_; } - - /// skew - inline double skew() const { return s_; } - - /// image center in x - inline double px() const { return u0_; } - - /// image center in y - inline double py() const { return v0_; } - /// First distortion coefficient inline double k1() const { return k1_; } @@ -113,9 +102,6 @@ class GTSAM_EXPORT Cal3Fisheye { /// Second tangential distortion coefficient inline double k4() const { return k4_; } - /// return calibration matrix - Matrix3 K() const; - /// return distortion parameter vector Vector4 k() const { return Vector4(k1_, k2_, k3_, k4_); } @@ -129,24 +115,34 @@ class GTSAM_EXPORT Cal3Fisheye { * @brief convert intrinsic coordinates [x_i; y_i] to (distorted) image * coordinates [u; v] * @param p point in intrinsic coordinates - * @param Dcal optional 2*9 Jacobian wrpt intrinsic parameters (fx, fy, ..., - * k4) + * @param Dcal optional 2*9 Jacobian wrpt intrinsic parameters * @param Dp optional 2*2 Jacobian wrpt intrinsic coordinates (xi, yi) * @return point in (distorted) image coordinates */ Point2 uncalibrate(const Point2& p, OptionalJacobian<2, 9> Dcal = boost::none, OptionalJacobian<2, 2> Dp = boost::none) const; - /// Convert (distorted) image coordinates [u;v] to intrinsic coordinates [x_i, - /// y_i] - Point2 calibrate(const Point2& p, const double tol = 1e-5) const; + /** + * Convert (distorted) image coordinates [u;v] to intrinsic coordinates [x_i, + * y_i] + * @param p point in image coordinates + * @param Dcal optional 2*9 Jacobian wrpt intrinsic parameters + * @param Dp optional 2*2 Jacobian wrpt intrinsic coordinates (xi, yi) + * @return point in intrinsic coordinates + */ + Point2 calibrate(const Point2& p, OptionalJacobian<2, 9> Dcal = boost::none, + OptionalJacobian<2, 2> Dp = boost::none) const; /// @} /// @name Testable /// @{ + /// Output stream operator + GTSAM_EXPORT friend std::ostream& operator<<(std::ostream& os, + const Cal3Fisheye& cal); + /// print with optional string - virtual void print(const std::string& s = "") const; + virtual void print(const std::string& s = "") const override; /// assert equality up to a tolerance bool equals(const Cal3Fisheye& K, double tol = 10e-9) const; @@ -155,17 +151,21 @@ class GTSAM_EXPORT Cal3Fisheye { /// @name Manifold /// @{ + /// Return dimensions of calibration manifold object + virtual size_t dim() const override { return Dim(); } + + /// Return dimensions of calibration manifold object + inline static size_t Dim() { return dimension; } + /// Given delta vector, update calibration - Cal3Fisheye retract(const Vector& d) const; + inline Cal3Fisheye retract(const Vector& d) const { + return Cal3Fisheye(vector() + d); + } /// Given a different calibration, calculate update to obtain it - Vector localCoordinates(const Cal3Fisheye& T2) const; - - /// Return dimensions of calibration manifold object - virtual size_t dim() const { return 9; } - - /// Return dimensions of calibration manifold object - static size_t Dim() { return 9; } + Vector localCoordinates(const Cal3Fisheye& T2) const { + return T2.vector() - vector(); + } /// @} /// @name Clone @@ -186,11 +186,8 @@ class GTSAM_EXPORT Cal3Fisheye { friend class boost::serialization::access; template void serialize(Archive& ar, const unsigned int /*version*/) { - ar& BOOST_SERIALIZATION_NVP(fx_); - ar& BOOST_SERIALIZATION_NVP(fy_); - ar& BOOST_SERIALIZATION_NVP(s_); - ar& BOOST_SERIALIZATION_NVP(u0_); - ar& BOOST_SERIALIZATION_NVP(v0_); + ar& boost::serialization::make_nvp( + "Cal3Fisheye", boost::serialization::base_object(*this)); ar& BOOST_SERIALIZATION_NVP(k1_); ar& BOOST_SERIALIZATION_NVP(k2_); ar& BOOST_SERIALIZATION_NVP(k3_); diff --git a/gtsam/geometry/Cal3Unified.cpp b/gtsam/geometry/Cal3Unified.cpp index b1b9c3722..11aabcaa7 100644 --- a/gtsam/geometry/Cal3Unified.cpp +++ b/gtsam/geometry/Cal3Unified.cpp @@ -13,21 +13,18 @@ * @file Cal3Unified.cpp * @date Mar 8, 2014 * @author Jing Dong + * @author Varun Agrawal */ -#include #include -#include +#include #include +#include #include namespace gtsam { -/* ************************************************************************* */ -Cal3Unified::Cal3Unified(const Vector &v): - Base(v[0], v[1], v[2], v[3], v[4], v[5], v[6], v[7], v[8]), xi_(v[9]) {} - /* ************************************************************************* */ Vector10 Cal3Unified::vector() const { Vector10 v; @@ -35,6 +32,13 @@ Vector10 Cal3Unified::vector() const { return v; } +/* ************************************************************************* */ +std::ostream& operator<<(std::ostream& os, const Cal3Unified& cal) { + os << (Cal3DS2_Base&)cal; + os << ", xi: " << cal.xi(); + return os; +} + /* ************************************************************************* */ void Cal3Unified::print(const std::string& s) const { Base::print(s); @@ -43,20 +47,14 @@ void Cal3Unified::print(const std::string& s) const { /* ************************************************************************* */ bool Cal3Unified::equals(const Cal3Unified& K, double tol) const { - if (std::abs(fx_ - K.fx_) > tol || std::abs(fy_ - K.fy_) > tol || std::abs(s_ - K.s_) > tol || - std::abs(u0_ - K.u0_) > tol || std::abs(v0_ - K.v0_) > tol || std::abs(k1_ - K.k1_) > tol || - std::abs(k2_ - K.k2_) > tol || std::abs(p1_ - K.p1_) > tol || std::abs(p2_ - K.p2_) > tol || - std::abs(xi_ - K.xi_) > tol) - return false; - return true; + const Cal3DS2_Base* base = dynamic_cast(&K); + return Cal3DS2_Base::equals(*base, tol) && std::fabs(xi_ - K.xi_) < tol; } /* ************************************************************************* */ // todo: make a fixed sized jacobian version of this -Point2 Cal3Unified::uncalibrate(const Point2& p, - OptionalJacobian<2,10> H1, - OptionalJacobian<2,2> H2) const { - +Point2 Cal3Unified::uncalibrate(const Point2& p, OptionalJacobian<2, 10> Dcal, + OptionalJacobian<2, 2> Dp) const { // this part of code is modified from Cal3DS2, // since the second part of this model (after project to normalized plane) // is same as Cal3DS2 @@ -69,50 +67,53 @@ Point2 Cal3Unified::uncalibrate(const Point2& p, const double sqrt_nx = sqrt(xs * xs + ys * ys + 1.0); const double xi_sqrt_nx = 1.0 / (1 + xi * sqrt_nx); const double xi_sqrt_nx2 = xi_sqrt_nx * xi_sqrt_nx; - const double x = xs * xi_sqrt_nx, y = ys * xi_sqrt_nx; // points on NPlane + const double x = xs * xi_sqrt_nx, y = ys * xi_sqrt_nx; // points on NPlane // Part2: project NPlane point to pixel plane: use Cal3DS2 - Point2 m(x,y); + Point2 m(x, y); Matrix29 H1base; - Matrix2 H2base; // jacobians from Base class + Matrix2 H2base; // jacobians from Base class Point2 puncalib = Base::uncalibrate(m, H1base, H2base); // Inlined derivative for calibration - if (H1) { + if (Dcal) { // part1 Vector2 DU; - DU << -xs * sqrt_nx * xi_sqrt_nx2, // + DU << -xs * sqrt_nx * xi_sqrt_nx2, // -ys * sqrt_nx * xi_sqrt_nx2; - *H1 << H1base, H2base * DU; + *Dcal << H1base, H2base * DU; } // Inlined derivative for points - if (H2) { + if (Dp) { // part1 const double denom = 1.0 * xi_sqrt_nx2 / sqrt_nx; - const double mid = -(xi * xs*ys) * denom; + const double mid = -(xi * xs * ys) * denom; Matrix2 DU; - DU << (sqrt_nx + xi*(ys*ys + 1)) * denom, mid, // - mid, (sqrt_nx + xi*(xs*xs + 1)) * denom; + DU << (sqrt_nx + xi * (ys * ys + 1)) * denom, mid, // + mid, (sqrt_nx + xi * (xs * xs + 1)) * denom; - *H2 << H2base * DU; + *Dp << H2base * DU; } return puncalib; } /* ************************************************************************* */ -Point2 Cal3Unified::calibrate(const Point2& pi, const double tol) const { - +Point2 Cal3Unified::calibrate(const Point2& pi, OptionalJacobian<2, 10> Dcal, + OptionalJacobian<2, 2> Dp) const { // calibrate point to Nplane use base class::calibrate() - Point2 pnplane = Base::calibrate(pi, tol); + Point2 pnplane = Base::calibrate(pi); // call nplane to space - return this->nPlaneToSpace(pnplane); + Point2 pn = this->nPlaneToSpace(pnplane); + + calibrateJacobians(*this, pn, Dcal, Dp); + + return pn; } /* ************************************************************************* */ Point2 Cal3Unified::nPlaneToSpace(const Point2& p) const { - const double x = p.x(), y = p.y(); const double xy2 = x * x + y * y; const double sq_xy = (xi_ + sqrt(1 + (1 - xi_ * xi_) * xy2)) / (xy2 + 1); @@ -122,7 +123,6 @@ Point2 Cal3Unified::nPlaneToSpace(const Point2& p) const { /* ************************************************************************* */ Point2 Cal3Unified::spaceToNPlane(const Point2& p) const { - const double x = p.x(), y = p.y(); const double sq_xy = 1 + xi_ * sqrt(x * x + y * y + 1); @@ -135,11 +135,10 @@ Cal3Unified Cal3Unified::retract(const Vector& d) const { } /* ************************************************************************* */ -Vector10 Cal3Unified::localCoordinates(const Cal3Unified& T2) const { +Vector Cal3Unified::localCoordinates(const Cal3Unified& T2) const { return T2.vector() - vector(); } -} /* ************************************************************************* */ - +} // \ namespace gtsam diff --git a/gtsam/geometry/Cal3Unified.h b/gtsam/geometry/Cal3Unified.h index 381405d20..ee388c8c1 100644 --- a/gtsam/geometry/Cal3Unified.h +++ b/gtsam/geometry/Cal3Unified.h @@ -14,6 +14,7 @@ * @brief Unified Calibration Model, see Mei07icra for details * @date Mar 8, 2014 * @author Jing Dong + * @author Varun Agrawal */ /** @@ -27,40 +28,39 @@ namespace gtsam { /** - * @brief Calibration of a omni-directional camera with mirror + lens radial distortion + * @brief Calibration of a omni-directional camera with mirror + lens radial + * distortion * @addtogroup geometry * \nosubgrouping * * Similar to Cal3DS2, does distortion but has additional mirror parameter xi * K = [ fx s u0 ; 0 fy v0 ; 0 0 1 ] - * Pn = [ P.x / (1 + xi * \sqrt{P.x^2 + P.y^2 + 1}), P.y / (1 + xi * \sqrt{P.x^2 + P.y^2 + 1})] - * rr = Pn.x^2 + Pn.y^2 - * \hat{pn} = (1 + k1*rr + k2*rr^2 ) pn + [ 2*k3 pn.x pn.y + k4 (rr + 2 Pn.x^2) ; - * k3 (rr + 2 Pn.y^2) + 2*k4 pn.x pn.y ] + * Pn = [ P.x / (1 + xi * \sqrt{P.x² + P.y² + 1}), P.y / (1 + xi * \sqrt{P.x² + + * P.y² + 1})] + * r² = Pn.x² + Pn.y² + * \hat{pn} = (1 + k1*r² + k2*r⁴ ) pn + [ 2*k3 pn.x pn.y + k4 (r² + 2 Pn.x²) ; + * k3 (rr + 2 Pn.y²) + 2*k4 pn.x pn.y ] * pi = K*pn */ class GTSAM_EXPORT Cal3Unified : public Cal3DS2_Base { + using This = Cal3Unified; + using Base = Cal3DS2_Base; - typedef Cal3Unified This; - typedef Cal3DS2_Base Base; - -private: - - double xi_; // mirror parameter - -public: + private: + double xi_ = 0.0f; ///< mirror parameter + public: enum { dimension = 10 }; /// @name Standard Constructors /// @{ /// Default Constructor with only unit focal length - Cal3Unified() : Base(), xi_(0) {} + Cal3Unified() = default; - Cal3Unified(double fx, double fy, double s, double u0, double v0, - double k1, double k2, double p1 = 0.0, double p2 = 0.0, double xi = 0.0) : - Base(fx, fy, s, u0, v0, k1, k2, p1, p2), xi_(xi) {} + Cal3Unified(double fx, double fy, double s, double u0, double v0, double k1, + double k2, double p1 = 0.0, double p2 = 0.0, double xi = 0.0) + : Base(fx, fy, s, u0, v0, k1, k2, p1, p2), xi_(xi) {} virtual ~Cal3Unified() {} @@ -68,12 +68,17 @@ public: /// @name Advanced Constructors /// @{ - Cal3Unified(const Vector &v) ; + Cal3Unified(const Vector10& v) + : Base(v(0), v(1), v(2), v(3), v(4), v(5), v(6), v(7), v(8)), xi_(v(9)) {} /// @} /// @name Testable /// @{ + /// Output stream operator + GTSAM_EXPORT friend std::ostream& operator<<(std::ostream& os, + const Cal3Unified& cal); + /// print with optional string void print(const std::string& s = "") const override; @@ -85,7 +90,10 @@ public: /// @{ /// mirror parameter - inline double xi() const { return xi_;} + inline double xi() const { return xi_; } + + /// Return all parameters as a vector + Vector10 vector() const; /** * convert intrinsic coordinates xy to image coordinates uv @@ -95,11 +103,12 @@ public: * @return point in image coordinates */ Point2 uncalibrate(const Point2& p, - OptionalJacobian<2,10> Dcal = boost::none, - OptionalJacobian<2,2> Dp = boost::none) const ; + OptionalJacobian<2, 10> Dcal = boost::none, + OptionalJacobian<2, 2> Dp = boost::none) const; /// Conver a pixel coordinate to ideal coordinate - Point2 calibrate(const Point2& p, const double tol=1e-5) const; + Point2 calibrate(const Point2& p, OptionalJacobian<2, 10> Dcal = boost::none, + OptionalJacobian<2, 2> Dp = boost::none) const; /// Convert a 3D point to normalized unit plane Point2 spaceToNPlane(const Point2& p) const; @@ -112,41 +121,33 @@ public: /// @{ /// Given delta vector, update calibration - Cal3Unified retract(const Vector& d) const ; + Cal3Unified retract(const Vector& d) const; /// Given a different calibration, calculate update to obtain it - Vector10 localCoordinates(const Cal3Unified& T2) const ; + Vector localCoordinates(const Cal3Unified& T2) const; /// Return dimensions of calibration manifold object - virtual size_t dim() const { return dimension ; } + virtual size_t dim() const override { return Dim(); } /// Return dimensions of calibration manifold object - static size_t Dim() { return dimension; } - - /// Return all parameters as a vector - Vector10 vector() const ; + inline static size_t Dim() { return dimension; } /// @} -private: - + private: /** Serialization function */ friend class boost::serialization::access; - template - void serialize(Archive & ar, const unsigned int /*version*/) - { - ar & boost::serialization::make_nvp("Cal3Unified", - boost::serialization::base_object(*this)); - ar & BOOST_SERIALIZATION_NVP(xi_); + template + void serialize(Archive& ar, const unsigned int /*version*/) { + ar& boost::serialization::make_nvp( + "Cal3Unified", boost::serialization::base_object(*this)); + ar& BOOST_SERIALIZATION_NVP(xi_); } - }; -template<> +template <> struct traits : public internal::Manifold {}; -template<> +template <> struct traits : public internal::Manifold {}; - } - diff --git a/gtsam/geometry/Cal3_S2.cpp b/gtsam/geometry/Cal3_S2.cpp index b3d1be4b6..1a76c3f6f 100644 --- a/gtsam/geometry/Cal3_S2.cpp +++ b/gtsam/geometry/Cal3_S2.cpp @@ -22,95 +22,55 @@ #include namespace gtsam { -using namespace std; /* ************************************************************************* */ -Cal3_S2::Cal3_S2(double fov, int w, int h) : - s_(0), u0_((double) w / 2.0), v0_((double) h / 2.0) { - double a = fov * M_PI / 360.0; // fov/2 in radians - fx_ = (double) w / (2.0 * tan(a)); // old formula: fx_ = (double) w * tan(a); - fy_ = fx_; -} - -/* ************************************************************************* */ -Cal3_S2::Cal3_S2(const std::string &path) : - fx_(320), fy_(320), s_(0), u0_(320), v0_(140) { - - char buffer[200]; - buffer[0] = 0; - sprintf(buffer, "%s/calibration_info.txt", path.c_str()); - std::ifstream infile(buffer, std::ios::in); - - if (infile) - infile >> fx_ >> fy_ >> s_ >> u0_ >> v0_; - else { - throw std::runtime_error("Cal3_S2: Unable to load the calibration"); - } - - infile.close(); -} - -/* ************************************************************************* */ -ostream& operator<<(ostream& os, const Cal3_S2& cal) { - os << "{fx: " << cal.fx() << ", fy: " << cal.fy() << ", s:" << cal.skew() << ", px:" << cal.px() - << ", py:" << cal.py() << "}"; +std::ostream& operator<<(std::ostream& os, const Cal3_S2& cal) { + // Use the base class version since it is identical. + os << (Cal3&)cal; return os; } /* ************************************************************************* */ void Cal3_S2::print(const std::string& s) const { - gtsam::print((Matrix)matrix(), s); + gtsam::print((Matrix)K(), s); } /* ************************************************************************* */ bool Cal3_S2::equals(const Cal3_S2& K, double tol) const { - if (std::abs(fx_ - K.fx_) > tol) - return false; - if (std::abs(fy_ - K.fy_) > tol) - return false; - if (std::abs(s_ - K.s_) > tol) - return false; - if (std::abs(u0_ - K.u0_) > tol) - return false; - if (std::abs(v0_ - K.v0_) > tol) - return false; - return true; + return Cal3::equals(K, tol); } /* ************************************************************************* */ Point2 Cal3_S2::uncalibrate(const Point2& p, OptionalJacobian<2, 5> Dcal, - OptionalJacobian<2, 2> Dp) const { + OptionalJacobian<2, 2> Dp) const { const double x = p.x(), y = p.y(); - if (Dcal) - *Dcal << x, 0.0, y, 1.0, 0.0, 0.0, y, 0.0, 0.0, 1.0; - if (Dp) - *Dp << fx_, s_, 0.0, fy_; + if (Dcal) *Dcal << x, 0.0, y, 1.0, 0.0, 0.0, y, 0.0, 0.0, 1.0; + if (Dp) *Dp << fx_, s_, 0.0, fy_; return Point2(fx_ * x + s_ * y + u0_, fy_ * y + v0_); } /* ************************************************************************* */ -Point2 Cal3_S2::calibrate(const Point2& p, OptionalJacobian<2,5> Dcal, - OptionalJacobian<2,2> Dp) const { - const double u = p.x(), v = p.y(); - double delta_u = u - u0_, delta_v = v - v0_; - double inv_fx = 1/ fx_, inv_fy = 1/fy_; - double inv_fy_delta_v = inv_fy * delta_v, inv_fx_s_inv_fy = inv_fx * s_ * inv_fy; - Point2 point(inv_fx * (delta_u - s_ * inv_fy_delta_v), - inv_fy_delta_v); - if(Dcal) - *Dcal << - inv_fx * point.x(), inv_fx * s_ * inv_fy * inv_fy_delta_v, -inv_fx * point.y(), - -inv_fx, inv_fx_s_inv_fy, - 0, -inv_fy * point.y(), 0, 0, -inv_fy; - if(Dp) - *Dp << inv_fx, -inv_fx_s_inv_fy, 0, inv_fy; - return point; +Point2 Cal3_S2::calibrate(const Point2& p, OptionalJacobian<2, 5> Dcal, + OptionalJacobian<2, 2> Dp) const { + const double u = p.x(), v = p.y(); + double delta_u = u - u0_, delta_v = v - v0_; + double inv_fx = 1 / fx_, inv_fy = 1 / fy_; + double inv_fy_delta_v = inv_fy * delta_v; + double inv_fx_s_inv_fy = inv_fx * s_ * inv_fy; + + Point2 point(inv_fx * (delta_u - s_ * inv_fy_delta_v), inv_fy_delta_v); + if (Dcal) { + *Dcal << -inv_fx * point.x(), inv_fx * s_ * inv_fy * inv_fy_delta_v, + -inv_fx * point.y(), -inv_fx, inv_fx_s_inv_fy, 0, -inv_fy * point.y(), + 0, 0, -inv_fy; + } + if (Dp) *Dp << inv_fx, -inv_fx_s_inv_fy, 0, inv_fy; + return point; } /* ************************************************************************* */ -Vector3 Cal3_S2::calibrate(const Vector3& p) const { - return matrix_inverse() * p; -} +Vector3 Cal3_S2::calibrate(const Vector3& p) const { return inverse() * p; } /* ************************************************************************* */ -} // namespace gtsam +} // namespace gtsam diff --git a/gtsam/geometry/Cal3_S2.h b/gtsam/geometry/Cal3_S2.h index f2848d0a3..93b98a7e1 100644 --- a/gtsam/geometry/Cal3_S2.h +++ b/gtsam/geometry/Cal3_S2.h @@ -21,6 +21,7 @@ #pragma once +#include #include namespace gtsam { @@ -30,31 +31,25 @@ namespace gtsam { * @addtogroup geometry * \nosubgrouping */ -class GTSAM_EXPORT Cal3_S2 { -private: - double fx_, fy_, s_, u0_, v0_; - -public: +class GTSAM_EXPORT Cal3_S2 : public Cal3 { + public: enum { dimension = 5 }; - typedef boost::shared_ptr shared_ptr; ///< shared pointer to calibration object + + ///< shared pointer to calibration object + using shared_ptr = boost::shared_ptr; /// @name Standard Constructors /// @{ /// Create a default calibration that leaves coordinates unchanged - Cal3_S2() : - fx_(1), fy_(1), s_(0), u0_(0), v0_(0) { - } + Cal3_S2() = default; /// constructor from doubles - Cal3_S2(double fx, double fy, double s, double u0, double v0) : - fx_(fx), fy_(fy), s_(s), u0_(u0), v0_(v0) { - } + Cal3_S2(double fx, double fy, double s, double u0, double v0) + : Cal3(fx, fy, s, u0, v0) {} /// constructor from vector - Cal3_S2(const Vector &d) : - fx_(d(0)), fy_(d(1)), s_(d(2)), u0_(d(3)), v0_(d(4)) { - } + Cal3_S2(const Vector5& d) : Cal3(d) {} /** * Easy constructor, takes fov in degrees, asssumes zero skew, unit aspect @@ -62,141 +57,65 @@ public: * @param w image width * @param h image height */ - Cal3_S2(double fov, int w, int h); + Cal3_S2(double fov, int w, int h) : Cal3(fov, w, h) {} - /// @} - /// @name Advanced Constructors - /// @{ + /** + * Convert intrinsic coordinates xy to image coordinates uv, fixed derivaitves + * @param p point in intrinsic coordinates + * @param Dcal optional 2*5 Jacobian wrpt Cal3 parameters + * @param Dp optional 2*2 Jacobian wrpt intrinsic coordinates + * @return point in image coordinates + */ + Point2 uncalibrate(const Point2& p, OptionalJacobian<2, 5> Dcal = boost::none, + OptionalJacobian<2, 2> Dp = boost::none) const; - /// load calibration from location (default name is calibration_info.txt) - Cal3_S2(const std::string &path); + /** + * Convert image coordinates uv to intrinsic coordinates xy + * @param p point in image coordinates + * @param Dcal optional 2*5 Jacobian wrpt Cal3 parameters + * @param Dp optional 2*2 Jacobian wrpt intrinsic coordinates + * @return point in intrinsic coordinates + */ + Point2 calibrate(const Point2& p, OptionalJacobian<2, 5> Dcal = boost::none, + OptionalJacobian<2, 2> Dp = boost::none) const; + + /** + * Convert homogeneous image coordinates to intrinsic coordinates + * @param p point in image coordinates + * @return point in intrinsic coordinates + */ + Vector3 calibrate(const Vector3& p) const; /// @} /// @name Testable /// @{ /// Output stream operator - GTSAM_EXPORT friend std::ostream &operator<<(std::ostream &os, const Cal3_S2& cal); + GTSAM_EXPORT friend std::ostream& operator<<(std::ostream& os, + const Cal3_S2& cal); /// print with optional string - void print(const std::string& s = "Cal3_S2") const; + void print(const std::string& s = "Cal3_S2") const override; /// Check if equal up to specified tolerance bool equals(const Cal3_S2& K, double tol = 10e-9) const; - /// @} - /// @name Standard Interface - /// @{ - - /// focal length x - inline double fx() const { - return fx_; - } - - /// focal length y - inline double fy() const { - return fy_; - } - - /// aspect ratio - inline double aspectRatio() const { - return fx_/fy_; - } - - /// skew - inline double skew() const { - return s_; - } - - /// image center in x - inline double px() const { - return u0_; - } - - /// image center in y - inline double py() const { - return v0_; - } - - /// return the principal point - Point2 principalPoint() const { - return Point2(u0_, v0_); - } - - /// vectorized form (column-wise) - Vector5 vector() const { - Vector5 v; - v << fx_, fy_, s_, u0_, v0_; - return v; - } - - /// return calibration matrix K - Matrix3 K() const { - Matrix3 K; - K << fx_, s_, u0_, 0.0, fy_, v0_, 0.0, 0.0, 1.0; - return K; - } - - /** @deprecated The following function has been deprecated, use K above */ - Matrix3 matrix() const { - return K(); - } - - /// return inverted calibration matrix inv(K) - Matrix3 matrix_inverse() const { - const double fxy = fx_ * fy_, sv0 = s_ * v0_, fyu0 = fy_ * u0_; - Matrix3 K_inverse; - K_inverse << 1.0 / fx_, -s_ / fxy, (sv0 - fyu0) / fxy, 0.0, - 1.0 / fy_, -v0_ / fy_, 0.0, 0.0, 1.0; - return K_inverse; - } - - /** - * convert intrinsic coordinates xy to image coordinates uv, fixed derivaitves - * @param p point in intrinsic coordinates - * @param Dcal optional 2*5 Jacobian wrpt Cal3_S2 parameters - * @param Dp optional 2*2 Jacobian wrpt intrinsic coordinates - * @return point in image coordinates - */ - Point2 uncalibrate(const Point2& p, OptionalJacobian<2,5> Dcal = boost::none, - OptionalJacobian<2,2> Dp = boost::none) const; - - /** - * convert image coordinates uv to intrinsic coordinates xy - * @param p point in image coordinates - * @param Dcal optional 2*5 Jacobian wrpt Cal3_S2 parameters - * @param Dp optional 2*2 Jacobian wrpt intrinsic coordinates - * @return point in intrinsic coordinates - */ - Point2 calibrate(const Point2& p, OptionalJacobian<2,5> Dcal = boost::none, - OptionalJacobian<2,2> Dp = boost::none) const; - - /** - * convert homogeneous image coordinates to intrinsic coordinates - * @param p point in image coordinates - * @return point in intrinsic coordinates - */ - Vector3 calibrate(const Vector3& p) const; - /// "Between", subtracts calibrations. between(p,q) == compose(inverse(p),q) inline Cal3_S2 between(const Cal3_S2& q, - OptionalJacobian<5,5> H1=boost::none, - OptionalJacobian<5,5> H2=boost::none) const { - if(H1) *H1 = -I_5x5; - if(H2) *H2 = I_5x5; - return Cal3_S2(q.fx_-fx_, q.fy_-fy_, q.s_-s_, q.u0_-u0_, q.v0_-v0_); + OptionalJacobian<5, 5> H1 = boost::none, + OptionalJacobian<5, 5> H2 = boost::none) const { + if (H1) *H1 = -I_5x5; + if (H2) *H2 = I_5x5; + return Cal3_S2(q.fx_ - fx_, q.fy_ - fy_, q.s_ - s_, q.u0_ - u0_, + q.v0_ - v0_); } - /// @} /// @name Manifold /// @{ /// return DOF, dimensionality of tangent space - inline size_t dim() const { return dimension; } - - /// return DOF, dimensionality of tangent space - static size_t Dim() { return dimension; } + inline static size_t Dim() { return dimension; } /// Given 5-dim tangent vector, create new calibration inline Cal3_S2 retract(const Vector& d) const { @@ -212,27 +131,22 @@ public: /// @name Advanced Interface /// @{ -private: - + private: /// Serialization function friend class boost::serialization::access; - template - void serialize(Archive & ar, const unsigned int /*version*/) { - ar & BOOST_SERIALIZATION_NVP(fx_); - ar & BOOST_SERIALIZATION_NVP(fy_); - ar & BOOST_SERIALIZATION_NVP(s_); - ar & BOOST_SERIALIZATION_NVP(u0_); - ar & BOOST_SERIALIZATION_NVP(v0_); + template + void serialize(Archive& ar, const unsigned int /*version*/) { + ar& boost::serialization::make_nvp( + "Cal3_S2", boost::serialization::base_object(*this)); } /// @} - }; -template<> +template <> struct traits : public internal::Manifold {}; -template<> +template <> struct traits : public internal::Manifold {}; -} // \ namespace gtsam +} // \ namespace gtsam diff --git a/gtsam/geometry/Cal3_S2Stereo.cpp b/gtsam/geometry/Cal3_S2Stereo.cpp index 9b5aea4ed..9ef8c83a3 100644 --- a/gtsam/geometry/Cal3_S2Stereo.cpp +++ b/gtsam/geometry/Cal3_S2Stereo.cpp @@ -20,20 +20,56 @@ #include namespace gtsam { -using namespace std; + +/* ************************************************************************* */ +std::ostream& operator<<(std::ostream& os, const Cal3_S2Stereo& cal) { + os << (Cal3_S2&)cal; + os << ", b: " << cal.baseline(); + return os; +} /* ************************************************************************* */ void Cal3_S2Stereo::print(const std::string& s) const { - K_.print(s+"K: "); - std::cout << s << "Baseline: " << b_ << std::endl; - } + std::cout << s << (s != "" ? " " : ""); + std::cout << "K: " << (Matrix)K() << std::endl; + std::cout << "Baseline: " << b_ << std::endl; +} /* ************************************************************************* */ bool Cal3_S2Stereo::equals(const Cal3_S2Stereo& other, double tol) const { - if (std::abs(b_ - other.b_) > tol) return false; - return K_.equals(other.K_,tol); + const Cal3_S2* base = dynamic_cast(&other); + return (Cal3_S2::equals(*base, tol) && + std::fabs(b_ - other.baseline()) < tol); +} + +/* ************************************************************************* */ +Point2 Cal3_S2Stereo::uncalibrate(const Point2& p, OptionalJacobian<2, 6> Dcal, + OptionalJacobian<2, 2> Dp) const { + const double x = p.x(), y = p.y(); + if (Dcal) *Dcal << x, 0.0, y, 1.0, 0.0, 0.0, 0.0, y, 0.0, 0.0, 1.0, 0.0; + if (Dp) *Dp << fx_, s_, 0.0, fy_; + return Point2(fx_ * x + s_ * y + u0_, fy_ * y + v0_); +} + +/* ************************************************************************* */ +Point2 Cal3_S2Stereo::calibrate(const Point2& p, OptionalJacobian<2, 6> Dcal, + OptionalJacobian<2, 2> Dp) const { + const double u = p.x(), v = p.y(); + double delta_u = u - u0_, delta_v = v - v0_; + double inv_fx = 1 / fx_, inv_fy = 1 / fy_; + double inv_fy_delta_v = inv_fy * delta_v; + double inv_fx_s_inv_fy = inv_fx * s_ * inv_fy; + + Point2 point(inv_fx * (delta_u - s_ * inv_fy_delta_v), inv_fy_delta_v); + if (Dcal) { + *Dcal << -inv_fx * point.x(), inv_fx * s_ * inv_fy * inv_fy_delta_v, + -inv_fx * point.y(), -inv_fx, inv_fx_s_inv_fy, 0, 0, + -inv_fy * point.y(), 0, 0, -inv_fy, 0; + } + if (Dp) *Dp << inv_fx, -inv_fx_s_inv_fy, 0, inv_fy; + return point; } /* ************************************************************************* */ -} // namespace gtsam +} // namespace gtsam diff --git a/gtsam/geometry/Cal3_S2Stereo.h b/gtsam/geometry/Cal3_S2Stereo.h index a6eb41b60..ae0052fd5 100644 --- a/gtsam/geometry/Cal3_S2Stereo.h +++ b/gtsam/geometry/Cal3_S2Stereo.h @@ -22,135 +22,143 @@ namespace gtsam { +/** + * @brief The most common 5DOF 3D->2D calibration, stereo version + * @addtogroup geometry + * \nosubgrouping + */ +class GTSAM_EXPORT Cal3_S2Stereo : public Cal3_S2 { + private: + double b_ = 1.0f; ///< Stereo baseline. + + public: + enum { dimension = 6 }; + + ///< shared pointer to stereo calibration object + using shared_ptr = boost::shared_ptr; + + /// @name Standard Constructors + /// @ + + /// default calibration leaves coordinates unchanged + Cal3_S2Stereo() = default; + + /// constructor from doubles + Cal3_S2Stereo(double fx, double fy, double s, double u0, double v0, double b) + : Cal3_S2(fx, fy, s, u0, v0), b_(b) {} + + /// constructor from vector + Cal3_S2Stereo(const Vector6& d) + : Cal3_S2(d(0), d(1), d(2), d(3), d(4)), b_(d(5)) {} + + /// easy constructor; field-of-view in degrees, assumes zero skew + Cal3_S2Stereo(double fov, int w, int h, double b) + : Cal3_S2(fov, w, h), b_(b) {} + /** - * @brief The most common 5DOF 3D->2D calibration, stereo version - * @addtogroup geometry - * \nosubgrouping + * Convert intrinsic coordinates xy to image coordinates uv, fixed derivaitves + * @param p point in intrinsic coordinates + * @param Dcal optional 2*6 Jacobian wrpt Cal3_S2Stereo parameters + * @param Dp optional 2*2 Jacobian wrpt intrinsic coordinates + * @return point in image coordinates */ - class GTSAM_EXPORT Cal3_S2Stereo { - private: + Point2 uncalibrate(const Point2& p, OptionalJacobian<2, 6> Dcal = boost::none, + OptionalJacobian<2, 2> Dp = boost::none) const; - Cal3_S2 K_; - double b_; + /** + * Convert image coordinates uv to intrinsic coordinates xy + * @param p point in image coordinates + * @param Dcal optional 2*6 Jacobian wrpt Cal3_S2Stereo parameters + * @param Dp optional 2*2 Jacobian wrpt intrinsic coordinates + * @return point in intrinsic coordinates + */ + Point2 calibrate(const Point2& p, OptionalJacobian<2, 6> Dcal = boost::none, + OptionalJacobian<2, 2> Dp = boost::none) const; - public: + /** + * Convert homogeneous image coordinates to intrinsic coordinates + * @param p point in image coordinates + * @return point in intrinsic coordinates + */ + Vector3 calibrate(const Vector3& p) const { return Cal3_S2::calibrate(p); } - enum { dimension = 6 }; - typedef boost::shared_ptr shared_ptr; ///< shared pointer to stereo calibration object + /// @} + /// @name Testable + /// @{ - /// @name Standard Constructors - /// @ + /// Output stream operator + GTSAM_EXPORT friend std::ostream& operator<<(std::ostream& os, + const Cal3_S2Stereo& cal); - /// default calibration leaves coordinates unchanged - Cal3_S2Stereo() : - K_(1, 1, 0, 0, 0), b_(1.0) { - } + /// print with optional string + void print(const std::string& s = "") const override; - /// constructor from doubles - Cal3_S2Stereo(double fx, double fy, double s, double u0, double v0, double b) : - K_(fx, fy, s, u0, v0), b_(b) { - } + /// Check if equal up to specified tolerance + bool equals(const Cal3_S2Stereo& other, double tol = 10e-9) const; - /// constructor from vector - Cal3_S2Stereo(const Vector &d): K_(d(0), d(1), d(2), d(3), d(4)), b_(d(5)){} + /// @} + /// @name Standard Interface + /// @{ - /// easy constructor; field-of-view in degrees, assumes zero skew - Cal3_S2Stereo(double fov, int w, int h, double b) : - K_(fov, w, h), b_(b) { - } + /// return calibration, same for left and right + const Cal3_S2& calibration() const { return *this; } - /// @} - /// @name Testable - /// @{ + /// return calibration matrix K, same for left and right + Matrix3 K() const override { return Cal3_S2::K(); } - void print(const std::string& s = "") const; + /// return baseline + inline double baseline() const { return b_; } - /// Check if equal up to specified tolerance - bool equals(const Cal3_S2Stereo& other, double tol = 10e-9) const; + /// vectorized form (column-wise) + Vector6 vector() const { + Vector6 v; + v << Cal3_S2::vector(), b_; + return v; + } - /// @} - /// @name Standard Interface - /// @{ + /// @} + /// @name Manifold + /// @{ - /// return calibration, same for left and right - const Cal3_S2& calibration() const { return K_;} + /// return DOF, dimensionality of tangent space + inline size_t dim() const override { return Dim(); } - /// return calibration matrix K, same for left and right - Matrix matrix() const { return K_.matrix();} + /// return DOF, dimensionality of tangent space + inline static size_t Dim() { return dimension; } - /// focal length x - inline double fx() const { return K_.fx();} + /// Given 6-dim tangent vector, create new calibration + inline Cal3_S2Stereo retract(const Vector& d) const { + return Cal3_S2Stereo(fx() + d(0), fy() + d(1), skew() + d(2), px() + d(3), + py() + d(4), b_ + d(5)); + } - /// focal length x - inline double fy() const { return K_.fy();} + /// Unretraction for the calibration + Vector6 localCoordinates(const Cal3_S2Stereo& T2) const { + return T2.vector() - vector(); + } - /// skew - inline double skew() const { return K_.skew();} + /// @} + /// @name Advanced Interface + /// @{ - /// image center in x - inline double px() const { return K_.px();} + private: + /** Serialization function */ + friend class boost::serialization::access; + template + void serialize(Archive& ar, const unsigned int /*version*/) { + ar& boost::serialization::make_nvp( + "Cal3_S2", boost::serialization::base_object(*this)); + ar& BOOST_SERIALIZATION_NVP(b_); + } + /// @} +}; - /// image center in y - inline double py() const { return K_.py();} +// Define GTSAM traits +template <> +struct traits : public internal::Manifold {}; - /// return the principal point - Point2 principalPoint() const { return K_.principalPoint();} +template <> +struct traits : public internal::Manifold { +}; - /// return baseline - inline double baseline() const { return b_; } - - /// vectorized form (column-wise) - Vector6 vector() const { - Vector6 v; - v << K_.vector(), b_; - return v; - } - - /// @} - /// @name Manifold - /// @{ - - /// return DOF, dimensionality of tangent space - inline size_t dim() const { return dimension; } - - /// return DOF, dimensionality of tangent space - static size_t Dim() { return dimension; } - - /// Given 6-dim tangent vector, create new calibration - inline Cal3_S2Stereo retract(const Vector& d) const { - return Cal3_S2Stereo(K_.fx() + d(0), K_.fy() + d(1), K_.skew() + d(2), K_.px() + d(3), K_.py() + d(4), b_ + d(5)); - } - - /// Unretraction for the calibration - Vector6 localCoordinates(const Cal3_S2Stereo& T2) const { - return T2.vector() - vector(); - } - - - /// @} - /// @name Advanced Interface - /// @{ - - private: - /** Serialization function */ - friend class boost::serialization::access; - template - void serialize(Archive & ar, const unsigned int /*version*/) - { - ar & BOOST_SERIALIZATION_NVP(K_); - ar & BOOST_SERIALIZATION_NVP(b_); - } - /// @} - - }; - - // Define GTSAM traits - template<> - struct traits : public internal::Manifold { - }; - - template<> - struct traits : public internal::Manifold { - }; - -} // \ namespace gtsam +} // \ namespace gtsam diff --git a/gtsam/geometry/Line3.h b/gtsam/geometry/Line3.h index 1c7ed2f4c..f70e13ca7 100644 --- a/gtsam/geometry/Line3.h +++ b/gtsam/geometry/Line3.h @@ -102,6 +102,27 @@ class Line3 { */ Point3 point(double distance = 0) const; + /** + * Return the rotation of the line. + */ + inline Rot3 R() const { + return R_; + } + + /** + * Return the x-coordinate of the intersection of the line with the xy plane. + */ + inline double a() const { + return a_; + } + + /** + * Return the y-coordinate of the intersection of the line with the xy plane. + */ + inline double b() const { + return b_; + } + /** * Transform a line from world to camera frame * @param wTc - Pose3 of camera in world frame diff --git a/gtsam/geometry/Point3.h b/gtsam/geometry/Point3.h index 57188fc5e..001218ff7 100644 --- a/gtsam/geometry/Point3.h +++ b/gtsam/geometry/Point3.h @@ -61,7 +61,7 @@ GTSAM_EXPORT double dot(const Point3& p, const Point3& q, /// mean template -GTSAM_EXPORT Point3 mean(const CONTAINER& points) { +Point3 mean(const CONTAINER& points) { if (points.size() == 0) throw std::invalid_argument("Point3::mean input container is empty"); Point3 sum(0, 0, 0); sum = std::accumulate(points.begin(), points.end(), sum); diff --git a/gtsam/geometry/Pose2.cpp b/gtsam/geometry/Pose2.cpp index 71df0f753..bebe53dfa 100644 --- a/gtsam/geometry/Pose2.cpp +++ b/gtsam/geometry/Pose2.cpp @@ -48,7 +48,13 @@ Matrix3 Pose2::matrix() const { /* ************************************************************************* */ void Pose2::print(const string& s) const { - cout << s << "(" << t_.x() << ", " << t_.y() << ", " << r_.theta() << ")" << endl; + cout << s << this << endl; +} + +/* ************************************************************************* */ +std::ostream &operator<<(std::ostream &os, const Pose2& pose) { + os << "(" << pose.x() << ", " << pose.y() << ", " << pose.theta() << ")"; + return os; } /* ************************************************************************* */ diff --git a/gtsam/geometry/Pose2.h b/gtsam/geometry/Pose2.h index 6372779c3..a54951728 100644 --- a/gtsam/geometry/Pose2.h +++ b/gtsam/geometry/Pose2.h @@ -287,6 +287,10 @@ public: */ static std::pair rotationInterval() { return std::make_pair(2, 2); } + /// Output stream operator + GTSAM_EXPORT + friend std::ostream &operator<<(std::ostream &os, const Pose2& p); + /// @} private: diff --git a/gtsam/geometry/Pose3.cpp b/gtsam/geometry/Pose3.cpp index 22849d4f5..c183e32ed 100644 --- a/gtsam/geometry/Pose3.cpp +++ b/gtsam/geometry/Pose3.cpp @@ -106,8 +106,8 @@ Vector6 Pose3::adjointTranspose(const Vector6& xi, const Vector6& y, } /* ************************************************************************* */ -void Pose3::print(const string& s) const { - cout << (s.empty() ? s : s + " ") << *this << endl; +void Pose3::print(const std::string& s) const { + std::cout << (s.empty() ? s : s + " ") << *this << std::endl; } /* ************************************************************************* */ diff --git a/gtsam/geometry/Pose3.h b/gtsam/geometry/Pose3.h index 990ffdfe2..4c8973996 100644 --- a/gtsam/geometry/Pose3.h +++ b/gtsam/geometry/Pose3.h @@ -112,6 +112,25 @@ public: return Pose3(R_ * T.R_, t_ + R_ * T.t_); } + /** + * Interpolate between two poses via individual rotation and translation + * interpolation. + * + * The default "interpolate" method defined in Lie.h minimizes the geodesic + * distance on the manifold, leading to a screw motion interpolation in + * Cartesian space, which might not be what is expected. + * In contrast, this method executes a straight line interpolation for the + * translation, while still using interpolate (aka "slerp") for the rotational + * component. This might be more intuitive in many applications. + * + * @param T End point of interpolation. + * @param t A value in [0, 1]. + */ + Pose3 interpolateRt(const Pose3& T, double t) const { + return Pose3(interpolate(R_, T.R_, t), + interpolate(t_, T.t_, t)); + } + /// @} /// @name Lie Group /// @{ diff --git a/gtsam/geometry/SOn-inl.h b/gtsam/geometry/SOn-inl.h index 6180f4cc7..284ae76de 100644 --- a/gtsam/geometry/SOn-inl.h +++ b/gtsam/geometry/SOn-inl.h @@ -22,8 +22,6 @@ #include -using namespace std; - namespace gtsam { // Implementation for N>=5 just uses dynamic version @@ -108,7 +106,7 @@ typename SO::VectorN2 SO::vec( template void SO::print(const std::string& s) const { - cout << s << matrix_ << endl; + std::cout << s << matrix_ << std::endl; } } // namespace gtsam diff --git a/gtsam/geometry/SimpleCamera.cpp b/gtsam/geometry/SimpleCamera.cpp index 6134ae3d4..d1a5ed330 100644 --- a/gtsam/geometry/SimpleCamera.cpp +++ b/gtsam/geometry/SimpleCamera.cpp @@ -21,6 +21,7 @@ namespace gtsam { +#ifdef GTSAM_ALLOW_DEPRECATED_SINCE_V41 SimpleCamera simpleCamera(const Matrix34& P) { // P = [A|a] = s K cRw [I|-T], with s the unknown scale @@ -45,5 +46,6 @@ namespace gtsam { return SimpleCamera(Pose3(wRc, T), Cal3_S2(K(0, 0), K(1, 1), K(0, 1), K(0, 2), K(1, 2))); } +#endif } diff --git a/gtsam/geometry/SimpleCamera.h b/gtsam/geometry/SimpleCamera.h index 82f26aee2..aa00222c7 100644 --- a/gtsam/geometry/SimpleCamera.h +++ b/gtsam/geometry/SimpleCamera.h @@ -19,14 +19,22 @@ #pragma once #include -#include +#include +#include +#include #include +#include namespace gtsam { - /// A simple camera class with a Cal3_S2 calibration -typedef gtsam::PinholeCamera PinholeCameraCal3_S2; + /// Convenient aliases for Pinhole camera classes with different calibrations. + /// Also needed as forward declarations in the wrapper. + using PinholeCameraCal3_S2 = gtsam::PinholeCamera; + using PinholeCameraCal3Bundler = gtsam::PinholeCamera; + using PinholeCameraCal3DS2 = gtsam::PinholeCamera; + using PinholeCameraCal3Unified = gtsam::PinholeCamera; +#ifdef GTSAM_ALLOW_DEPRECATED_SINCE_V41 /** * @deprecated: SimpleCamera for backwards compatability with GTSAM 3.x * Use PinholeCameraCal3_S2 instead @@ -140,4 +148,6 @@ struct traits : public internal::Manifold {}; template struct Range : HasRange {}; +#endif + } // namespace gtsam diff --git a/gtsam/geometry/tests/testCal3Bundler.cpp b/gtsam/geometry/tests/testCal3Bundler.cpp index 448600266..b821d295b 100644 --- a/gtsam/geometry/tests/testCal3Bundler.cpp +++ b/gtsam/geometry/tests/testCal3Bundler.cpp @@ -11,11 +11,12 @@ /** * @file testCal3Bundler.cpp - * @brief Unit tests for transform derivatives + * @brief Unit tests for Bundler calibration model. */ #include #include +#include #include #include @@ -25,30 +26,27 @@ GTSAM_CONCEPT_TESTABLE_INST(Cal3Bundler) GTSAM_CONCEPT_MANIFOLD_INST(Cal3Bundler) static Cal3Bundler K(500, 1e-3, 1e-3, 1000, 2000); -static Point2 p(2,3); +static Point2 p(2, 3); /* ************************************************************************* */ -TEST( Cal3Bundler, vector) -{ +TEST(Cal3Bundler, vector) { Cal3Bundler K; Vector expected(3); expected << 1, 0, 0; - CHECK(assert_equal(expected,K.vector())); + CHECK(assert_equal(expected, K.vector())); } /* ************************************************************************* */ -TEST( Cal3Bundler, uncalibrate) -{ - Vector v = K.vector() ; - double r = p.x()*p.x() + p.y()*p.y() ; - double g = v[0]*(1+v[1]*r+v[2]*r*r) ; - Point2 expected (1000+g*p.x(), 2000+g*p.y()) ; +TEST(Cal3Bundler, uncalibrate) { + Vector v = K.vector(); + double r = p.x() * p.x() + p.y() * p.y(); + double g = v[0] * (1 + v[1] * r + v[2] * r * r); + Point2 expected(1000 + g * p.x(), 2000 + g * p.y()); Point2 actual = K.uncalibrate(p); - CHECK(assert_equal(expected,actual)); + CHECK(assert_equal(expected, actual)); } -TEST( Cal3Bundler, calibrate ) -{ +TEST(Cal3Bundler, calibrate) { Point2 pn(0.5, 0.5); Point2 pi = K.uncalibrate(pn); Point2 pn_hat = K.calibrate(pi); @@ -56,26 +54,28 @@ TEST( Cal3Bundler, calibrate ) } /* ************************************************************************* */ -Point2 uncalibrate_(const Cal3Bundler& k, const Point2& pt) { return k.uncalibrate(pt); } +Point2 uncalibrate_(const Cal3Bundler& k, const Point2& pt) { + return k.uncalibrate(pt); +} -Point2 calibrate_(const Cal3Bundler& k, const Point2& pt) { return k.calibrate(pt); } - -/* ************************************************************************* */ -TEST( Cal3Bundler, Duncalibrate) -{ - Matrix Dcal, Dp; - Point2 actual = K.uncalibrate(p, Dcal, Dp); - Point2 expected(2182, 3773); - CHECK(assert_equal(expected,actual,1e-7)); - Matrix numerical1 = numericalDerivative21(uncalibrate_, K, p); - Matrix numerical2 = numericalDerivative22(uncalibrate_, K, p); - CHECK(assert_equal(numerical1,Dcal,1e-7)); - CHECK(assert_equal(numerical2,Dp,1e-7)); +Point2 calibrate_(const Cal3Bundler& k, const Point2& pt) { + return k.calibrate(pt); } /* ************************************************************************* */ -TEST( Cal3Bundler, Dcalibrate) -{ +TEST(Cal3Bundler, Duncalibrate) { + Matrix Dcal, Dp; + Point2 actual = K.uncalibrate(p, Dcal, Dp); + Point2 expected(2182, 3773); + CHECK(assert_equal(expected, actual, 1e-7)); + Matrix numerical1 = numericalDerivative21(uncalibrate_, K, p); + Matrix numerical2 = numericalDerivative22(uncalibrate_, K, p); + CHECK(assert_equal(numerical1, Dcal, 1e-7)); + CHECK(assert_equal(numerical2, Dp, 1e-7)); +} + +/* ************************************************************************* */ +TEST(Cal3Bundler, Dcalibrate) { Matrix Dcal, Dp; Point2 pn(0.5, 0.5); Point2 pi = K.uncalibrate(pn); @@ -83,27 +83,41 @@ TEST( Cal3Bundler, Dcalibrate) CHECK(assert_equal(pn, actual, 1e-7)); Matrix numerical1 = numericalDerivative21(calibrate_, K, pi); Matrix numerical2 = numericalDerivative22(calibrate_, K, pi); - CHECK(assert_equal(numerical1,Dcal,1e-5)); - CHECK(assert_equal(numerical2,Dp,1e-5)); + CHECK(assert_equal(numerical1, Dcal, 1e-5)); + CHECK(assert_equal(numerical2, Dp, 1e-5)); } /* ************************************************************************* */ -TEST( Cal3Bundler, assert_equal) -{ - CHECK(assert_equal(K,K,1e-7)); -} +TEST(Cal3Bundler, assert_equal) { CHECK(assert_equal(K, K, 1e-7)); } /* ************************************************************************* */ -TEST( Cal3Bundler, retract) -{ +TEST(Cal3Bundler, retract) { Cal3Bundler expected(510, 2e-3, 2e-3, 1000, 2000); - Vector d(3); + EXPECT_LONGS_EQUAL(3, expected.dim()); + + EXPECT_LONGS_EQUAL(Cal3Bundler::Dim(), 3); + EXPECT_LONGS_EQUAL(expected.dim(), 3); + + Vector3 d; d << 10, 1e-3, 1e-3; Cal3Bundler actual = K.retract(d); - CHECK(assert_equal(expected,actual,1e-7)); - CHECK(assert_equal(d,K.localCoordinates(actual),1e-7)); + CHECK(assert_equal(expected, actual, 1e-7)); + CHECK(assert_equal(d, K.localCoordinates(actual), 1e-7)); } /* ************************************************************************* */ -int main() { TestResult tr; return TestRegistry::runAllTests(tr); } +TEST(Cal3_S2, Print) { + Cal3Bundler cal(1, 2, 3, 4, 5); + std::stringstream os; + os << "f: " << cal.fx() << ", k1: " << cal.k1() << ", k2: " << cal.k2() + << ", px: " << cal.px() << ", py: " << cal.py(); + + EXPECT(assert_stdout_equal(os.str(), cal)); +} + +/* ************************************************************************* */ +int main() { + TestResult tr; + return TestRegistry::runAllTests(tr); +} /* ************************************************************************* */ diff --git a/gtsam/geometry/tests/testCal3DFisheye.cpp b/gtsam/geometry/tests/testCal3DFisheye.cpp index 9317fb737..28064a92c 100644 --- a/gtsam/geometry/tests/testCal3DFisheye.cpp +++ b/gtsam/geometry/tests/testCal3DFisheye.cpp @@ -10,12 +10,13 @@ * -------------------------------------------------------------------------- */ /** - * @file testCal3DFisheye.cpp + * @file testCal3Fisheye.cpp * @brief Unit tests for fisheye calibration class * @author ghaggin */ #include +#include #include #include #include @@ -41,7 +42,11 @@ TEST(Cal3Fisheye, retract) { Cal3Fisheye expected(K.fx() + 1, K.fy() + 2, K.skew() + 3, K.px() + 4, K.py() + 5, K.k1() + 6, K.k2() + 7, K.k3() + 8, K.k4() + 9); - Vector d(9); + + EXPECT_LONGS_EQUAL(Cal3Fisheye::Dim(), 9); + EXPECT_LONGS_EQUAL(expected.dim(), 9); + + Vector9 d; d << 1, 2, 3, 4, 5, 6, 7, 8, 9; Cal3Fisheye actual = K.retract(d); CHECK(assert_equal(expected, actual, 1e-7)); @@ -181,6 +186,33 @@ TEST(Cal3Fisheye, calibrate3) { CHECK(assert_equal(xi_hat, xi)); } +Point2 calibrate_(const Cal3Fisheye& k, const Point2& pt) { + return k.calibrate(pt); +} + +/* ************************************************************************* */ +TEST(Cal3Fisheye, Dcalibrate) { + Point2 p(0.5, 0.5); + Point2 pi = K.uncalibrate(p); + Matrix Dcal, Dp; + K.calibrate(pi, Dcal, Dp); + Matrix numerical1 = numericalDerivative21(calibrate_, K, pi); + CHECK(assert_equal(numerical1, Dcal, 1e-5)); + Matrix numerical2 = numericalDerivative22(calibrate_, K, pi); + CHECK(assert_equal(numerical2, Dp, 1e-5)); +} + +/* ************************************************************************* */ +TEST(Cal3Fisheye, Print) { + Cal3Fisheye cal(1, 2, 3, 4, 5, 6, 7, 8, 9); + std::stringstream os; + os << "fx: " << cal.fx() << ", fy: " << cal.fy() << ", s: " << cal.skew() + << ", px: " << cal.px() << ", py: " << cal.py() << ", k1: " << cal.k1() + << ", k2: " << cal.k2() << ", k3: " << cal.k3() << ", k4: " << cal.k4(); + + EXPECT(assert_stdout_equal(os.str(), cal)); +} + /* ************************************************************************* */ int main() { TestResult tr; diff --git a/gtsam/geometry/tests/testCal3DS2.cpp b/gtsam/geometry/tests/testCal3DS2.cpp index 416665d46..7ef6e5001 100644 --- a/gtsam/geometry/tests/testCal3DS2.cpp +++ b/gtsam/geometry/tests/testCal3DS2.cpp @@ -11,12 +11,12 @@ /** * @file testCal3DS2.cpp - * @brief Unit tests for transform derivatives + * @brief Unit tests for Cal3DS2 calibration model. */ - #include #include +#include #include #include @@ -25,73 +25,103 @@ using namespace gtsam; GTSAM_CONCEPT_TESTABLE_INST(Cal3DS2) GTSAM_CONCEPT_MANIFOLD_INST(Cal3DS2) -static Cal3DS2 K(500, 100, 0.1, 320, 240, 1e-3, 2.0*1e-3, 3.0*1e-3, 4.0*1e-3); -static Point2 p(2,3); +static Cal3DS2 K(500, 100, 0.1, 320, 240, 1e-3, 2.0 * 1e-3, 3.0 * 1e-3, + 4.0 * 1e-3); +static Point2 p(2, 3); /* ************************************************************************* */ -TEST( Cal3DS2, uncalibrate) -{ - Vector k = K.k() ; - double r = p.x()*p.x() + p.y()*p.y() ; - double g = 1+k[0]*r+k[1]*r*r ; - double tx = 2*k[2]*p.x()*p.y() + k[3]*(r+2*p.x()*p.x()) ; - double ty = k[2]*(r+2*p.y()*p.y()) + 2*k[3]*p.x()*p.y() ; - Vector v_hat = (Vector(3) << g*p.x() + tx, g*p.y() + ty, 1.0).finished(); - Vector v_i = K.K() * v_hat ; - Point2 p_i(v_i(0)/v_i(2), v_i(1)/v_i(2)) ; +TEST(Cal3DS2, Uncalibrate) { + Vector k = K.k(); + double r = p.x() * p.x() + p.y() * p.y(); + double g = 1 + k[0] * r + k[1] * r * r; + double tx = 2 * k[2] * p.x() * p.y() + k[3] * (r + 2 * p.x() * p.x()); + double ty = k[2] * (r + 2 * p.y() * p.y()) + 2 * k[3] * p.x() * p.y(); + Vector v_hat = (Vector(3) << g * p.x() + tx, g * p.y() + ty, 1.0).finished(); + Vector v_i = K.K() * v_hat; + Point2 p_i(v_i(0) / v_i(2), v_i(1) / v_i(2)); Point2 q = K.uncalibrate(p); - CHECK(assert_equal(q,p_i)); + CHECK(assert_equal(q, p_i)); } -TEST( Cal3DS2, calibrate ) -{ +TEST(Cal3DS2, Calibrate) { Point2 pn(0.5, 0.5); Point2 pi = K.uncalibrate(pn); Point2 pn_hat = K.calibrate(pi); - CHECK( traits::Equals(pn, pn_hat, 1e-5)); + CHECK(traits::Equals(pn, pn_hat, 1e-5)); } -Point2 uncalibrate_(const Cal3DS2& k, const Point2& pt) { return k.uncalibrate(pt); } +Point2 uncalibrate_(const Cal3DS2& k, const Point2& pt) { + return k.uncalibrate(pt); +} /* ************************************************************************* */ -TEST( Cal3DS2, Duncalibrate1) -{ +TEST(Cal3DS2, Duncalibrate1) { Matrix computed; K.uncalibrate(p, computed, boost::none); Matrix numerical = numericalDerivative21(uncalibrate_, K, p, 1e-7); - CHECK(assert_equal(numerical,computed,1e-5)); + CHECK(assert_equal(numerical, computed, 1e-5)); Matrix separate = K.D2d_calibration(p); - CHECK(assert_equal(numerical,separate,1e-5)); + CHECK(assert_equal(numerical, separate, 1e-5)); } /* ************************************************************************* */ -TEST( Cal3DS2, Duncalibrate2) -{ - Matrix computed; K.uncalibrate(p, boost::none, computed); +TEST(Cal3DS2, Duncalibrate2) { + Matrix computed; + K.uncalibrate(p, boost::none, computed); Matrix numerical = numericalDerivative22(uncalibrate_, K, p, 1e-7); - CHECK(assert_equal(numerical,computed,1e-5)); + CHECK(assert_equal(numerical, computed, 1e-5)); Matrix separate = K.D2d_intrinsic(p); - CHECK(assert_equal(numerical,separate,1e-5)); + CHECK(assert_equal(numerical, separate, 1e-5)); +} + +Point2 calibrate_(const Cal3DS2& k, const Point2& pt) { + return k.calibrate(pt); } /* ************************************************************************* */ -TEST( Cal3DS2, assert_equal) -{ - CHECK(assert_equal(K,K,1e-5)); +TEST(Cal3DS2, Dcalibrate) { + Point2 pn(0.5, 0.5); + Point2 pi = K.uncalibrate(pn); + Matrix Dcal, Dp; + K.calibrate(pi, Dcal, Dp); + Matrix numerical1 = numericalDerivative21(calibrate_, K, pi, 1e-7); + CHECK(assert_equal(numerical1, Dcal, 1e-5)); + Matrix numerical2 = numericalDerivative22(calibrate_, K, pi, 1e-7); + CHECK(assert_equal(numerical2, Dp, 1e-5)); } /* ************************************************************************* */ -TEST( Cal3DS2, retract) -{ +TEST(Cal3DS2, Equal) { CHECK(assert_equal(K, K, 1e-5)); } + +/* ************************************************************************* */ +TEST(Cal3DS2, Retract) { Cal3DS2 expected(500 + 1, 100 + 2, 0.1 + 3, 320 + 4, 240 + 5, 1e-3 + 6, - 2.0 * 1e-3 + 7, 3.0 * 1e-3 + 8, 4.0 * 1e-3 + 9); - Vector d(9); - d << 1,2,3,4,5,6,7,8,9; + 2.0 * 1e-3 + 7, 3.0 * 1e-3 + 8, 4.0 * 1e-3 + 9); + + EXPECT_LONGS_EQUAL(Cal3DS2::Dim(), 9); + EXPECT_LONGS_EQUAL(expected.dim(), 9); + + Vector9 d; + d << 1, 2, 3, 4, 5, 6, 7, 8, 9; Cal3DS2 actual = K.retract(d); - CHECK(assert_equal(expected,actual,1e-7)); - CHECK(assert_equal(d,K.localCoordinates(actual),1e-7)); + CHECK(assert_equal(expected, actual, 1e-7)); + CHECK(assert_equal(d, K.localCoordinates(actual), 1e-7)); } /* ************************************************************************* */ -int main() { TestResult tr; return TestRegistry::runAllTests(tr); } +TEST(Cal3DS2, Print) { + Cal3DS2 cal(1, 2, 3, 4, 5, 6, 7, 8, 9); + std::stringstream os; + os << "fx: " << cal.fx() << ", fy: " << cal.fy() << ", s: " << cal.skew() + << ", px: " << cal.px() << ", py: " << cal.py() << ", k1: " << cal.k1() + << ", k2: " << cal.k2() << ", p1: " << cal.p1() << ", p2: " << cal.p2(); + + EXPECT(assert_stdout_equal(os.str(), cal)); +} + +/* ************************************************************************* */ +int main() { + TestResult tr; + return TestRegistry::runAllTests(tr); +} /* ************************************************************************* */ diff --git a/gtsam/geometry/tests/testCal3Unified.cpp b/gtsam/geometry/tests/testCal3Unified.cpp index 2c5ffd7fb..648bb358c 100644 --- a/gtsam/geometry/tests/testCal3Unified.cpp +++ b/gtsam/geometry/tests/testCal3Unified.cpp @@ -10,17 +10,18 @@ * -------------------------------------------------------------------------- */ /** - * @file testCal3Unify.cpp - * @brief Unit tests for transform derivatives + * @file testCal3Unified.cpp + * @brief Unit tests for Cal3Unified calibration model. */ #include #include +#include #include #include -#include #include +#include using namespace gtsam; @@ -35,74 +36,87 @@ V = [0.1, 1e-3, 2.0*1e-3, 3.0*1e-3, 4.0*1e-3, 0, 0, 100, 105, 320, 240]; matlab toolbox available at http://homepages.laas.fr/~cmei/index.php/Toolbox */ -static Cal3Unified K(100, 105, 0.0, 320, 240, 1e-3, 2.0*1e-3, 3.0*1e-3, 4.0*1e-3, 0.1); +static Cal3Unified K(100, 105, 0.0, 320, 240, 1e-3, 2.0 * 1e-3, 3.0 * 1e-3, + 4.0 * 1e-3, 0.1); static Point2 p(0.5, 0.7); /* ************************************************************************* */ -TEST( Cal3Unified, uncalibrate) -{ - Point2 p_i(364.7791831734982, 305.6677211952602) ; +TEST(Cal3Unified, Uncalibrate) { + Point2 p_i(364.7791831734982, 305.6677211952602); Point2 q = K.uncalibrate(p); - CHECK(assert_equal(q,p_i)); + CHECK(assert_equal(q, p_i)); } /* ************************************************************************* */ -TEST( Cal3Unified, spaceNplane) -{ +TEST(Cal3Unified, SpaceNplane) { Point2 q = K.spaceToNPlane(p); CHECK(assert_equal(Point2(0.441731600049497, 0.618424240069295), q)); CHECK(assert_equal(p, K.nPlaneToSpace(q))); } /* ************************************************************************* */ -TEST( Cal3Unified, calibrate) -{ +TEST(Cal3Unified, Calibrate) { Point2 pi = K.uncalibrate(p); Point2 pn_hat = K.calibrate(pi); - CHECK( traits::Equals(p, pn_hat, 1e-8)); + CHECK(traits::Equals(p, pn_hat, 1e-8)); } -Point2 uncalibrate_(const Cal3Unified& k, const Point2& pt) { return k.uncalibrate(pt); } +Point2 uncalibrate_(const Cal3Unified& k, const Point2& pt) { + return k.uncalibrate(pt); +} /* ************************************************************************* */ -TEST( Cal3Unified, Duncalibrate1) -{ +TEST(Cal3Unified, Duncalibrate1) { Matrix computed; K.uncalibrate(p, computed, boost::none); Matrix numerical = numericalDerivative21(uncalibrate_, K, p, 1e-7); - CHECK(assert_equal(numerical,computed,1e-6)); + CHECK(assert_equal(numerical, computed, 1e-6)); } /* ************************************************************************* */ -TEST( Cal3Unified, Duncalibrate2) -{ +TEST(Cal3Unified, Duncalibrate2) { Matrix computed; K.uncalibrate(p, boost::none, computed); Matrix numerical = numericalDerivative22(uncalibrate_, K, p, 1e-7); - CHECK(assert_equal(numerical,computed,1e-6)); + CHECK(assert_equal(numerical, computed, 1e-6)); +} + +Point2 calibrate_(const Cal3Unified& k, const Point2& pt) { + return k.calibrate(pt); } /* ************************************************************************* */ -TEST( Cal3Unified, assert_equal) -{ - CHECK(assert_equal(K,K,1e-9)); +TEST(Cal3Unified, Dcalibrate) { + Point2 pi = K.uncalibrate(p); + Matrix Dcal, Dp; + K.calibrate(pi, Dcal, Dp); + Matrix numerical1 = numericalDerivative21(calibrate_, K, pi); + CHECK(assert_equal(numerical1, Dcal, 1e-5)); + Matrix numerical2 = numericalDerivative22(calibrate_, K, pi); + CHECK(assert_equal(numerical2, Dp, 1e-5)); } /* ************************************************************************* */ -TEST( Cal3Unified, retract) -{ - Cal3Unified expected(100 + 2, 105 + 3, 0.0 + 4, 320 + 5, 240 + 6, - 1e-3 + 7, 2.0*1e-3 + 8, 3.0*1e-3 + 9, 4.0*1e-3 + 10, 0.1 + 1); - Vector d(10); +TEST(Cal3Unified, Equal) { CHECK(assert_equal(K, K, 1e-9)); } + +/* ************************************************************************* */ +TEST(Cal3Unified, Retract) { + Cal3Unified expected(100 + 2, 105 + 3, 0.0 + 4, 320 + 5, 240 + 6, 1e-3 + 7, + 2.0 * 1e-3 + 8, 3.0 * 1e-3 + 9, 4.0 * 1e-3 + 10, + 0.1 + 1); + + EXPECT_LONGS_EQUAL(Cal3Unified::Dim(), 10); + EXPECT_LONGS_EQUAL(expected.dim(), 10); + + Vector10 d; d << 2, 3, 4, 5, 6, 7, 8, 9, 10, 1; Cal3Unified actual = K.retract(d); - CHECK(assert_equal(expected,actual,1e-9)); - CHECK(assert_equal(d,K.localCoordinates(actual),1e-9)); + CHECK(assert_equal(expected, actual, 1e-9)); + CHECK(assert_equal(d, K.localCoordinates(actual), 1e-9)); } /* ************************************************************************* */ -TEST( Cal3Unified, DerivedValue) -{ +TEST(Cal3Unified, DerivedValue) { Values values; Cal3Unified cal(1, 2, 3, 4, 5, 6, 7, 8, 9, 10); Key key = 1; @@ -110,9 +124,24 @@ TEST( Cal3Unified, DerivedValue) Cal3Unified calafter = values.at(key); - CHECK(assert_equal(cal,calafter,1e-9)); + CHECK(assert_equal(cal, calafter, 1e-9)); } /* ************************************************************************* */ -int main() { TestResult tr; return TestRegistry::runAllTests(tr); } +TEST(Cal3Unified, Print) { + Cal3Unified cal(0, 1, 2, 3, 4, 5, 6, 7, 8, 9); + std::stringstream os; + os << "fx: " << cal.fx() << ", fy: " << cal.fy() << ", s: " << cal.skew() + << ", px: " << cal.px() << ", py: " << cal.py() << ", k1: " << cal.k1() + << ", k2: " << cal.k2() << ", p1: " << cal.p1() << ", p2: " << cal.p2() + << ", xi: " << cal.xi(); + + EXPECT(assert_stdout_equal(os.str(), cal)); +} + +/* ************************************************************************* */ +int main() { + TestResult tr; + return TestRegistry::runAllTests(tr); +} /* ************************************************************************* */ diff --git a/gtsam/geometry/tests/testCal3_S2.cpp b/gtsam/geometry/tests/testCal3_S2.cpp index 55ea32e32..41be5ea8e 100644 --- a/gtsam/geometry/tests/testCal3_S2.cpp +++ b/gtsam/geometry/tests/testCal3_S2.cpp @@ -11,7 +11,7 @@ /** * @file testCal3_S2.cpp - * @brief Unit tests for transform derivatives + * @brief Unit tests for basic Cal3_S2 calibration model. */ #include @@ -31,90 +31,94 @@ static Point2 p_uv(1320.3, 1740); static Point2 p_xy(2, 3); /* ************************************************************************* */ -TEST( Cal3_S2, easy_constructor) -{ +TEST(Cal3_S2, Constructor) { Cal3_S2 expected(554.256, 554.256, 0, 640 / 2, 480 / 2); - double fov = 60; // degrees - size_t w=640,h=480; - Cal3_S2 actual(fov,w,h); + double fov = 60; // degrees + size_t w = 640, h = 480; + Cal3_S2 actual(fov, w, h); - CHECK(assert_equal(expected,actual,1e-3)); + CHECK(assert_equal(expected, actual, 1e-3)); } /* ************************************************************************* */ -TEST( Cal3_S2, calibrate) -{ - Point2 intrinsic(2,3); +TEST(Cal3_S2, Calibrate) { + Point2 intrinsic(2, 3); Point2 expectedimage(1320.3, 1740); Point2 imagecoordinates = K.uncalibrate(intrinsic); - CHECK(assert_equal(expectedimage,imagecoordinates)); - CHECK(assert_equal(intrinsic,K.calibrate(imagecoordinates))); + CHECK(assert_equal(expectedimage, imagecoordinates)); + CHECK(assert_equal(intrinsic, K.calibrate(imagecoordinates))); } /* ************************************************************************* */ -TEST( Cal3_S2, calibrate_homogeneous) { +TEST(Cal3_S2, CalibrateHomogeneous) { Vector3 intrinsic(2, 3, 1); Vector3 image(1320.3, 1740, 1); - CHECK(assert_equal((Vector)intrinsic,(Vector)K.calibrate(image))); + CHECK(assert_equal((Vector)intrinsic, (Vector)K.calibrate(image))); } /* ************************************************************************* */ -Point2 uncalibrate_(const Cal3_S2& k, const Point2& pt) { return k.uncalibrate(pt); } -TEST( Cal3_S2, Duncalibrate1) -{ - Matrix25 computed; K.uncalibrate(p, computed, boost::none); +Point2 uncalibrate_(const Cal3_S2& k, const Point2& pt) { + return k.uncalibrate(pt); +} + +TEST(Cal3_S2, Duncalibrate1) { + Matrix25 computed; + K.uncalibrate(p, computed, boost::none); Matrix numerical = numericalDerivative21(uncalibrate_, K, p); - CHECK(assert_equal(numerical,computed,1e-8)); + CHECK(assert_equal(numerical, computed, 1e-8)); } /* ************************************************************************* */ -TEST( Cal3_S2, Duncalibrate2) -{ - Matrix computed; K.uncalibrate(p, boost::none, computed); +TEST(Cal3_S2, Duncalibrate2) { + Matrix computed; + K.uncalibrate(p, boost::none, computed); Matrix numerical = numericalDerivative22(uncalibrate_, K, p); - CHECK(assert_equal(numerical,computed,1e-9)); + CHECK(assert_equal(numerical, computed, 1e-9)); } -Point2 calibrate_(const Cal3_S2& k, const Point2& pt) {return k.calibrate(pt); } -/* ************************************************************************* */ -TEST(Cal3_S2, Dcalibrate1) -{ - Matrix computed; - Point2 expected = K.calibrate(p_uv, computed, boost::none); - Matrix numerical = numericalDerivative21(calibrate_, K, p_uv); - CHECK(assert_equal(expected, p_xy, 1e-8)); - CHECK(assert_equal(numerical, computed, 1e-8)); +Point2 calibrate_(const Cal3_S2& k, const Point2& pt) { + return k.calibrate(pt); } /* ************************************************************************* */ -TEST(Cal3_S2, Dcalibrate2) -{ - Matrix computed; - Point2 expected = K.calibrate(p_uv, boost::none, computed); - Matrix numerical = numericalDerivative22(calibrate_, K, p_uv); - CHECK(assert_equal(expected, p_xy, 1e-8)); - CHECK(assert_equal(numerical, computed, 1e-8)); +TEST(Cal3_S2, Dcalibrate1) { + Matrix computed; + Point2 expected = K.calibrate(p_uv, computed, boost::none); + Matrix numerical = numericalDerivative21(calibrate_, K, p_uv); + CHECK(assert_equal(expected, p_xy, 1e-8)); + CHECK(assert_equal(numerical, computed, 1e-8)); } /* ************************************************************************* */ -TEST( Cal3_S2, assert_equal) -{ - CHECK(assert_equal(K,K,1e-9)); +TEST(Cal3_S2, Dcalibrate2) { + Matrix computed; + Point2 expected = K.calibrate(p_uv, boost::none, computed); + Matrix numerical = numericalDerivative22(calibrate_, K, p_uv); + CHECK(assert_equal(expected, p_xy, 1e-8)); + CHECK(assert_equal(numerical, computed, 1e-8)); +} + +/* ************************************************************************* */ +TEST(Cal3_S2, Equal) { + CHECK(assert_equal(K, K, 1e-9)); Cal3_S2 K1(500, 500, 0.1, 640 / 2, 480 / 2); - CHECK(assert_equal(K,K1,1e-9)); + CHECK(assert_equal(K, K1, 1e-9)); } /* ************************************************************************* */ -TEST( Cal3_S2, retract) -{ - Cal3_S2 expected(500+1, 500+2, 0.1+3, 640 / 2+4, 480 / 2+5); - Vector d(5); - d << 1,2,3,4,5; +TEST(Cal3_S2, Retract) { + Cal3_S2 expected(500 + 1, 500 + 2, 0.1 + 3, 640 / 2 + 4, 480 / 2 + 5); + + EXPECT_LONGS_EQUAL(Cal3_S2::Dim(), 5); + EXPECT_LONGS_EQUAL(expected.dim(), 5); + + Vector5 d; + d << 1, 2, 3, 4, 5; Cal3_S2 actual = K.retract(d); - CHECK(assert_equal(expected,actual,1e-7)); - CHECK(assert_equal(d,K.localCoordinates(actual),1e-7)); + CHECK(assert_equal(expected, actual, 1e-7)); + CHECK(assert_equal(d, K.localCoordinates(actual), 1e-7)); } /* ************************************************************************* */ @@ -122,18 +126,17 @@ TEST(Cal3_S2, between) { Cal3_S2 k1(5, 5, 5, 5, 5), k2(5, 6, 7, 8, 9); Matrix H1, H2; - EXPECT(assert_equal(Cal3_S2(0,1,2,3,4), k1.between(k2, H1, H2))); + EXPECT(assert_equal(Cal3_S2(0, 1, 2, 3, 4), k1.between(k2, H1, H2))); EXPECT(assert_equal(-I_5x5, H1)); EXPECT(assert_equal(I_5x5, H2)); - } /* ************************************************************************* */ TEST(Cal3_S2, Print) { Cal3_S2 cal(5, 5, 5, 5, 5); std::stringstream os; - os << "{fx: " << cal.fx() << ", fy: " << cal.fy() << ", s:" << cal.skew() << ", px:" << cal.px() - << ", py:" << cal.py() << "}"; + os << "fx: " << cal.fx() << ", fy: " << cal.fy() << ", s: " << cal.skew() + << ", px: " << cal.px() << ", py: " << cal.py(); EXPECT(assert_stdout_equal(os.str(), cal)); } @@ -144,4 +147,3 @@ int main() { return TestRegistry::runAllTests(tr); } /* ************************************************************************* */ - diff --git a/gtsam/geometry/tests/testCal3_S2Stereo.cpp b/gtsam/geometry/tests/testCal3_S2Stereo.cpp new file mode 100644 index 000000000..070eee8fe --- /dev/null +++ b/gtsam/geometry/tests/testCal3_S2Stereo.cpp @@ -0,0 +1,129 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file testCal3_S2Stereo.cpp + * @brief Unit tests for stereo-rig calibration model. + */ + +#include +#include +#include +#include +#include + +using namespace gtsam; + +GTSAM_CONCEPT_TESTABLE_INST(Cal3_S2Stereo) +GTSAM_CONCEPT_MANIFOLD_INST(Cal3_S2Stereo) + +static Cal3_S2Stereo K(500, 500, 0.1, 640 / 2, 480 / 2, 1); +static Point2 p(1, -2); +static Point2 p_uv(1320.3, 1740); +static Point2 p_xy(2, 3); + +/* ************************************************************************* */ +TEST(Cal3_S2Stereo, Constructor) { + Cal3_S2Stereo expected(554.256, 554.256, 0, 640 / 2, 480 / 2, 3); + + double fov = 60; // degrees + size_t w = 640, h = 480; + Cal3_S2Stereo actual(fov, w, h, 3); + + CHECK(assert_equal(expected, actual, 1e-3)); +} + +/* ************************************************************************* */ +TEST(Cal3_S2Stereo, Calibrate) { + Point2 intrinsic(2, 3); + Point2 expectedimage(1320.3, 1740); + Point2 imagecoordinates = K.uncalibrate(intrinsic); + CHECK(assert_equal(expectedimage, imagecoordinates)); + CHECK(assert_equal(intrinsic, K.calibrate(imagecoordinates))); +} + +/* ************************************************************************* */ +TEST(Cal3_S2Stereo, CalibrateHomogeneous) { + Vector3 intrinsic(2, 3, 1); + Vector3 image(1320.3, 1740, 1); + CHECK(assert_equal(intrinsic, K.calibrate(image))); +} + +/* ************************************************************************* */ +Point2 uncalibrate_(const Cal3_S2Stereo& k, const Point2& pt) { + return k.uncalibrate(pt); +} + +TEST(Cal3_S2Stereo, Duncalibrate) { + Matrix26 Dcal; + Matrix22 Dp; + K.uncalibrate(p, Dcal, Dp); + + Matrix numerical1 = numericalDerivative21(uncalibrate_, K, p); + CHECK(assert_equal(numerical1, Dcal, 1e-8)); + Matrix numerical2 = numericalDerivative22(uncalibrate_, K, p); + CHECK(assert_equal(numerical2, Dp, 1e-9)); +} + +Point2 calibrate_(const Cal3_S2Stereo& K, const Point2& pt) { + return K.calibrate(pt); +} +/* ************************************************************************* */ +TEST(Cal3_S2Stereo, Dcalibrate) { + Matrix26 Dcal; + Matrix22 Dp; + Point2 expected = K.calibrate(p_uv, Dcal, Dp); + CHECK(assert_equal(expected, p_xy, 1e-8)); + + Matrix numerical1 = numericalDerivative21(calibrate_, K, p_uv); + CHECK(assert_equal(numerical1, Dcal, 1e-8)); + Matrix numerical2 = numericalDerivative22(calibrate_, K, p_uv); + CHECK(assert_equal(numerical2, Dp, 1e-8)); +} + +/* ************************************************************************* */ +TEST(Cal3_S2Stereo, Equal) { + CHECK(assert_equal(K, K, 1e-9)); + + Cal3_S2Stereo K1(500, 500, 0.1, 640 / 2, 480 / 2, 1); + CHECK(assert_equal(K, K1, 1e-9)); +} + +/* ************************************************************************* */ +TEST(Cal3_S2Stereo, Retract) { + Cal3_S2Stereo expected(500 + 1, 500 + 2, 0.1 + 3, 640 / 2 + 4, 480 / 2 + 5, + 7); + EXPECT_LONGS_EQUAL(Cal3_S2Stereo::Dim(), 6); + EXPECT_LONGS_EQUAL(expected.dim(), 6); + + Vector6 d; + d << 1, 2, 3, 4, 5, 6; + Cal3_S2Stereo actual = K.retract(d); + CHECK(assert_equal(expected, actual, 1e-7)); + CHECK(assert_equal(d, K.localCoordinates(actual), 1e-7)); +} + +/* ************************************************************************* */ +TEST(Cal3_S2Stereo, Print) { + Cal3_S2Stereo cal(5, 5, 5, 5, 5, 2); + std::stringstream os; + os << "fx: " << cal.fx() << ", fy: " << cal.fy() << ", s: " << cal.skew() + << ", px: " << cal.px() << ", py: " << cal.py() + << ", b: " << cal.baseline(); + EXPECT(assert_stdout_equal(os.str(), cal)); +} + +/* ************************************************************************* */ +int main() { + TestResult tr; + return TestRegistry::runAllTests(tr); +} +/* ************************************************************************* */ diff --git a/gtsam/geometry/tests/testLine3.cpp b/gtsam/geometry/tests/testLine3.cpp index 9ed12aef7..09371bad4 100644 --- a/gtsam/geometry/tests/testLine3.cpp +++ b/gtsam/geometry/tests/testLine3.cpp @@ -14,6 +14,16 @@ GTSAM_CONCEPT_MANIFOLD_INST(Line3) static const Line3 l(Rot3(), 1, 1); +// Testing getters +TEST(Line3, getMethods) { + const double a = 5, b = 10; + const Rot3 R = Rot3::Expmap(Vector3(0.1, 0.2, 0.3)); + const Line3 line(R, a, b); + EXPECT_DOUBLES_EQUAL(a, line.a(), 1e-8); + EXPECT_DOUBLES_EQUAL(b, line.b(), 1e-8); + EXPECT(assert_equal(R, line.R(), 1e-8)); +} + // Testing equals function of Line3 TEST(Line3, equals) { Line3 l_same = l; diff --git a/gtsam/geometry/tests/testPose3.cpp b/gtsam/geometry/tests/testPose3.cpp index 6de2c0a33..594d15c91 100644 --- a/gtsam/geometry/tests/testPose3.cpp +++ b/gtsam/geometry/tests/testPose3.cpp @@ -1016,6 +1016,33 @@ TEST(Pose3, TransformCovariance6) { TEST(Pose3, interpolate) { EXPECT(assert_equal(T2, interpolate(T2,T3, 0.0))); EXPECT(assert_equal(T3, interpolate(T2,T3, 1.0))); + + // Trivial example: start at origin and move to (1, 0, 0) while rotating pi/2 + // about z-axis. + Pose3 start; + Pose3 end(Rot3::Rz(M_PI_2), Point3(1, 0, 0)); + // This interpolation is easy to calculate by hand. + double t = 0.5; + Pose3 expected0(Rot3::Rz(M_PI_4), Point3(0.5, 0, 0)); + EXPECT(assert_equal(expected0, start.interpolateRt(end, t))); + + // Example from Peter Corke + // https://robotacademy.net.au/lesson/interpolating-pose-in-3d/ + t = 0.0759; // corresponds to the 10th element when calling `ctraj` in + // the video + Pose3 O; + Pose3 F(Rot3::Roll(0.6).compose(Rot3::Pitch(0.8)).compose(Rot3::Yaw(1.4)), + Point3(1, 2, 3)); + + // The expected answer matches the result presented in the video. + Pose3 expected1(interpolate(O.rotation(), F.rotation(), t), + interpolate(O.translation(), F.translation(), t)); + EXPECT(assert_equal(expected1, O.interpolateRt(F, t))); + + // Non-trivial interpolation, translation value taken from output. + Pose3 expected2(interpolate(T2.rotation(), T3.rotation(), t), + interpolate(T2.translation(), T3.translation(), t)); + EXPECT(assert_equal(expected2, T2.interpolateRt(T3, t))); } /* ************************************************************************* */ diff --git a/gtsam/geometry/tests/testRot3.cpp b/gtsam/geometry/tests/testRot3.cpp index 7b792f8bd..290945837 100644 --- a/gtsam/geometry/tests/testRot3.cpp +++ b/gtsam/geometry/tests/testRot3.cpp @@ -807,15 +807,15 @@ TEST(Rot3, RQ_derivative) { test_xyz.push_back(VecAndErr{{0, 0, 0}, error}); test_xyz.push_back(VecAndErr{{0, 0.5, -0.5}, error}); test_xyz.push_back(VecAndErr{{0.3, 0, 0.2}, error}); - test_xyz.push_back(VecAndErr{{-0.6, 1.3, 0}, error}); + test_xyz.push_back(VecAndErr{{-0.6, 1.3, 0}, 1e-8}); test_xyz.push_back(VecAndErr{{1.0, 0.7, 0.8}, error}); test_xyz.push_back(VecAndErr{{3.0, 0.7, -0.6}, error}); test_xyz.push_back(VecAndErr{{M_PI / 2, 0, 0}, error}); test_xyz.push_back(VecAndErr{{0, 0, M_PI / 2}, error}); // Test close to singularity - test_xyz.push_back(VecAndErr{{0, M_PI / 2 - 1e-1, 0}, 1e-8}); - test_xyz.push_back(VecAndErr{{0, 3 * M_PI / 2 + 1e-1, 0}, 1e-8}); + test_xyz.push_back(VecAndErr{{0, M_PI / 2 - 1e-1, 0}, 1e-7}); + test_xyz.push_back(VecAndErr{{0, 3 * M_PI / 2 + 1e-1, 0}, 1e-7}); test_xyz.push_back(VecAndErr{{0, M_PI / 2 - 1.1e-2, 0}, 1e-4}); test_xyz.push_back(VecAndErr{{0, 3 * M_PI / 2 + 1.1e-2, 0}, 1e-4}); @@ -825,7 +825,7 @@ TEST(Rot3, RQ_derivative) { const auto R = Rot3::RzRyRx(xyz).matrix(); const auto num = numericalDerivative11(RQ_proxy, R); Matrix39 calc; - RQ(R, calc).second; + auto dummy = RQ(R, calc).second; const auto err = vec_err.second; CHECK(assert_equal(num, calc, err)); diff --git a/gtsam/geometry/tests/testSimpleCamera.cpp b/gtsam/geometry/tests/testSimpleCamera.cpp index edf122d3c..18a25c553 100644 --- a/gtsam/geometry/tests/testSimpleCamera.cpp +++ b/gtsam/geometry/tests/testSimpleCamera.cpp @@ -26,6 +26,8 @@ using namespace std; using namespace gtsam; +#ifdef GTSAM_ALLOW_DEPRECATED_SINCE_V41 + static const Cal3_S2 K(625, 625, 0, 0, 0); static const Pose3 pose1(Rot3(Vector3(1, -1, -1).asDiagonal()), @@ -149,6 +151,8 @@ TEST( SimpleCamera, simpleCamera) CHECK(assert_equal(expected, actual,1e-1)); } +#endif + /* ************************************************************************* */ int main() { TestResult tr; return TestRegistry::runAllTests(tr); } /* ************************************************************************* */ diff --git a/gtsam/geometry/triangulation.h b/gtsam/geometry/triangulation.h index 6f6c645b8..1df9efd22 100644 --- a/gtsam/geometry/triangulation.h +++ b/gtsam/geometry/triangulation.h @@ -18,8 +18,10 @@ #pragma once -#include +#include +#include #include +#include #include #include #include @@ -494,5 +496,9 @@ TriangulationResult triangulateSafe(const CameraSet& cameras, } } +// Vector of Cameras - used by the Python/MATLAB wrapper +using CameraSetCal3Bundler = CameraSet>; +using CameraSetCal3_S2 = CameraSet>; + } // \namespace gtsam diff --git a/gtsam/gtsam.i b/gtsam/gtsam.i index 1b4d976da..22c2cc17d 100644 --- a/gtsam/gtsam.i +++ b/gtsam/gtsam.i @@ -329,7 +329,7 @@ virtual class Value { }; #include -template +template virtual class GenericValue : gtsam::Value { void serializable() const; }; @@ -852,8 +852,7 @@ class Cal3_S2 { gtsam::Point2 principalPoint() const; Vector vector() const; Matrix K() const; - Matrix matrix() const; - Matrix matrix_inverse() const; + Matrix inverse() const; // enabling serialization functionality void serialize() const; @@ -881,7 +880,7 @@ virtual class Cal3DS2_Base { // Action on Point2 gtsam::Point2 uncalibrate(const gtsam::Point2& p) const; - gtsam::Point2 calibrate(const gtsam::Point2& p, double tol) const; + gtsam::Point2 calibrate(const gtsam::Point2& p) const; // enabling serialization functionality void serialize() const; @@ -1059,56 +1058,24 @@ class PinholeCamera { void serialize() const; }; +// Forward declaration of PinholeCameraCalX is defined here. #include -virtual class SimpleCamera { - // Standard Constructors and Named Constructors - SimpleCamera(); - SimpleCamera(const gtsam::Pose3& pose); - SimpleCamera(const gtsam::Pose3& pose, const gtsam::Cal3_S2& K); - static gtsam::SimpleCamera Level(const gtsam::Cal3_S2& K, const gtsam::Pose2& pose, double height); - static gtsam::SimpleCamera Level(const gtsam::Pose2& pose, double height); - static gtsam::SimpleCamera Lookat(const gtsam::Point3& eye, const gtsam::Point3& target, - const gtsam::Point3& upVector, const gtsam::Cal3_S2& K); - static gtsam::SimpleCamera Lookat(const gtsam::Point3& eye, const gtsam::Point3& target, - const gtsam::Point3& upVector); - - // Testable - void print(string s) const; - bool equals(const gtsam::SimpleCamera& camera, double tol) const; - - // Standard Interface - gtsam::Pose3 pose() const; - gtsam::Cal3_S2 calibration() const; - - // Manifold - gtsam::SimpleCamera retract(Vector d) const; - Vector localCoordinates(const gtsam::SimpleCamera& T2) const; - size_t dim() const; - static size_t Dim(); - - // Transformations and measurement functions - static gtsam::Point2 Project(const gtsam::Point3& cameraPoint); - pair projectSafe(const gtsam::Point3& pw) const; - gtsam::Point2 project(const gtsam::Point3& point); - gtsam::Point3 backproject(const gtsam::Point2& p, double depth) const; - double range(const gtsam::Point3& point); - double range(const gtsam::Pose3& pose); - - // enabling serialization functionality - void serialize() const; - -}; - -gtsam::SimpleCamera simpleCamera(const Matrix& P); - // Some typedefs for common camera types // PinholeCameraCal3_S2 is the same as SimpleCamera above typedef gtsam::PinholeCamera PinholeCameraCal3_S2; -//TODO (Issue 237) due to lack of jacobians of Cal3DS2_Base::calibrate, PinholeCamera does not apply to Cal3DS2/Unified -//typedef gtsam::PinholeCamera PinholeCameraCal3DS2; -//typedef gtsam::PinholeCamera PinholeCameraCal3Unified; +typedef gtsam::PinholeCamera PinholeCameraCal3DS2; +typedef gtsam::PinholeCamera PinholeCameraCal3Unified; typedef gtsam::PinholeCamera PinholeCameraCal3Bundler; +template +class CameraSet { + CameraSet(); + + // structure specific methods + T at(size_t i) const; + void push_back(const T& cam); +}; + #include class StereoCamera { // Standard Constructors and Named Constructors @@ -1140,7 +1107,7 @@ class StereoCamera { #include -// Templates appear not yet supported for free functions +// Templates appear not yet supported for free functions - issue raised at borglab/wrap#14 to add support gtsam::Point3 triangulatePoint3(const gtsam::Pose3Vector& poses, gtsam::Cal3_S2* sharedCal, const gtsam::Point2Vector& measurements, double rank_tol, bool optimize); @@ -1150,7 +1117,13 @@ gtsam::Point3 triangulatePoint3(const gtsam::Pose3Vector& poses, gtsam::Point3 triangulatePoint3(const gtsam::Pose3Vector& poses, gtsam::Cal3Bundler* sharedCal, const gtsam::Point2Vector& measurements, double rank_tol, bool optimize); - +gtsam::Point3 triangulatePoint3(const gtsam::CameraSetCal3_S2& cameras, + const gtsam::Point2Vector& measurements, double rank_tol, + bool optimize); +gtsam::Point3 triangulatePoint3(const gtsam::CameraSetCal3Bundler& cameras, + const gtsam::Point2Vector& measurements, double rank_tol, + bool optimize); + //************************************************************************* // Symbolic //************************************************************************* @@ -1963,6 +1936,21 @@ class KalmanFilter { //************************************************************************* #include + +class Symbol { + Symbol(); + Symbol(char c, uint64_t j); + Symbol(size_t key); + + size_t key() const; + void print(const string& s) const; + bool equals(const gtsam::Symbol& expected, double tol) const; + + char chr() const; + uint64_t index() const; + string string() const; +}; + size_t symbol(char chr, size_t index); char symbolChr(size_t key); size_t symbolIndex(size_t key); @@ -2069,7 +2057,7 @@ class NonlinearFactorGraph { gtsam::KeySet keys() const; gtsam::KeyVector keyVector() const; - template, gtsam::imuBias::ConstantBias}> + template, gtsam::imuBias::ConstantBias}> void addPrior(size_t key, const T& prior, const gtsam::noiseModel::Base* noiseModel); // NonlinearFactorGraph @@ -2083,6 +2071,7 @@ class NonlinearFactorGraph { // enabling serialization functionality void serialize() const; + void saveGraph(const string& s) const; }; #include @@ -2493,7 +2482,7 @@ class ISAM2 { template , + gtsam::PinholeCameraCal3_S2, gtsam::PinholeCamera, Vector, Matrix}> VALUE calculateEstimate(size_t key) const; gtsam::Values calculateBestEstimate() const; @@ -2527,12 +2516,11 @@ class NonlinearISAM { //************************************************************************* // Nonlinear factor types //************************************************************************* -#include #include #include #include -template}> +template}> virtual class PriorFactor : gtsam::NoiseModelFactor { PriorFactor(size_t key, const T& prior, const gtsam::noiseModel::Base* noiseModel); T prior() const; @@ -2556,7 +2544,7 @@ virtual class BetweenFactor : gtsam::NoiseModelFactor { template virtual class NonlinearEquality : gtsam::NoiseModelFactor { // Constructor - forces exact evaluation @@ -2611,6 +2599,7 @@ virtual class BearingFactor : gtsam::NoiseModelFactor { }; typedef gtsam::BearingFactor BearingFactor2D; +typedef gtsam::BearingFactor BearingFactor3D; typedef gtsam::BearingFactor BearingFactorPose2; #include @@ -2634,6 +2623,8 @@ virtual class BearingRangeFactor : gtsam::NoiseModelFactor { const BEARING& measuredBearing, const RANGE& measuredRange, const gtsam::noiseModel::Base* noiseModel); + BearingRange measured() const; + // enabling serialization functionality void serialize() const; }; @@ -2675,11 +2666,10 @@ virtual class GeneralSFMFactor : gtsam::NoiseModelFactor { gtsam::Point2 measured() const; }; typedef gtsam::GeneralSFMFactor GeneralSFMFactorCal3_S2; -//TODO (Issue 237) due to lack of jacobians of Cal3DS2_Base::calibrate, GeneralSFMFactor does not apply to Cal3DS2 -//typedef gtsam::GeneralSFMFactor GeneralSFMFactorCal3DS2; +typedef gtsam::GeneralSFMFactor GeneralSFMFactorCal3DS2; typedef gtsam::GeneralSFMFactor, gtsam::Point3> GeneralSFMFactorCal3Bundler; -template +template virtual class GeneralSFMFactor2 : gtsam::NoiseModelFactor { GeneralSFMFactor2(const gtsam::Point2& measured, const gtsam::noiseModel::Base* model, size_t poseKey, size_t landmarkKey, size_t calibKey); gtsam::Point2 measured() const; @@ -2780,6 +2770,12 @@ class SfmTrack { pair measurement(size_t idx) const; pair siftIndex(size_t idx) const; void add_measurement(size_t idx, const gtsam::Point2& m); + + // enabling serialization functionality + void serialize() const; + + // enabling function to compare objects + bool equals(const gtsam::SfmTrack& expected, double tol) const; }; class SfmData { @@ -2790,6 +2786,12 @@ class SfmData { gtsam::SfmTrack track(size_t idx) const; void add_track(const gtsam::SfmTrack& t) ; void add_camera(const gtsam::SfmCamera& cam); + + // enabling serialization functionality + void serialize() const; + + // enabling function to compare objects + bool equals(const gtsam::SfmData& expected, double tol) const; }; gtsam::SfmData readBal(string filename); @@ -2933,9 +2935,14 @@ class ShonanAveragingParameters2 { void setAnchorWeight(double value); double getAnchorWeight() const; void setKarcherWeight(double value); - double getKarcherWeight(); + double getKarcherWeight() const; void setGaugesWeight(double value); - double getGaugesWeight(); + double getGaugesWeight() const; + void setUseHuber(bool value); + bool getUseHuber() const; + void setCertifyOptimality(bool value); + bool getCertifyOptimality() const; + void print() const; }; class ShonanAveragingParameters3 { @@ -2949,9 +2956,14 @@ class ShonanAveragingParameters3 { void setAnchorWeight(double value); double getAnchorWeight() const; void setKarcherWeight(double value); - double getKarcherWeight(); + double getKarcherWeight() const; void setGaugesWeight(double value); - double getGaugesWeight(); + double getGaugesWeight() const; + void setUseHuber(bool value); + bool getUseHuber() const; + void setCertifyOptimality(bool value); + bool getCertifyOptimality() const; + void print() const; }; class ShonanAveraging2 { diff --git a/gtsam/inference/Symbol.h b/gtsam/inference/Symbol.h index 469082f16..d5699e7fe 100644 --- a/gtsam/inference/Symbol.h +++ b/gtsam/inference/Symbol.h @@ -80,6 +80,9 @@ public: /** Create a string from the key */ operator std::string() const; + /// Return string representation of the key + std::string string() const { return std::string(*this); }; + /** Comparison for use in maps */ bool operator<(const Symbol& comp) const { return c_ < comp.c_ || (comp.c_ == c_ && j_ < comp.j_); @@ -167,10 +170,11 @@ inline Key Z(std::uint64_t j) { return Symbol('z', j); } /** Generates symbol shorthands with alternative names different than the * one-letter predefined ones. */ class SymbolGenerator { - const char c_; + const unsigned char c_; public: - SymbolGenerator(const char c) : c_(c) {} + constexpr SymbolGenerator(const unsigned char c) : c_(c) {} Symbol operator()(const std::uint64_t j) const { return Symbol(c_, j); } + constexpr unsigned char chr() const { return c_; } }; /// traits diff --git a/gtsam/inference/tests/testKey.cpp b/gtsam/inference/tests/testKey.cpp index 64674c36f..98c5d36bf 100644 --- a/gtsam/inference/tests/testKey.cpp +++ b/gtsam/inference/tests/testKey.cpp @@ -59,6 +59,12 @@ TEST(Key, SymbolGenerator) { EXPECT(assert_equal(a1, ddz1)); } +/* ************************************************************************* */ +TEST(Key, SymbolGeneratorConstexpr) { + constexpr auto Z = gtsam::SymbolGenerator('x'); + EXPECT(assert_equal(Z.chr(), 'x')); +} + /* ************************************************************************* */ template Key KeyTestValue(); diff --git a/gtsam/linear/AcceleratedPowerMethod.h b/gtsam/linear/AcceleratedPowerMethod.h new file mode 100644 index 000000000..6653d43c9 --- /dev/null +++ b/gtsam/linear/AcceleratedPowerMethod.h @@ -0,0 +1,176 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010-2019, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file AcceleratedPowerMethod.h + * @date Sept 2020 + * @author Jing Wu + * @brief accelerated power method for fast eigenvalue and eigenvector + * computation + */ + +#pragma once + +#include + +namespace gtsam { + +using Sparse = Eigen::SparseMatrix; + +/** + * \brief Compute maximum Eigenpair with accelerated power method + * + * References : + * 1) G. Golub and C. V. Loan, Matrix Computations, 3rd ed. Baltimore, Johns + * Hopkins University Press, 1996, pp.405-411 + * 2) Rosen, D. and Carlone, L., 2017, September. Computational + * enhancements for certifiably correct SLAM. In Proceedings of the + * International Conference on Intelligent Robots and Systems. + * 3) Yulun Tian and Kasra Khosoussi and David M. Rosen and Jonathan P. How, + * 2020, Aug, Distributed Certifiably Correct Pose-Graph Optimization, Arxiv + * 4) C. de Sa, B. He, I. Mitliagkas, C. Ré, and P. Xu, “Accelerated + * stochastic power iteration,” in Proc. Mach. Learn. Res., no. 84, 2018, pp. + * 58–67 + * + * It performs the following iteration: \f$ x_{k+1} = A * x_k - \beta * + * x_{k-1} \f$ where A is the aim matrix we want to get eigenpair of, x is the + * Ritz vector + * + * Template argument Operator just needs multiplication operator + * + */ +template +class AcceleratedPowerMethod : public PowerMethod { + + double beta_ = 0; // a Polyak momentum term + + Vector previousVector_; // store previous vector + + public: + /** + * Constructor from aim matrix A (given as Matrix or Sparse), optional intial + * vector as ritzVector + */ + explicit AcceleratedPowerMethod( + const Operator &A, const boost::optional initial = boost::none, + double initialBeta = 0.0) + : PowerMethod(A, initial) { + // initialize Ritz eigen vector and previous vector + this->ritzVector_ = initial ? initial.get() : Vector::Random(this->dim_); + this->ritzVector_.normalize(); + previousVector_ = Vector::Zero(this->dim_); + + // initialize beta_ + beta_ = initialBeta; + } + + /** + * Run accelerated power iteration to get ritzVector with beta and previous + * two ritzVector x0 and x00, and return y = (A * x0 - \beta * x00) / || A * x0 + * - \beta * x00 || + */ + Vector acceleratedPowerIteration (const Vector &x1, const Vector &x0, + const double beta) const { + Vector y = this->A_ * x1 - beta * x0; + y.normalize(); + return y; + } + + /** + * Run accelerated power iteration to get ritzVector with beta and previous + * two ritzVector x0 and x00, and return y = (A * x0 - \beta * x00) / || A * x0 + * - \beta * x00 || + */ + Vector acceleratedPowerIteration () const { + Vector y = acceleratedPowerIteration(this->ritzVector_, previousVector_, beta_); + return y; + } + + /** + * Tuning the momentum beta using the Best Heavy Ball algorithm in Ref(3), T + * is the iteration time to find beta with largest Rayleigh quotient + */ + double estimateBeta(const size_t T = 10) const { + // set initial estimation of maxBeta + Vector initVector = this->ritzVector_; + const double up = initVector.dot( this->A_ * initVector ); + const double down = initVector.dot(initVector); + const double mu = up / down; + double maxBeta = mu * mu / 4; + size_t maxIndex; + std::vector betas; + + Matrix R = Matrix::Zero(this->dim_, 10); + // run T times of iteration to find the beta that has the largest Rayleigh quotient + for (size_t t = 0; t < T; t++) { + // after each t iteration, reset the betas with the current maxBeta + betas = {2 / 3 * maxBeta, 0.99 * maxBeta, maxBeta, 1.01 * maxBeta, + 1.5 * maxBeta}; + // iterate through every beta value + for (size_t k = 0; k < betas.size(); ++k) { + // initialize x0 and x00 in each iteration of each beta + Vector x0 = initVector; + Vector x00 = Vector::Zero(this->dim_); + // run 10 steps of accelerated power iteration with this beta + for (size_t j = 1; j < 10; j++) { + if (j < 2) { + R.col(0) = acceleratedPowerIteration(x0, x00, betas[k]); + R.col(1) = acceleratedPowerIteration(R.col(0), x0, betas[k]); + } else { + R.col(j) = acceleratedPowerIteration(R.col(j - 1), R.col(j - 2), + betas[k]); + } + } + // compute the Rayleigh quotient for the randomly sampled vector after + // 10 steps of power accelerated iteration + const Vector x = R.col(9); + const double up = x.dot(this->A_ * x); + const double down = x.dot(x); + const double mu = up / down; + // store the momentum with largest Rayleigh quotient and its according index of beta_ + if (mu * mu / 4 > maxBeta) { + // save the max beta index + maxIndex = k; + maxBeta = mu * mu / 4; + } + } + } + // set beta_ to momentum with largest Rayleigh quotient + return betas[maxIndex]; + } + + /** + * Start the accelerated iteration, after performing the + * accelerated iteration, calculate the ritz error, repeat this + * operation until the ritz error converge. If converged return true, else + * false. + */ + bool compute(size_t maxIterations, double tol) { + // Starting + bool isConverged = false; + + for (size_t i = 0; i < maxIterations && !isConverged; i++) { + ++(this->nrIterations_); + Vector tmp = this->ritzVector_; + // update the ritzVector after accelerated power iteration + this->ritzVector_ = acceleratedPowerIteration(); + // update the previousVector with ritzVector + previousVector_ = tmp; + // update the ritzValue + this->ritzValue_ = this->ritzVector_.dot(this->A_ * this->ritzVector_); + isConverged = this->converged(tol); + } + + return isConverged; + } +}; + +} // namespace gtsam diff --git a/gtsam/linear/PowerMethod.h b/gtsam/linear/PowerMethod.h new file mode 100644 index 000000000..8834777cc --- /dev/null +++ b/gtsam/linear/PowerMethod.h @@ -0,0 +1,152 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010-2019, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file PowerMethod.h + * @date Sept 2020 + * @author Jing Wu + * @brief Power method for fast eigenvalue and eigenvector + * computation + */ + +#pragma once + +#include +#include + +#include +#include +#include +#include + +namespace gtsam { + +using Sparse = Eigen::SparseMatrix; + +/** + * \brief Compute maximum Eigenpair with power method + * + * References : + * 1) G. Golub and C. V. Loan, Matrix Computations, 3rd ed. Baltimore, Johns + * Hopkins University Press, 1996, pp.405-411 + * 2) Rosen, D. and Carlone, L., 2017, September. Computational + * enhancements for certifiably correct SLAM. In Proceedings of the + * International Conference on Intelligent Robots and Systems. + * 3) Yulun Tian and Kasra Khosoussi and David M. Rosen and Jonathan P. How, + * 2020, Aug, Distributed Certifiably Correct Pose-Graph Optimization, Arxiv + * 4) C. de Sa, B. He, I. Mitliagkas, C. Ré, and P. Xu, “Accelerated + * stochastic power iteration,” in Proc. Mach. Learn. Res., no. 84, 2018, pp. + * 58–67 + * + * It performs the following iteration: \f$ x_{k+1} = A * x_k \f$ + * where A is the aim matrix we want to get eigenpair of, x is the + * Ritz vector + * + * Template argument Operator just needs multiplication operator + * + */ +template +class PowerMethod { + protected: + /** + * Const reference to an externally-held matrix whose minimum-eigenvalue we + * want to compute + */ + const Operator &A_; + + const int dim_; // dimension of Matrix A + + size_t nrIterations_; // number of iterations + + double ritzValue_; // Ritz eigenvalue + Vector ritzVector_; // Ritz eigenvector + + public: + /// @name Standard Constructors + /// @{ + + /// Construct from the aim matrix and intial ritz vector + explicit PowerMethod(const Operator &A, + const boost::optional initial = boost::none) + : A_(A), dim_(A.rows()), nrIterations_(0) { + Vector x0; + x0 = initial ? initial.get() : Vector::Random(dim_); + x0.normalize(); + + // initialize Ritz eigen value + ritzValue_ = 0.0; + + // initialize Ritz eigen vector + ritzVector_ = powerIteration(x0); + } + + /** + * Run power iteration to get ritzVector with previous ritzVector x, and + * return A * x / || A * x || + */ + Vector powerIteration(const Vector &x) const { + Vector y = A_ * x; + y.normalize(); + return y; + } + + /** + * Run power iteration to get ritzVector with previous ritzVector x, and + * return A * x / || A * x || + */ + Vector powerIteration() const { return powerIteration(ritzVector_); } + + /** + * After Perform power iteration on a single Ritz value, check if the Ritz + * residual for the current Ritz pair is less than the required convergence + * tol, return true if yes, else false + */ + bool converged(double tol) const { + const Vector x = ritzVector_; + // store the Ritz eigen value + const double ritzValue = x.dot(A_ * x); + const double error = (A_ * x - ritzValue * x).norm(); + return error < tol; + } + + /// Return the number of iterations + size_t nrIterations() const { return nrIterations_; } + + /** + * Start the power/accelerated iteration, after performing the + * power/accelerated iteration, calculate the ritz error, repeat this + * operation until the ritz error converge. If converged return true, else + * false. + */ + bool compute(size_t maxIterations, double tol) { + // Starting + bool isConverged = false; + + for (size_t i = 0; i < maxIterations && !isConverged; i++) { + ++nrIterations_; + // update the ritzVector after power iteration + ritzVector_ = powerIteration(); + // update the ritzValue + ritzValue_ = ritzVector_.dot(A_ * ritzVector_); + isConverged = converged(tol); + } + + return isConverged; + } + + /// Return the eigenvalue + double eigenvalue() const { return ritzValue_; } + + /// Return the eigenvector + Vector eigenvector() const { return ritzVector_; } +}; + +} // namespace gtsam diff --git a/gtsam/linear/SparseEigen.h b/gtsam/linear/SparseEigen.h new file mode 100644 index 000000000..7963d3ef5 --- /dev/null +++ b/gtsam/linear/SparseEigen.h @@ -0,0 +1,119 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file SparseEigen.h + * + * @brief Utilities for creating Eigen sparse matrices (gtsam::SparseEigen) + * + * @date Aug 2019 + * @author Mandy Xie + * @author Fan Jiang + * @author Gerry Chen + * @author Frank Dellaert + */ + +#pragma once + +#include +#include + +#include + +namespace gtsam { + +typedef Eigen::SparseMatrix SparseEigen; + +/// Constructs an Eigen-format SparseMatrix of a GaussianFactorGraph +SparseEigen sparseJacobianEigen( + const GaussianFactorGraph &gfg, const Ordering &ordering) { + // TODO(gerry): eliminate copy/pasta by making GaussianFactorGraph version + // more general, or by creating an Eigen::Triplet compatible wrapper for + // boost::tuple return type + + // First find dimensions of each variable + std::map dims; + for (const boost::shared_ptr &factor : gfg) { + if (!static_cast(factor)) continue; + + for (auto it = factor->begin(); it != factor->end(); ++it) { + dims[*it] = factor->getDim(it); + } + } + + // Compute first scalar column of each variable + size_t currentColIndex = 0; + std::map columnIndices; + for (const auto key : ordering) { + columnIndices[key] = currentColIndex; + currentColIndex += dims[key]; + } + + // Iterate over all factors, adding sparse scalar entries + std::vector> entries; + entries.reserve(60 * gfg.size()); + + size_t row = 0; + for (const boost::shared_ptr &factor : gfg) { + if (!static_cast(factor)) continue; + + // Convert to JacobianFactor if necessary + JacobianFactor::shared_ptr jacobianFactor( + boost::dynamic_pointer_cast(factor)); + if (!jacobianFactor) { + HessianFactor::shared_ptr hessian( + boost::dynamic_pointer_cast(factor)); + if (hessian) + jacobianFactor.reset(new JacobianFactor(*hessian)); + else + throw std::invalid_argument( + "GaussianFactorGraph contains a factor that is neither a " + "JacobianFactor nor a HessianFactor."); + } + + // Whiten the factor and add entries for it + // iterate over all variables in the factor + const JacobianFactor whitened(jacobianFactor->whiten()); + for (JacobianFactor::const_iterator key = whitened.begin(); + key < whitened.end(); ++key) { + JacobianFactor::constABlock whitenedA = whitened.getA(key); + // find first column index for this key + size_t column_start = columnIndices[*key]; + for (size_t i = 0; i < (size_t)whitenedA.rows(); i++) + for (size_t j = 0; j < (size_t)whitenedA.cols(); j++) { + double s = whitenedA(i, j); + if (std::abs(s) > 1e-12) + entries.emplace_back(row + i, column_start + j, s); + } + } + + JacobianFactor::constBVector whitenedb(whitened.getb()); + size_t bcolumn = currentColIndex; + for (size_t i = 0; i < (size_t)whitenedb.size(); i++) { + double s = whitenedb(i); + if (std::abs(s) > 1e-12) entries.emplace_back(row + i, bcolumn, s); + } + + // Increment row index + row += jacobianFactor->rows(); + } + + // ...and make a sparse matrix with it. + SparseEigen Ab(row, currentColIndex + 1); + Ab.setFromTriplets(entries.begin(), entries.end()); + return Ab; +} + +SparseEigen sparseJacobianEigen(const GaussianFactorGraph &gfg) { + return sparseJacobianEigen(gfg, Ordering(gfg.keys())); +} + +} // namespace gtsam diff --git a/gtsam/linear/SubgraphBuilder.cpp b/gtsam/linear/SubgraphBuilder.cpp index c6b3ca15f..1919d38be 100644 --- a/gtsam/linear/SubgraphBuilder.cpp +++ b/gtsam/linear/SubgraphBuilder.cpp @@ -383,7 +383,7 @@ Subgraph SubgraphBuilder::operator()(const GaussianFactorGraph &gfg) const { const vector tree = buildTree(gfg, forward_ordering, weights); if (tree.size() != n - 1) { throw std::runtime_error( - "SubgraphBuilder::operator() failure: tree.size() != n-1"); + "SubgraphBuilder::operator() failure: tree.size() != n-1, might be caused by disconnected graph"); } // Downweight the tree edges to zero. diff --git a/gtsam/linear/VectorValues.cpp b/gtsam/linear/VectorValues.cpp index 9b5868744..746275847 100644 --- a/gtsam/linear/VectorValues.cpp +++ b/gtsam/linear/VectorValues.cpp @@ -161,7 +161,7 @@ namespace gtsam { bool VectorValues::equals(const VectorValues& x, double tol) const { if(this->size() != x.size()) return false; - for(const auto& values: boost::combine(*this, x)) { + for(const auto values: boost::combine(*this, x)) { if(values.get<0>().first != values.get<1>().first || !equal_with_abs_tol(values.get<0>().second, values.get<1>().second, tol)) return false; @@ -233,7 +233,7 @@ namespace gtsam { double result = 0.0; typedef boost::tuple ValuePair; using boost::adaptors::map_values; - for(const ValuePair& values: boost::combine(*this, v)) { + for(const ValuePair values: boost::combine(*this, v)) { assert_throw(values.get<0>().first == values.get<1>().first, invalid_argument("VectorValues::dot called with a VectorValues of different structure")); assert_throw(values.get<0>().second.size() == values.get<1>().second.size(), diff --git a/gtsam/linear/tests/powerMethodExample.h b/gtsam/linear/tests/powerMethodExample.h new file mode 100644 index 000000000..f80299386 --- /dev/null +++ b/gtsam/linear/tests/powerMethodExample.h @@ -0,0 +1,67 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010-2019, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * powerMethodExample.h + * + * @file powerMethodExample.h + * @date Nov 2020 + * @author Jing Wu + * @brief Create sparse and dense factor graph for + * PowerMethod/AcceleratedPowerMethod + */ + +#include + +#include + + +namespace gtsam { +namespace linear { +namespace test { +namespace example { + +/* ************************************************************************* */ +inline GaussianFactorGraph createSparseGraph() { + using symbol_shorthand::X; + // Let's make a scalar synchronization graph with 4 nodes + GaussianFactorGraph fg; + auto model = noiseModel::Unit::Create(1); + for (size_t j = 0; j < 3; j++) { + fg.add(X(j), -I_1x1, X(j + 1), I_1x1, Vector1::Zero(), model); + } + fg.add(X(3), -I_1x1, X(0), I_1x1, Vector1::Zero(), model); // extra row + + return fg; +} + +/* ************************************************************************* */ +inline GaussianFactorGraph createDenseGraph() { + using symbol_shorthand::X; + // Let's make a scalar synchronization graph with 10 nodes + GaussianFactorGraph fg; + auto model = noiseModel::Unit::Create(1); + // Iterate over nodes + for (size_t j = 0; j < 10; j++) { + // Each node has an edge with all the others + for (size_t i = 1; i < 10; i++) + fg.add(X(j), -I_1x1, X((j + i) % 10), I_1x1, Vector1::Zero(), model); + } + + return fg; +} + +/* ************************************************************************* */ + +} // namespace example +} // namespace test +} // namespace linear +} // namespace gtsam diff --git a/gtsam/linear/tests/testAcceleratedPowerMethod.cpp b/gtsam/linear/tests/testAcceleratedPowerMethod.cpp new file mode 100644 index 000000000..7c4a90936 --- /dev/null +++ b/gtsam/linear/tests/testAcceleratedPowerMethod.cpp @@ -0,0 +1,140 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010-2019, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * testPowerMethod.cpp + * + * @file testAcceleratedPowerMethod.cpp + * @date Sept 2020 + * @author Jing Wu + * @brief Check eigenvalue and eigenvector computed by accelerated power method + */ + +#include +#include +#include +#include +#include +#include +#include + +#include +#include +#include +#include +#include + +using namespace std; +using namespace gtsam; + +/* ************************************************************************* */ +TEST(AcceleratedPowerMethod, acceleratedPowerIteration) { + // test power iteration, beta is set to 0 + Sparse A(6, 6); + A.coeffRef(0, 0) = 6; + A.coeffRef(1, 1) = 5; + A.coeffRef(2, 2) = 4; + A.coeffRef(3, 3) = 3; + A.coeffRef(4, 4) = 2; + A.coeffRef(5, 5) = 1; + Vector initial = (Vector(6) << 0.24434602, 0.22829942, 0.70094486, 0.15463092, 0.55871359, + 0.2465342).finished(); + const double ev1 = 6.0; + + // test accelerated power iteration + AcceleratedPowerMethod apf(A, initial); + apf.compute(100, 1e-5); + EXPECT_LONGS_EQUAL(6, apf.eigenvector().rows()); + + Vector6 actual1 = apf.eigenvector(); + const double ritzValue = actual1.dot(A * actual1); + const double ritzResidual = (A * actual1 - ritzValue * actual1).norm(); + EXPECT_DOUBLES_EQUAL(0, ritzResidual, 1e-5); + + EXPECT_DOUBLES_EQUAL(ev1, apf.eigenvalue(), 1e-5); +} + +/* ************************************************************************* */ +TEST(AcceleratedPowerMethod, useFactorGraphSparse) { + // Let's make a scalar synchronization graph with 4 nodes + GaussianFactorGraph fg = gtsam::linear::test::example::createSparseGraph(); + + // Get eigenvalues and eigenvectors with Eigen + auto L = fg.hessian(); + Eigen::EigenSolver solver(L.first); + + // find the index of the max eigenvalue + size_t maxIdx = 0; + for (auto i = 0; i < solver.eigenvalues().rows(); ++i) { + if (solver.eigenvalues()(i).real() >= solver.eigenvalues()(maxIdx).real()) + maxIdx = i; + } + // Store the max eigenvalue and its according eigenvector + const auto ev1 = solver.eigenvalues()(maxIdx).real(); + + Vector disturb = Vector4::Random(); + disturb.normalize(); + Vector initial = L.first.row(0); + double magnitude = initial.norm(); + initial += 0.03 * magnitude * disturb; + AcceleratedPowerMethod apf(L.first, initial); + apf.compute(100, 1e-5); + // Check if the eigenvalue is the maximum eigen value + EXPECT_DOUBLES_EQUAL(ev1, apf.eigenvalue(), 1e-8); + + // Check if the according ritz residual converged to the threshold + Vector actual1 = apf.eigenvector(); + const double ritzValue = actual1.dot(L.first * actual1); + const double ritzResidual = (L.first * actual1 - ritzValue * actual1).norm(); + EXPECT_DOUBLES_EQUAL(0, ritzResidual, 1e-5); +} + +/* ************************************************************************* */ +TEST(AcceleratedPowerMethod, useFactorGraphDense) { + // Let's make a scalar synchronization graph with 10 nodes + GaussianFactorGraph fg = gtsam::linear::test::example::createDenseGraph(); + + // Get eigenvalues and eigenvectors with Eigen + auto L = fg.hessian(); + Eigen::EigenSolver solver(L.first); + + // find the index of the max eigenvalue + size_t maxIdx = 0; + for (auto i = 0; i < solver.eigenvalues().rows(); ++i) { + if (solver.eigenvalues()(i).real() >= solver.eigenvalues()(maxIdx).real()) + maxIdx = i; + } + // Store the max eigenvalue and its according eigenvector + const auto ev1 = solver.eigenvalues()(maxIdx).real(); + + Vector disturb = Vector10::Random(); + disturb.normalize(); + Vector initial = L.first.row(0); + double magnitude = initial.norm(); + initial += 0.03 * magnitude * disturb; + AcceleratedPowerMethod apf(L.first, initial); + apf.compute(100, 1e-5); + // Check if the eigenvalue is the maximum eigen value + EXPECT_DOUBLES_EQUAL(ev1, apf.eigenvalue(), 1e-8); + + // Check if the according ritz residual converged to the threshold + Vector actual1 = apf.eigenvector(); + const double ritzValue = actual1.dot(L.first * actual1); + const double ritzResidual = (L.first * actual1 - ritzValue * actual1).norm(); + EXPECT_DOUBLES_EQUAL(0, ritzResidual, 1e-5); +} + +/* ************************************************************************* */ +int main() { + TestResult tr; + return TestRegistry::runAllTests(tr); +} +/* ************************************************************************* */ diff --git a/gtsam/linear/tests/testGaussianFactorGraph.cpp b/gtsam/linear/tests/testGaussianFactorGraph.cpp index 45f652d05..8b9ce94a9 100644 --- a/gtsam/linear/tests/testGaussianFactorGraph.cpp +++ b/gtsam/linear/tests/testGaussianFactorGraph.cpp @@ -36,9 +36,18 @@ using namespace boost::assign; using namespace std; using namespace gtsam; -// static SharedDiagonal -// sigma0_1 = noiseModel::Isotropic::Sigma(2,0.1), sigma_02 = noiseModel::Isotropic::Sigma(2,0.2), -// constraintModel = noiseModel::Constrained::All(2); +typedef boost::tuple BoostTriplet; +bool triplet_equal(BoostTriplet a, BoostTriplet b) { + if (a.get<0>() == b.get<0>() && a.get<1>() == b.get<1>() && + a.get<2>() == b.get<2>()) return true; + + cout << "not equal:" << endl; + cout << "\texpected: " + "(" << a.get<0>() << ", " << a.get<1>() << ") = " << a.get<2>() << endl; + cout << "\tactual: " + "(" << b.get<0>() << ", " << b.get<1>() << ") = " << b.get<2>() << endl; + return false; +} /* ************************************************************************* */ TEST(GaussianFactorGraph, initialization) { @@ -74,8 +83,8 @@ TEST(GaussianFactorGraph, sparseJacobian) { // 9 10 0 11 12 13 // 0 0 0 14 15 16 - // Expected - NOTE that we transpose this! - Matrix expectedT = (Matrix(16, 3) << + // Expected + Matrix expected = (Matrix(16, 3) << 1., 1., 2., 1., 2., 4., 1., 3., 6., @@ -93,17 +102,32 @@ TEST(GaussianFactorGraph, sparseJacobian) { 3., 6.,26., 4., 6.,32.).finished(); - Matrix expected = expectedT.transpose(); + // expected: in matlab format - NOTE the transpose!) + Matrix expectedMatlab = expected.transpose(); GaussianFactorGraph gfg; SharedDiagonal model = noiseModel::Isotropic::Sigma(2, 0.5); - gfg.add(0, (Matrix(2, 3) << 1., 2., 3., 5., 6., 7.).finished(), Vector2(4., 8.), model); - gfg.add(0, (Matrix(2, 3) << 9., 10., 0., 0., 0., 0.).finished(), 1, - (Matrix(2, 2) << 11., 12., 14., 15.).finished(), Vector2(13., 16.), model); + const Key x123 = 0, x45 = 1; + gfg.add(x123, (Matrix(2, 3) << 1, 2, 3, 5, 6, 7).finished(), + Vector2(4, 8), model); + gfg.add(x123, (Matrix(2, 3) << 9, 10, 0, 0, 0, 0).finished(), + x45, (Matrix(2, 2) << 11, 12, 14, 15.).finished(), + Vector2(13, 16), model); Matrix actual = gfg.sparseJacobian_(); - EXPECT(assert_equal(expected, actual)); + EXPECT(assert_equal(expectedMatlab, actual)); + + // BoostTriplets + auto boostActual = gfg.sparseJacobian(); + // check the triplets size... + EXPECT_LONGS_EQUAL(16, boostActual.size()); + // check content + for (int i = 0; i < 16; i++) { + EXPECT(triplet_equal( + BoostTriplet(expected(i, 0) - 1, expected(i, 1) - 1, expected(i, 2)), + boostActual.at(i))); + } } /* ************************************************************************* */ diff --git a/gtsam/linear/tests/testPowerMethod.cpp b/gtsam/linear/tests/testPowerMethod.cpp new file mode 100644 index 000000000..54d4c720d --- /dev/null +++ b/gtsam/linear/tests/testPowerMethod.cpp @@ -0,0 +1,124 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010-2019, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * testPowerMethod.cpp + * + * @file testPowerMethod.cpp + * @date Sept 2020 + * @author Jing Wu + * @brief Check eigenvalue and eigenvector computed by power method + */ + +#include +#include +#include +#include +#include +#include +#include + +#include +#include +#include +#include +#include + +using namespace std; +using namespace gtsam; + +/* ************************************************************************* */ +TEST(PowerMethod, powerIteration) { + // test power iteration, beta is set to 0 + Sparse A(6, 6); + A.coeffRef(0, 0) = 6; + A.coeffRef(1, 1) = 5; + A.coeffRef(2, 2) = 4; + A.coeffRef(3, 3) = 3; + A.coeffRef(4, 4) = 2; + A.coeffRef(5, 5) = 1; + Vector initial = (Vector(6) << 0.24434602, 0.22829942, 0.70094486, 0.15463092, 0.55871359, + 0.2465342).finished(); + PowerMethod pf(A, initial); + pf.compute(100, 1e-5); + EXPECT_LONGS_EQUAL(6, pf.eigenvector().rows()); + + Vector6 actual1 = pf.eigenvector(); + const double ritzValue = actual1.dot(A * actual1); + const double ritzResidual = (A * actual1 - ritzValue * actual1).norm(); + EXPECT_DOUBLES_EQUAL(0, ritzResidual, 1e-5); + + const double ev1 = 6.0; + EXPECT_DOUBLES_EQUAL(ev1, pf.eigenvalue(), 1e-5); +} + +/* ************************************************************************* */ +TEST(PowerMethod, useFactorGraphSparse) { + // Let's make a scalar synchronization graph with 4 nodes + GaussianFactorGraph fg = gtsam::linear::test::example::createSparseGraph(); + + // Get eigenvalues and eigenvectors with Eigen + auto L = fg.hessian(); + Eigen::EigenSolver solver(L.first); + + // find the index of the max eigenvalue + size_t maxIdx = 0; + for (auto i = 0; i < solver.eigenvalues().rows(); ++i) { + if (solver.eigenvalues()(i).real() >= solver.eigenvalues()(maxIdx).real()) + maxIdx = i; + } + // Store the max eigenvalue and its according eigenvector + const auto ev1 = solver.eigenvalues()(maxIdx).real(); + + Vector initial = Vector4::Random(); + PowerMethod pf(L.first, initial); + pf.compute(100, 1e-5); + EXPECT_DOUBLES_EQUAL(ev1, pf.eigenvalue(), 1e-8); + auto actual2 = pf.eigenvector(); + const double ritzValue = actual2.dot(L.first * actual2); + const double ritzResidual = (L.first * actual2 - ritzValue * actual2).norm(); + EXPECT_DOUBLES_EQUAL(0, ritzResidual, 1e-5); +} + +/* ************************************************************************* */ +TEST(PowerMethod, useFactorGraphDense) { + // Let's make a scalar synchronization graph with 10 nodes + GaussianFactorGraph fg = gtsam::linear::test::example::createDenseGraph(); + + // Get eigenvalues and eigenvectors with Eigen + auto L = fg.hessian(); + Eigen::EigenSolver solver(L.first); + + // find the index of the max eigenvalue + size_t maxIdx = 0; + for (auto i = 0; i < solver.eigenvalues().rows(); ++i) { + if (solver.eigenvalues()(i).real() >= solver.eigenvalues()(maxIdx).real()) + maxIdx = i; + } + // Store the max eigenvalue and its according eigenvector + const auto ev1 = solver.eigenvalues()(maxIdx).real(); + + Vector initial = Vector10::Random(); + PowerMethod pf(L.first, initial); + pf.compute(100, 1e-5); + EXPECT_DOUBLES_EQUAL(ev1, pf.eigenvalue(), 1e-8); + auto actual2 = pf.eigenvector(); + const double ritzValue = actual2.dot(L.first * actual2); + const double ritzResidual = (L.first * actual2 - ritzValue * actual2).norm(); + EXPECT_DOUBLES_EQUAL(0, ritzResidual, 1e-5); +} + +/* ************************************************************************* */ +int main() { + TestResult tr; + return TestRegistry::runAllTests(tr); +} +/* ************************************************************************* */ diff --git a/gtsam/linear/tests/testSparseEigen.cpp b/gtsam/linear/tests/testSparseEigen.cpp new file mode 100644 index 000000000..225e1dab2 --- /dev/null +++ b/gtsam/linear/tests/testSparseEigen.cpp @@ -0,0 +1,72 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file testSparseMatrix.cpp + * @author Mandy Xie + * @author Fan Jiang + * @author Gerry Chen + * @author Frank Dellaert + * @date Jan, 2021 + */ + +#include +#include + +#include +using boost::assign::list_of; + +#include +#include + +using namespace std; +using namespace gtsam; + +/* ************************************************************************* */ +TEST(SparseEigen, sparseJacobianEigen) { + GaussianFactorGraph gfg; + SharedDiagonal model = noiseModel::Isotropic::Sigma(2, 0.5); + const Key x123 = 0, x45 = 1; + gfg.add(x123, (Matrix(2, 3) << 1, 2, 3, 5, 6, 7).finished(), + Vector2(4, 8), model); + gfg.add(x123, (Matrix(2, 3) << 9, 10, 0, 0, 0, 0).finished(), + x45, (Matrix(2, 2) << 11, 12, 14, 15.).finished(), + Vector2(13, 16), model); + + // Sparse Matrix + auto sparseResult = sparseJacobianEigen(gfg); + EXPECT_LONGS_EQUAL(16, sparseResult.nonZeros()); + EXPECT(assert_equal(4, sparseResult.rows())); + EXPECT(assert_equal(6, sparseResult.cols())); + EXPECT(assert_equal(gfg.augmentedJacobian(), Matrix(sparseResult))); + + // Call sparseJacobian with optional ordering... + auto ordering = Ordering(list_of(x45)(x123)); + + // Eigen Sparse with optional ordering + EXPECT(assert_equal(gfg.augmentedJacobian(ordering), + Matrix(sparseJacobianEigen(gfg, ordering)))); + + // Check matrix dimensions when zero rows / cols + gfg.add(x123, Matrix23::Zero(), Vector2::Zero(), model); // zero row + gfg.add(2, Matrix21::Zero(), Vector2::Zero(), model); // zero col + sparseResult = sparseJacobianEigen(gfg); + EXPECT_LONGS_EQUAL(16, sparseResult.nonZeros()); + EXPECT(assert_equal(8, sparseResult.rows())); + EXPECT(assert_equal(7, sparseResult.cols())); +} + +/* ************************************************************************* */ +int main() { + TestResult tr; + return TestRegistry::runAllTests(tr); +} +/* ************************************************************************* */ diff --git a/gtsam/navigation/ImuBias.h b/gtsam/navigation/ImuBias.h index d52b4eb29..fad952232 100644 --- a/gtsam/navigation/ImuBias.h +++ b/gtsam/navigation/ImuBias.h @@ -29,8 +29,8 @@ namespace imuBias { class GTSAM_EXPORT ConstantBias { private: - Vector3 biasAcc_; - Vector3 biasGyro_; + Vector3 biasAcc_; ///< The units for stddev are σ = m/s² or m √Hz/s² + Vector3 biasGyro_; ///< The units for stddev are σ = rad/s or rad √Hz/s public: /// dimension of the variable - used to autodetect sizes diff --git a/gtsam/navigation/PreintegratedRotation.h b/gtsam/navigation/PreintegratedRotation.h index 0e0559a32..e52d28e1e 100644 --- a/gtsam/navigation/PreintegratedRotation.h +++ b/gtsam/navigation/PreintegratedRotation.h @@ -29,7 +29,9 @@ namespace gtsam { /// Parameters for pre-integration: /// Usage: Create just a single Params and pass a shared pointer to the constructor struct GTSAM_EXPORT PreintegratedRotationParams { - Matrix3 gyroscopeCovariance; ///< continuous-time "Covariance" of gyroscope measurements + /// Continuous-time "Covariance" of gyroscope measurements + /// The units for stddev are σ = rad/s/√Hz + Matrix3 gyroscopeCovariance; boost::optional omegaCoriolis; ///< Coriolis constant boost::optional body_P_sensor; ///< The pose of the sensor in the body frame diff --git a/gtsam/navigation/PreintegrationParams.h b/gtsam/navigation/PreintegrationParams.h index ce1f0e734..960f67e24 100644 --- a/gtsam/navigation/PreintegrationParams.h +++ b/gtsam/navigation/PreintegrationParams.h @@ -24,7 +24,9 @@ namespace gtsam { /// Parameters for pre-integration: /// Usage: Create just a single Params and pass a shared pointer to the constructor struct GTSAM_EXPORT PreintegrationParams: PreintegratedRotationParams { - Matrix3 accelerometerCovariance; ///< continuous-time "Covariance" of accelerometer + /// Continuous-time "Covariance" of accelerometer + /// The units for stddev are σ = m/s²/√Hz + Matrix3 accelerometerCovariance; Matrix3 integrationCovariance; ///< continuous-time "Covariance" describing integration uncertainty bool use2ndOrderCoriolis; ///< Whether to use second order Coriolis integration Vector3 n_gravity; ///< Gravity vector in nav frame diff --git a/gtsam/nonlinear/FunctorizedFactor.h b/gtsam/nonlinear/FunctorizedFactor.h index 688b3aaa2..53a48f097 100644 --- a/gtsam/nonlinear/FunctorizedFactor.h +++ b/gtsam/nonlinear/FunctorizedFactor.h @@ -87,8 +87,8 @@ class GTSAM_EXPORT FunctorizedFactor : public NoiseModelFactor1 { NonlinearFactor::shared_ptr(new FunctorizedFactor(*this))); } - Vector evaluateError(const T ¶ms, - boost::optional H = boost::none) const override { + Vector evaluateError(const T ¶ms, boost::optional H = + boost::none) const override { R x = func_(params, H); Vector error = traits::Local(measured_, x); return error; @@ -96,8 +96,9 @@ class GTSAM_EXPORT FunctorizedFactor : public NoiseModelFactor1 { /// @name Testable /// @{ - void print(const std::string &s = "", - const KeyFormatter &keyFormatter = DefaultKeyFormatter) const override { + void print( + const std::string &s = "", + const KeyFormatter &keyFormatter = DefaultKeyFormatter) const override { Base::print(s, keyFormatter); std::cout << s << (s != "" ? " " : "") << "FunctorizedFactor(" << keyFormatter(this->key()) << ")" << std::endl; @@ -144,4 +145,111 @@ FunctorizedFactor MakeFunctorizedFactor(Key key, const R &z, return FunctorizedFactor(key, z, model, func); } +/** + * Factor which evaluates provided binary functor and uses the result to compute + * error with respect to the provided measurement. + * + * Template parameters are + * @param R: The return type of the functor after evaluation. + * @param T1: The first argument type for the functor. + * @param T2: The second argument type for the functor. + */ +template +class GTSAM_EXPORT FunctorizedFactor2 : public NoiseModelFactor2 { + private: + using Base = NoiseModelFactor2; + + R measured_; ///< value that is compared with functor return value + SharedNoiseModel noiseModel_; ///< noise model + using FunctionType = std::function, + boost::optional)>; + FunctionType func_; ///< functor instance + + public: + /** default constructor - only use for serialization */ + FunctorizedFactor2() {} + + /** Construct with given x and the parameters of the basis + * + * @param key: Factor key + * @param z: Measurement object of same type as that returned by functor + * @param model: Noise model + * @param func: The instance of the functor object + */ + FunctorizedFactor2(Key key1, Key key2, const R &z, + const SharedNoiseModel &model, const FunctionType func) + : Base(model, key1, key2), + measured_(z), + noiseModel_(model), + func_(func) {} + + virtual ~FunctorizedFactor2() {} + + /// @return a deep copy of this factor + NonlinearFactor::shared_ptr clone() const override { + return boost::static_pointer_cast( + NonlinearFactor::shared_ptr(new FunctorizedFactor2(*this))); + } + + Vector evaluateError( + const T1 ¶ms1, const T2 ¶ms2, + boost::optional H1 = boost::none, + boost::optional H2 = boost::none) const override { + R x = func_(params1, params2, H1, H2); + Vector error = traits::Local(measured_, x); + return error; + } + + /// @name Testable + /// @{ + void print( + const std::string &s = "", + const KeyFormatter &keyFormatter = DefaultKeyFormatter) const override { + Base::print(s, keyFormatter); + std::cout << s << (s != "" ? " " : "") << "FunctorizedFactor2(" + << keyFormatter(this->key1()) << ", " + << keyFormatter(this->key2()) << ")" << std::endl; + traits::Print(measured_, " measurement: "); + std::cout << " noise model sigmas: " << noiseModel_->sigmas().transpose() + << std::endl; + } + + bool equals(const NonlinearFactor &other, double tol = 1e-9) const override { + const FunctorizedFactor2 *e = + dynamic_cast *>(&other); + return e && Base::equals(other, tol) && + traits::Equals(this->measured_, e->measured_, tol); + } + /// @} + + private: + /** Serialization function */ + friend class boost::serialization::access; + template + void serialize(ARCHIVE &ar, const unsigned int /*version*/) { + ar &boost::serialization::make_nvp( + "NoiseModelFactor2", boost::serialization::base_object(*this)); + ar &BOOST_SERIALIZATION_NVP(measured_); + ar &BOOST_SERIALIZATION_NVP(func_); + } +}; + +/// traits +template +struct traits> + : public Testable> {}; + +/** + * Helper function to create a functorized factor. + * + * Uses function template deduction to identify return type and functor type, so + * template list only needs the functor argument type. + */ +template +FunctorizedFactor2 MakeFunctorizedFactor2( + Key key1, Key key2, const R &z, const SharedNoiseModel &model, + const FUNC func) { + return FunctorizedFactor2(key1, key2, z, model, func); +} + } // namespace gtsam diff --git a/gtsam/nonlinear/GaussNewtonOptimizer.h b/gtsam/nonlinear/GaussNewtonOptimizer.h index a436597e5..a3923524b 100644 --- a/gtsam/nonlinear/GaussNewtonOptimizer.h +++ b/gtsam/nonlinear/GaussNewtonOptimizer.h @@ -28,6 +28,8 @@ class GaussNewtonOptimizer; * NonlinearOptimizationParams. */ class GTSAM_EXPORT GaussNewtonParams : public NonlinearOptimizerParams { +public: + using OptimizerType = GaussNewtonOptimizer; }; /** diff --git a/gtsam/nonlinear/GncOptimizer.h b/gtsam/nonlinear/GncOptimizer.h new file mode 100644 index 000000000..cd0b4c81a --- /dev/null +++ b/gtsam/nonlinear/GncOptimizer.h @@ -0,0 +1,338 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file GncOptimizer.h + * @brief The GncOptimizer class + * @author Jingnan Shi + * @author Luca Carlone + * @author Frank Dellaert + * + * Implementation of the paper: Yang, Antonante, Tzoumas, Carlone, "Graduated Non-Convexity for Robust Spatial Perception: + * From Non-Minimal Solvers to Global Outlier Rejection", ICRA/RAL, 2020. (arxiv version: https://arxiv.org/pdf/1909.08605.pdf) + * + * See also: + * Antonante, Tzoumas, Yang, Carlone, "Outlier-Robust Estimation: Hardness, Minimally-Tuned Algorithms, and Applications", + * arxiv: https://arxiv.org/pdf/2007.15109.pdf, 2020. + */ + +#pragma once + +#include +#include + +namespace gtsam { + +/* ************************************************************************* */ +template +class GncOptimizer { + public: + /// For each parameter, specify the corresponding optimizer: e.g., GaussNewtonParams -> GaussNewtonOptimizer. + typedef typename GncParameters::OptimizerType BaseOptimizer; + + private: + NonlinearFactorGraph nfg_; ///< Original factor graph to be solved by GNC. + Values state_; ///< Initial values to be used at each iteration by GNC. + GncParameters params_; ///< GNC parameters. + Vector weights_; ///< Weights associated to each factor in GNC (this could be a local variable in optimize, but it is useful to make it accessible from outside). + + public: + /// Constructor. + GncOptimizer(const NonlinearFactorGraph& graph, const Values& initialValues, + const GncParameters& params = GncParameters()) + : state_(initialValues), + params_(params) { + + // make sure all noiseModels are Gaussian or convert to Gaussian + nfg_.resize(graph.size()); + for (size_t i = 0; i < graph.size(); i++) { + if (graph[i]) { + NoiseModelFactor::shared_ptr factor = boost::dynamic_pointer_cast< + NoiseModelFactor>(graph[i]); + auto robust = boost::dynamic_pointer_cast< + noiseModel::Robust>(factor->noiseModel()); + // if the factor has a robust loss, we remove the robust loss + nfg_[i] = robust ? factor-> cloneWithNewNoiseModel(robust->noise()) : factor; + } + } + } + + /// Access a copy of the internal factor graph. + const NonlinearFactorGraph& getFactors() const { return nfg_; } + + /// Access a copy of the internal values. + const Values& getState() const { return state_; } + + /// Access a copy of the parameters. + const GncParameters& getParams() const { return params_;} + + /// Access a copy of the GNC weights. + const Vector& getWeights() const { return weights_;} + + /// Compute optimal solution using graduated non-convexity. + Values optimize() { + // start by assuming all measurements are inliers + weights_ = Vector::Ones(nfg_.size()); + BaseOptimizer baseOptimizer(nfg_, state_); + Values result = baseOptimizer.optimize(); + double mu = initializeMu(); + double prev_cost = nfg_.error(result); + double cost = 0.0; // this will be updated in the main loop + + // handle the degenerate case that corresponds to small + // maximum residual errors at initialization + // For GM: if residual error is small, mu -> 0 + // For TLS: if residual error is small, mu -> -1 + if (mu <= 0) { + if (params_.verbosity >= GncParameters::Verbosity::SUMMARY) { + std::cout << "GNC Optimizer stopped because maximum residual at " + "initialization is small." + << std::endl; + } + if (params_.verbosity >= GncParameters::Verbosity::VALUES) { + result.print("result\n"); + std::cout << "mu: " << mu << std::endl; + } + return result; + } + + size_t iter; + for (iter = 0; iter < params_.maxIterations; iter++) { + + // display info + if (params_.verbosity >= GncParameters::Verbosity::VALUES) { + std::cout << "iter: " << iter << std::endl; + result.print("result\n"); + std::cout << "mu: " << mu << std::endl; + std::cout << "weights: " << weights_ << std::endl; + } + // weights update + weights_ = calculateWeights(result, mu); + + // variable/values update + NonlinearFactorGraph graph_iter = this->makeWeightedGraph(weights_); + BaseOptimizer baseOptimizer_iter(graph_iter, state_); + result = baseOptimizer_iter.optimize(); + + // stopping condition + cost = graph_iter.error(result); + if (checkConvergence(mu, weights_, cost, prev_cost)) { + break; + } + + // update mu + mu = updateMu(mu); + + // get ready for next iteration + prev_cost = cost; + + // display info + if (params_.verbosity >= GncParameters::Verbosity::VALUES) { + std::cout << "previous cost: " << prev_cost << std::endl; + std::cout << "current cost: " << cost << std::endl; + } + } + // display info + if (params_.verbosity >= GncParameters::Verbosity::SUMMARY) { + std::cout << "final iterations: " << iter << std::endl; + std::cout << "final mu: " << mu << std::endl; + std::cout << "final weights: " << weights_ << std::endl; + std::cout << "previous cost: " << prev_cost << std::endl; + std::cout << "current cost: " << cost << std::endl; + } + return result; + } + + /// Initialize the gnc parameter mu such that loss is approximately convex (remark 5 in GNC paper). + double initializeMu() const { + // compute largest error across all factors + double rmax_sq = 0.0; + for (size_t i = 0; i < nfg_.size(); i++) { + if (nfg_[i]) { + rmax_sq = std::max(rmax_sq, nfg_[i]->error(state_)); + } + } + // set initial mu + switch (params_.lossType) { + case GncLossType::GM: + // surrogate cost is convex for large mu + return 2 * rmax_sq / params_.barcSq; // initial mu + case GncLossType::TLS: + /* initialize mu to the value specified in Remark 5 in GNC paper. + surrogate cost is convex for mu close to zero + degenerate case: 2 * rmax_sq - params_.barcSq < 0 (handled in the main loop) + according to remark mu = params_.barcSq / (2 * rmax_sq - params_.barcSq) = params_.barcSq/ excessResidual + however, if the denominator is 0 or negative, we return mu = -1 which leads to termination of the main GNC loop + */ + return + (2 * rmax_sq - params_.barcSq) > 0 ? + params_.barcSq / (2 * rmax_sq - params_.barcSq) : -1; + default: + throw std::runtime_error( + "GncOptimizer::initializeMu: called with unknown loss type."); + } + } + + /// Update the gnc parameter mu to gradually increase nonconvexity. + double updateMu(const double mu) const { + switch (params_.lossType) { + case GncLossType::GM: + // reduce mu, but saturate at 1 (original cost is recovered for mu -> 1) + return std::max(1.0, mu / params_.muStep); + case GncLossType::TLS: + // increases mu at each iteration (original cost is recovered for mu -> inf) + return mu * params_.muStep; + default: + throw std::runtime_error( + "GncOptimizer::updateMu: called with unknown loss type."); + } + } + + /// Check if we have reached the value of mu for which the surrogate loss matches the original loss. + bool checkMuConvergence(const double mu) const { + bool muConverged = false; + switch (params_.lossType) { + case GncLossType::GM: + muConverged = std::fabs(mu - 1.0) < 1e-9; // mu=1 recovers the original GM function + break; + case GncLossType::TLS: + muConverged = false; // for TLS there is no stopping condition on mu (it must tend to infinity) + break; + default: + throw std::runtime_error( + "GncOptimizer::checkMuConvergence: called with unknown loss type."); + } + if (muConverged && params_.verbosity >= GncParameters::Verbosity::SUMMARY) + std::cout << "muConverged = true " << std::endl; + return muConverged; + } + + /// Check convergence of relative cost differences. + bool checkCostConvergence(const double cost, const double prev_cost) const { + bool costConverged = std::fabs(cost - prev_cost) / std::max(prev_cost, 1e-7) + < params_.relativeCostTol; + if (costConverged && params_.verbosity >= GncParameters::Verbosity::SUMMARY) + std::cout << "checkCostConvergence = true " << std::endl; + return costConverged; + } + + /// Check convergence of weights to binary values. + bool checkWeightsConvergence(const Vector& weights) const { + bool weightsConverged = false; + switch (params_.lossType) { + case GncLossType::GM: + weightsConverged = false; // for GM, there is no clear binary convergence for the weights + break; + case GncLossType::TLS: + weightsConverged = true; + for (size_t i = 0; i < weights.size(); i++) { + if (std::fabs(weights[i] - std::round(weights[i])) + > params_.weightsTol) { + weightsConverged = false; + break; + } + } + break; + default: + throw std::runtime_error( + "GncOptimizer::checkWeightsConvergence: called with unknown loss type."); + } + if (weightsConverged + && params_.verbosity >= GncParameters::Verbosity::SUMMARY) + std::cout << "weightsConverged = true " << std::endl; + return weightsConverged; + } + + /// Check for convergence between consecutive GNC iterations. + bool checkConvergence(const double mu, const Vector& weights, + const double cost, const double prev_cost) const { + return checkCostConvergence(cost, prev_cost) + || checkWeightsConvergence(weights) || checkMuConvergence(mu); + } + + /// Create a graph where each factor is weighted by the gnc weights. + NonlinearFactorGraph makeWeightedGraph(const Vector& weights) const { + // make sure all noiseModels are Gaussian or convert to Gaussian + NonlinearFactorGraph newGraph; + newGraph.resize(nfg_.size()); + for (size_t i = 0; i < nfg_.size(); i++) { + if (nfg_[i]) { + auto factor = boost::dynamic_pointer_cast< + NoiseModelFactor>(nfg_[i]); + auto noiseModel = + boost::dynamic_pointer_cast( + factor->noiseModel()); + if (noiseModel) { + Matrix newInfo = weights[i] * noiseModel->information(); + auto newNoiseModel = noiseModel::Gaussian::Information(newInfo); + newGraph[i] = factor->cloneWithNewNoiseModel(newNoiseModel); + } else { + throw std::runtime_error( + "GncOptimizer::makeWeightedGraph: unexpected non-Gaussian noise model."); + } + } + } + return newGraph; + } + + /// Calculate gnc weights. + Vector calculateWeights(const Values& currentEstimate, const double mu) { + Vector weights = Vector::Ones(nfg_.size()); + + // do not update the weights that the user has decided are known inliers + std::vector allWeights; + for (size_t k = 0; k < nfg_.size(); k++) { + allWeights.push_back(k); + } + std::vector unknownWeights; + std::set_difference(allWeights.begin(), allWeights.end(), + params_.knownInliers.begin(), + params_.knownInliers.end(), + std::inserter(unknownWeights, unknownWeights.begin())); + + // update weights of known inlier/outlier measurements + switch (params_.lossType) { + case GncLossType::GM: { // use eq (12) in GNC paper + for (size_t k : unknownWeights) { + if (nfg_[k]) { + double u2_k = nfg_[k]->error(currentEstimate); // squared (and whitened) residual + weights[k] = std::pow( + (mu * params_.barcSq) / (u2_k + mu * params_.barcSq), 2); + } + } + return weights; + } + case GncLossType::TLS: { // use eq (14) in GNC paper + double upperbound = (mu + 1) / mu * params_.barcSq; + double lowerbound = mu / (mu + 1) * params_.barcSq; + for (size_t k : unknownWeights) { + if (nfg_[k]) { + double u2_k = nfg_[k]->error(currentEstimate); // squared (and whitened) residual + if (u2_k >= upperbound) { + weights[k] = 0; + } else if (u2_k <= lowerbound) { + weights[k] = 1; + } else { + weights[k] = std::sqrt(params_.barcSq * mu * (mu + 1) / u2_k) + - mu; + } + } + } + return weights; + } + default: + throw std::runtime_error( + "GncOptimizer::calculateWeights: called with unknown loss type."); + } + } +}; + +} diff --git a/gtsam/nonlinear/GncParams.h b/gtsam/nonlinear/GncParams.h new file mode 100644 index 000000000..0388a7fd1 --- /dev/null +++ b/gtsam/nonlinear/GncParams.h @@ -0,0 +1,164 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file GncOptimizer.h + * @brief The GncOptimizer class + * @author Jingnan Shi + * @author Luca Carlone + * @author Frank Dellaert + * + * Implementation of the paper: Yang, Antonante, Tzoumas, Carlone, "Graduated Non-Convexity for Robust Spatial Perception: + * From Non-Minimal Solvers to Global Outlier Rejection", ICRA/RAL, 2020. (arxiv version: https://arxiv.org/pdf/1909.08605.pdf) + * + * See also: + * Antonante, Tzoumas, Yang, Carlone, "Outlier-Robust Estimation: Hardness, Minimally-Tuned Algorithms, and Applications", + * arxiv: https://arxiv.org/pdf/2007.15109.pdf, 2020. + */ + +#pragma once + +#include +#include + +namespace gtsam { + +/* ************************************************************************* */ +/// Choice of robust loss function for GNC. +enum GncLossType { + GM /*Geman McClure*/, + TLS /*Truncated least squares*/ +}; + +template +class GncParams { + public: + /// For each parameter, specify the corresponding optimizer: e.g., GaussNewtonParams -> GaussNewtonOptimizer. + typedef typename BaseOptimizerParameters::OptimizerType OptimizerType; + + /// Verbosity levels + enum Verbosity { + SILENT = 0, + SUMMARY, + VALUES + }; + + /// Constructor. + GncParams(const BaseOptimizerParameters& baseOptimizerParams) + : baseOptimizerParams(baseOptimizerParams) { + } + + /// Default constructor. + GncParams() + : baseOptimizerParams() { + } + + /// GNC parameters. + BaseOptimizerParameters baseOptimizerParams; ///< Optimization parameters used to solve the weighted least squares problem at each GNC iteration + /// any other specific GNC parameters: + GncLossType lossType = TLS; ///< Default loss + size_t maxIterations = 100; ///< Maximum number of iterations + double barcSq = 1.0; ///< A factor is considered an inlier if factor.error() < barcSq. Note that factor.error() whitens by the covariance + double muStep = 1.4; ///< Multiplicative factor to reduce/increase the mu in gnc + double relativeCostTol = 1e-5; ///< If relative cost change is below this threshold, stop iterating + double weightsTol = 1e-4; ///< If the weights are within weightsTol from being binary, stop iterating (only for TLS) + Verbosity verbosity = SILENT; ///< Verbosity level + std::vector knownInliers = std::vector(); ///< Slots in the factor graph corresponding to measurements that we know are inliers + + /// Set the robust loss function to be used in GNC (chosen among the ones in GncLossType). + void setLossType(const GncLossType type) { + lossType = type; + } + + /// Set the maximum number of iterations in GNC (changing the max nr of iters might lead to less accurate solutions and is not recommended). + void setMaxIterations(const size_t maxIter) { + std::cout + << "setMaxIterations: changing the max nr of iters might lead to less accurate solutions and is not recommended! " + << std::endl; + maxIterations = maxIter; + } + + /** Set the maximum weighted residual error for an inlier. For a factor in the form f(x) = 0.5 * || r(x) ||^2_Omega, + * the inlier threshold is the largest value of f(x) for the corresponding measurement to be considered an inlier. + * In other words, an inlier at x is such that 0.5 * || r(x) ||^2_Omega <= barcSq. + * Assuming a isotropic measurement covariance sigma^2 * Identity, the cost becomes: 0.5 * 1/sigma^2 || r(x) ||^2 <= barcSq. + * Hence || r(x) ||^2 <= 2 * barcSq * sigma^2. + * */ + void setInlierCostThreshold(const double inth) { + barcSq = inth; + } + + /// Set the graduated non-convexity step: at each GNC iteration, mu is updated as mu <- mu * muStep. + void setMuStep(const double step) { + muStep = step; + } + + /// Set the maximum relative difference in mu values to stop iterating. + void setRelativeCostTol(double value) { + relativeCostTol = value; + } + + /// Set the maximum difference between the weights and their rounding in {0,1} to stop iterating. + void setWeightsTol(double value) { + weightsTol = value; + } + + /// Set the verbosity level. + void setVerbosityGNC(const Verbosity value) { + verbosity = value; + } + + /** (Optional) Provide a vector of measurements that must be considered inliers. The enties in the vector + * corresponds to the slots in the factor graph. For instance, if you have a nonlinear factor graph nfg, + * and you provide knownIn = {0, 2, 15}, GNC will not apply outlier rejection to nfg[0], nfg[2], and nfg[15]. + * This functionality is commonly used in SLAM when one may assume the odometry is outlier free, and + * only apply GNC to prune outliers from the loop closures. + * */ + void setKnownInliers(const std::vector& knownIn) { + for (size_t i = 0; i < knownIn.size(); i++) + knownInliers.push_back(knownIn[i]); + } + + /// Equals. + bool equals(const GncParams& other, double tol = 1e-9) const { + return baseOptimizerParams.equals(other.baseOptimizerParams) + && lossType == other.lossType && maxIterations == other.maxIterations + && std::fabs(barcSq - other.barcSq) <= tol + && std::fabs(muStep - other.muStep) <= tol + && verbosity == other.verbosity && knownInliers == other.knownInliers; + } + + /// Print. + void print(const std::string& str) const { + std::cout << str << "\n"; + switch (lossType) { + case GM: + std::cout << "lossType: Geman McClure" << "\n"; + break; + case TLS: + std::cout << "lossType: Truncated Least-squares" << "\n"; + break; + default: + throw std::runtime_error("GncParams::print: unknown loss type."); + } + std::cout << "maxIterations: " << maxIterations << "\n"; + std::cout << "barcSq: " << barcSq << "\n"; + std::cout << "muStep: " << muStep << "\n"; + std::cout << "relativeCostTol: " << relativeCostTol << "\n"; + std::cout << "weightsTol: " << weightsTol << "\n"; + std::cout << "verbosity: " << verbosity << "\n"; + for (size_t i = 0; i < knownInliers.size(); i++) + std::cout << "knownInliers: " << knownInliers[i] << "\n"; + baseOptimizerParams.print(str); + } +}; + +} diff --git a/gtsam/nonlinear/LevenbergMarquardtParams.h b/gtsam/nonlinear/LevenbergMarquardtParams.h index 4962ad366..30e783fc9 100644 --- a/gtsam/nonlinear/LevenbergMarquardtParams.h +++ b/gtsam/nonlinear/LevenbergMarquardtParams.h @@ -25,6 +25,8 @@ namespace gtsam { +class LevenbergMarquardtOptimizer; + /** Parameters for Levenberg-Marquardt optimization. Note that this parameters * class inherits from NonlinearOptimizerParams, which specifies the parameters * common to all nonlinear optimization algorithms. This class also contains @@ -40,6 +42,7 @@ public: static VerbosityLM verbosityLMTranslator(const std::string &s); static std::string verbosityLMTranslator(VerbosityLM value); + using OptimizerType = LevenbergMarquardtOptimizer; public: diff --git a/gtsam/nonlinear/NonlinearConjugateGradientOptimizer.h b/gtsam/nonlinear/NonlinearConjugateGradientOptimizer.h index abf6b257a..a85f27425 100644 --- a/gtsam/nonlinear/NonlinearConjugateGradientOptimizer.h +++ b/gtsam/nonlinear/NonlinearConjugateGradientOptimizer.h @@ -200,6 +200,10 @@ boost::tuple nonlinearConjugateGradient(const S &system, currentValues = system.advance(prevValues, alpha, direction); currentError = system.error(currentValues); + // User hook: + if (params.iterationHook) + params.iterationHook(iteration, prevError, currentError); + // Maybe show output if (params.verbosity >= NonlinearOptimizerParams::ERROR) std::cout << "iteration: " << iteration << ", currentError: " << currentError << std::endl; diff --git a/gtsam/nonlinear/NonlinearFactor.cpp b/gtsam/nonlinear/NonlinearFactor.cpp index 1cfcba274..8b8d2da6c 100644 --- a/gtsam/nonlinear/NonlinearFactor.cpp +++ b/gtsam/nonlinear/NonlinearFactor.cpp @@ -76,6 +76,14 @@ bool NoiseModelFactor::equals(const NonlinearFactor& f, double tol) const { && noiseModel_->equals(*e->noiseModel_, tol))); } +/* ************************************************************************* */ +NoiseModelFactor::shared_ptr NoiseModelFactor::cloneWithNewNoiseModel( + const SharedNoiseModel newNoise) const { + NoiseModelFactor::shared_ptr new_factor = boost::dynamic_pointer_cast(clone()); + new_factor->noiseModel_ = newNoise; + return new_factor; +} + /* ************************************************************************* */ static void check(const SharedNoiseModel& noiseModel, size_t m) { if (noiseModel && m != noiseModel->dim()) diff --git a/gtsam/nonlinear/NonlinearFactor.h b/gtsam/nonlinear/NonlinearFactor.h index 80fbfbb11..00311fb87 100644 --- a/gtsam/nonlinear/NonlinearFactor.h +++ b/gtsam/nonlinear/NonlinearFactor.h @@ -244,6 +244,12 @@ public: */ boost::shared_ptr linearize(const Values& x) const override; + /** + * Creates a shared_ptr clone of the + * factor with a new noise model + */ + shared_ptr cloneWithNewNoiseModel(const SharedNoiseModel newNoise) const; + private: /** Serialization function */ friend class boost::serialization::access; diff --git a/gtsam/nonlinear/NonlinearFactorGraph.cpp b/gtsam/nonlinear/NonlinearFactorGraph.cpp index 0b876f376..6a9e0cd0a 100644 --- a/gtsam/nonlinear/NonlinearFactorGraph.cpp +++ b/gtsam/nonlinear/NonlinearFactorGraph.cpp @@ -34,6 +34,7 @@ #endif #include +#include #include using namespace std; @@ -256,6 +257,16 @@ void NonlinearFactorGraph::saveGraph(std::ostream &stm, const Values& values, stm << "}\n"; } +/* ************************************************************************* */ +void NonlinearFactorGraph::saveGraph( + const std::string& file, const Values& values, + const GraphvizFormatting& graphvizFormatting, + const KeyFormatter& keyFormatter) const { + std::ofstream of(file); + saveGraph(of, values, graphvizFormatting, keyFormatter); + of.close(); +} + /* ************************************************************************* */ double NonlinearFactorGraph::error(const Values& values) const { gttic(NonlinearFactorGraph_error); @@ -365,7 +376,7 @@ static Scatter scatterFromValues(const Values& values) { scatter.reserve(values.size()); // use "natural" ordering with keys taken from the initial values - for (const auto& key_value : values) { + for (const auto key_value : values) { scatter.add(key_value.key, key_value.value.dim()); } diff --git a/gtsam/nonlinear/NonlinearFactorGraph.h b/gtsam/nonlinear/NonlinearFactorGraph.h index 0e17700d0..989f493d3 100644 --- a/gtsam/nonlinear/NonlinearFactorGraph.h +++ b/gtsam/nonlinear/NonlinearFactorGraph.h @@ -11,7 +11,7 @@ /** * @file NonlinearFactorGraph.h - * @brief Factor Graph Constsiting of non-linear factors + * @brief Factor Graph consisting of non-linear factors * @author Frank Dellaert * @author Carlos Nieto * @author Christian Potthast @@ -111,11 +111,21 @@ namespace gtsam { /** Test equality */ bool equals(const NonlinearFactorGraph& other, double tol = 1e-9) const; - /** Write the graph in GraphViz format for visualization */ + /// Write the graph in GraphViz format for visualization void saveGraph(std::ostream& stm, const Values& values = Values(), const GraphvizFormatting& graphvizFormatting = GraphvizFormatting(), const KeyFormatter& keyFormatter = DefaultKeyFormatter) const; + /** + * Write the graph in GraphViz format to file for visualization. + * + * This is a wrapper friendly version since wrapped languages don't have + * access to C++ streams. + */ + void saveGraph(const std::string& file, const Values& values = Values(), + const GraphvizFormatting& graphvizFormatting = GraphvizFormatting(), + const KeyFormatter& keyFormatter = DefaultKeyFormatter) const; + /** unnormalized error, \f$ 0.5 \sum_i (h_i(X_i)-z)^2/\sigma^2 \f$ in the most common case */ double error(const Values& values) const; diff --git a/gtsam/nonlinear/NonlinearOptimizer.cpp b/gtsam/nonlinear/NonlinearOptimizer.cpp index fd9961742..0d7e9e17f 100644 --- a/gtsam/nonlinear/NonlinearOptimizer.cpp +++ b/gtsam/nonlinear/NonlinearOptimizer.cpp @@ -97,7 +97,11 @@ void NonlinearOptimizer::defaultOptimize() { // Update newError for either printouts or conditional-end checks: newError = error(); - + + // User hook: + if (params.iterationHook) + params.iterationHook(iterations(), currentError, newError); + // Maybe show output if (params.verbosity >= NonlinearOptimizerParams::VALUES) values().print("newValues"); diff --git a/gtsam/nonlinear/NonlinearOptimizer.h b/gtsam/nonlinear/NonlinearOptimizer.h index 9935f44ce..6fe369dd3 100644 --- a/gtsam/nonlinear/NonlinearOptimizer.h +++ b/gtsam/nonlinear/NonlinearOptimizer.h @@ -81,7 +81,7 @@ protected: public: /** A shared pointer to this class */ - typedef boost::shared_ptr shared_ptr; + using shared_ptr = boost::shared_ptr; /// @name Standard interface /// @{ diff --git a/gtsam/nonlinear/NonlinearOptimizerParams.h b/gtsam/nonlinear/NonlinearOptimizerParams.h index 65fdd1c92..218230421 100644 --- a/gtsam/nonlinear/NonlinearOptimizerParams.h +++ b/gtsam/nonlinear/NonlinearOptimizerParams.h @@ -38,21 +38,12 @@ public: SILENT, TERMINATION, ERROR, VALUES, DELTA, LINEAR }; - size_t maxIterations; ///< The maximum iterations to stop iterating (default 100) - double relativeErrorTol; ///< The maximum relative error decrease to stop iterating (default 1e-5) - double absoluteErrorTol; ///< The maximum absolute error decrease to stop iterating (default 1e-5) - double errorTol; ///< The maximum total error to stop iterating (default 0.0) - Verbosity verbosity; ///< The printing verbosity during optimization (default SILENT) - Ordering::OrderingType orderingType; ///< The method of ordering use during variable elimination (default COLAMD) - - NonlinearOptimizerParams() : - maxIterations(100), relativeErrorTol(1e-5), absoluteErrorTol(1e-5), errorTol( - 0.0), verbosity(SILENT), orderingType(Ordering::COLAMD), - linearSolverType(MULTIFRONTAL_CHOLESKY) {} - - virtual ~NonlinearOptimizerParams() { - } - virtual void print(const std::string& str = "") const; + size_t maxIterations = 100; ///< The maximum iterations to stop iterating (default 100) + double relativeErrorTol = 1e-5; ///< The maximum relative error decrease to stop iterating (default 1e-5) + double absoluteErrorTol = 1e-5; ///< The maximum absolute error decrease to stop iterating (default 1e-5) + double errorTol = 0.0; ///< The maximum total error to stop iterating (default 0.0) + Verbosity verbosity = SILENT; ///< The printing verbosity during optimization (default SILENT) + Ordering::OrderingType orderingType = Ordering::COLAMD; ///< The method of ordering use during variable elimination (default COLAMD) size_t getMaxIterations() const { return maxIterations; } double getRelativeErrorTol() const { return relativeErrorTol; } @@ -71,6 +62,37 @@ public: static Verbosity verbosityTranslator(const std::string &s) ; static std::string verbosityTranslator(Verbosity value) ; + /** Type for an optional user-provided hook to be called after each + * internal optimizer iteration. See iterationHook below. */ + using IterationHook = std::function< + void(size_t /*iteration*/, double/*errorBefore*/, double/*errorAfter*/)>; + + /** Optional user-provided iteration hook to be called after each + * optimization iteration (Default: none). + * Note that `IterationHook` is defined as a std::function<> with this + * signature: + * \code + * void(size_t iteration, double errorBefore, double errorAfter) + * \endcode + * which allows binding by means of a reference to a regular function: + * \code + * void foo(size_t iteration, double errorBefore, double errorAfter); + * // ... + * lmOpts.iterationHook = &foo; + * \endcode + * or to a C++11 lambda (preferred if you need to capture additional + * context variables, such that the optimizer object itself, the factor graph, + * etc.): + * \code + * lmOpts.iterationHook = [&](size_t iter, double oldError, double newError) + * { + * // ... + * }; + * \endcode + * or to the result of a properly-formed `std::bind` call. + */ + IterationHook iterationHook; + /** See NonlinearOptimizerParams::linearSolverType */ enum LinearSolverType { MULTIFRONTAL_CHOLESKY, @@ -81,10 +103,27 @@ public: CHOLMOD, /* Experimental Flag */ }; - LinearSolverType linearSolverType; ///< The type of linear solver to use in the nonlinear optimizer + LinearSolverType linearSolverType = MULTIFRONTAL_CHOLESKY; ///< The type of linear solver to use in the nonlinear optimizer boost::optional ordering; ///< The optional variable elimination ordering, or empty to use COLAMD (default: empty) IterativeOptimizationParameters::shared_ptr iterativeParams; ///< The container for iterativeOptimization parameters. used in CG Solvers. + NonlinearOptimizerParams() = default; + virtual ~NonlinearOptimizerParams() { + } + + virtual void print(const std::string& str = "") const; + + bool equals(const NonlinearOptimizerParams& other, double tol = 1e-9) const { + return maxIterations == other.getMaxIterations() + && std::abs(relativeErrorTol - other.getRelativeErrorTol()) <= tol + && std::abs(absoluteErrorTol - other.getAbsoluteErrorTol()) <= tol + && std::abs(errorTol - other.getErrorTol()) <= tol + && verbosityTranslator(verbosity) == other.getVerbosity(); + // && orderingType.equals(other.getOrderingType()_; + // && linearSolverType == other.getLinearSolverType(); + // TODO: check ordering, iterativeParams, and iterationsHook + } + inline bool isMultifrontal() const { return (linearSolverType == MULTIFRONTAL_CHOLESKY) || (linearSolverType == MULTIFRONTAL_QR); diff --git a/gtsam/nonlinear/Values-inl.h b/gtsam/nonlinear/Values-inl.h index d0f8a4790..19813adba 100644 --- a/gtsam/nonlinear/Values-inl.h +++ b/gtsam/nonlinear/Values-inl.h @@ -217,7 +217,7 @@ namespace gtsam { /** Constructor from a Filtered view copies out all values */ template Values::Values(const Values::Filtered& view) { - for(const typename Filtered::KeyValuePair& key_value: view) { + for(const auto key_value: view) { Key key = key_value.key; insert(key, static_cast(key_value.value)); } @@ -226,7 +226,7 @@ namespace gtsam { /* ************************************************************************* */ template Values::Values(const Values::ConstFiltered& view) { - for(const typename ConstFiltered::KeyValuePair& key_value: view) { + for(const auto key_value: view) { Key key = key_value.key; insert(key, static_cast(key_value.value)); } @@ -338,19 +338,18 @@ namespace gtsam { } // internal /* ************************************************************************* */ - template - ValueType Values::at(Key j) const { + template + const ValueType Values::at(Key j) const { // Find the item KeyValueMap::const_iterator item = values_.find(j); // Throw exception if it does not exist - if(item == values_.end()) - throw ValuesKeyDoesNotExist("at", j); + if (item == values_.end()) throw ValuesKeyDoesNotExist("at", j); - // Check the type and throw exception if incorrect - // h() split in two lines to avoid internal compiler error (MSVC2017) - auto h = internal::handle(); - return h(j,item->second); + // Check the type and throw exception if incorrect + // h() split in two lines to avoid internal compiler error (MSVC2017) + auto h = internal::handle(); + return h(j, item->second); } /* ************************************************************************* */ diff --git a/gtsam/nonlinear/Values.cpp b/gtsam/nonlinear/Values.cpp index b672031ca..89a4206ee 100644 --- a/gtsam/nonlinear/Values.cpp +++ b/gtsam/nonlinear/Values.cpp @@ -206,7 +206,7 @@ namespace gtsam { /* ************************************************************************* */ size_t Values::dim() const { size_t result = 0; - for(const ConstKeyValuePair& key_value: *this) { + for(const auto key_value: *this) { result += key_value.value.dim(); } return result; @@ -215,7 +215,7 @@ namespace gtsam { /* ************************************************************************* */ VectorValues Values::zeroVectors() const { VectorValues result; - for(const ConstKeyValuePair& key_value: *this) + for(const auto key_value: *this) result.insert(key_value.key, Vector::Zero(key_value.value.dim())); return result; } diff --git a/gtsam/nonlinear/Values.h b/gtsam/nonlinear/Values.h index b49188b68..120c8839c 100644 --- a/gtsam/nonlinear/Values.h +++ b/gtsam/nonlinear/Values.h @@ -187,8 +187,8 @@ namespace gtsam { * Dynamic matrices/vectors can be retrieved as fixed-size, but not vice-versa. * @return The stored value */ - template - ValueType at(Key j) const; + template + const ValueType at(Key j) const; /// version for double double atDouble(size_t key) const { return at(key);} diff --git a/gtsam/nonlinear/internal/LevenbergMarquardtState.h b/gtsam/nonlinear/internal/LevenbergMarquardtState.h index 8ab2e7466..cee839540 100644 --- a/gtsam/nonlinear/internal/LevenbergMarquardtState.h +++ b/gtsam/nonlinear/internal/LevenbergMarquardtState.h @@ -126,7 +126,7 @@ struct LevenbergMarquardtState : public NonlinearOptimizerState { noiseModelCache.resize(0); // for each of the variables, add a prior damped.reserve(damped.size() + values.size()); - for (const auto& key_value : values) { + for (const auto key_value : values) { const Key key = key_value.key; const size_t dim = key_value.value.dim(); const CachedModel* item = getCachedModel(dim); diff --git a/gtsam/nonlinear/tests/testFunctorizedFactor.cpp b/gtsam/nonlinear/tests/testFunctorizedFactor.cpp index cb91320cf..b0ec5e722 100644 --- a/gtsam/nonlinear/tests/testFunctorizedFactor.cpp +++ b/gtsam/nonlinear/tests/testFunctorizedFactor.cpp @@ -27,8 +27,15 @@ using namespace std; using namespace gtsam; +// Key for FunctorizedFactor Key key = Symbol('X', 0); + +// Keys for FunctorizedFactor2 +Key keyA = Symbol('A', 0); +Key keyx = Symbol('x', 0); + auto model = noiseModel::Isotropic::Sigma(9, 1); +auto model2 = noiseModel::Isotropic::Sigma(3, 1); /// Functor that takes a matrix and multiplies every element by m class MultiplyFunctor { @@ -44,6 +51,21 @@ class MultiplyFunctor { } }; +/// Functor that performs Ax where A is a matrix and x is a vector. +class ProjectionFunctor { + public: + Vector operator()(const Matrix &A, const Vector &x, + OptionalJacobian<-1, -1> H1 = boost::none, + OptionalJacobian<-1, -1> H2 = boost::none) const { + if (H1) { + H1->resize(x.size(), A.size()); + *H1 << I_3x3, I_3x3, I_3x3; + } + if (H2) *H2 = A; + return A * x; + } +}; + /* ************************************************************************* */ // Test identity operation for FunctorizedFactor. TEST(FunctorizedFactor, Identity) { @@ -88,7 +110,7 @@ TEST(FunctorizedFactor, Equality) { EXPECT(factor1.equals(factor2)); } -/* *************************************************************************** */ +/* ************************************************************************* */ // Test Jacobians of FunctorizedFactor. TEST(FunctorizedFactor, Jacobians) { Matrix X = Matrix::Identity(3, 3); @@ -168,6 +190,83 @@ TEST(FunctorizedFactor, Lambda) { EXPECT(assert_equal(Vector::Zero(9), error, 1e-9)); } +/* ************************************************************************* */ +// Test identity operation for FunctorizedFactor2. +TEST(FunctorizedFactor, Identity2) { + // x = Ax since A is I_3x3 + Matrix A = Matrix::Identity(3, 3); + Vector x = Vector::Ones(3); + + auto functor = ProjectionFunctor(); + auto factor = + MakeFunctorizedFactor2(keyA, keyx, x, model2, functor); + + Vector error = factor.evaluateError(A, x); + + EXPECT(assert_equal(Vector::Zero(3), error, 1e-9)); +} + +/* ************************************************************************* */ +// Test Jacobians of FunctorizedFactor2. +TEST(FunctorizedFactor, Jacobians2) { + Matrix A = Matrix::Identity(3, 3); + Vector x = Vector::Ones(3); + Matrix actualH1, actualH2; + + auto factor = MakeFunctorizedFactor2(keyA, keyx, x, model2, + ProjectionFunctor()); + + Values values; + values.insert(keyA, A); + values.insert(keyx, x); + + // Check Jacobians + EXPECT_CORRECT_FACTOR_JACOBIANS(factor, values, 1e-7, 1e-5); +} + +/* ************************************************************************* */ +// Test FunctorizedFactor2 using a std::function type. +TEST(FunctorizedFactor, Functional2) { + Matrix A = Matrix::Identity(3, 3); + Vector3 x(1, 2, 3); + Vector measurement = A * x; + + std::function, + boost::optional)> + functional = ProjectionFunctor(); + auto factor = MakeFunctorizedFactor2(keyA, keyx, measurement, + model2, functional); + + Vector error = factor.evaluateError(A, x); + + EXPECT(assert_equal(Vector::Zero(3), error, 1e-9)); +} + +/* ************************************************************************* */ +// Test FunctorizedFactor2 with a lambda function. +TEST(FunctorizedFactor, Lambda2) { + Matrix A = Matrix::Identity(3, 3); + Vector3 x = Vector3(1, 2, 3); + Matrix measurement = A * x; + + auto lambda = [](const Matrix &A, const Vector &x, + OptionalJacobian<-1, -1> H1 = boost::none, + OptionalJacobian<-1, -1> H2 = boost::none) { + if (H1) { + H1->resize(x.size(), A.size()); + *H1 << I_3x3, I_3x3, I_3x3; + } + if (H2) *H2 = A; + return A * x; + }; + // FunctorizedFactor factor(key, measurement, model, lambda); + auto factor = MakeFunctorizedFactor2(keyA, keyx, measurement, model2, lambda); + + Vector error = factor.evaluateError(A, x); + + EXPECT(assert_equal(Vector::Zero(3), error, 1e-9)); +} + /* ************************************************************************* */ int main() { TestResult tr; diff --git a/gtsam/nonlinear/tests/testValues.cpp b/gtsam/nonlinear/tests/testValues.cpp index 88cfb666f..aacceb276 100644 --- a/gtsam/nonlinear/tests/testValues.cpp +++ b/gtsam/nonlinear/tests/testValues.cpp @@ -175,10 +175,11 @@ TEST(Values, basic_functions) { Values values; const Values& values_c = values; - values.insert(2, Vector3()); - values.insert(4, Vector3()); - values.insert(6, Matrix23()); - values.insert(8, Matrix23()); + Matrix23 M1 = Matrix23::Zero(), M2 = Matrix23::Zero(); + values.insert(2, Vector3(0, 0, 0)); + values.insert(4, Vector3(0, 0, 0)); + values.insert(6, M1); + values.insert(8, M2); // find EXPECT_LONGS_EQUAL(4, values.find(4)->key); @@ -335,7 +336,7 @@ TEST(Values, filter) { int i = 0; Values::Filtered filtered = values.filter(boost::bind(std::greater_equal(), _1, 2)); EXPECT_LONGS_EQUAL(2, (long)filtered.size()); - for(const Values::Filtered<>::KeyValuePair& key_value: filtered) { + for(const auto key_value: filtered) { if(i == 0) { LONGS_EQUAL(2, (long)key_value.key); try {key_value.value.cast();} catch (const std::bad_cast& e) { FAIL("can't cast Value to Pose2");} @@ -370,7 +371,7 @@ TEST(Values, filter) { i = 0; Values::ConstFiltered pose_filtered = values.filter(); EXPECT_LONGS_EQUAL(2, (long)pose_filtered.size()); - for(const Values::ConstFiltered::KeyValuePair& key_value: pose_filtered) { + for(const auto key_value: pose_filtered) { if(i == 0) { EXPECT_LONGS_EQUAL(1, (long)key_value.key); EXPECT(assert_equal(pose1, key_value.value)); @@ -408,7 +409,7 @@ TEST(Values, Symbol_filter) { values.insert(Symbol('y', 3), pose3); int i = 0; - for(const Values::Filtered::KeyValuePair& key_value: values.filter(Symbol::ChrTest('y'))) { + for(const auto key_value: values.filter(Symbol::ChrTest('y'))) { if(i == 0) { LONGS_EQUAL(Symbol('y', 1), (long)key_value.key); EXPECT(assert_equal(pose1, key_value.value.cast())); diff --git a/gtsam/sfm/BinaryMeasurement.h b/gtsam/sfm/BinaryMeasurement.h index c525c1b9e..99e553f7a 100644 --- a/gtsam/sfm/BinaryMeasurement.h +++ b/gtsam/sfm/BinaryMeasurement.h @@ -45,10 +45,11 @@ private: T measured_; ///< The measurement SharedNoiseModel noiseModel_; ///< Noise model -public: + public: BinaryMeasurement(Key key1, Key key2, const T &measured, const SharedNoiseModel &model = nullptr) - : Factor(std::vector({key1, key2})), measured_(measured), + : Factor(std::vector({key1, key2})), + measured_(measured), noiseModel_(model) {} /// @name Standard Interface @@ -80,4 +81,4 @@ public: } /// @} }; -} // namespace gtsam \ No newline at end of file +} // namespace gtsam diff --git a/gtsam/sfm/MFAS.cpp b/gtsam/sfm/MFAS.cpp index 4cd983ecd..913752d8a 100644 --- a/gtsam/sfm/MFAS.cpp +++ b/gtsam/sfm/MFAS.cpp @@ -121,8 +121,8 @@ MFAS::MFAS(const TranslationEdges& relativeTranslations, } } -vector MFAS::computeOrdering() const { - vector ordering; // Nodes in MFAS order (result). +KeyVector MFAS::computeOrdering() const { + KeyVector ordering; // Nodes in MFAS order (result). // A graph is an unordered map from keys to nodes. Each node contains a list // of its adjacent nodes. Create the graph from the edgeWeights. @@ -140,7 +140,7 @@ vector MFAS::computeOrdering() const { map MFAS::computeOutlierWeights() const { // Find the ordering. - vector ordering = computeOrdering(); + KeyVector ordering = computeOrdering(); // Create a map from the node key to its position in the ordering. This makes // it easier to lookup positions of different nodes. diff --git a/gtsam/sfm/MFAS.h b/gtsam/sfm/MFAS.h index 3b01122a9..decfbed0f 100644 --- a/gtsam/sfm/MFAS.h +++ b/gtsam/sfm/MFAS.h @@ -84,7 +84,7 @@ class MFAS { * @brief Computes the 1D MFAS ordering of nodes in the graph * @return orderedNodes: vector of nodes in the obtained order */ - std::vector computeOrdering() const; + KeyVector computeOrdering() const; /** * @brief Computes the outlier weights of the graph. We define the outlier diff --git a/gtsam/sfm/ShonanAveraging.cpp b/gtsam/sfm/ShonanAveraging.cpp index df2d72c28..53f8f6b6c 100644 --- a/gtsam/sfm/ShonanAveraging.cpp +++ b/gtsam/sfm/ShonanAveraging.cpp @@ -17,6 +17,7 @@ */ #include +#include #include #include #include @@ -53,7 +54,9 @@ ShonanAveragingParameters::ShonanAveragingParameters( optimalityThreshold(optimalityThreshold), alpha(alpha), beta(beta), - gamma(gamma) { + gamma(gamma), + useHuber(false), + certifyOptimality(true) { // By default, we will do conjugate gradient lm.linearSolverType = LevenbergMarquardtParams::Iterative; @@ -140,25 +143,23 @@ template NonlinearFactorGraph ShonanAveraging::buildGraphAt(size_t p) const { NonlinearFactorGraph graph; auto G = boost::make_shared(SO<-1>::VectorizedGenerators(p)); + for (const auto &measurement : measurements_) { const auto &keys = measurement.keys(); const auto &Rij = measurement.measured(); const auto &model = measurement.noiseModel(); graph.emplace_shared>(keys[0], keys[1], Rij, p, model, G); } - // Possibly add Karcher prior if (parameters_.beta > 0) { const size_t dim = SOn::Dimension(p); graph.emplace_shared>(graph.keys(), dim); } - // Possibly add gauge factors - they are probably useless as gradient is zero if (parameters_.gamma > 0 && p > d + 1) { for (auto key : graph.keys()) graph.emplace_shared(key, p, d, parameters_.gamma); } - return graph; } @@ -186,7 +187,6 @@ ShonanAveraging::createOptimizerAt(size_t p, const Values &initial) const { graph.emplace_shared>(i, SOn::Lift(p, value.matrix()), model); } - // Optimize return boost::make_shared(graph, initial, parameters_.lm); @@ -334,15 +334,33 @@ double ShonanAveraging::cost(const Values &values) const { /* ************************************************************************* */ // Get kappa from noise model -template -static double Kappa(const BinaryMeasurement &measurement) { +template +static double Kappa(const BinaryMeasurement &measurement, + const ShonanAveragingParameters ¶meters) { const auto &isotropic = boost::dynamic_pointer_cast( measurement.noiseModel()); - if (!isotropic) { - throw std::invalid_argument( - "Shonan averaging noise models must be isotropic."); + double sigma; + if (isotropic) { + sigma = isotropic->sigma(); + } else { + const auto &robust = boost::dynamic_pointer_cast( + measurement.noiseModel()); + // Check if noise model is robust + if (robust) { + // If robust, check if optimality certificate is expected + if (parameters.getCertifyOptimality()) { + throw std::invalid_argument( + "Certification of optimality does not work with robust cost."); + } else { + // Optimality certificate not required, so setting default sigma + sigma = 1; + } + } else { + throw std::invalid_argument( + "Shonan averaging noise models must be isotropic (but robust losses " + "are allowed)."); + } } - const double sigma = isotropic->sigma(); return 1.0 / (sigma * sigma); } @@ -362,7 +380,7 @@ Sparse ShonanAveraging::buildD() const { const auto &keys = measurement.keys(); // Get kappa from noise model - double kappa = Kappa(measurement); + double kappa = Kappa(measurement, parameters_); const size_t di = d * keys[0], dj = d * keys[1]; for (size_t k = 0; k < d; k++) { @@ -400,7 +418,7 @@ Sparse ShonanAveraging::buildQ() const { const auto Rij = measurement.measured().matrix(); // Get kappa from noise model - double kappa = Kappa(measurement); + double kappa = Kappa(measurement, parameters_); const size_t di = d * keys[0], dj = d * keys[1]; for (size_t r = 0; r < d; r++) { @@ -470,8 +488,88 @@ Sparse ShonanAveraging::computeA(const Values &values) const { return Lambda - Q_; } +/* ************************************************************************* */ +template +Sparse ShonanAveraging::computeA(const Matrix &S) const { + auto Lambda = computeLambda(S); + return Lambda - Q_; +} + +/* ************************************************************************* */ +// Perturb the initial initialVector by adding a spherically-uniformly +// distributed random vector with 0.03*||initialVector||_2 magnitude to +// initialVector +// ref : Part III. C, Rosen, D. and Carlone, L., 2017, September. Computational +// enhancements for certifiably correct SLAM. In Proceedings of the +// International Conference on Intelligent Robots and Systems. +static Vector perturb(const Vector &initialVector) { + // generate a 0.03*||x_0||_2 as stated in David's paper + int n = initialVector.rows(); + Vector disturb = Vector::Random(n); + disturb.normalize(); + + double magnitude = initialVector.norm(); + Vector perturbedVector = initialVector + 0.03 * magnitude * disturb; + perturbedVector.normalize(); + return perturbedVector; +} + /* ************************************************************************* */ /// MINIMUM EIGENVALUE COMPUTATIONS +// Alg.6 from paper Distributed Certifiably Correct Pose-Graph Optimization, +// it takes in the certificate matrix A as input, the maxIterations and the +// minEigenvalueNonnegativityTolerance is set to 1000 and 10e-4 ad default, +// there are two parts +// in this algorithm: +// (1) compute the maximum eigenpair (\lamda_dom, \vect{v}_dom) of A by power +// method. if \lamda_dom is less than zero, then return the eigenpair. (2) +// compute the maximum eigenpair (\theta, \vect{v}) of C = \lamda_dom * I - A by +// accelerated power method. Then return (\lamda_dom - \theta, \vect{v}). +static bool PowerMinimumEigenValue( + const Sparse &A, const Matrix &S, double &minEigenValue, + Vector *minEigenVector = 0, size_t *numIterations = 0, + size_t maxIterations = 1000, + double minEigenvalueNonnegativityTolerance = 10e-4) { + + // a. Compute dominant eigenpair of S using power method + PowerMethod pmOperator(A); + + const bool pmConverged = pmOperator.compute( + maxIterations, 1e-5); + + // Check convergence and bail out if necessary + if (!pmConverged) return false; + + const double pmEigenValue = pmOperator.eigenvalue(); + + if (pmEigenValue < 0) { + // The largest-magnitude eigenvalue is negative, and therefore also the + // minimum eigenvalue, so just return this solution + minEigenValue = pmEigenValue; + if (minEigenVector) { + *minEigenVector = pmOperator.eigenvector(); + minEigenVector->normalize(); // Ensure that this is a unit vector + } + return true; + } + + const Sparse C = pmEigenValue * Matrix::Identity(A.rows(), A.cols()) - A; + const boost::optional initial = perturb(S.row(0)); + AcceleratedPowerMethod apmShiftedOperator(C, initial); + + const bool minConverged = apmShiftedOperator.compute( + maxIterations, minEigenvalueNonnegativityTolerance / pmEigenValue); + + if (!minConverged) return false; + + minEigenValue = pmEigenValue - apmShiftedOperator.eigenvalue(); + if (minEigenVector) { + *minEigenVector = apmShiftedOperator.eigenvector(); + minEigenVector->normalize(); // Ensure that this is a unit vector + } + if (numIterations) *numIterations = apmShiftedOperator.nrIterations(); + return true; +} /** This is a lightweight struct used in conjunction with Spectra to compute * the minimum eigenvalue and eigenvector of a sparse matrix A; it has a single @@ -617,13 +715,6 @@ static bool SparseMinimumEigenValue( return true; } -/* ************************************************************************* */ -template -Sparse ShonanAveraging::computeA(const Matrix &S) const { - auto Lambda = computeLambda(S); - return Lambda - Q_; -} - /* ************************************************************************* */ template double ShonanAveraging::computeMinEigenValue(const Values &values, @@ -641,6 +732,23 @@ double ShonanAveraging::computeMinEigenValue(const Values &values, return minEigenValue; } +/* ************************************************************************* */ +template +double ShonanAveraging::computeMinEigenValueAP(const Values &values, + Vector *minEigenVector) const { + assert(values.size() == nrUnknowns()); + const Matrix S = StiefelElementMatrix(values); + auto A = computeA(S); + + double minEigenValue = 0; + bool success = PowerMinimumEigenValue(A, S, minEigenValue, minEigenVector); + if (!success) { + throw std::runtime_error( + "PowerMinimumEigenValue failed to compute minimum eigenvalue."); + } + return minEigenValue; +} + /* ************************************************************************* */ template std::pair ShonanAveraging::computeMinEigenVector( @@ -793,21 +901,30 @@ std::pair ShonanAveraging::run(const Values &initialEstimate, for (size_t p = pMin; p <= pMax; p++) { // Optimize until convergence at this level Qstar = tryOptimizingAt(p, initialSOp); - - // Check certificate of global optimzality - Vector minEigenVector; - double minEigenValue = computeMinEigenValue(Qstar, &minEigenVector); - if (minEigenValue > parameters_.optimalityThreshold) { - // If at global optimum, round and return solution + if (parameters_.getUseHuber() || !parameters_.getCertifyOptimality()) { + // in this case, there is no optimality certification + if (pMin != pMax) { + throw std::runtime_error( + "When using robust norm, Shonan only tests a single rank. Set pMin = pMax"); + } const Values SO3Values = roundSolution(Qstar); - return std::make_pair(SO3Values, minEigenValue); - } + return std::make_pair(SO3Values, 0); + } else { + // Check certificate of global optimality + Vector minEigenVector; + double minEigenValue = computeMinEigenValue(Qstar, &minEigenVector); + if (minEigenValue > parameters_.optimalityThreshold) { + // If at global optimum, round and return solution + const Values SO3Values = roundSolution(Qstar); + return std::make_pair(SO3Values, minEigenValue); + } - // Not at global optimimum yet, so check whether we will go to next level - if (p != pMax) { - // Calculate initial estimate for next level by following minEigenVector - initialSOp = - initializeWithDescent(p + 1, Qstar, minEigenVector, minEigenValue); + // Not at global optimimum yet, so check whether we will go to next level + if (p != pMax) { + // Calculate initial estimate for next level by following minEigenVector + initialSOp = + initializeWithDescent(p + 1, Qstar, minEigenVector, minEigenValue); + } } } throw std::runtime_error("Shonan::run did not converge for given pMax"); @@ -819,9 +936,13 @@ template class ShonanAveraging<2>; ShonanAveraging2::ShonanAveraging2(const Measurements &measurements, const Parameters ¶meters) - : ShonanAveraging<2>(measurements, parameters) {} + : ShonanAveraging<2>(maybeRobust(measurements, parameters.getUseHuber()), + parameters) {} + ShonanAveraging2::ShonanAveraging2(string g2oFile, const Parameters ¶meters) - : ShonanAveraging<2>(parseMeasurements(g2oFile), parameters) {} + : ShonanAveraging<2>(maybeRobust(parseMeasurements(g2oFile), + parameters.getUseHuber()), + parameters) {} /* ************************************************************************* */ // Explicit instantiation for d=3 @@ -829,10 +950,13 @@ template class ShonanAveraging<3>; ShonanAveraging3::ShonanAveraging3(const Measurements &measurements, const Parameters ¶meters) - : ShonanAveraging<3>(measurements, parameters) {} + : ShonanAveraging<3>(maybeRobust(measurements, parameters.getUseHuber()), + parameters) {} ShonanAveraging3::ShonanAveraging3(string g2oFile, const Parameters ¶meters) - : ShonanAveraging<3>(parseMeasurements(g2oFile), parameters) {} + : ShonanAveraging<3>(maybeRobust(parseMeasurements(g2oFile), + parameters.getUseHuber()), + parameters) {} // TODO(frank): Deprecate after we land pybind wrapper @@ -847,9 +971,9 @@ static BinaryMeasurement convert( "parseMeasurements can only convert Pose3 measurements " "with Gaussian noise models."); const Matrix6 M = gaussian->covariance(); - return BinaryMeasurement( - f->key1(), f->key2(), f->measured().rotation(), - noiseModel::Gaussian::Covariance(M.block<3, 3>(3, 3), true)); + auto model = noiseModel::Gaussian::Covariance(M.block<3, 3>(3, 3)); + return BinaryMeasurement(f->key1(), f->key2(), f->measured().rotation(), + model); } static ShonanAveraging3::Measurements extractRot3Measurements( @@ -862,7 +986,9 @@ static ShonanAveraging3::Measurements extractRot3Measurements( ShonanAveraging3::ShonanAveraging3(const BetweenFactorPose3s &factors, const Parameters ¶meters) - : ShonanAveraging<3>(extractRot3Measurements(factors), parameters) {} + : ShonanAveraging<3>(maybeRobust(extractRot3Measurements(factors), + parameters.getUseHuber()), + parameters) {} /* ************************************************************************* */ } // namespace gtsam diff --git a/gtsam/sfm/ShonanAveraging.h b/gtsam/sfm/ShonanAveraging.h index edd9f33a2..0a8bdc8c1 100644 --- a/gtsam/sfm/ShonanAveraging.h +++ b/gtsam/sfm/ShonanAveraging.h @@ -26,6 +26,8 @@ #include #include #include +#include +#include #include #include @@ -46,13 +48,17 @@ struct GTSAM_EXPORT ShonanAveragingParameters { using Rot = typename std::conditional::type; using Anchor = std::pair; - // Paremeters themselves: - LevenbergMarquardtParams lm; // LM parameters - double optimalityThreshold; // threshold used in checkOptimality - Anchor anchor; // pose to use as anchor if not Karcher - double alpha; // weight of anchor-based prior (default 0) - double beta; // weight of Karcher-based prior (default 1) - double gamma; // weight of gauge-fixing factors (default 0) + // Parameters themselves: + LevenbergMarquardtParams lm; ///< LM parameters + double optimalityThreshold; ///< threshold used in checkOptimality + Anchor anchor; ///< pose to use as anchor if not Karcher + double alpha; ///< weight of anchor-based prior (default 0) + double beta; ///< weight of Karcher-based prior (default 1) + double gamma; ///< weight of gauge-fixing factors (default 0) + /// if enabled, the Huber loss is used (default false) + bool useHuber; + /// if enabled solution optimality is certified (default true) + bool certifyOptimality; ShonanAveragingParameters(const LevenbergMarquardtParams &lm = LevenbergMarquardtParams::CeresDefaults(), @@ -67,16 +73,31 @@ struct GTSAM_EXPORT ShonanAveragingParameters { double getOptimalityThreshold() const { return optimalityThreshold; } void setAnchor(size_t index, const Rot &value) { anchor = {index, value}; } - std::pair getAnchor() { return anchor; } + std::pair getAnchor() const { return anchor; } void setAnchorWeight(double value) { alpha = value; } - double getAnchorWeight() { return alpha; } + double getAnchorWeight() const { return alpha; } void setKarcherWeight(double value) { beta = value; } - double getKarcherWeight() { return beta; } + double getKarcherWeight() const { return beta; } void setGaugesWeight(double value) { gamma = value; } - double getGaugesWeight() { return gamma; } + double getGaugesWeight() const { return gamma; } + + void setUseHuber(bool value) { useHuber = value; } + bool getUseHuber() const { return useHuber; } + + void setCertifyOptimality(bool value) { certifyOptimality = value; } + bool getCertifyOptimality() const { return certifyOptimality; } + + /// Print the parameters and flags used for rotation averaging. + void print() const { + std::cout << " ShonanAveragingParameters: " << std::endl; + std::cout << " alpha: " << alpha << std::endl; + std::cout << " beta: " << beta << std::endl; + std::cout << " gamma: " << gamma << std::endl; + std::cout << " useHuber: " << useHuber << std::endl; + } }; using ShonanAveragingParameters2 = ShonanAveragingParameters<2>; @@ -107,7 +128,6 @@ class GTSAM_EXPORT ShonanAveraging { using Rot = typename Parameters::Rot; // We store SO(d) BetweenFactors to get noise model - // TODO(frank): use BinaryMeasurement? using Measurements = std::vector>; private: @@ -151,6 +171,36 @@ class GTSAM_EXPORT ShonanAveraging { return measurements_[k]; } + /** + * Update factors to use robust Huber loss. + * + * @param measurements Vector of BinaryMeasurements. + * @param k Huber noise model threshold. + */ + Measurements makeNoiseModelRobust(const Measurements &measurements, + double k = 1.345) const { + Measurements robustMeasurements; + for (auto &measurement : measurements) { + auto model = measurement.noiseModel(); + const auto &robust = + boost::dynamic_pointer_cast(model); + + SharedNoiseModel robust_model; + // Check if the noise model is already robust + if (robust) { + robust_model = model; + } else { + // make robust + robust_model = noiseModel::Robust::Create( + noiseModel::mEstimator::Huber::Create(k), model); + } + BinaryMeasurement meas(measurement.key1(), measurement.key2(), + measurement.measured(), robust_model); + robustMeasurements.push_back(meas); + } + return robustMeasurements; + } + /// k^th measurement, as a Rot. const Rot &measured(size_t k) const { return measurements_[k].measured(); } @@ -202,6 +252,13 @@ class GTSAM_EXPORT ShonanAveraging { double computeMinEigenValue(const Values &values, Vector *minEigenVector = nullptr) const; + /** + * Compute minimum eigenvalue with accelerated power method. + * @param values: should be of type SOn + */ + double computeMinEigenValueAP(const Values &values, + Vector *minEigenVector = nullptr) const; + /// Project pxdN Stiefel manifold matrix S to Rot3^N Values roundSolutionS(const Matrix &S) const; @@ -345,24 +402,40 @@ class GTSAM_EXPORT ShonanAveraging { std::pair run(const Values &initialEstimate, size_t pMin = d, size_t pMax = 10) const; /// @} + + /** + * Helper function to convert measurements to robust noise model + * if flag is set. + * + * @tparam T the type of measurement, e.g. Rot3. + * @param measurements vector of BinaryMeasurements of type T. + * @param useRobustModel flag indicating whether use robust noise model + * instead. + */ + template + inline std::vector> maybeRobust( + const std::vector> &measurements, + bool useRobustModel = false) const { + return useRobustModel ? makeNoiseModelRobust(measurements) : measurements; + } }; // Subclasses for d=2 and d=3 that explicitly instantiate, as well as provide a // convenience interface with file access. -class ShonanAveraging2 : public ShonanAveraging<2> { +class GTSAM_EXPORT ShonanAveraging2 : public ShonanAveraging<2> { public: ShonanAveraging2(const Measurements &measurements, const Parameters ¶meters = Parameters()); - explicit ShonanAveraging2(string g2oFile, + explicit ShonanAveraging2(std::string g2oFile, const Parameters ¶meters = Parameters()); }; -class ShonanAveraging3 : public ShonanAveraging<3> { +class GTSAM_EXPORT ShonanAveraging3 : public ShonanAveraging<3> { public: ShonanAveraging3(const Measurements &measurements, const Parameters ¶meters = Parameters()); - explicit ShonanAveraging3(string g2oFile, + explicit ShonanAveraging3(std::string g2oFile, const Parameters ¶meters = Parameters()); // TODO(frank): Deprecate after we land pybind wrapper diff --git a/gtsam/sfm/TranslationRecovery.cpp b/gtsam/sfm/TranslationRecovery.cpp index 319129840..d4100b00a 100644 --- a/gtsam/sfm/TranslationRecovery.cpp +++ b/gtsam/sfm/TranslationRecovery.cpp @@ -11,13 +11,12 @@ /** * @file TranslationRecovery.cpp - * @author Frank Dellaert + * @author Frank Dellaert, Akshay Krishnan * @date March 2020 * @brief Source code for recovering translations when rotations are given */ -#include - +#include #include #include #include @@ -27,11 +26,45 @@ #include #include #include +#include #include +#include +#include + using namespace gtsam; using namespace std; +TranslationRecovery::TranslationRecovery( + const TranslationRecovery::TranslationEdges &relativeTranslations, + const LevenbergMarquardtParams &lmParams) + : params_(lmParams) { + // Some relative translations may be zero. We treat nodes that have a zero + // relativeTranslation as a single node. + + // A DSFMap is used to find sets of nodes that have a zero relative + // translation. Add the nodes in each edge to the DSFMap, and merge nodes that + // are connected by a zero relative translation. + DSFMap sameTranslationDSF; + for (const auto &edge : relativeTranslations) { + Key key1 = sameTranslationDSF.find(edge.key1()); + Key key2 = sameTranslationDSF.find(edge.key2()); + if (key1 != key2 && edge.measured().equals(Unit3(0.0, 0.0, 0.0))) { + sameTranslationDSF.merge(key1, key2); + } + } + // Use only those edges for which two keys have a distinct root in the DSFMap. + for (const auto &edge : relativeTranslations) { + Key key1 = sameTranslationDSF.find(edge.key1()); + Key key2 = sameTranslationDSF.find(edge.key2()); + if (key1 == key2) continue; + relativeTranslations_.emplace_back(key1, key2, edge.measured(), + edge.noiseModel()); + } + // Store the DSF map for post-processing results. + sameTranslationNodes_ = sameTranslationDSF.sets(); +} + NonlinearFactorGraph TranslationRecovery::buildGraph() const { NonlinearFactorGraph graph; @@ -44,13 +77,14 @@ NonlinearFactorGraph TranslationRecovery::buildGraph() const { return graph; } -void TranslationRecovery::addPrior(const double scale, - NonlinearFactorGraph *graph, - const SharedNoiseModel &priorNoiseModel) const { +void TranslationRecovery::addPrior( + const double scale, NonlinearFactorGraph *graph, + const SharedNoiseModel &priorNoiseModel) const { auto edge = relativeTranslations_.begin(); - graph->emplace_shared >(edge->key1(), Point3(0, 0, 0), priorNoiseModel); - graph->emplace_shared >(edge->key2(), scale * edge->measured().point3(), - edge->noiseModel()); + graph->emplace_shared >(edge->key1(), Point3(0, 0, 0), + priorNoiseModel); + graph->emplace_shared >( + edge->key2(), scale * edge->measured().point3(), edge->noiseModel()); } Values TranslationRecovery::initalizeRandomly() const { @@ -77,6 +111,19 @@ Values TranslationRecovery::run(const double scale) const { const Values initial = initalizeRandomly(); LevenbergMarquardtOptimizer lm(graph, initial, params_); Values result = lm.optimize(); + + // Nodes that were not optimized are stored in sameTranslationNodes_ as a map + // from a key that was optimized to keys that were not optimized. Iterate over + // map and add results for keys not optimized. + for (const auto &optimizedAndDuplicateKeys : sameTranslationNodes_) { + Key optimizedKey = optimizedAndDuplicateKeys.first; + std::set duplicateKeys = optimizedAndDuplicateKeys.second; + // Add the result for the duplicate key if it does not already exist. + for (const Key duplicateKey : duplicateKeys) { + if (result.exists(duplicateKey)) continue; + result.insert(duplicateKey, result.at(optimizedKey)); + } + } return result; } diff --git a/gtsam/sfm/TranslationRecovery.h b/gtsam/sfm/TranslationRecovery.h index d5538f91b..c99836853 100644 --- a/gtsam/sfm/TranslationRecovery.h +++ b/gtsam/sfm/TranslationRecovery.h @@ -16,14 +16,16 @@ * @brief Recovering translations in an epipolar graph when rotations are given. */ +#include +#include +#include +#include + #include #include #include #include -#include -#include - namespace gtsam { // Set up an optimization problem for the unknown translations Ti in the world @@ -52,23 +54,30 @@ class TranslationRecovery { using TranslationEdges = std::vector>; private: + // Translation directions between camera pairs. TranslationEdges relativeTranslations_; + + // Parameters used by the LM Optimizer. LevenbergMarquardtParams params_; + // Map from a key in the graph to a set of keys that share the same + // translation. + std::map> sameTranslationNodes_; + public: /** * @brief Construct a new Translation Recovery object * * @param relativeTranslations the relative translations, in world coordinate - * frames, vector of BinaryMeasurements of Unit3, where each key of a measurement - * is a point in 3D. + * frames, vector of BinaryMeasurements of Unit3, where each key of a + * measurement is a point in 3D. * @param lmParams (optional) gtsam::LavenbergMarquardtParams that can be * used to modify the parameters for the LM optimizer. By default, uses the - * default LM parameters. + * default LM parameters. */ - TranslationRecovery(const TranslationEdges &relativeTranslations, - const LevenbergMarquardtParams &lmParams = LevenbergMarquardtParams()) - : relativeTranslations_(relativeTranslations), params_(lmParams) {} + TranslationRecovery( + const TranslationEdges &relativeTranslations, + const LevenbergMarquardtParams &lmParams = LevenbergMarquardtParams()); /** * @brief Build the factor graph to do the optimization. @@ -108,8 +117,8 @@ class TranslationRecovery { * * @param poses SE(3) ground truth poses stored as Values * @param edges pairs (a,b) for which a measurement w_aZb will be generated. - * @return TranslationEdges vector of binary measurements where the keys are - * the cameras and the measurement is the simulated Unit3 translation + * @return TranslationEdges vector of binary measurements where the keys are + * the cameras and the measurement is the simulated Unit3 translation * direction between the cameras. */ static TranslationEdges SimulateMeasurements( diff --git a/gtsam/sfm/tests/testBinaryMeasurement.cpp b/gtsam/sfm/tests/testBinaryMeasurement.cpp index 3dd81c2c1..ae13e54c4 100644 --- a/gtsam/sfm/tests/testBinaryMeasurement.cpp +++ b/gtsam/sfm/tests/testBinaryMeasurement.cpp @@ -36,6 +36,7 @@ static SharedNoiseModel rot3_model(noiseModel::Isotropic::Sigma(3, 0.05)); const Unit3 unit3Measured(Vector3(1, 1, 1)); const Rot3 rot3Measured; +/* ************************************************************************* */ TEST(BinaryMeasurement, Unit3) { BinaryMeasurement unit3Measurement(kKey1, kKey2, unit3Measured, unit3_model); @@ -48,6 +49,7 @@ TEST(BinaryMeasurement, Unit3) { EXPECT(unit3Measurement.equals(unit3MeasurementCopy)); } +/* ************************************************************************* */ TEST(BinaryMeasurement, Rot3) { // testing the accessors BinaryMeasurement rot3Measurement(kKey1, kKey2, rot3Measured, @@ -62,6 +64,21 @@ TEST(BinaryMeasurement, Rot3) { EXPECT(rot3Measurement.equals(rot3MeasurementCopy)); } +/* ************************************************************************* */ +TEST(BinaryMeasurement, Rot3MakeRobust) { + auto huber_model = noiseModel::Robust::Create( + noiseModel::mEstimator::Huber::Create(1.345), rot3_model); + BinaryMeasurement rot3Measurement(kKey1, kKey2, rot3Measured, + huber_model); + + EXPECT_LONGS_EQUAL(rot3Measurement.key1(), kKey1); + EXPECT_LONGS_EQUAL(rot3Measurement.key2(), kKey2); + EXPECT(rot3Measurement.measured().equals(rot3Measured)); + const auto &robust = boost::dynamic_pointer_cast( + rot3Measurement.noiseModel()); + EXPECT(robust); +} + /* ************************************************************************* */ int main() { TestResult tr; diff --git a/gtsam/sfm/tests/testMFAS.cpp b/gtsam/sfm/tests/testMFAS.cpp index 362027d5d..a1f6dfa5f 100644 --- a/gtsam/sfm/tests/testMFAS.cpp +++ b/gtsam/sfm/tests/testMFAS.cpp @@ -25,7 +25,7 @@ using namespace gtsam; vector edges = {make_pair(3, 2), make_pair(0, 1), make_pair(3, 1), make_pair(1, 2), make_pair(0, 2), make_pair(3, 0)}; // nodes in the graph -vector nodes = {Key(0), Key(1), Key(2), Key(3)}; +KeyVector nodes = {Key(0), Key(1), Key(2), Key(3)}; // weights from projecting in direction-1 (bad direction, outlier accepted) vector weights1 = {2, 1.5, 0.5, 0.25, 1, 0.75}; // weights from projecting in direction-2 (good direction, outlier rejected) @@ -47,10 +47,10 @@ map getEdgeWeights(const vector &edges, TEST(MFAS, OrderingWeights2) { MFAS mfas_obj(getEdgeWeights(edges, weights2)); - vector ordered_nodes = mfas_obj.computeOrdering(); + KeyVector ordered_nodes = mfas_obj.computeOrdering(); // ground truth (expected) ordering in this example - vector gt_ordered_nodes = {0, 1, 3, 2}; + KeyVector gt_ordered_nodes = {0, 1, 3, 2}; // check if the expected ordering is obtained for (size_t i = 0; i < ordered_nodes.size(); i++) { @@ -77,10 +77,10 @@ TEST(MFAS, OrderingWeights2) { TEST(MFAS, OrderingWeights1) { MFAS mfas_obj(getEdgeWeights(edges, weights1)); - vector ordered_nodes = mfas_obj.computeOrdering(); + KeyVector ordered_nodes = mfas_obj.computeOrdering(); // "ground truth" expected ordering in this example - vector gt_ordered_nodes = {3, 0, 1, 2}; + KeyVector gt_ordered_nodes = {3, 0, 1, 2}; // check if the expected ordering is obtained for (size_t i = 0; i < ordered_nodes.size(); i++) { diff --git a/gtsam/sfm/tests/testShonanAveraging.cpp b/gtsam/sfm/tests/testShonanAveraging.cpp index 1200c8ebb..556289d22 100644 --- a/gtsam/sfm/tests/testShonanAveraging.cpp +++ b/gtsam/sfm/tests/testShonanAveraging.cpp @@ -17,6 +17,7 @@ */ #include +#include #include #include #include @@ -91,6 +92,27 @@ TEST(ShonanAveraging3, checkOptimality) { EXPECT(!kShonan.checkOptimality(random)); } +/* ************************************************************************* */ +TEST(ShonanAveraging3, checkSubgraph) { + // Create parameter with solver set to SUBGRAPH + auto params = ShonanAveragingParameters3( + gtsam::LevenbergMarquardtParams::CeresDefaults(), "SUBGRAPH"); + ShonanAveraging3::Measurements measurements; + + // The toyExample.g2o has 5 vertices, from 0-4 + // The edges are: 1-2, 2-3, 3-4, 3-1, 1-4, 0-1, + // which can build a connected graph + auto subgraphShonan = fromExampleName("toyExample.g2o", params); + + // Create initial random estimation + Values initial; + initial = subgraphShonan.initializeRandomly(kRandomNumberGenerator); + + // Run Shonan with SUBGRAPH solver + auto result = subgraphShonan.run(initial, 3, 3); + EXPECT_DOUBLES_EQUAL(1e-11, subgraphShonan.cost(result.first), 1e-4); +} + /* ************************************************************************* */ TEST(ShonanAveraging3, tryOptimizingAt3) { const Values randomRotations = kShonan.initializeRandomly(kRandomNumberGenerator); @@ -166,9 +188,14 @@ TEST(ShonanAveraging3, CheckWithEigen) { for (int i = 1; i < lambdas.size(); i++) minEigenValue = min(lambdas(i), minEigenValue); + // Compute Eigenvalue with Accelerated Power method + double lambdaAP = kShonan.computeMinEigenValueAP(Qstar3); + // Actual check EXPECT_DOUBLES_EQUAL(0, lambda, 1e-11); EXPECT_DOUBLES_EQUAL(0, minEigenValue, 1e-11); + EXPECT_DOUBLES_EQUAL(0, lambdaAP, 1e-11); + // Construct test descent direction (as minEigenVector is not predictable // across platforms, being one from a basically flat 3d- subspace) @@ -321,6 +348,42 @@ TEST(ShonanAveraging2, noisyToyGraph) { EXPECT_DOUBLES_EQUAL(0, result.second, 1e-10); // certificate! } +/* ************************************************************************* */ +TEST(ShonanAveraging2, noisyToyGraphWithHuber) { + // Load 2D toy example + auto lmParams = LevenbergMarquardtParams::CeresDefaults(); + string g2oFile = findExampleDataFile("noisyToyGraph.txt"); + ShonanAveraging2::Parameters parameters(lmParams); + auto measurements = parseMeasurements(g2oFile); + parameters.setUseHuber(true); + parameters.setCertifyOptimality(false); + + string parameters_print = + " ShonanAveragingParameters: \n alpha: 0\n beta: 1\n gamma: 0\n " + "useHuber: 1\n"; + assert_print_equal(parameters_print, parameters); + + ShonanAveraging2 shonan(measurements, parameters); + EXPECT_LONGS_EQUAL(4, shonan.nrUnknowns()); + + // Check graph building + NonlinearFactorGraph graph = shonan.buildGraphAt(2); + EXPECT_LONGS_EQUAL(6, graph.size()); + + // test that each factor is actually robust + for (size_t i=0; i<=4; i++) { // note: last is the Gauge factor and is not robust + const auto &robust = boost::dynamic_pointer_cast( + boost::dynamic_pointer_cast(graph[i])->noiseModel()); + EXPECT(robust); // we expect the factors to be use a robust noise model (in particular, Huber) + } + + // test result + auto initial = shonan.initializeRandomly(kRandomNumberGenerator); + auto result = shonan.run(initial, 2,2); + EXPECT_DOUBLES_EQUAL(0.0008211, shonan.cost(result.first), 1e-6); + EXPECT_DOUBLES_EQUAL(0, result.second, 1e-10); // certificate! +} + /* ************************************************************************* */ // Test alpha/beta/gamma prior weighting. TEST(ShonanAveraging3, PriorWeights) { diff --git a/gtsam/slam/FrobeniusFactor.cpp b/gtsam/slam/FrobeniusFactor.cpp index 5697a0cd6..8c0baaf38 100644 --- a/gtsam/slam/FrobeniusFactor.cpp +++ b/gtsam/slam/FrobeniusFactor.cpp @@ -23,17 +23,25 @@ using namespace std; namespace gtsam { //****************************************************************************** -boost::shared_ptr +SharedNoiseModel ConvertNoiseModel(const SharedNoiseModel &model, size_t d, bool defaultToUnit) { double sigma = 1.0; + if (model != nullptr) { - auto sigmas = model->sigmas(); + const auto &robust = boost::dynamic_pointer_cast(model); + Vector sigmas; + if (robust) { + sigmas = robust->noise()->sigmas(); + } else { + sigmas = model->sigmas(); + } + size_t n = sigmas.size(); if (n == 1) { sigma = sigmas(0); // Rot2 goto exit; } - if (n == 3 || n == 6) { + else if (n == 3 || n == 6) { sigma = sigmas(2); // Pose2, Rot3, or Pose3 if (sigmas(0) != sigma || sigmas(1) != sigma) { if (!defaultToUnit) { @@ -46,8 +54,15 @@ ConvertNoiseModel(const SharedNoiseModel &model, size_t d, bool defaultToUnit) { throw std::runtime_error("Can only convert Pose2/Pose3 noise models"); } } -exit: - return noiseModel::Isotropic::Sigma(d, sigma); + exit: + auto isoModel = noiseModel::Isotropic::Sigma(d, sigma); + const auto &robust = boost::dynamic_pointer_cast(model); + if (robust) { + return noiseModel::Robust::Create( + noiseModel::mEstimator::Huber::Create(1.345), isoModel); + } else { + return isoModel; + } } //****************************************************************************** diff --git a/gtsam/slam/FrobeniusFactor.h b/gtsam/slam/FrobeniusFactor.h index 1fc37c785..f17a9e421 100644 --- a/gtsam/slam/FrobeniusFactor.h +++ b/gtsam/slam/FrobeniusFactor.h @@ -26,15 +26,20 @@ namespace gtsam { /** - * When creating (any) FrobeniusFactor we can convert a Rot/Pose - * BetweenFactor noise model into a n-dimensional isotropic noise - * model used to weight the Frobenius norm. If the noise model passed is - * null we return a n-dimensional isotropic noise model with sigma=1.0. If - * not, we we check if the d-dimensional noise model on rotations is + * When creating (any) FrobeniusFactor we can convert a Rot/Pose BetweenFactor + * noise model into a n-dimensional isotropic noise + * model used to weight the Frobenius norm. + * If the noise model passed is null we return a n-dimensional isotropic noise + * model with sigma=1.0. + * If not, we we check if the d-dimensional noise model on rotations is * isotropic. If it is, we extend to 'n' dimensions, otherwise we throw an - * error. If defaultToUnit == false throws an exception on unexepcted input. + * error. + * If the noise model is a robust error model, we use the sigmas of the + * underlying noise model. + * + * If defaultToUnit == false throws an exception on unexepcted input. */ -GTSAM_EXPORT boost::shared_ptr +GTSAM_EXPORT SharedNoiseModel ConvertNoiseModel(const SharedNoiseModel &model, size_t n, bool defaultToUnit = true); diff --git a/gtsam/slam/GeneralSFMFactor.h b/gtsam/slam/GeneralSFMFactor.h index f848a56ca..c9639d4d5 100644 --- a/gtsam/slam/GeneralSFMFactor.h +++ b/gtsam/slam/GeneralSFMFactor.h @@ -86,12 +86,15 @@ public: * @param cameraKey is the index of the camera * @param landmarkKey is the index of the landmark */ - GeneralSFMFactor(const Point2& measured, const SharedNoiseModel& model, Key cameraKey, Key landmarkKey) : - Base(model, cameraKey, landmarkKey), measured_(measured) {} + GeneralSFMFactor(const Point2& measured, const SharedNoiseModel& model, + Key cameraKey, Key landmarkKey) + : Base(model, cameraKey, landmarkKey), measured_(measured) {} - GeneralSFMFactor():measured_(0.0,0.0) {} ///< default constructor - GeneralSFMFactor(const Point2 & p):measured_(p) {} ///< constructor that takes a Point2 - GeneralSFMFactor(double x, double y):measured_(x,y) {} ///< constructor that takes doubles x,y to make a Point2 + GeneralSFMFactor() : measured_(0.0, 0.0) {} ///< default constructor + ///< constructor that takes a Point2 + GeneralSFMFactor(const Point2& p) : measured_(p) {} + ///< constructor that takes doubles x,y to make a Point2 + GeneralSFMFactor(double x, double y) : measured_(x, y) {} virtual ~GeneralSFMFactor() {} ///< destructor @@ -127,7 +130,7 @@ public: catch( CheiralityException& e) { if (H1) *H1 = JacobianC::Zero(); if (H2) *H2 = JacobianL::Zero(); - // TODO warn if verbose output asked for + //TODO Print the exception via logging return Z_2x1; } } @@ -149,7 +152,7 @@ public: H1.setZero(); H2.setZero(); b.setZero(); - // TODO warn if verbose output asked for + //TODO Print the exception via logging } // Whiten the system if needed diff --git a/gtsam/slam/InitializePose.h b/gtsam/slam/InitializePose.h index be249b0b5..f9b99e47e 100644 --- a/gtsam/slam/InitializePose.h +++ b/gtsam/slam/InitializePose.h @@ -62,7 +62,7 @@ static Values computePoses(const Values& initialRot, // Upgrade rotations to full poses Values initialPose; - for (const auto& key_value : initialRot) { + for (const auto key_value : initialRot) { Key key = key_value.key; const auto& rot = initialRot.at(key); Pose initializedPose = Pose(rot, origin); @@ -86,7 +86,7 @@ static Values computePoses(const Values& initialRot, // put into Values structure Values estimate; - for (const auto& key_value : GNresult) { + for (const auto key_value : GNresult) { Key key = key_value.key; if (key != kAnchorKey) { const Pose& pose = GNresult.at(key); diff --git a/gtsam/slam/InitializePose3.cpp b/gtsam/slam/InitializePose3.cpp index af1fc609e..43404df53 100644 --- a/gtsam/slam/InitializePose3.cpp +++ b/gtsam/slam/InitializePose3.cpp @@ -124,7 +124,7 @@ Values InitializePose3::computeOrientationsGradient( // this works on the inverse rotations, according to Tron&Vidal,2011 Values inverseRot; inverseRot.insert(initialize::kAnchorKey, Rot3()); - for(const auto& key_value: givenGuess) { + for(const auto key_value: givenGuess) { Key key = key_value.key; const Pose3& pose = givenGuess.at(key); inverseRot.insert(key, pose.rotation().inverse()); @@ -139,7 +139,7 @@ Values InitializePose3::computeOrientationsGradient( // calculate max node degree & allocate gradient size_t maxNodeDeg = 0; VectorValues grad; - for(const auto& key_value: inverseRot) { + for(const auto key_value: inverseRot) { Key key = key_value.key; grad.insert(key,Z_3x1); size_t currNodeDeg = (adjEdgesMap.at(key)).size(); @@ -162,7 +162,7 @@ Values InitializePose3::computeOrientationsGradient( ////////////////////////////////////////////////////////////////////////// // compute the gradient at each node maxGrad = 0; - for (const auto& key_value : inverseRot) { + for (const auto key_value : inverseRot) { Key key = key_value.key; Vector gradKey = Z_3x1; // collect the gradient for each edge incident on key @@ -203,7 +203,7 @@ Values InitializePose3::computeOrientationsGradient( // Return correct rotations const Rot3& Rref = inverseRot.at(initialize::kAnchorKey); // This will be set to the identity as so far we included no prior Values estimateRot; - for(const auto& key_value: inverseRot) { + for(const auto key_value: inverseRot) { Key key = key_value.key; if (key != initialize::kAnchorKey) { const Rot3& R = inverseRot.at(key); diff --git a/gtsam/slam/SmartFactorBase.h b/gtsam/slam/SmartFactorBase.h index d9f2b9c3d..85f9e7c3f 100644 --- a/gtsam/slam/SmartFactorBase.h +++ b/gtsam/slam/SmartFactorBase.h @@ -13,6 +13,7 @@ * @file SmartFactorBase.h * @brief Base class to create smart factors on poses or cameras * @author Luca Carlone + * @author Antoni Rosinol * @author Zsolt Kira * @author Frank Dellaert * @author Chris Beall @@ -131,9 +132,10 @@ protected: /** * Add a bunch of measurements, together with the camera keys */ - void add(ZVector& measurements, KeyVector& cameraKeys) { + void add(const ZVector& measurements, const KeyVector& cameraKeys) { + assert(measurements.size() == cameraKeys.size()); for (size_t i = 0; i < measurements.size(); i++) { - this->add(measurements.at(i), cameraKeys.at(i)); + this->add(measurements[i], cameraKeys[i]); } } diff --git a/gtsam/slam/dataset.cpp b/gtsam/slam/dataset.cpp index 74e074c9e..c8a8b15c5 100644 --- a/gtsam/slam/dataset.cpp +++ b/gtsam/slam/dataset.cpp @@ -586,7 +586,7 @@ void save2D(const NonlinearFactorGraph &graph, const Values &config, fstream stream(filename.c_str(), fstream::out); // save poses - for (const Values::ConstKeyValuePair key_value : config) { + for (const auto key_value : config) { const Pose2 &pose = key_value.value.cast(); stream << "VERTEX2 " << key_value.key << " " << pose.x() << " " << pose.y() << " " << pose.theta() << endl; diff --git a/gtsam/slam/dataset.h b/gtsam/slam/dataset.h index 93bd2b2ee..ec5d6dce9 100644 --- a/gtsam/slam/dataset.h +++ b/gtsam/slam/dataset.h @@ -29,6 +29,8 @@ #include #include #include +#include +#include #include #include @@ -216,13 +218,17 @@ typedef std::pair SiftIndex; /// Define the structure for the 3D points struct SfmTrack { - SfmTrack(): p(0,0,0) {} - SfmTrack(const gtsam::Point3& pt) : p(pt) {} + SfmTrack(float r = 0, float g = 0, float b = 0): p(0,0,0), r(r), g(g), b(b) {} + SfmTrack(const gtsam::Point3& pt, float r = 0, float g = 0, float b = 0) : p(pt), r(r), g(g), b(b) {} + Point3 p; ///< 3D position of the point float r, g, b; ///< RGB color of the 3D point std::vector measurements; ///< The 2D image projections (id,(u,v)) std::vector siftIndices; + /// Get RGB values describing 3d point + const Point3 rgb() const { return Point3(r, g, b); } + /// Total number of measurements in this track size_t number_measurements() const { return measurements.size(); @@ -243,6 +249,73 @@ struct SfmTrack { void add_measurement(size_t idx, const gtsam::Point2& m) { measurements.emplace_back(idx, m); } + + /** Serialization function */ + friend class boost::serialization::access; + template + void serialize(ARCHIVE & ar, const unsigned int /*version*/) { + ar & BOOST_SERIALIZATION_NVP(p); + ar & BOOST_SERIALIZATION_NVP(r); + ar & BOOST_SERIALIZATION_NVP(g); + ar & BOOST_SERIALIZATION_NVP(b); + ar & BOOST_SERIALIZATION_NVP(measurements); + ar & BOOST_SERIALIZATION_NVP(siftIndices); + } + + /// assert equality up to a tolerance + bool equals(const SfmTrack &sfmTrack, double tol = 1e-9) const { + // check the 3D point + if (!p.isApprox(sfmTrack.p)) { + return false; + } + + // check the RGB values + if (r!=sfmTrack.r || g!=sfmTrack.g || b!=sfmTrack.b) { + return false; + } + + // compare size of vectors for measurements and siftIndices + if (number_measurements() != sfmTrack.number_measurements() || + siftIndices.size() != sfmTrack.siftIndices.size()) { + return false; + } + + // compare measurements (order sensitive) + for (size_t idx = 0; idx < number_measurements(); ++idx) { + SfmMeasurement measurement = measurements[idx]; + SfmMeasurement otherMeasurement = sfmTrack.measurements[idx]; + + if (measurement.first != otherMeasurement.first || + !measurement.second.isApprox(otherMeasurement.second)) { + return false; + } + } + + // compare sift indices (order sensitive) + for (size_t idx = 0; idx < siftIndices.size(); ++idx) { + SiftIndex index = siftIndices[idx]; + SiftIndex otherIndex = sfmTrack.siftIndices[idx]; + + if (index.first != otherIndex.first || + index.second != otherIndex.second) { + return false; + } + } + + return true; + } + + /// print + void print(const std::string& s = "") const { + std::cout << "Track with " << measurements.size(); + std::cout << " measurements of point " << p << std::endl; + } +}; + +/* ************************************************************************* */ +/// traits +template<> +struct traits : public Testable { }; @@ -269,13 +342,62 @@ struct SfmData { return tracks[idx]; } /// Add a track to SfmData - void add_track(const SfmTrack& t) { + void add_track(const SfmTrack& t) { tracks.push_back(t); } /// Add a camera to SfmData - void add_camera(const SfmCamera& cam){ + void add_camera(const SfmCamera& cam) { cameras.push_back(cam); } + + /** Serialization function */ + friend class boost::serialization::access; + template + void serialize(Archive & ar, const unsigned int /*version*/) { + ar & BOOST_SERIALIZATION_NVP(cameras); + ar & BOOST_SERIALIZATION_NVP(tracks); + } + + /// @} + /// @name Testable + /// @{ + + /// assert equality up to a tolerance + bool equals(const SfmData &sfmData, double tol = 1e-9) const { + // check number of cameras and tracks + if (number_cameras() != sfmData.number_cameras() || + number_tracks() != sfmData.number_tracks()) { + return false; + } + + // check each camera + for (size_t i = 0; i < number_cameras(); ++i) { + if (!camera(i).equals(sfmData.camera(i), tol)) { + return false; + } + } + + // check each track + for (size_t j = 0; j < number_tracks(); ++j) { + if (!track(j).equals(sfmData.track(j), tol)) { + return false; + } + } + + return true; + } + + /// print + void print(const std::string& s = "") const { + std::cout << "Number of cameras = " << number_cameras() << std::endl; + std::cout << "Number of tracks = " << number_tracks() << std::endl; + } +}; + +/* ************************************************************************* */ +/// traits +template<> +struct traits : public Testable { }; /** diff --git a/gtsam/slam/tests/testInitializePose3.cpp b/gtsam/slam/tests/testInitializePose3.cpp index 01ec9edb1..995a109fa 100644 --- a/gtsam/slam/tests/testInitializePose3.cpp +++ b/gtsam/slam/tests/testInitializePose3.cpp @@ -75,8 +75,15 @@ NonlinearFactorGraph graph2() { g.add(BetweenFactor(x0, x1, pose0.between(pose1), noiseModel::Isotropic::Precision(6, 1.0))); g.add(BetweenFactor(x1, x2, pose1.between(pose2), noiseModel::Isotropic::Precision(6, 1.0))); g.add(BetweenFactor(x2, x3, pose2.between(pose3), noiseModel::Isotropic::Precision(6, 1.0))); - g.add(BetweenFactor(x2, x0, Pose3(Rot3::Ypr(0.1,0,0.1), Point3()), noiseModel::Isotropic::Precision(6, 0.0))); // random pose, but zero information - g.add(BetweenFactor(x0, x3, Pose3(Rot3::Ypr(0.5,-0.2,0.2), Point3(10,20,30)), noiseModel::Isotropic::Precision(6, 0.0))); // random pose, but zero informatoin + // random pose, but zero information + auto noise_zero_info = noiseModel::Isotropic::Precision(6, 0.0); + g.add(BetweenFactor( + x2, x0, Pose3(Rot3::Ypr(0.1, 0.0, 0.1), Point3(0.0, 0.0, 0.0)), + noise_zero_info)); + // random pose, but zero information + g.add(BetweenFactor( + x0, x3, Pose3(Rot3::Ypr(0.5, -0.2, 0.2), Point3(10, 20, 30)), + noise_zero_info)); g.addPrior(x0, pose0, model); return g; } diff --git a/gtsam/slam/tests/testLago.cpp b/gtsam/slam/tests/testLago.cpp index 55449d86e..781317d7a 100644 --- a/gtsam/slam/tests/testLago.cpp +++ b/gtsam/slam/tests/testLago.cpp @@ -284,7 +284,7 @@ TEST( Lago, largeGraphNoisy_orientations ) { Values::shared_ptr expected; boost::tie(gmatlab, expected) = readG2o(matlabFile); - for(const Values::KeyValuePair& key_val: *expected){ + for(const auto key_val: *expected){ Key k = key_val.key; EXPECT(assert_equal(expected->at(k), actual.at(k), 1e-5)); } @@ -310,7 +310,7 @@ TEST( Lago, largeGraphNoisy ) { Values::shared_ptr expected; boost::tie(gmatlab, expected) = readG2o(matlabFile); - for(const Values::KeyValuePair& key_val: *expected){ + for(const auto key_val: *expected){ Key k = key_val.key; EXPECT(assert_equal(expected->at(k), actual.at(k), 1e-2)); } diff --git a/gtsam/slam/tests/testSerializationDataset.cpp b/gtsam/slam/tests/testSerializationDataset.cpp new file mode 100644 index 000000000..6ef82f07f --- /dev/null +++ b/gtsam/slam/tests/testSerializationDataset.cpp @@ -0,0 +1,58 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file testSerializationDataset.cpp + * @brief serialization tests for dataset.cpp + * @author Ayush Baid + * @date Jan 1, 2021 + */ + +#include + +#include +#include + +using namespace std; +using namespace gtsam; +using namespace gtsam::serializationTestHelpers; + +/* ************************************************************************* */ +TEST(dataSet, sfmDataSerialization) { + // Test the serialization of SfmData + const string filename = findExampleDataFile("dubrovnik-3-7-pre"); + SfmData mydata; + CHECK(readBAL(filename, mydata)); + + // round-trip equality check on serialization and subsequent deserialization + EXPECT(equalsObj(mydata)); + EXPECT(equalsXML(mydata)); + EXPECT(equalsBinary(mydata)); +} + +/* ************************************************************************* */ +TEST(dataSet, sfmTrackSerialization) { + // Test the serialization of SfmTrack + const string filename = findExampleDataFile("dubrovnik-3-7-pre"); + SfmData mydata; + CHECK(readBAL(filename, mydata)); + + SfmTrack track = mydata.track(0); + + // round-trip equality check on serialization and subsequent deserialization + EXPECT(equalsObj(track)); + EXPECT(equalsXML(track)); + EXPECT(equalsBinary(track)); +} + +/* ************************************************************************* */ +int main() { TestResult tr; return TestRegistry::runAllTests(tr); } +/* ************************************************************************* */ diff --git a/gtsam_unstable/examples/ConcurrentFilteringAndSmoothingExample.cpp b/gtsam_unstable/examples/ConcurrentFilteringAndSmoothingExample.cpp index 939d3a5c8..1494d784b 100644 --- a/gtsam_unstable/examples/ConcurrentFilteringAndSmoothingExample.cpp +++ b/gtsam_unstable/examples/ConcurrentFilteringAndSmoothingExample.cpp @@ -308,11 +308,11 @@ int main(int argc, char** argv) { // And to demonstrate the fixed-lag aspect, print the keys contained in each smoother after 3.0 seconds cout << "After 15.0 seconds, each version contains to the following keys:" << endl; cout << " Concurrent Filter Keys: " << endl; - for(const auto& key_value: concurrentFilter.getLinearizationPoint()) { + for(const auto key_value: concurrentFilter.getLinearizationPoint()) { cout << setprecision(5) << " Key: " << key_value.key << endl; } cout << " Concurrent Smoother Keys: " << endl; - for(const auto& key_value: concurrentSmoother.getLinearizationPoint()) { + for(const auto key_value: concurrentSmoother.getLinearizationPoint()) { cout << setprecision(5) << " Key: " << key_value.key << endl; } cout << " Fixed-Lag Smoother Keys: " << endl; diff --git a/examples/ISAM2_SmartFactorStereo_IMU.cpp b/gtsam_unstable/examples/ISAM2_SmartFactorStereo_IMU.cpp similarity index 100% rename from examples/ISAM2_SmartFactorStereo_IMU.cpp rename to gtsam_unstable/examples/ISAM2_SmartFactorStereo_IMU.cpp diff --git a/gtsam_unstable/examples/SmartRangeExample_plaza1.cpp b/gtsam_unstable/examples/SmartRangeExample_plaza1.cpp index 5fdc7a743..64afa8030 100644 --- a/gtsam_unstable/examples/SmartRangeExample_plaza1.cpp +++ b/gtsam_unstable/examples/SmartRangeExample_plaza1.cpp @@ -188,7 +188,8 @@ int main(int argc, char** argv) { smartFactors[j]->addRange(i, range); printf("adding range %g for %d",range,(int)j); } catch (const invalid_argument& e) { - printf("warning: omitting duplicate range %g for %d",range,(int)j); + printf("warning: omitting duplicate range %g for %d: %s", range, + (int)j, e.what()); } cout << endl; } @@ -233,7 +234,7 @@ int main(int argc, char** argv) { } } countK = 0; - for(const Values::ConstFiltered::KeyValuePair& it: result.filter()) + for(const auto it: result.filter()) os2 << it.key << "\t" << it.value.x() << "\t" << it.value.y() << "\t1" << endl; if (smart) { @@ -256,7 +257,7 @@ int main(int argc, char** argv) { // Write result to file Values result = isam.calculateEstimate(); ofstream os("rangeResult.txt"); - for(const Values::ConstFiltered::KeyValuePair& it: result.filter()) + for(const auto it: result.filter()) os << it.key << "\t" << it.value.x() << "\t" << it.value.y() << "\t" << it.value.theta() << endl; exit(0); diff --git a/gtsam_unstable/examples/SmartRangeExample_plaza2.cpp b/gtsam_unstable/examples/SmartRangeExample_plaza2.cpp index 90b2a30ff..95aff85a7 100644 --- a/gtsam_unstable/examples/SmartRangeExample_plaza2.cpp +++ b/gtsam_unstable/examples/SmartRangeExample_plaza2.cpp @@ -202,11 +202,11 @@ int main(int argc, char** argv) { // Write result to file Values result = isam.calculateEstimate(); ofstream os2("rangeResultLM.txt"); - for(const Values::ConstFiltered::KeyValuePair& it: result.filter()) + for(const auto it: result.filter()) os2 << it.key << "\t" << it.value.x() << "\t" << it.value.y() << "\t1" << endl; ofstream os("rangeResult.txt"); - for(const Values::ConstFiltered::KeyValuePair& it: result.filter()) + for(const auto it: result.filter()) os << it.key << "\t" << it.value.x() << "\t" << it.value.y() << "\t" << it.value.theta() << endl; exit(0); diff --git a/gtsam_unstable/linear/QPSParser.cpp b/gtsam_unstable/linear/QPSParser.cpp index 3039185f2..df21c0132 100644 --- a/gtsam_unstable/linear/QPSParser.cpp +++ b/gtsam_unstable/linear/QPSParser.cpp @@ -81,7 +81,7 @@ class QPSVisitor { varname_to_key; // Variable QPS string name to key std::unordered_map> H; // H from hessian - double f; // Constant term of quadratic cost + double f = 0; // Constant term of quadratic cost std::string obj_name; // the objective function has a name in the QPS std::string name_; // the quadratic program has a name in the QPS std::unordered_map @@ -175,10 +175,11 @@ class QPSVisitor { string var_ = fromChars<1>(vars); string row_ = fromChars<3>(vars); double coefficient = at_c<5>(vars); - if (row_ == obj_name) + if (row_ == obj_name) { f = -coefficient; - else + } else { b[row_] = coefficient; + } if (debug) { cout << "Added RHS for Var: " << var_ << " Row: " << row_ @@ -194,15 +195,17 @@ class QPSVisitor { string row2_ = fromChars<7>(vars); double coefficient1 = at_c<5>(vars); double coefficient2 = at_c<9>(vars); - if (row1_ == obj_name) + if (row1_ == obj_name) { f = -coefficient1; - else + } else { b[row1_] = coefficient1; + } - if (row2_ == obj_name) + if (row2_ == obj_name) { f = -coefficient2; - else + } else { b[row2_] = coefficient2; + } if (debug) { cout << "Added RHS for Var: " << var_ << " Row: " << row1_ diff --git a/gtsam_unstable/nonlinear/BatchFixedLagSmoother.cpp b/gtsam_unstable/nonlinear/BatchFixedLagSmoother.cpp index 777e4b2d3..fd18e7c6d 100644 --- a/gtsam_unstable/nonlinear/BatchFixedLagSmoother.cpp +++ b/gtsam_unstable/nonlinear/BatchFixedLagSmoother.cpp @@ -59,7 +59,7 @@ FixedLagSmoother::Result BatchFixedLagSmoother::update( // Add the new variables to theta theta_.insert(newTheta); // Add new variables to the end of the ordering - for (const auto& key_value : newTheta) { + for (const auto key_value : newTheta) { ordering_.push_back(key_value.key); } // Augment Delta @@ -267,7 +267,7 @@ FixedLagSmoother::Result BatchFixedLagSmoother::optimize() { // Put the linearization points and deltas back for specific variables if (enforceConsistency_ && (linearKeys_.size() > 0)) { theta_.update(linearKeys_); - for(const auto& key_value: linearKeys_) { + for(const auto key_value: linearKeys_) { delta_.at(key_value.key) = newDelta.at(key_value.key); } } diff --git a/gtsam_unstable/nonlinear/ConcurrentBatchFilter.cpp b/gtsam_unstable/nonlinear/ConcurrentBatchFilter.cpp index 758bcfe48..83d0ab719 100644 --- a/gtsam_unstable/nonlinear/ConcurrentBatchFilter.cpp +++ b/gtsam_unstable/nonlinear/ConcurrentBatchFilter.cpp @@ -139,7 +139,7 @@ ConcurrentBatchFilter::Result ConcurrentBatchFilter::update(const NonlinearFacto // Add the new variables to theta theta_.insert(newTheta); // Add new variables to the end of the ordering - for(const Values::ConstKeyValuePair& key_value: newTheta) { + for(const auto key_value: newTheta) { ordering_.push_back(key_value.key); } // Augment Delta @@ -222,7 +222,7 @@ void ConcurrentBatchFilter::synchronize(const NonlinearFactorGraph& smootherSumm // Find the set of new separator keys KeySet newSeparatorKeys; - for(const Values::ConstKeyValuePair& key_value: separatorValues_) { + for(const auto key_value: separatorValues_) { newSeparatorKeys.insert(key_value.key); } @@ -236,7 +236,7 @@ void ConcurrentBatchFilter::synchronize(const NonlinearFactorGraph& smootherSumm graph.push_back(smootherShortcut_); Values values; values.insert(smootherSummarizationValues); - for(const Values::ConstKeyValuePair& key_value: separatorValues_) { + for(const auto key_value: separatorValues_) { if(!values.exists(key_value.key)) { values.insert(key_value.key, key_value.value); } @@ -471,7 +471,7 @@ void ConcurrentBatchFilter::optimize(const NonlinearFactorGraph& factors, Values // Put the linearization points and deltas back for specific variables if(linearValues.size() > 0) { theta.update(linearValues); - for(const Values::ConstKeyValuePair& key_value: linearValues) { + for(const auto key_value: linearValues) { delta.at(key_value.key) = newDelta.at(key_value.key); } } @@ -574,7 +574,7 @@ void ConcurrentBatchFilter::moveSeparator(const FastList& keysToMove) { // Calculate the set of new separator keys: AffectedKeys + PreviousSeparatorKeys - KeysToMove KeySet newSeparatorKeys = removedFactors.keys(); - for(const Values::ConstKeyValuePair& key_value: separatorValues_) { + for(const auto key_value: separatorValues_) { newSeparatorKeys.insert(key_value.key); } for(Key key: keysToMove) { diff --git a/gtsam_unstable/nonlinear/ConcurrentBatchSmoother.cpp b/gtsam_unstable/nonlinear/ConcurrentBatchSmoother.cpp index 600baa9f0..75d491bde 100644 --- a/gtsam_unstable/nonlinear/ConcurrentBatchSmoother.cpp +++ b/gtsam_unstable/nonlinear/ConcurrentBatchSmoother.cpp @@ -61,7 +61,7 @@ ConcurrentBatchSmoother::Result ConcurrentBatchSmoother::update(const NonlinearF theta_.insert(newTheta); // Add new variables to the end of the ordering - for(const Values::ConstKeyValuePair& key_value: newTheta) { + for(const auto key_value: newTheta) { ordering_.push_back(key_value.key); } @@ -135,7 +135,7 @@ void ConcurrentBatchSmoother::synchronize(const NonlinearFactorGraph& smootherFa removeFactors(filterSummarizationSlots_); // Insert new linpoints into the values, augment the ordering, and store new dims to augment delta - for(const Values::ConstKeyValuePair& key_value: smootherValues) { + for(const auto key_value: smootherValues) { std::pair iter_inserted = theta_.tryInsert(key_value.key, key_value.value); if(iter_inserted.second) { // If the insert succeeded @@ -146,7 +146,7 @@ void ConcurrentBatchSmoother::synchronize(const NonlinearFactorGraph& smootherFa iter_inserted.first->value = key_value.value; } } - for(const Values::ConstKeyValuePair& key_value: separatorValues) { + for(const auto key_value: separatorValues) { std::pair iter_inserted = theta_.tryInsert(key_value.key, key_value.value); if(iter_inserted.second) { // If the insert succeeded @@ -322,7 +322,7 @@ ConcurrentBatchSmoother::Result ConcurrentBatchSmoother::optimize() { // Put the linearization points and deltas back for specific variables if(separatorValues_.size() > 0) { theta_.update(separatorValues_); - for(const Values::ConstKeyValuePair& key_value: separatorValues_) { + for(const auto key_value: separatorValues_) { delta_.at(key_value.key) = newDelta.at(key_value.key); } } @@ -372,7 +372,7 @@ void ConcurrentBatchSmoother::updateSmootherSummarization() { // Get the set of separator keys gtsam::KeySet separatorKeys; - for(const Values::ConstKeyValuePair& key_value: separatorValues_) { + for(const auto key_value: separatorValues_) { separatorKeys.insert(key_value.key); } diff --git a/gtsam_unstable/nonlinear/ConcurrentIncrementalFilter.cpp b/gtsam_unstable/nonlinear/ConcurrentIncrementalFilter.cpp index b70b9efc2..b9cf66a97 100644 --- a/gtsam_unstable/nonlinear/ConcurrentIncrementalFilter.cpp +++ b/gtsam_unstable/nonlinear/ConcurrentIncrementalFilter.cpp @@ -69,13 +69,13 @@ ConcurrentIncrementalFilter::Result ConcurrentIncrementalFilter::update(const No int group = 1; // Set all existing variables to Group1 if(isam2_.getLinearizationPoint().size() > 0) { - for(const Values::ConstKeyValuePair& key_value: isam2_.getLinearizationPoint()) { + for(const auto key_value: isam2_.getLinearizationPoint()) { orderingConstraints->operator[](key_value.key) = group; } ++group; } // Assign new variables to the root - for(const Values::ConstKeyValuePair& key_value: newTheta) { + for(const auto key_value: newTheta) { orderingConstraints->operator[](key_value.key) = group; } // Set marginalizable variables to Group0 @@ -201,7 +201,7 @@ void ConcurrentIncrementalFilter::synchronize(const NonlinearFactorGraph& smooth // Force iSAM2 not to relinearize anything during this iteration FastList noRelinKeys; - for(const Values::ConstKeyValuePair& key_value: isam2_.getLinearizationPoint()) { + for(const auto key_value: isam2_.getLinearizationPoint()) { noRelinKeys.push_back(key_value.key); } diff --git a/gtsam_unstable/nonlinear/ConcurrentIncrementalSmoother.cpp b/gtsam_unstable/nonlinear/ConcurrentIncrementalSmoother.cpp index 714d7c8d0..3886d0e42 100644 --- a/gtsam_unstable/nonlinear/ConcurrentIncrementalSmoother.cpp +++ b/gtsam_unstable/nonlinear/ConcurrentIncrementalSmoother.cpp @@ -66,7 +66,7 @@ ConcurrentIncrementalSmoother::Result ConcurrentIncrementalSmoother::update(cons // Also, mark the separator keys as fixed linearization points FastMap constrainedKeys; FastList noRelinKeys; - for(const Values::ConstKeyValuePair& key_value: separatorValues_) { + for(const auto key_value: separatorValues_) { constrainedKeys[key_value.key] = 1; noRelinKeys.push_back(key_value.key); } @@ -82,12 +82,12 @@ ConcurrentIncrementalSmoother::Result ConcurrentIncrementalSmoother::update(cons Values values(newTheta); // Unfortunately, we must be careful here, as some of the smoother values // and/or separator values may have been added previously - for(const Values::ConstKeyValuePair& key_value: smootherValues_) { + for(const auto key_value: smootherValues_) { if(!isam2_.getLinearizationPoint().exists(key_value.key)) { values.insert(key_value.key, smootherValues_.at(key_value.key)); } } - for(const Values::ConstKeyValuePair& key_value: separatorValues_) { + for(const auto key_value: separatorValues_) { if(!isam2_.getLinearizationPoint().exists(key_value.key)) { values.insert(key_value.key, separatorValues_.at(key_value.key)); } @@ -246,7 +246,7 @@ void ConcurrentIncrementalSmoother::updateSmootherSummarization() { // Get the set of separator keys KeySet separatorKeys; - for(const Values::ConstKeyValuePair& key_value: separatorValues_) { + for(const auto key_value: separatorValues_) { separatorKeys.insert(key_value.key); } diff --git a/gtsam_unstable/nonlinear/tests/testConcurrentBatchFilter.cpp b/gtsam_unstable/nonlinear/tests/testConcurrentBatchFilter.cpp index 1f19c0e8a..61db05167 100644 --- a/gtsam_unstable/nonlinear/tests/testConcurrentBatchFilter.cpp +++ b/gtsam_unstable/nonlinear/tests/testConcurrentBatchFilter.cpp @@ -64,7 +64,7 @@ NonlinearFactorGraph CalculateMarginals(const NonlinearFactorGraph& factorGraph, std::set KeysToKeep; - for(const Values::ConstKeyValuePair& key_value: linPoint) { // we cycle over all the keys of factorGraph + for(const auto key_value: linPoint) { // we cycle over all the keys of factorGraph KeysToKeep.insert(key_value.key); } // so far we are keeping all keys, but we want to delete the ones that we are going to marginalize for(Key key: keysToMarginalize) { diff --git a/gtsam_unstable/nonlinear/tests/testConcurrentBatchSmoother.cpp b/gtsam_unstable/nonlinear/tests/testConcurrentBatchSmoother.cpp index ae9a3f827..b5fb61428 100644 --- a/gtsam_unstable/nonlinear/tests/testConcurrentBatchSmoother.cpp +++ b/gtsam_unstable/nonlinear/tests/testConcurrentBatchSmoother.cpp @@ -560,7 +560,7 @@ TEST( ConcurrentBatchSmoother, synchronize_3 ) GaussianFactorGraph::shared_ptr linearFactors = allFactors.linearize(allValues); KeySet eliminateKeys = linearFactors->keys(); - for(const Values::ConstKeyValuePair& key_value: filterSeparatorValues) { + for(const auto key_value: filterSeparatorValues) { eliminateKeys.erase(key_value.key); } KeyVector variables(eliminateKeys.begin(), eliminateKeys.end()); diff --git a/gtsam_unstable/nonlinear/tests/testConcurrentIncrementalFilter.cpp b/gtsam_unstable/nonlinear/tests/testConcurrentIncrementalFilter.cpp index c5dba1a69..08d71a420 100644 --- a/gtsam_unstable/nonlinear/tests/testConcurrentIncrementalFilter.cpp +++ b/gtsam_unstable/nonlinear/tests/testConcurrentIncrementalFilter.cpp @@ -80,7 +80,7 @@ NonlinearFactorGraph CalculateMarginals(const NonlinearFactorGraph& factorGraph, std::set KeysToKeep; - for(const Values::ConstKeyValuePair& key_value: linPoint) { // we cycle over all the keys of factorGraph + for(const auto key_value: linPoint) { // we cycle over all the keys of factorGraph KeysToKeep.insert(key_value.key); } // so far we are keeping all keys, but we want to delete the ones that we are going to marginalize for(Key key: keysToMarginalize) { diff --git a/gtsam_unstable/nonlinear/tests/testConcurrentIncrementalSmootherDL.cpp b/gtsam_unstable/nonlinear/tests/testConcurrentIncrementalSmootherDL.cpp index 5de115013..ccb5a104e 100644 --- a/gtsam_unstable/nonlinear/tests/testConcurrentIncrementalSmootherDL.cpp +++ b/gtsam_unstable/nonlinear/tests/testConcurrentIncrementalSmootherDL.cpp @@ -512,7 +512,7 @@ TEST( ConcurrentIncrementalSmootherDL, synchronize_2 ) // Values expectedLinearizationPoint = BatchOptimize(allFactors, allValues, 1); Values expectedLinearizationPoint = filterSeparatorValues; Values actualLinearizationPoint; - for(const Values::ConstKeyValuePair& key_value: filterSeparatorValues) { + for(const auto key_value: filterSeparatorValues) { actualLinearizationPoint.insert(key_value.key, smoother.getLinearizationPoint().at(key_value.key)); } CHECK(assert_equal(expectedLinearizationPoint, actualLinearizationPoint, 1e-6)); @@ -580,7 +580,7 @@ TEST( ConcurrentIncrementalSmootherDL, synchronize_3 ) // GaussianBayesNet::shared_ptr GBNsptr = GSS.eliminate(); KeySet allkeys = LinFactorGraph->keys(); - for(const Values::ConstKeyValuePair& key_value: filterSeparatorValues) { + for(const auto key_value: filterSeparatorValues) { allkeys.erase(key_value.key); } KeyVector variables(allkeys.begin(), allkeys.end()); diff --git a/gtsam_unstable/nonlinear/tests/testConcurrentIncrementalSmootherGN.cpp b/gtsam_unstable/nonlinear/tests/testConcurrentIncrementalSmootherGN.cpp index ec78ee6e2..53c3d1610 100644 --- a/gtsam_unstable/nonlinear/tests/testConcurrentIncrementalSmootherGN.cpp +++ b/gtsam_unstable/nonlinear/tests/testConcurrentIncrementalSmootherGN.cpp @@ -513,7 +513,7 @@ TEST( ConcurrentIncrementalSmootherGN, synchronize_2 ) // Values expectedLinearizationPoint = BatchOptimize(allFactors, allValues, 1); Values expectedLinearizationPoint = filterSeparatorValues; Values actualLinearizationPoint; - for(const Values::ConstKeyValuePair& key_value: filterSeparatorValues) { + for(const auto key_value: filterSeparatorValues) { actualLinearizationPoint.insert(key_value.key, smoother.getLinearizationPoint().at(key_value.key)); } CHECK(assert_equal(expectedLinearizationPoint, actualLinearizationPoint, 1e-6)); @@ -582,7 +582,7 @@ TEST( ConcurrentIncrementalSmootherGN, synchronize_3 ) // GaussianBayesNet::shared_ptr GBNsptr = GSS.eliminate(); KeySet allkeys = LinFactorGraph->keys(); - for(const Values::ConstKeyValuePair& key_value: filterSeparatorValues) + for(const auto key_value: filterSeparatorValues) allkeys.erase(key_value.key); KeyVector variables(allkeys.begin(), allkeys.end()); std::pair result = LinFactorGraph->eliminatePartialSequential(variables, EliminateCholesky); diff --git a/gtsam_unstable/slam/SmartStereoProjectionPoseFactor.cpp b/gtsam_unstable/slam/SmartStereoProjectionPoseFactor.cpp new file mode 100644 index 000000000..c28cb25a1 --- /dev/null +++ b/gtsam_unstable/slam/SmartStereoProjectionPoseFactor.cpp @@ -0,0 +1,97 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file SmartStereoProjectionPoseFactor.cpp + * @brief Smart stereo factor on poses, assuming camera calibration is fixed + * @author Luca Carlone + * @author Antoni Rosinol + * @author Chris Beall + * @author Zsolt Kira + * @author Frank Dellaert + */ + +#include + +namespace gtsam { + +SmartStereoProjectionPoseFactor::SmartStereoProjectionPoseFactor( + const SharedNoiseModel& sharedNoiseModel, + const SmartStereoProjectionParams& params, + const boost::optional& body_P_sensor) + : Base(sharedNoiseModel, params, body_P_sensor) {} + +void SmartStereoProjectionPoseFactor::add( + const StereoPoint2& measured, const Key& poseKey, + const boost::shared_ptr& K) { + Base::add(measured, poseKey); + K_all_.push_back(K); +} + +void SmartStereoProjectionPoseFactor::add( + const std::vector& measurements, const KeyVector& poseKeys, + const std::vector>& Ks) { + assert(measurements.size() == poseKeys.size()); + assert(poseKeys.size() == Ks.size()); + Base::add(measurements, poseKeys); + K_all_.insert(K_all_.end(), Ks.begin(), Ks.end()); +} + +void SmartStereoProjectionPoseFactor::add( + const std::vector& measurements, const KeyVector& poseKeys, + const boost::shared_ptr& K) { + assert(poseKeys.size() == measurements.size()); + for (size_t i = 0; i < measurements.size(); i++) { + Base::add(measurements[i], poseKeys[i]); + K_all_.push_back(K); + } +} + +void SmartStereoProjectionPoseFactor::print( + const std::string& s, const KeyFormatter& keyFormatter) const { + std::cout << s << "SmartStereoProjectionPoseFactor, z = \n "; + for (const boost::shared_ptr& K : K_all_) { + K->print("calibration = "); + } + Base::print("", keyFormatter); +} + +bool SmartStereoProjectionPoseFactor::equals(const NonlinearFactor& p, + double tol) const { + const SmartStereoProjectionPoseFactor* e = + dynamic_cast(&p); + + return e && Base::equals(p, tol); +} + +double SmartStereoProjectionPoseFactor::error(const Values& values) const { + if (this->active(values)) { + return this->totalReprojectionError(cameras(values)); + } else { // else of active flag + return 0.0; + } +} + +SmartStereoProjectionPoseFactor::Base::Cameras +SmartStereoProjectionPoseFactor::cameras(const Values& values) const { + assert(keys_.size() == K_all_.size()); + Base::Cameras cameras; + for (size_t i = 0; i < keys_.size(); i++) { + Pose3 pose = values.at(keys_[i]); + if (Base::body_P_sensor_) { + pose = pose.compose(*(Base::body_P_sensor_)); + } + cameras.push_back(StereoCamera(pose, K_all_[i])); + } + return cameras; +} + +} // \ namespace gtsam diff --git a/gtsam_unstable/slam/SmartStereoProjectionPoseFactor.h b/gtsam_unstable/slam/SmartStereoProjectionPoseFactor.h index 124e45005..2ecd7b75c 100644 --- a/gtsam_unstable/slam/SmartStereoProjectionPoseFactor.h +++ b/gtsam_unstable/slam/SmartStereoProjectionPoseFactor.h @@ -13,6 +13,7 @@ * @file SmartStereoProjectionPoseFactor.h * @brief Smart stereo factor on poses, assuming camera calibration is fixed * @author Luca Carlone + * @author Antoni Rosinol * @author Chris Beall * @author Zsolt Kira * @author Frank Dellaert @@ -28,8 +29,9 @@ namespace gtsam { * @addtogroup SLAM * * If you are using the factor, please cite: - * L. Carlone, Z. Kira, C. Beall, V. Indelman, F. Dellaert, Eliminating conditionally - * independent sets in factor graphs: a unifying perspective based on smart factors, + * L. Carlone, Z. Kira, C. Beall, V. Indelman, F. Dellaert, + * Eliminating conditionally independent sets in factor graphs: + * a unifying perspective based on smart factors, * Int. Conf. on Robotics and Automation (ICRA), 2014. * */ @@ -41,14 +43,12 @@ namespace gtsam { * This factor requires that values contains the involved poses (Pose3). * @addtogroup SLAM */ -class SmartStereoProjectionPoseFactor: public SmartStereoProjectionFactor { - -protected: - - std::vector > K_all_; ///< shared pointer to calibration object (one for each camera) - -public: +class SmartStereoProjectionPoseFactor : public SmartStereoProjectionFactor { + protected: + /// shared pointer to calibration object (one for each camera) + std::vector> K_all_; + public: EIGEN_MAKE_ALIGNED_OPERATOR_NEW /// shorthand for base class type @@ -65,54 +65,49 @@ public: * @param Isotropic measurement noise * @param params internal parameters of the smart factors */ - SmartStereoProjectionPoseFactor(const SharedNoiseModel& sharedNoiseModel, + SmartStereoProjectionPoseFactor( + const SharedNoiseModel& sharedNoiseModel, const SmartStereoProjectionParams& params = SmartStereoProjectionParams(), - const boost::optional body_P_sensor = boost::none) : - Base(sharedNoiseModel, params, body_P_sensor) { - } + const boost::optional& body_P_sensor = boost::none); /** Virtual destructor */ - virtual ~SmartStereoProjectionPoseFactor() {} + virtual ~SmartStereoProjectionPoseFactor() = default; /** * add a new measurement and pose key - * @param measured is the 2m dimensional location of the projection of a single landmark in the m view (the measurement) - * @param poseKey is key corresponding to the camera observing the same landmark + * @param measured is the 2m dimensional location of the projection of a + * single landmark in the m view (the measurement) + * @param poseKey is key corresponding to the camera observing the same + * landmark * @param K is the (fixed) camera calibration */ - void add(const StereoPoint2 measured, const Key poseKey, - const boost::shared_ptr K) { - Base::add(measured, poseKey); - K_all_.push_back(K); - } + void add(const StereoPoint2& measured, const Key& poseKey, + const boost::shared_ptr& K); /** * Variant of the previous one in which we include a set of measurements - * @param measurements vector of the 2m dimensional location of the projection of a single landmark in the m view (the measurement) - * @param poseKeys vector of keys corresponding to the camera observing the same landmark + * @param measurements vector of the 2m dimensional location of the projection + * of a single landmark in the m view (the measurement) + * @param poseKeys vector of keys corresponding to the camera observing + * the same landmark * @param Ks vector of calibration objects */ - void add(std::vector measurements, KeyVector poseKeys, - std::vector > Ks) { - Base::add(measurements, poseKeys); - for (size_t i = 0; i < measurements.size(); i++) { - K_all_.push_back(Ks.at(i)); - } - } + void add(const std::vector& measurements, + const KeyVector& poseKeys, + const std::vector>& Ks); /** - * Variant of the previous one in which we include a set of measurements with the same noise and calibration - * @param measurements vector of the 2m dimensional location of the projection of a single landmark in the m view (the measurement) - * @param poseKeys vector of keys corresponding to the camera observing the same landmark + * Variant of the previous one in which we include a set of measurements with + * the same noise and calibration + * @param measurements vector of the 2m dimensional location of the projection + * of a single landmark in the m view (the measurement) + * @param poseKeys vector of keys corresponding to the camera observing the + * same landmark * @param K the (known) camera calibration (same for all measurements) */ - void add(std::vector measurements, KeyVector poseKeys, - const boost::shared_ptr K) { - for (size_t i = 0; i < measurements.size(); i++) { - Base::add(measurements.at(i), poseKeys.at(i)); - K_all_.push_back(K); - } - } + void add(const std::vector& measurements, + const KeyVector& poseKeys, + const boost::shared_ptr& K); /** * print @@ -120,74 +115,45 @@ public: * @param keyFormatter optional formatter useful for printing Symbols */ void print(const std::string& s = "", const KeyFormatter& keyFormatter = - DefaultKeyFormatter) const override { - std::cout << s << "SmartStereoProjectionPoseFactor, z = \n "; - for(const boost::shared_ptr& K: K_all_) - K->print("calibration = "); - Base::print("", keyFormatter); - } + DefaultKeyFormatter) const override; /// equals - bool equals(const NonlinearFactor& p, double tol = 1e-9) const override { - const SmartStereoProjectionPoseFactor *e = - dynamic_cast(&p); - - return e && Base::equals(p, tol); - } + virtual bool equals(const NonlinearFactor& p, + double tol = 1e-9) const override; /** * error calculates the error of the factor. */ - double error(const Values& values) const override { - if (this->active(values)) { - return this->totalReprojectionError(cameras(values)); - } else { // else of active flag - return 0.0; - } - } + double error(const Values& values) const override; /** return the calibration object */ - inline const std::vector > calibration() const { + inline std::vector> calibration() const { return K_all_; } /** * Collect all cameras involved in this factor - * @param values Values structure which must contain camera poses corresponding + * @param values Values structure which must contain camera poses + * corresponding * to keys involved in this factor * @return vector of Values */ - Base::Cameras cameras(const Values& values) const override { - Base::Cameras cameras; - size_t i=0; - for(const Key& k: this->keys_) { - Pose3 pose = values.at(k); - - if (Base::body_P_sensor_) - pose = pose.compose(*(Base::body_P_sensor_)); - - StereoCamera camera(pose, K_all_[i++]); - cameras.push_back(camera); - } - return cameras; - } - -private: + Base::Cameras cameras(const Values& values) const override; + private: /// Serialization function friend class boost::serialization::access; - template - void serialize(ARCHIVE & ar, const unsigned int /*version*/) { - ar & BOOST_SERIALIZATION_BASE_OBJECT_NVP(Base); - ar & BOOST_SERIALIZATION_NVP(K_all_); + template + void serialize(ARCHIVE& ar, const unsigned int /*version*/) { + ar& BOOST_SERIALIZATION_BASE_OBJECT_NVP(Base); + ar& BOOST_SERIALIZATION_NVP(K_all_); } -}; // end of class declaration +}; // end of class declaration /// traits -template<> -struct traits : public Testable< - SmartStereoProjectionPoseFactor> { -}; +template <> +struct traits + : public Testable {}; -} // \ namespace gtsam +} // namespace gtsam diff --git a/gtsam_unstable/slam/serialization.cpp b/gtsam_unstable/slam/serialization.cpp index 8a661f2ef..88a94fd51 100644 --- a/gtsam_unstable/slam/serialization.cpp +++ b/gtsam_unstable/slam/serialization.cpp @@ -43,7 +43,6 @@ typedef PriorFactor PriorFactorPose3; typedef PriorFactor PriorFactorCal3_S2; typedef PriorFactor PriorFactorCal3DS2; typedef PriorFactor PriorFactorCalibratedCamera; -typedef PriorFactor PriorFactorSimpleCamera; typedef PriorFactor PriorFactorPinholeCameraCal3_S2; typedef PriorFactor PriorFactorStereoCamera; @@ -68,7 +67,6 @@ typedef NonlinearEquality NonlinearEqualityPose3; typedef NonlinearEquality NonlinearEqualityCal3_S2; typedef NonlinearEquality NonlinearEqualityCal3DS2; typedef NonlinearEquality NonlinearEqualityCalibratedCamera; -typedef NonlinearEquality NonlinearEqualitySimpleCamera; typedef NonlinearEquality NonlinearEqualityPinholeCameraCal3_S2; typedef NonlinearEquality NonlinearEqualityStereoCamera; @@ -77,10 +75,8 @@ typedef RangeFactor RangeFactor3D; typedef RangeFactor RangeFactorPose2; typedef RangeFactor RangeFactorPose3; typedef RangeFactor RangeFactorCalibratedCameraPoint; -typedef RangeFactor RangeFactorSimpleCameraPoint; typedef RangeFactor RangeFactorPinholeCameraCal3_S2Point; typedef RangeFactor RangeFactorCalibratedCamera; -typedef RangeFactor RangeFactorSimpleCamera; typedef RangeFactor RangeFactorPinholeCameraCal3_S2; typedef BearingRangeFactor BearingRangeFactor2D; @@ -90,7 +86,7 @@ typedef GenericProjectionFactor GenericProjectionFactorC typedef GenericProjectionFactor GenericProjectionFactorCal3DS2; typedef gtsam::GeneralSFMFactor GeneralSFMFactorCal3_S2; -//typedef gtsam::GeneralSFMFactor GeneralSFMFactorCal3DS2; +typedef gtsam::GeneralSFMFactor GeneralSFMFactorCal3DS2; typedef gtsam::GeneralSFMFactor2 GeneralSFMFactor2Cal3_S2; @@ -129,7 +125,6 @@ GTSAM_VALUE_EXPORT(gtsam::Cal3_S2); GTSAM_VALUE_EXPORT(gtsam::Cal3DS2); GTSAM_VALUE_EXPORT(gtsam::Cal3_S2Stereo); GTSAM_VALUE_EXPORT(gtsam::CalibratedCamera); -GTSAM_VALUE_EXPORT(gtsam::SimpleCamera); GTSAM_VALUE_EXPORT(gtsam::PinholeCameraCal3_S2); GTSAM_VALUE_EXPORT(gtsam::StereoCamera); @@ -150,7 +145,6 @@ BOOST_CLASS_EXPORT_GUID(PriorFactorPose3, "gtsam::PriorFactorPose3"); BOOST_CLASS_EXPORT_GUID(PriorFactorCal3_S2, "gtsam::PriorFactorCal3_S2"); BOOST_CLASS_EXPORT_GUID(PriorFactorCal3DS2, "gtsam::PriorFactorCal3DS2"); BOOST_CLASS_EXPORT_GUID(PriorFactorCalibratedCamera, "gtsam::PriorFactorCalibratedCamera"); -BOOST_CLASS_EXPORT_GUID(PriorFactorSimpleCamera, "gtsam::PriorFactorSimpleCamera"); BOOST_CLASS_EXPORT_GUID(PriorFactorStereoCamera, "gtsam::PriorFactorStereoCamera"); BOOST_CLASS_EXPORT_GUID(BetweenFactorLieVector, "gtsam::BetweenFactorLieVector"); @@ -174,7 +168,6 @@ BOOST_CLASS_EXPORT_GUID(NonlinearEqualityPose3, "gtsam::NonlinearEqualityPose3") BOOST_CLASS_EXPORT_GUID(NonlinearEqualityCal3_S2, "gtsam::NonlinearEqualityCal3_S2"); BOOST_CLASS_EXPORT_GUID(NonlinearEqualityCal3DS2, "gtsam::NonlinearEqualityCal3DS2"); BOOST_CLASS_EXPORT_GUID(NonlinearEqualityCalibratedCamera, "gtsam::NonlinearEqualityCalibratedCamera"); -BOOST_CLASS_EXPORT_GUID(NonlinearEqualitySimpleCamera, "gtsam::NonlinearEqualitySimpleCamera"); BOOST_CLASS_EXPORT_GUID(NonlinearEqualityStereoCamera, "gtsam::NonlinearEqualityStereoCamera"); BOOST_CLASS_EXPORT_GUID(RangeFactor2D, "gtsam::RangeFactor2D"); @@ -182,9 +175,7 @@ BOOST_CLASS_EXPORT_GUID(RangeFactor3D, "gtsam::RangeFactor3D"); BOOST_CLASS_EXPORT_GUID(RangeFactorPose2, "gtsam::RangeFactorPose2"); BOOST_CLASS_EXPORT_GUID(RangeFactorPose3, "gtsam::RangeFactorPose3"); BOOST_CLASS_EXPORT_GUID(RangeFactorCalibratedCameraPoint, "gtsam::RangeFactorCalibratedCameraPoint"); -BOOST_CLASS_EXPORT_GUID(RangeFactorSimpleCameraPoint, "gtsam::RangeFactorSimpleCameraPoint"); BOOST_CLASS_EXPORT_GUID(RangeFactorCalibratedCamera, "gtsam::RangeFactorCalibratedCamera"); -BOOST_CLASS_EXPORT_GUID(RangeFactorSimpleCamera, "gtsam::RangeFactorSimpleCamera"); BOOST_CLASS_EXPORT_GUID(BearingRangeFactor2D, "gtsam::BearingRangeFactor2D"); @@ -192,12 +183,28 @@ BOOST_CLASS_EXPORT_GUID(GenericProjectionFactorCal3_S2, "gtsam::GenericProjectio BOOST_CLASS_EXPORT_GUID(GenericProjectionFactorCal3DS2, "gtsam::GenericProjectionFactorCal3DS2"); BOOST_CLASS_EXPORT_GUID(GeneralSFMFactorCal3_S2, "gtsam::GeneralSFMFactorCal3_S2"); -//BOOST_CLASS_EXPORT_GUID(GeneralSFMFactorCal3DS2, "gtsam::GeneralSFMFactorCal3DS2"); +BOOST_CLASS_EXPORT_GUID(GeneralSFMFactorCal3DS2, "gtsam::GeneralSFMFactorCal3DS2"); BOOST_CLASS_EXPORT_GUID(GeneralSFMFactor2Cal3_S2, "gtsam::GeneralSFMFactor2Cal3_S2"); BOOST_CLASS_EXPORT_GUID(GenericStereoFactor3D, "gtsam::GenericStereoFactor3D"); +#ifdef GTSAM_ALLOW_DEPRECATED_SINCE_V41 + +typedef PriorFactor PriorFactorSimpleCamera; +typedef NonlinearEquality NonlinearEqualitySimpleCamera; +typedef RangeFactor RangeFactorSimpleCameraPoint; +typedef RangeFactor RangeFactorSimpleCamera; + +GTSAM_VALUE_EXPORT(gtsam::SimpleCamera); +BOOST_CLASS_EXPORT_GUID(PriorFactorSimpleCamera, "gtsam::PriorFactorSimpleCamera"); +BOOST_CLASS_EXPORT_GUID(NonlinearEqualitySimpleCamera, "gtsam::NonlinearEqualitySimpleCamera"); +BOOST_CLASS_EXPORT_GUID(RangeFactorSimpleCameraPoint, "gtsam::RangeFactorSimpleCameraPoint"); +BOOST_CLASS_EXPORT_GUID(RangeFactorSimpleCamera, "gtsam::RangeFactorSimpleCamera"); + +#endif + + /* ************************************************************************* */ // Actual implementations of functions /* ************************************************************************* */ diff --git a/matlab/+gtsam/Contents.m b/matlab/+gtsam/Contents.m index 035e7e509..fb6d3081e 100644 --- a/matlab/+gtsam/Contents.m +++ b/matlab/+gtsam/Contents.m @@ -99,6 +99,7 @@ % %% SLAM and SFM % BearingFactor2D - class BearingFactor2D, see Doxygen page for details +% BearingFactor3D - class BearingFactor3D, see Doxygen page for details % BearingRangeFactor2D - class BearingRangeFactor2D, see Doxygen page for details % BetweenFactorLieMatrix - class BetweenFactorLieMatrix, see Doxygen page for details % BetweenFactorLieScalar - class BetweenFactorLieScalar, see Doxygen page for details diff --git a/python/CMakeLists.txt b/python/CMakeLists.txt index 00b537340..b50701464 100644 --- a/python/CMakeLists.txt +++ b/python/CMakeLists.txt @@ -4,20 +4,26 @@ if (NOT GTSAM_BUILD_PYTHON) return() endif() -# Common directory for storing data/datasets stored with the package. -# This will store the data in the Python site package directly. -set(GTSAM_PYTHON_DATASET_DIR "./gtsam/Data") - # Generate setup.py. file(READ "${PROJECT_SOURCE_DIR}/README.md" README_CONTENTS) configure_file(${PROJECT_SOURCE_DIR}/python/setup.py.in ${GTSAM_PYTHON_BUILD_DIRECTORY}/setup.py) -set(WRAP_USE_CUSTOM_PYTHON_LIBRARY ${GTSAM_USE_CUSTOM_PYTHON_LIBRARY}) -set(WRAP_PYTHON_VERSION ${GTSAM_PYTHON_VERSION}) +# Supply MANIFEST.in for older versions of Python +file(COPY ${PROJECT_SOURCE_DIR}/python/MANIFEST.in + DESTINATION ${GTSAM_PYTHON_BUILD_DIRECTORY}) include(PybindWrap) +############################################################ +## Load the necessary files to compile the wrapper + +# Load the pybind11 code +add_subdirectory(${PROJECT_SOURCE_DIR}/wrap/pybind11 pybind11) +# Set the wrapping script variable +set(PYBIND_WRAP_SCRIPT "${PROJECT_SOURCE_DIR}/wrap/scripts/pybind_wrap.py") +############################################################ + add_custom_target(gtsam_header DEPENDS "${PROJECT_SOURCE_DIR}/gtsam/gtsam.i") add_custom_target(gtsam_unstable_header DEPENDS "${PROJECT_SOURCE_DIR}/gtsam_unstable/gtsam_unstable.i") @@ -67,53 +73,68 @@ set(GTSAM_MODULE_PATH ${GTSAM_PYTHON_BUILD_DIRECTORY}/gtsam) create_symlinks("${CMAKE_CURRENT_SOURCE_DIR}/gtsam" "${GTSAM_MODULE_PATH}") +# Common directory for data/datasets stored with the package. +# This will store the data in the Python site package directly. +file(COPY "${GTSAM_SOURCE_DIR}/examples/Data" DESTINATION "${GTSAM_MODULE_PATH}") + +# Add gtsam as a dependency to the install target +set(GTSAM_PYTHON_DEPENDENCIES gtsam_py) + + if(GTSAM_UNSTABLE_BUILD_PYTHON) -set(ignore - gtsam::Point2 - gtsam::Point3 - gtsam::LieVector - gtsam::LieMatrix - gtsam::ISAM2ThresholdMapValue - gtsam::FactorIndices - gtsam::FactorIndexSet - gtsam::BetweenFactorPose3s - gtsam::Point2Vector - gtsam::Pose3Vector - gtsam::KeyVector - gtsam::FixedLagSmootherKeyTimestampMapValue - gtsam::BinaryMeasurementsUnit3 - gtsam::KeyPairDoubleMap) - -pybind_wrap(gtsam_unstable_py # target - ${PROJECT_SOURCE_DIR}/gtsam_unstable/gtsam_unstable.i # interface_header - "gtsam_unstable.cpp" # generated_cpp - "gtsam_unstable" # module_name - "gtsam" # top_namespace - "${ignore}" # ignore_classes - ${PROJECT_SOURCE_DIR}/python/gtsam_unstable/gtsam_unstable.tpl - gtsam_unstable # libs - "gtsam_unstable;gtsam_unstable_header" # dependencies - ON # use_boost - ) + set(ignore + gtsam::Point2 + gtsam::Point3 + gtsam::LieVector + gtsam::LieMatrix + gtsam::ISAM2ThresholdMapValue + gtsam::FactorIndices + gtsam::FactorIndexSet + gtsam::BetweenFactorPose3s + gtsam::Point2Vector + gtsam::Pose3Vector + gtsam::KeyVector + gtsam::FixedLagSmootherKeyTimestampMapValue + gtsam::BinaryMeasurementsUnit3 + gtsam::CameraSetCal3_S2 + gtsam::CameraSetCal3Bundler + gtsam::KeyPairDoubleMap) + + pybind_wrap(gtsam_unstable_py # target + ${PROJECT_SOURCE_DIR}/gtsam_unstable/gtsam_unstable.i # interface_header + "gtsam_unstable.cpp" # generated_cpp + "gtsam_unstable" # module_name + "gtsam" # top_namespace + "${ignore}" # ignore_classes + ${PROJECT_SOURCE_DIR}/python/gtsam_unstable/gtsam_unstable.tpl + gtsam_unstable # libs + "gtsam_unstable;gtsam_unstable_header" # dependencies + ON # use_boost + ) -set_target_properties(gtsam_unstable_py PROPERTIES - INSTALL_RPATH "${CMAKE_INSTALL_PREFIX}/lib" - INSTALL_RPATH_USE_LINK_PATH TRUE - OUTPUT_NAME "gtsam_unstable" - LIBRARY_OUTPUT_DIRECTORY "${GTSAM_PYTHON_BUILD_DIRECTORY}/gtsam_unstable" - DEBUG_POSTFIX "" # Otherwise you will have a wrong name - RELWITHDEBINFO_POSTFIX "" # Otherwise you will have a wrong name - ) + set_target_properties(gtsam_unstable_py PROPERTIES + INSTALL_RPATH "${CMAKE_INSTALL_PREFIX}/lib" + INSTALL_RPATH_USE_LINK_PATH TRUE + OUTPUT_NAME "gtsam_unstable" + LIBRARY_OUTPUT_DIRECTORY "${GTSAM_PYTHON_BUILD_DIRECTORY}/gtsam_unstable" + DEBUG_POSTFIX "" # Otherwise you will have a wrong name + RELWITHDEBINFO_POSTFIX "" # Otherwise you will have a wrong name + ) -set(GTSAM_UNSTABLE_MODULE_PATH ${GTSAM_PYTHON_BUILD_DIRECTORY}/gtsam_unstable) + set(GTSAM_UNSTABLE_MODULE_PATH ${GTSAM_PYTHON_BUILD_DIRECTORY}/gtsam_unstable) + + # Symlink all tests .py files to build folder. + create_symlinks("${CMAKE_CURRENT_SOURCE_DIR}/gtsam_unstable" + "${GTSAM_UNSTABLE_MODULE_PATH}") + + # Add gtsam_unstable to the install target + list(APPEND GTSAM_PYTHON_DEPENDENCIES gtsam_unstable_py) -# Symlink all tests .py files to build folder. -create_symlinks("${CMAKE_CURRENT_SOURCE_DIR}/gtsam_unstable" - "${GTSAM_UNSTABLE_MODULE_PATH}") endif() +# Add custom target so we can install with `make python-install` set(GTSAM_PYTHON_INSTALL_TARGET python-install) add_custom_target(${GTSAM_PYTHON_INSTALL_TARGET} COMMAND ${PYTHON_EXECUTABLE} ${GTSAM_PYTHON_BUILD_DIRECTORY}/setup.py install - DEPENDS gtsam_py gtsam_unstable_py + DEPENDS ${GTSAM_PYTHON_DEPENDENCIES} WORKING_DIRECTORY ${GTSAM_PYTHON_BUILD_DIRECTORY}) diff --git a/python/MANIFEST.in b/python/MANIFEST.in new file mode 100644 index 000000000..41d7f0c59 --- /dev/null +++ b/python/MANIFEST.in @@ -0,0 +1 @@ +recursive-include gtsam/Data * diff --git a/python/gtsam/preamble.h b/python/gtsam/preamble.h index 6166f615e..b56766c72 100644 --- a/python/gtsam/preamble.h +++ b/python/gtsam/preamble.h @@ -10,3 +10,5 @@ PYBIND11_MAKE_OPAQUE(std::vector); PYBIND11_MAKE_OPAQUE(std::vector > >); PYBIND11_MAKE_OPAQUE(std::vector > >); PYBIND11_MAKE_OPAQUE(std::vector); +PYBIND11_MAKE_OPAQUE(gtsam::CameraSet >); +PYBIND11_MAKE_OPAQUE(gtsam::CameraSet >); diff --git a/python/gtsam/specializations.h b/python/gtsam/specializations.h index cacad874c..431697aac 100644 --- a/python/gtsam/specializations.h +++ b/python/gtsam/specializations.h @@ -13,3 +13,5 @@ py::bind_vector > >(m_, "Bina py::bind_map(m_, "IndexPairSetMap"); py::bind_vector(m_, "IndexPairVector"); py::bind_map(m_, "KeyPairDoubleMap"); +py::bind_vector > >(m_, "CameraSetCal3_S2"); +py::bind_vector > >(m_, "CameraSetCal3Bundler"); diff --git a/python/gtsam/tests/test_SimpleCamera.py b/python/gtsam/tests/test_SimpleCamera.py index efdfec561..358eb1f48 100644 --- a/python/gtsam/tests/test_SimpleCamera.py +++ b/python/gtsam/tests/test_SimpleCamera.py @@ -14,11 +14,12 @@ import unittest import numpy as np import gtsam -from gtsam import Cal3_S2, Point3, Pose2, Pose3, Rot3, SimpleCamera +from gtsam import Cal3_S2, Point3, Pose2, Pose3, Rot3, PinholeCameraCal3_S2 as SimpleCamera from gtsam.utils.test_case import GtsamTestCase K = Cal3_S2(625, 625, 0, 0, 0) + class TestSimpleCamera(GtsamTestCase): def test_constructor(self): @@ -29,15 +30,15 @@ class TestSimpleCamera(GtsamTestCase): def test_level2(self): # Create a level camera, looking in Y-direction - pose2 = Pose2(0.4,0.3,math.pi/2.0) + pose2 = Pose2(0.4, 0.3, math.pi/2.0) camera = SimpleCamera.Level(K, pose2, 0.1) # expected - x = Point3(1,0,0) - y = Point3(0,0,-1) - z = Point3(0,1,0) - wRc = Rot3(x,y,z) - expected = Pose3(wRc,Point3(0.4,0.3,0.1)) + x = Point3(1, 0, 0) + y = Point3(0, 0, -1) + z = Point3(0, 1, 0) + wRc = Rot3(x, y, z) + expected = Pose3(wRc, Point3(0.4, 0.3, 0.1)) self.gtsamAssertEquals(camera.pose(), expected, 1e-9) diff --git a/python/gtsam/tests/test_Triangulation.py b/python/gtsam/tests/test_Triangulation.py index b43ad9b57..399cf019d 100644 --- a/python/gtsam/tests/test_Triangulation.py +++ b/python/gtsam/tests/test_Triangulation.py @@ -12,69 +12,123 @@ import unittest import numpy as np -import gtsam as g +import gtsam +from gtsam import (Cal3_S2, Cal3Bundler, CameraSetCal3_S2, + CameraSetCal3Bundler, PinholeCameraCal3_S2, + PinholeCameraCal3Bundler, Point2Vector, Point3, Pose3, + Pose3Vector, Rot3) from gtsam.utils.test_case import GtsamTestCase -from gtsam import Cal3_S2, Cal3Bundler, Rot3, Pose3, \ - PinholeCameraCal3_S2, Point3, Point2Vector, Pose3Vector, triangulatePoint3 + class TestVisualISAMExample(GtsamTestCase): - def test_TriangulationExample(self): - # Some common constants - sharedCal = Cal3_S2(1500, 1200, 0, 640, 480) + """ Tests for triangulation with shared and individual calibrations """ + def setUp(self): + """ Set up two camera poses """ # Looking along X-axis, 1 meter above ground plane (x-y) upright = Rot3.Ypr(-np.pi / 2, 0., -np.pi / 2) pose1 = Pose3(upright, Point3(0, 0, 1)) - camera1 = PinholeCameraCal3_S2(pose1, sharedCal) # create second camera 1 meter to the right of first camera pose2 = pose1.compose(Pose3(Rot3(), Point3(1, 0, 0))) - camera2 = PinholeCameraCal3_S2(pose2, sharedCal) + # twoPoses + self.poses = Pose3Vector() + self.poses.append(pose1) + self.poses.append(pose2) # landmark ~5 meters infront of camera - landmark = Point3(5, 0.5, 1.2) + self.landmark = Point3(5, 0.5, 1.2) - # 1. Project two landmarks into two cameras and triangulate - z1 = camera1.project(landmark) - z2 = camera2.project(landmark) + def generate_measurements(self, calibration, camera_model, cal_params, camera_set=None): + """ + Generate vector of measurements for given calibration and camera model. - # twoPoses - poses = Pose3Vector() + Args: + calibration: Camera calibration e.g. Cal3_S2 + camera_model: Camera model e.g. PinholeCameraCal3_S2 + cal_params: Iterable of camera parameters for `calibration` e.g. [K1, K2] + camera_set: Cameraset object (for individual calibrations) + Returns: + list of measurements and list/CameraSet object for cameras + """ + if camera_set is not None: + cameras = camera_set() + else: + cameras = [] measurements = Point2Vector() - poses.append(pose1) - poses.append(pose2) - measurements.append(z1) - measurements.append(z2) + for k, pose in zip(cal_params, self.poses): + K = calibration(*k) + camera = camera_model(pose, K) + cameras.append(camera) + z = camera.project(self.landmark) + measurements.append(z) - optimize = True - rank_tol = 1e-9 + return measurements, cameras - triangulated_landmark = triangulatePoint3(poses,sharedCal, measurements, rank_tol, optimize) - self.gtsamAssertEquals(landmark, triangulated_landmark,1e-9) + def test_TriangulationExample(self): + """ Tests triangulation with shared Cal3_S2 calibration""" + # Some common constants + sharedCal = (1500, 1200, 0, 640, 480) - # 2. Add some noise and try again: result should be ~ (4.995, 0.499167, 1.19814) - measurements = Point2Vector() - measurements.append(z1 - np.array([0.1, 0.5])) - measurements.append(z2 - np.array([-0.2, 0.3])) + measurements, _ = self.generate_measurements(Cal3_S2, + PinholeCameraCal3_S2, + (sharedCal, sharedCal)) + + triangulated_landmark = gtsam.triangulatePoint3(self.poses, + Cal3_S2(sharedCal), + measurements, + rank_tol=1e-9, + optimize=True) + self.gtsamAssertEquals(self.landmark, triangulated_landmark, 1e-9) + + # Add some noise and try again: result should be ~ (4.995, 0.499167, 1.19814) + measurements_noisy = Point2Vector() + measurements_noisy.append(measurements[0] - np.array([0.1, 0.5])) + measurements_noisy.append(measurements[1] - np.array([-0.2, 0.3])) + + triangulated_landmark = gtsam.triangulatePoint3(self.poses, + Cal3_S2(sharedCal), + measurements_noisy, + rank_tol=1e-9, + optimize=True) + + self.gtsamAssertEquals(self.landmark, triangulated_landmark, 1e-2) + + def test_distinct_Ks(self): + """ Tests triangulation with individual Cal3_S2 calibrations """ + # two camera parameters + K1 = (1500, 1200, 0, 640, 480) + K2 = (1600, 1300, 0, 650, 440) + + measurements, cameras = self.generate_measurements(Cal3_S2, + PinholeCameraCal3_S2, + (K1, K2), + camera_set=CameraSetCal3_S2) + + triangulated_landmark = gtsam.triangulatePoint3(cameras, + measurements, + rank_tol=1e-9, + optimize=True) + self.gtsamAssertEquals(self.landmark, triangulated_landmark, 1e-9) + + def test_distinct_Ks_Bundler(self): + """ Tests triangulation with individual Cal3Bundler calibrations""" + # two camera parameters + K1 = (1500, 0, 0, 640, 480) + K2 = (1600, 0, 0, 650, 440) + + measurements, cameras = self.generate_measurements(Cal3Bundler, + PinholeCameraCal3Bundler, + (K1, K2), + camera_set=CameraSetCal3Bundler) + + triangulated_landmark = gtsam.triangulatePoint3(cameras, + measurements, + rank_tol=1e-9, + optimize=True) + self.gtsamAssertEquals(self.landmark, triangulated_landmark, 1e-9) - triangulated_landmark = triangulatePoint3(poses,sharedCal, measurements, rank_tol, optimize) - self.gtsamAssertEquals(landmark, triangulated_landmark,1e-2) - # - # # two Poses with Bundler Calibration - # bundlerCal = Cal3Bundler(1500, 0, 0, 640, 480) - # camera1 = PinholeCameraCal3Bundler(pose1, bundlerCal) - # camera2 = PinholeCameraCal3Bundler(pose2, bundlerCal) - # - # z1 = camera1.project(landmark) - # z2 = camera2.project(landmark) - # - # measurements = Point2Vector() - # measurements.append(z1) - # measurements.append(z2) - # - # triangulated_landmark = triangulatePoint3(poses,bundlerCal, measurements, rank_tol, optimize) - # self.gtsamAssertEquals(landmark, triangulated_landmark,1e-9) if __name__ == "__main__": unittest.main() diff --git a/python/gtsam/utils/plot.py b/python/gtsam/utils/plot.py index b2c2ab879..7f48d03a3 100644 --- a/python/gtsam/utils/plot.py +++ b/python/gtsam/utils/plot.py @@ -36,18 +36,15 @@ def set_axes_equal(fignum): ax.set_zlim3d([origin[2] - radius, origin[2] + radius]) -def ellipsoid(xc, yc, zc, rx, ry, rz, n): +def ellipsoid(rx, ry, rz, n): """ Numpy equivalent of Matlab's ellipsoid function. Args: - xc (double): Center of ellipsoid in X-axis. - yc (double): Center of ellipsoid in Y-axis. - zc (double): Center of ellipsoid in Z-axis. rx (double): Radius of ellipsoid in X-axis. ry (double): Radius of ellipsoid in Y-axis. rz (double): Radius of ellipsoid in Z-axis. - n (int): The granularity of the ellipsoid plotted. + n (int): The granularity of the ellipsoid plotted. Returns: tuple[numpy.ndarray]: The points in the x, y and z axes to use for the surface plot. @@ -72,7 +69,8 @@ def plot_covariance_ellipse_3d(axes, origin, P, scale=1, n=8, alpha=0.5): Args: axes (matplotlib.axes.Axes): Matplotlib axes. origin (gtsam.Point3): The origin in the world frame. - P (numpy.ndarray): The marginal covariance matrix of the 3D point which will be represented as an ellipse. + P (numpy.ndarray): The marginal covariance matrix of the 3D point + which will be represented as an ellipse. scale (float): Scaling factor of the radii of the covariance ellipse. n (int): Defines the granularity of the ellipse. Higher values indicate finer ellipses. alpha (float): Transparency value for the plotted surface in the range [0, 1]. @@ -85,7 +83,7 @@ def plot_covariance_ellipse_3d(axes, origin, P, scale=1, n=8, alpha=0.5): rx, ry, rz = radii # generate data for "unrotated" ellipsoid - xc, yc, zc = ellipsoid(0, 0, 0, rx, ry, rz, n) + xc, yc, zc = ellipsoid(rx, ry, rz, n) # rotate data with orientation matrix U and center c data = np.kron(U[:, 0:1], xc) + np.kron(U[:, 1:2], yc) + \ @@ -106,7 +104,8 @@ def plot_pose2_on_axes(axes, pose, axis_length=0.1, covariance=None): axes (matplotlib.axes.Axes): Matplotlib axes. pose (gtsam.Pose2): The pose to be plotted. axis_length (float): The length of the camera axes. - covariance (numpy.ndarray): Marginal covariance matrix to plot the uncertainty of the estimation. + covariance (numpy.ndarray): Marginal covariance matrix to plot + the uncertainty of the estimation. """ # get rotation and translation (center) gRp = pose.rotation().matrix() # rotation from pose to global @@ -146,7 +145,8 @@ def plot_pose2(fignum, pose, axis_length=0.1, covariance=None, fignum (int): Integer representing the figure number to use for plotting. pose (gtsam.Pose2): The pose to be plotted. axis_length (float): The length of the camera axes. - covariance (numpy.ndarray): Marginal covariance matrix to plot the uncertainty of the estimation. + covariance (numpy.ndarray): Marginal covariance matrix to plot + the uncertainty of the estimation. axis_labels (iterable[string]): List of axis labels to set. """ # get figure object @@ -215,7 +215,8 @@ def plot_3d_points(fignum, values, linespec="g*", marginals=None, fignum (int): Integer representing the figure number to use for plotting. values (gtsam.Values): Values dictionary consisting of points to be plotted. linespec (string): String representing formatting options for Matplotlib. - marginals (numpy.ndarray): Marginal covariance matrix to plot the uncertainty of the estimation. + marginals (numpy.ndarray): Marginal covariance matrix to plot the + uncertainty of the estimation. title (string): The title of the plot. axis_labels (iterable[string]): List of axis labels to set. """ @@ -238,6 +239,7 @@ def plot_3d_points(fignum, values, linespec="g*", marginals=None, continue # I guess it's not a Point3 + fig = plt.figure(fignum) fig.suptitle(title) fig.canvas.set_window_title(title.lower()) diff --git a/python/setup.py.in b/python/setup.py.in index 1ffe978f3..9aa4b71f4 100644 --- a/python/setup.py.in +++ b/python/setup.py.in @@ -1,6 +1,4 @@ -import glob -import os -import sys +"""Setup file to install the GTSAM package.""" try: from setuptools import setup, find_packages @@ -10,19 +8,17 @@ except ImportError: packages = find_packages(where=".") print("PACKAGES: ", packages) -data_path = '${GTSAM_SOURCE_DIR}/examples/Data/' -data_files_and_directories = glob.glob(data_path + '**', recursive=True) -data_files = [x for x in data_files_and_directories if not os.path.isdir(x)] - package_data = { '': [ - './*.so', - './*.dll', + "./*.so", + "./*.dll", + "Data/*" # Add the data files to the package + "Data/**/*" # Add the data files in subdirectories ] } # Cleaner to read in the contents rather than copy them over. -readme_contents = open("${PROJECT_SOURCE_DIR}/README.md").read() +readme_contents = open("${GTSAM_SOURCE_DIR}/README.md").read() setup( name='gtsam', @@ -49,9 +45,9 @@ setup( 'Programming Language :: Python :: 3', ], packages=packages, + include_package_data=True, package_data=package_data, - data_files=[('${GTSAM_PYTHON_DATASET_DIR}', data_files),], test_suite="gtsam.tests", - install_requires=["numpy"], + install_requires=open("${GTSAM_SOURCE_DIR}/python/requirements.txt").readlines(), zip_safe=False, ) diff --git a/tests/ImuMeasurement.h b/tests/ImuMeasurement.h new file mode 100644 index 000000000..d49759545 --- /dev/null +++ b/tests/ImuMeasurement.h @@ -0,0 +1,35 @@ +#pragma once + +#include + +namespace gtsam { + +/** + *\brief Contains data from the IMU mesaurements. + */ +class ImuMeasurement : public Measurement { + public: + enum Name { BODY = 0, RF_FOOT = 1, RH_FOOT = 2 }; + + Name name; ///< Unique string identifier + Eigen::Vector3d I_a_WI; ///< Raw acceleration from the IMU (m/s/s) + Eigen::Vector3d I_w_WI; ///< Raw angular velocity from the IMU (rad/s) + + ImuMeasurement() + : Measurement("ImuMeasurement"), I_a_WI{0, 0, 0}, I_w_WI{0, 0, 0} {} + + virtual ~ImuMeasurement() override {} + + friend std::ostream& operator<<(std::ostream& stream, + const ImuMeasurement& meas); +}; + +std::ostream& operator<<(std::ostream& stream, const ImuMeasurement& meas) { + stream << "IMU Measurement at time = " << meas.time << " : \n" + << "dt : " << meas.dt << "\n" + << "I_a_WI: " << meas.I_a_WI.transpose() << "\n" + << "I_w_WI: " << meas.I_w_WI.transpose() << "\n"; + return stream; +} + +} // namespace gtsam diff --git a/tests/Measurement.h b/tests/Measurement.h new file mode 100644 index 000000000..be38ac4f3 --- /dev/null +++ b/tests/Measurement.h @@ -0,0 +1,25 @@ +#pragma once + +#include +#include + +namespace gtsam { + +/** + * \brief This is the base class for all measurement types. + */ +class Measurement { + public: + EIGEN_MAKE_ALIGNED_OPERATOR_NEW + size_t dt; ///< Time since the last message of this type (nanoseconds). + size_t time; ///< ROS time message recieved (nanoseconds). + ///< The type of message (to enable dynamic/static casting). + std::string type; + + Measurement() : dt(0), time(0), type("UNDEFINED") {} + Measurement(std::string _type) : dt(0), time(0), type(_type) {} + + virtual ~Measurement() {} +}; + +} // namespace gtsam diff --git a/tests/smallExample.h b/tests/smallExample.h index 0c933d106..944899e70 100644 --- a/tests/smallExample.h +++ b/tests/smallExample.h @@ -342,10 +342,25 @@ struct UnaryFactor: public gtsam::NoiseModelFactor1 { return (h(x) - z_); } + gtsam::NonlinearFactor::shared_ptr clone() const override { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new UnaryFactor(*this))); } }; } +/* ************************************************************************* */ +inline NonlinearFactorGraph nonlinearFactorGraphWithGivenSigma(const double sigma) { + using symbol_shorthand::X; + using symbol_shorthand::L; + boost::shared_ptr fg(new NonlinearFactorGraph); + Point2 z(1.0, 0.0); + boost::shared_ptr factor( + new smallOptimize::UnaryFactor(z, noiseModel::Isotropic::Sigma(2,sigma), X(1))); + fg->push_back(factor); + return *fg; +} + /* ************************************************************************* */ inline boost::shared_ptr sharedReallyNonlinearFactorGraph() { using symbol_shorthand::X; @@ -363,6 +378,54 @@ inline NonlinearFactorGraph createReallyNonlinearFactorGraph() { return *sharedReallyNonlinearFactorGraph(); } +/* ************************************************************************* */ +inline NonlinearFactorGraph sharedNonRobustFactorGraphWithOutliers() { + using symbol_shorthand::X; + boost::shared_ptr fg(new NonlinearFactorGraph); + Point2 z(0.0, 0.0); + double sigma = 0.1; + + boost::shared_ptr> factor( + new PriorFactor(X(1), z, noiseModel::Isotropic::Sigma(2,sigma))); + // 3 noiseless inliers + fg->push_back(factor); + fg->push_back(factor); + fg->push_back(factor); + + // 1 outlier + Point2 z_out(1.0, 0.0); + boost::shared_ptr> factor_out( + new PriorFactor(X(1), z_out, noiseModel::Isotropic::Sigma(2,sigma))); + fg->push_back(factor_out); + + return *fg; +} + +/* ************************************************************************* */ +inline NonlinearFactorGraph sharedRobustFactorGraphWithOutliers() { + using symbol_shorthand::X; + boost::shared_ptr fg(new NonlinearFactorGraph); + Point2 z(0.0, 0.0); + double sigma = 0.1; + auto gmNoise = noiseModel::Robust::Create( + noiseModel::mEstimator::GemanMcClure::Create(1.0), noiseModel::Isotropic::Sigma(2,sigma)); + boost::shared_ptr> factor( + new PriorFactor(X(1), z, gmNoise)); + // 3 noiseless inliers + fg->push_back(factor); + fg->push_back(factor); + fg->push_back(factor); + + // 1 outlier + Point2 z_out(1.0, 0.0); + boost::shared_ptr> factor_out( + new PriorFactor(X(1), z_out, gmNoise)); + fg->push_back(factor_out); + + return *fg; +} + + /* ************************************************************************* */ inline std::pair createNonlinearSmoother(int T) { using namespace impl; diff --git a/tests/testGncOptimizer.cpp b/tests/testGncOptimizer.cpp new file mode 100644 index 000000000..738c77936 --- /dev/null +++ b/tests/testGncOptimizer.cpp @@ -0,0 +1,640 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file testGncOptimizer.cpp + * @brief Unit tests for GncOptimizer class + * @author Jingnan Shi + * @author Luca Carlone + * @author Frank Dellaert + * + * Implementation of the paper: Yang, Antonante, Tzoumas, Carlone, "Graduated + * Non-Convexity for Robust Spatial Perception: From Non-Minimal Solvers to + * Global Outlier Rejection", ICRA/RAL, 2020. (arxiv version: + * https://arxiv.org/pdf/1909.08605.pdf) + * + * See also: + * Antonante, Tzoumas, Yang, Carlone, "Outlier-Robust Estimation: Hardness, + * Minimally-Tuned Algorithms, and Applications", arxiv: + * https://arxiv.org/pdf/2007.15109.pdf, 2020. + */ + +#include +#include +#include +#include +#include + +using namespace std; +using namespace gtsam; + +using symbol_shorthand::L; +using symbol_shorthand::X; +static double tol = 1e-7; + +/* ************************************************************************* */ +TEST(GncOptimizer, gncParamsConstructor) { + // check params are correctly parsed + LevenbergMarquardtParams lmParams; + GncParams gncParams1(lmParams); + CHECK(lmParams.equals(gncParams1.baseOptimizerParams)); + + // check also default constructor + GncParams gncParams1b; + CHECK(lmParams.equals(gncParams1b.baseOptimizerParams)); + + // and check params become different if we change lmParams + lmParams.setVerbosity("DELTA"); + CHECK(!lmParams.equals(gncParams1.baseOptimizerParams)); + + // and same for GN + GaussNewtonParams gnParams; + GncParams gncParams2(gnParams); + CHECK(gnParams.equals(gncParams2.baseOptimizerParams)); + + // check default constructor + GncParams gncParams2b; + CHECK(gnParams.equals(gncParams2b.baseOptimizerParams)); + + // change something at the gncParams level + GncParams gncParams2c(gncParams2b); + gncParams2c.setLossType(GncLossType::GM); + CHECK(!gncParams2c.equals(gncParams2b.baseOptimizerParams)); +} + +/* ************************************************************************* */ +TEST(GncOptimizer, gncConstructor) { + // has to have Gaussian noise models ! + auto fg = example::createReallyNonlinearFactorGraph(); // just a unary factor + // on a 2D point + + Point2 p0(3, 3); + Values initial; + initial.insert(X(1), p0); + + GncParams gncParams; + auto gnc = GncOptimizer>(fg, initial, + gncParams); + + CHECK(gnc.getFactors().equals(fg)); + CHECK(gnc.getState().equals(initial)); + CHECK(gnc.getParams().equals(gncParams)); +} + +/* ************************************************************************* */ +TEST(GncOptimizer, gncConstructorWithRobustGraphAsInput) { + auto fg = example::sharedNonRobustFactorGraphWithOutliers(); + // same graph with robust noise model + auto fg_robust = example::sharedRobustFactorGraphWithOutliers(); + + Point2 p0(3, 3); + Values initial; + initial.insert(X(1), p0); + + GncParams gncParams; + auto gnc = GncOptimizer>(fg_robust, + initial, + gncParams); + + // make sure that when parsing the graph is transformed into one without + // robust loss + CHECK(fg.equals(gnc.getFactors())); +} + +/* ************************************************************************* */ +TEST(GncOptimizer, initializeMu) { + auto fg = example::createReallyNonlinearFactorGraph(); + + Point2 p0(3, 3); + Values initial; + initial.insert(X(1), p0); + + // testing GM mu initialization + GncParams gncParams; + gncParams.setLossType(GncLossType::GM); + auto gnc_gm = GncOptimizer>(fg, initial, + gncParams); + // according to rmk 5 in the gnc paper: m0 = 2 rmax^2 / barcSq + // (barcSq=1 in this example) + EXPECT_DOUBLES_EQUAL(gnc_gm.initializeMu(), 2 * 198.999, 1e-3); + + // testing TLS mu initialization + gncParams.setLossType(GncLossType::TLS); + auto gnc_tls = GncOptimizer>(fg, initial, + gncParams); + // according to rmk 5 in the gnc paper: m0 = barcSq / (2 * rmax^2 - barcSq) + // (barcSq=1 in this example) + EXPECT_DOUBLES_EQUAL(gnc_tls.initializeMu(), 1 / (2 * 198.999 - 1), 1e-3); +} + +/* ************************************************************************* */ +TEST(GncOptimizer, updateMuGM) { + // has to have Gaussian noise models ! + auto fg = example::createReallyNonlinearFactorGraph(); + + Point2 p0(3, 3); + Values initial; + initial.insert(X(1), p0); + + GncParams gncParams; + gncParams.setLossType(GncLossType::GM); + gncParams.setMuStep(1.4); + auto gnc = GncOptimizer>(fg, initial, + gncParams); + + double mu = 5.0; + EXPECT_DOUBLES_EQUAL(gnc.updateMu(mu), mu / 1.4, tol); + + // check it correctly saturates to 1 for GM + mu = 1.2; + EXPECT_DOUBLES_EQUAL(gnc.updateMu(mu), 1.0, tol); +} + +/* ************************************************************************* */ +TEST(GncOptimizer, updateMuTLS) { + // has to have Gaussian noise models ! + auto fg = example::createReallyNonlinearFactorGraph(); + + Point2 p0(3, 3); + Values initial; + initial.insert(X(1), p0); + + GncParams gncParams; + gncParams.setMuStep(1.4); + gncParams.setLossType(GncLossType::TLS); + auto gnc = GncOptimizer>(fg, initial, + gncParams); + + double mu = 5.0; + EXPECT_DOUBLES_EQUAL(gnc.updateMu(mu), mu * 1.4, tol); +} + +/* ************************************************************************* */ +TEST(GncOptimizer, checkMuConvergence) { + // has to have Gaussian noise models ! + auto fg = example::createReallyNonlinearFactorGraph(); + + Point2 p0(3, 3); + Values initial; + initial.insert(X(1), p0); + + { + GncParams gncParams; + gncParams.setLossType(GncLossType::GM); + auto gnc = GncOptimizer>(fg, initial, + gncParams); + + double mu = 1.0; + CHECK(gnc.checkMuConvergence(mu)); + } + { + GncParams gncParams; + gncParams.setLossType( + GncLossType::TLS); + auto gnc = GncOptimizer>(fg, initial, + gncParams); + + double mu = 1.0; + CHECK(!gnc.checkMuConvergence(mu)); //always false for TLS + } +} + +/* ************************************************************************* */ +TEST(GncOptimizer, checkCostConvergence) { + // has to have Gaussian noise models ! + auto fg = example::createReallyNonlinearFactorGraph(); + + Point2 p0(3, 3); + Values initial; + initial.insert(X(1), p0); + + { + GncParams gncParams; + gncParams.setRelativeCostTol(0.49); + auto gnc = GncOptimizer>(fg, initial, + gncParams); + + double prev_cost = 1.0; + double cost = 0.5; + // relative cost reduction = 0.5 > 0.49, hence checkCostConvergence = false + CHECK(!gnc.checkCostConvergence(cost, prev_cost)); + } + { + GncParams gncParams; + gncParams.setRelativeCostTol(0.51); + auto gnc = GncOptimizer>(fg, initial, + gncParams); + + double prev_cost = 1.0; + double cost = 0.5; + // relative cost reduction = 0.5 < 0.51, hence checkCostConvergence = true + CHECK(gnc.checkCostConvergence(cost, prev_cost)); + } +} + +/* ************************************************************************* */ +TEST(GncOptimizer, checkWeightsConvergence) { + // has to have Gaussian noise models ! + auto fg = example::createReallyNonlinearFactorGraph(); + + Point2 p0(3, 3); + Values initial; + initial.insert(X(1), p0); + + { + GncParams gncParams; + gncParams.setLossType(GncLossType::GM); + auto gnc = GncOptimizer>(fg, initial, + gncParams); + + Vector weights = Vector::Ones(fg.size()); + CHECK(!gnc.checkWeightsConvergence(weights)); //always false for GM + } + { + GncParams gncParams; + gncParams.setLossType( + GncLossType::TLS); + auto gnc = GncOptimizer>(fg, initial, + gncParams); + + Vector weights = Vector::Ones(fg.size()); + // weights are binary, so checkWeightsConvergence = true + CHECK(gnc.checkWeightsConvergence(weights)); + } + { + GncParams gncParams; + gncParams.setLossType( + GncLossType::TLS); + auto gnc = GncOptimizer>(fg, initial, + gncParams); + + Vector weights = Vector::Ones(fg.size()); + weights[0] = 0.9; // more than weightsTol = 1e-4 from 1, hence checkWeightsConvergence = false + CHECK(!gnc.checkWeightsConvergence(weights)); + } + { + GncParams gncParams; + gncParams.setLossType( + GncLossType::TLS); + gncParams.setWeightsTol(0.1); + auto gnc = GncOptimizer>(fg, initial, + gncParams); + + Vector weights = Vector::Ones(fg.size()); + weights[0] = 0.9; // exactly weightsTol = 0.1 from 1, hence checkWeightsConvergence = true + CHECK(gnc.checkWeightsConvergence(weights)); + } +} + +/* ************************************************************************* */ +TEST(GncOptimizer, checkConvergenceTLS) { + // has to have Gaussian noise models ! + auto fg = example::createReallyNonlinearFactorGraph(); + + Point2 p0(3, 3); + Values initial; + initial.insert(X(1), p0); + + GncParams gncParams; + gncParams.setRelativeCostTol(1e-5); + gncParams.setLossType(GncLossType::TLS); + auto gnc = GncOptimizer>(fg, initial, + gncParams); + + CHECK(gnc.checkCostConvergence(1.0, 1.0)); + CHECK(!gnc.checkCostConvergence(1.0, 2.0)); +} + +/* ************************************************************************* */ +TEST(GncOptimizer, calculateWeightsGM) { + auto fg = example::sharedNonRobustFactorGraphWithOutliers(); + + Point2 p0(0, 0); + Values initial; + initial.insert(X(1), p0); + + // we have 4 factors, 3 with zero errors (inliers), 1 with error 50 = 0.5 * + // 1/sigma^2 || [1;0] - [0;0] ||^2 (outlier) + Vector weights_expected = Vector::Zero(4); + weights_expected[0] = 1.0; // zero error + weights_expected[1] = 1.0; // zero error + weights_expected[2] = 1.0; // zero error + weights_expected[3] = std::pow(1.0 / (50.0 + 1.0), 2); // outlier, error = 50 + + GaussNewtonParams gnParams; + GncParams gncParams(gnParams); + gncParams.setLossType(GncLossType::GM); + auto gnc = GncOptimizer>(fg, initial, gncParams); + double mu = 1.0; + Vector weights_actual = gnc.calculateWeights(initial, mu); + CHECK(assert_equal(weights_expected, weights_actual, tol)); + + mu = 2.0; + double barcSq = 5.0; + weights_expected[3] = std::pow(mu * barcSq / (50.0 + mu * barcSq), 2); // outlier, error = 50 + gncParams.setInlierCostThreshold(barcSq); + auto gnc2 = GncOptimizer>(fg, initial, + gncParams); + weights_actual = gnc2.calculateWeights(initial, mu); + CHECK(assert_equal(weights_expected, weights_actual, tol)); +} + +/* ************************************************************************* */ +TEST(GncOptimizer, calculateWeightsTLS) { + auto fg = example::sharedNonRobustFactorGraphWithOutliers(); + + Point2 p0(0, 0); + Values initial; + initial.insert(X(1), p0); + + // we have 4 factors, 3 with zero errors (inliers), 1 with error + Vector weights_expected = Vector::Zero(4); + weights_expected[0] = 1.0; // zero error + weights_expected[1] = 1.0; // zero error + weights_expected[2] = 1.0; // zero error + weights_expected[3] = 0; // outliers + + GaussNewtonParams gnParams; + GncParams gncParams(gnParams); + gncParams.setLossType(GncLossType::TLS); + auto gnc = GncOptimizer>(fg, initial, gncParams); + double mu = 1.0; + Vector weights_actual = gnc.calculateWeights(initial, mu); + CHECK(assert_equal(weights_expected, weights_actual, tol)); +} + +/* ************************************************************************* */ +TEST(GncOptimizer, calculateWeightsTLS2) { + + // create values + Point2 x_val(0.0, 0.0); + Point2 x_prior(1.0, 0.0); + Values initial; + initial.insert(X(1), x_val); + + // create very simple factor graph with a single factor 0.5 * 1/sigma^2 * || x - [1;0] ||^2 + double sigma = 1; + SharedDiagonal noise = noiseModel::Diagonal::Sigmas(Vector2(sigma, sigma)); + NonlinearFactorGraph nfg; + nfg.add(PriorFactor(X(1), x_prior, noise)); + + // cost of the factor: + DOUBLES_EQUAL(0.5 * 1 / (sigma * sigma), nfg.error(initial), tol); + + // check the TLS weights are correct: CASE 1: residual below barcsq + { + // expected: + Vector weights_expected = Vector::Zero(1); + weights_expected[0] = 1.0; // inlier + // actual: + GaussNewtonParams gnParams; + GncParams gncParams(gnParams); + gncParams.setLossType(GncLossType::TLS); + gncParams.setInlierCostThreshold(0.51); // if inlier threshold is slightly larger than 0.5, then measurement is inlier + auto gnc = GncOptimizer>(nfg, initial, + gncParams); + double mu = 1e6; + Vector weights_actual = gnc.calculateWeights(initial, mu); + CHECK(assert_equal(weights_expected, weights_actual, tol)); + } + // check the TLS weights are correct: CASE 2: residual above barcsq + { + // expected: + Vector weights_expected = Vector::Zero(1); + weights_expected[0] = 0.0; // outlier + // actual: + GaussNewtonParams gnParams; + GncParams gncParams(gnParams); + gncParams.setLossType(GncLossType::TLS); + gncParams.setInlierCostThreshold(0.49); // if inlier threshold is slightly below 0.5, then measurement is outlier + auto gnc = GncOptimizer>(nfg, initial, + gncParams); + double mu = 1e6; // very large mu recovers original TLS cost + Vector weights_actual = gnc.calculateWeights(initial, mu); + CHECK(assert_equal(weights_expected, weights_actual, tol)); + } + // check the TLS weights are correct: CASE 2: residual at barcsq + { + // expected: + Vector weights_expected = Vector::Zero(1); + weights_expected[0] = 0.5; // undecided + // actual: + GaussNewtonParams gnParams; + GncParams gncParams(gnParams); + gncParams.setLossType(GncLossType::TLS); + gncParams.setInlierCostThreshold(0.5); // if inlier threshold is slightly below 0.5, then measurement is outlier + auto gnc = GncOptimizer>(nfg, initial, + gncParams); + double mu = 1e6; // very large mu recovers original TLS cost + Vector weights_actual = gnc.calculateWeights(initial, mu); + CHECK(assert_equal(weights_expected, weights_actual, 1e-5)); + } +} + +/* ************************************************************************* */ +TEST(GncOptimizer, makeWeightedGraph) { + // create original factor + double sigma1 = 0.1; + NonlinearFactorGraph nfg = example::nonlinearFactorGraphWithGivenSigma( + sigma1); + + // create expected + double sigma2 = 10; + NonlinearFactorGraph expected = example::nonlinearFactorGraphWithGivenSigma( + sigma2); + + // create weights + Vector weights = Vector::Ones(1); // original info:1/0.1^2 = 100. New info: 1/10^2 = 0.01. Ratio is 10-4 + weights[0] = 1e-4; + + // create actual + Point2 p0(3, 3); + Values initial; + initial.insert(X(1), p0); + + LevenbergMarquardtParams lmParams; + GncParams gncParams(lmParams); + auto gnc = GncOptimizer>(nfg, initial, + gncParams); + NonlinearFactorGraph actual = gnc.makeWeightedGraph(weights); + + // check it's all good + CHECK(assert_equal(expected, actual)); +} + +/* ************************************************************************* */ +TEST(GncOptimizer, optimizeSimple) { + auto fg = example::createReallyNonlinearFactorGraph(); + + Point2 p0(3, 3); + Values initial; + initial.insert(X(1), p0); + + LevenbergMarquardtParams lmParams; + GncParams gncParams(lmParams); + auto gnc = GncOptimizer>(fg, initial, + gncParams); + + Values actual = gnc.optimize(); + DOUBLES_EQUAL(0, fg.error(actual), tol); +} + +/* ************************************************************************* */ +TEST(GncOptimizer, optimize) { + auto fg = example::sharedNonRobustFactorGraphWithOutliers(); + + Point2 p0(1, 0); + Values initial; + initial.insert(X(1), p0); + + // try with nonrobust cost function and standard GN + GaussNewtonParams gnParams; + GaussNewtonOptimizer gn(fg, initial, gnParams); + Values gn_results = gn.optimize(); + // converges to incorrect point due to lack of robustness to an outlier, ideal + // solution is Point2(0,0) + CHECK(assert_equal(Point2(0.25, 0.0), gn_results.at(X(1)), 1e-3)); + + // try with robust loss function and standard GN + auto fg_robust = example::sharedRobustFactorGraphWithOutliers(); // same as fg, but with + // factors wrapped in + // Geman McClure losses + GaussNewtonOptimizer gn2(fg_robust, initial, gnParams); + Values gn2_results = gn2.optimize(); + // converges to incorrect point, this time due to the nonconvexity of the loss + CHECK(assert_equal(Point2(0.999706, 0.0), gn2_results.at(X(1)), 1e-3)); + + // .. but graduated nonconvexity ensures both robustness and convergence in + // the face of nonconvexity + GncParams gncParams(gnParams); + // gncParams.setVerbosityGNC(GncParams::Verbosity::SUMMARY); + auto gnc = GncOptimizer>(fg, initial, gncParams); + Values gnc_result = gnc.optimize(); + CHECK(assert_equal(Point2(0.0, 0.0), gnc_result.at(X(1)), 1e-3)); +} + +/* ************************************************************************* */ +TEST(GncOptimizer, optimizeWithKnownInliers) { + auto fg = example::sharedNonRobustFactorGraphWithOutliers(); + + Point2 p0(1, 0); + Values initial; + initial.insert(X(1), p0); + + std::vector knownInliers; + knownInliers.push_back(0); + knownInliers.push_back(1); + knownInliers.push_back(2); + + // nonconvexity with known inliers + { + GncParams gncParams; + gncParams.setKnownInliers(knownInliers); + gncParams.setLossType(GncLossType::GM); + //gncParams.setVerbosityGNC(GncParams::Verbosity::SUMMARY); + auto gnc = GncOptimizer>(fg, initial, + gncParams); + + Values gnc_result = gnc.optimize(); + CHECK(assert_equal(Point2(0.0, 0.0), gnc_result.at(X(1)), 1e-3)); + + // check weights were actually fixed: + Vector finalWeights = gnc.getWeights(); + DOUBLES_EQUAL(1.0, finalWeights[0], tol); + DOUBLES_EQUAL(1.0, finalWeights[1], tol); + DOUBLES_EQUAL(1.0, finalWeights[2], tol); + } + { + GncParams gncParams; + gncParams.setKnownInliers(knownInliers); + gncParams.setLossType(GncLossType::TLS); + // gncParams.setVerbosityGNC(GncParams::Verbosity::SUMMARY); + auto gnc = GncOptimizer>(fg, initial, + gncParams); + + Values gnc_result = gnc.optimize(); + CHECK(assert_equal(Point2(0.0, 0.0), gnc_result.at(X(1)), 1e-3)); + + // check weights were actually fixed: + Vector finalWeights = gnc.getWeights(); + DOUBLES_EQUAL(1.0, finalWeights[0], tol); + DOUBLES_EQUAL(1.0, finalWeights[1], tol); + DOUBLES_EQUAL(1.0, finalWeights[2], tol); + DOUBLES_EQUAL(0.0, finalWeights[3], tol); + } + { + // if we set the threshold large, they are all inliers + GncParams gncParams; + gncParams.setKnownInliers(knownInliers); + gncParams.setLossType(GncLossType::TLS); + //gncParams.setVerbosityGNC(GncParams::Verbosity::VALUES); + gncParams.setInlierCostThreshold(100.0); + auto gnc = GncOptimizer>(fg, initial, + gncParams); + + Values gnc_result = gnc.optimize(); + CHECK(assert_equal(Point2(0.25, 0.0), gnc_result.at(X(1)), 1e-3)); + + // check weights were actually fixed: + Vector finalWeights = gnc.getWeights(); + DOUBLES_EQUAL(1.0, finalWeights[0], tol); + DOUBLES_EQUAL(1.0, finalWeights[1], tol); + DOUBLES_EQUAL(1.0, finalWeights[2], tol); + DOUBLES_EQUAL(1.0, finalWeights[3], tol); + } +} + +/* ************************************************************************* */ +TEST(GncOptimizer, optimizeSmallPoseGraph) { + /// load small pose graph + const string filename = findExampleDataFile("w100.graph"); + NonlinearFactorGraph::shared_ptr graph; + Values::shared_ptr initial; + boost::tie(graph, initial) = load2D(filename); + // Add a Gaussian prior on first poses + Pose2 priorMean(0.0, 0.0, 0.0); // prior at origin + SharedDiagonal priorNoise = noiseModel::Diagonal::Sigmas( + Vector3(0.01, 0.01, 0.01)); + graph->addPrior(0, priorMean, priorNoise); + + /// get expected values by optimizing outlier-free graph + Values expected = LevenbergMarquardtOptimizer(*graph, *initial).optimize(); + + // add a few outliers + SharedDiagonal betweenNoise = noiseModel::Diagonal::Sigmas( + Vector3(0.1, 0.1, 0.01)); + graph->push_back(BetweenFactor(90, 50, Pose2(), betweenNoise)); // some arbitrary and incorrect between factor + + /// get expected values by optimizing outlier-free graph + Values expectedWithOutliers = LevenbergMarquardtOptimizer(*graph, *initial) + .optimize(); + // as expected, the following test fails due to the presence of an outlier! + // CHECK(assert_equal(expected, expectedWithOutliers, 1e-3)); + + // GNC + // Note: in difficult instances, we set the odometry measurements to be + // inliers, but this problem is simple enought to succeed even without that + // assumption std::vector knownInliers; + GncParams gncParams; + auto gnc = GncOptimizer>(*graph, *initial, + gncParams); + Values actual = gnc.optimize(); + + // compare + CHECK(assert_equal(expected, actual, 1e-3)); // yay! we are robust to outliers! +} + +/* ************************************************************************* */ +int main() { + TestResult tr; + return TestRegistry::runAllTests(tr); +} +/* ************************************************************************* */ diff --git a/tests/testImuPreintegration.cpp b/tests/testImuPreintegration.cpp new file mode 100644 index 000000000..1f584be0e --- /dev/null +++ b/tests/testImuPreintegration.cpp @@ -0,0 +1,127 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file testImuPreintegration.cpp + * @brief Unit tests for IMU Preintegration + * @author Russell Buchanan + **/ + +#include +#include +#include +#include +#include +#include + +#include +#include + +using namespace std; +using namespace gtsam; + +/* ************************************************************************* */ +/** + * \brief Uses the GTSAM library to perform IMU preintegration on an + * acceleration input. + */ +TEST(TestImuPreintegration, LoadedSimulationData) { + Vector3 finalPos(0, 0, 0); + + vector imuMeasurements; + + double accNoiseSigma = 0.001249; + double accBiasRwSigma = 0.000106; + double gyrNoiseSigma = 0.000208; + double gyrBiasRwSigma = 0.000004; + double integrationCovariance = 1e-8; + double biasAccOmegaInt = 1e-5; + + double gravity = 9.81; + double rate = 400.0; // Hz + + string inFileString = findExampleDataFile("quadraped_imu_data.csv"); + ifstream inputFile(inFileString); + string line; + while (getline(inputFile, line)) { + stringstream ss(line); + string str; + vector results; + while (getline(ss, str, ',')) { + results.push_back(atof(str.c_str())); + } + ImuMeasurement measurement; + measurement.dt = static_cast(1e9 * (1 / rate)); + measurement.time = results[2]; + measurement.I_a_WI = {results[29], results[30], results[31]}; + measurement.I_w_WI = {results[17], results[18], results[19]}; + imuMeasurements.push_back(measurement); + } + + // Assume a Z-up navigation (assuming we are performing optimization in the + // IMU frame). + auto imuPreintegratedParams = + PreintegratedCombinedMeasurements::Params::MakeSharedU(gravity); + imuPreintegratedParams->accelerometerCovariance = + I_3x3 * pow(accNoiseSigma, 2); + imuPreintegratedParams->biasAccCovariance = I_3x3 * pow(accBiasRwSigma, 2); + imuPreintegratedParams->gyroscopeCovariance = I_3x3 * pow(gyrNoiseSigma, 2); + imuPreintegratedParams->biasOmegaCovariance = I_3x3 * pow(gyrBiasRwSigma, 2); + imuPreintegratedParams->integrationCovariance = I_3x3 * integrationCovariance; + imuPreintegratedParams->biasAccOmegaInt = I_6x6 * biasAccOmegaInt; + + // Initial state + Pose3 priorPose; + Vector3 priorVelocity(0, 0, 0); + imuBias::ConstantBias priorImuBias; + PreintegratedCombinedMeasurements imuPreintegrated; + Vector3 position(0, 0, 0); + Vector3 velocity(0, 0, 0); + NavState propState; + + NavState initialNavState(priorPose, priorVelocity); + + // Assume zero bias for simulated data + priorImuBias = + imuBias::ConstantBias(Eigen::Vector3d(0, 0, 0), Eigen::Vector3d(0, 0, 0)); + + imuPreintegrated = + PreintegratedCombinedMeasurements(imuPreintegratedParams, priorImuBias); + + // start at 1 to skip header + for (size_t n = 1; n < imuMeasurements.size(); n++) { + // integrate + imuPreintegrated.integrateMeasurement(imuMeasurements[n].I_a_WI, + imuMeasurements[n].I_w_WI, 1 / rate); + // predict + propState = imuPreintegrated.predict(initialNavState, priorImuBias); + position = propState.pose().translation(); + velocity = propState.velocity(); + } + + Vector3 rotation = propState.pose().rotation().rpy(); + + // Dont have ground truth for x and y position yet + // DOUBLES_EQUAL(0.1, position[0], 1e-2); + // DOUBLES_EQUAL(0.1, position[1], 1e-2); + DOUBLES_EQUAL(0.0, position[2], 1e-2); + + DOUBLES_EQUAL(0.0, rotation[0], 1e-2); + DOUBLES_EQUAL(0.0, rotation[1], 1e-2); + DOUBLES_EQUAL(0.0, rotation[2], 1e-2); +} + +/* ************************************************************************* */ +int main() { + TestResult tr; + return TestRegistry::runAllTests(tr); +} +/* ************************************************************************* */ diff --git a/tests/testNonlinearFactor.cpp b/tests/testNonlinearFactor.cpp index 662b071df..84bba850b 100644 --- a/tests/testNonlinearFactor.cpp +++ b/tests/testNonlinearFactor.cpp @@ -233,6 +233,26 @@ TEST( NonlinearFactor, linearize_constraint2 ) CHECK(assert_equal((const GaussianFactor&)expected, *actual)); } +/* ************************************************************************* */ +TEST( NonlinearFactor, cloneWithNewNoiseModel ) +{ + // create original factor + double sigma1 = 0.1; + NonlinearFactorGraph nfg = example::nonlinearFactorGraphWithGivenSigma(sigma1); + + // create expected + double sigma2 = 10; + NonlinearFactorGraph expected = example::nonlinearFactorGraphWithGivenSigma(sigma2); + + // create actual + NonlinearFactorGraph actual; + SharedNoiseModel noise2 = noiseModel::Isotropic::Sigma(2,sigma2); + actual.push_back( boost::dynamic_pointer_cast(nfg[0])->cloneWithNewNoiseModel(noise2) ); + + // check it's all good + CHECK(assert_equal(expected, actual)); +} + /* ************************************************************************* */ class TestFactor4 : public NoiseModelFactor4 { public: diff --git a/tests/testNonlinearOptimizer.cpp b/tests/testNonlinearOptimizer.cpp index dc19801a2..295721cc4 100644 --- a/tests/testNonlinearOptimizer.cpp +++ b/tests/testNonlinearOptimizer.cpp @@ -48,6 +48,19 @@ const double tol = 1e-5; using symbol_shorthand::X; using symbol_shorthand::L; +/* ************************************************************************* */ +TEST( NonlinearOptimizer, paramsEquals ) +{ + // default constructors lead to two identical params + GaussNewtonParams gnParams1; + GaussNewtonParams gnParams2; + CHECK(gnParams1.equals(gnParams2)); + + // but the params become different if we change something in gnParams2 + gnParams2.setVerbosity("DELTA"); + CHECK(!gnParams1.equals(gnParams2)); +} + /* ************************************************************************* */ TEST( NonlinearOptimizer, iterateLM ) { @@ -566,6 +579,58 @@ TEST( NonlinearOptimizer, logfile ) // EXPECT(actual.str()==expected.str()); } +/* ************************************************************************* */ +TEST( NonlinearOptimizer, iterationHook_LM ) +{ + NonlinearFactorGraph fg(example::createReallyNonlinearFactorGraph()); + + Point2 x0(3,3); + Values c0; + c0.insert(X(1), x0); + + // Levenberg-Marquardt + LevenbergMarquardtParams lmParams; + size_t lastIterCalled = 0; + lmParams.iterationHook = [&](size_t iteration, double oldError, double newError) + { + // Tests: + lastIterCalled = iteration; + EXPECT(newError " << newError <<"\n"; + }; + LevenbergMarquardtOptimizer(fg, c0, lmParams).optimize(); + + EXPECT(lastIterCalled>5); +} +/* ************************************************************************* */ +TEST( NonlinearOptimizer, iterationHook_CG ) +{ + NonlinearFactorGraph fg(example::createReallyNonlinearFactorGraph()); + + Point2 x0(3,3); + Values c0; + c0.insert(X(1), x0); + + // Levenberg-Marquardt + NonlinearConjugateGradientOptimizer::Parameters cgParams; + size_t lastIterCalled = 0; + cgParams.iterationHook = [&](size_t iteration, double oldError, double newError) + { + // Tests: + lastIterCalled = iteration; + EXPECT(newError " << newError <<"\n"; + }; + NonlinearConjugateGradientOptimizer(fg, c0, cgParams).optimize(); + + EXPECT(lastIterCalled>5); +} + + /* ************************************************************************* */ //// Minimal traits example struct MyType : public Vector3 { diff --git a/tests/testSerializationSLAM.cpp b/tests/testSerializationSLAM.cpp index 84e521156..2e99aff71 100644 --- a/tests/testSerializationSLAM.cpp +++ b/tests/testSerializationSLAM.cpp @@ -89,10 +89,8 @@ typedef RangeFactor RangeFactor3D; typedef RangeFactor RangeFactorPose2; typedef RangeFactor RangeFactorPose3; typedef RangeFactor RangeFactorCalibratedCameraPoint; -typedef RangeFactor RangeFactorSimpleCameraPoint; typedef RangeFactor RangeFactorPinholeCameraCal3_S2Point; typedef RangeFactor RangeFactorCalibratedCamera; -typedef RangeFactor RangeFactorSimpleCamera; typedef RangeFactor RangeFactorPinholeCameraCal3_S2; typedef BearingRangeFactor BearingRangeFactor2D; @@ -102,7 +100,7 @@ typedef GenericProjectionFactor GenericProjectionFactorC typedef GenericProjectionFactor GenericProjectionFactorCal3DS2; typedef gtsam::GeneralSFMFactor GeneralSFMFactorCal3_S2; -//typedef gtsam::GeneralSFMFactor GeneralSFMFactorCal3DS2; +typedef gtsam::GeneralSFMFactor GeneralSFMFactorCal3DS2; typedef gtsam::GeneralSFMFactor2 GeneralSFMFactor2Cal3_S2; @@ -145,7 +143,6 @@ GTSAM_VALUE_EXPORT(gtsam::Cal3_S2); GTSAM_VALUE_EXPORT(gtsam::Cal3DS2); GTSAM_VALUE_EXPORT(gtsam::Cal3_S2Stereo); GTSAM_VALUE_EXPORT(gtsam::CalibratedCamera); -GTSAM_VALUE_EXPORT(gtsam::SimpleCamera); GTSAM_VALUE_EXPORT(gtsam::PinholeCameraCal3_S2); GTSAM_VALUE_EXPORT(gtsam::StereoCamera); @@ -190,9 +187,9 @@ BOOST_CLASS_EXPORT_GUID(RangeFactor3D, "gtsam::RangeFactor3D"); BOOST_CLASS_EXPORT_GUID(RangeFactorPose2, "gtsam::RangeFactorPose2"); BOOST_CLASS_EXPORT_GUID(RangeFactorPose3, "gtsam::RangeFactorPose3"); BOOST_CLASS_EXPORT_GUID(RangeFactorCalibratedCameraPoint, "gtsam::RangeFactorCalibratedCameraPoint"); -BOOST_CLASS_EXPORT_GUID(RangeFactorSimpleCameraPoint, "gtsam::RangeFactorSimpleCameraPoint"); +BOOST_CLASS_EXPORT_GUID(RangeFactorPinholeCameraCal3_S2Point, "gtsam::RangeFactorPinholeCameraCal3_S2Point"); BOOST_CLASS_EXPORT_GUID(RangeFactorCalibratedCamera, "gtsam::RangeFactorCalibratedCamera"); -BOOST_CLASS_EXPORT_GUID(RangeFactorSimpleCamera, "gtsam::RangeFactorSimpleCamera"); +BOOST_CLASS_EXPORT_GUID(RangeFactorPinholeCameraCal3_S2, "gtsam::RangeFactorPinholeCameraCal3_S2"); BOOST_CLASS_EXPORT_GUID(BearingRangeFactor2D, "gtsam::BearingRangeFactor2D"); @@ -200,7 +197,7 @@ BOOST_CLASS_EXPORT_GUID(GenericProjectionFactorCal3_S2, "gtsam::GenericProjectio BOOST_CLASS_EXPORT_GUID(GenericProjectionFactorCal3DS2, "gtsam::GenericProjectionFactorCal3DS2"); BOOST_CLASS_EXPORT_GUID(GeneralSFMFactorCal3_S2, "gtsam::GeneralSFMFactorCal3_S2"); -//BOOST_CLASS_EXPORT_GUID(GeneralSFMFactorCal3DS2, "gtsam::GeneralSFMFactorCal3DS2"); +BOOST_CLASS_EXPORT_GUID(GeneralSFMFactorCal3DS2, "gtsam::GeneralSFMFactorCal3DS2"); BOOST_CLASS_EXPORT_GUID(GeneralSFMFactor2Cal3_S2, "gtsam::GeneralSFMFactor2Cal3_S2"); @@ -352,9 +349,9 @@ TEST (testSerializationSLAM, factors) { RangeFactorPose2 rangeFactorPose2(a08, b08, 2.0, model1); RangeFactorPose3 rangeFactorPose3(a09, b09, 2.0, model1); RangeFactorCalibratedCameraPoint rangeFactorCalibratedCameraPoint(a12, a05, 2.0, model1); - RangeFactorSimpleCameraPoint rangeFactorSimpleCameraPoint(a13, a05, 2.0, model1); + RangeFactorPinholeCameraCal3_S2Point rangeFactorPinholeCameraCal3_S2Point(a13, a05, 2.0, model1); RangeFactorCalibratedCamera rangeFactorCalibratedCamera(a12, b12, 2.0, model1); - RangeFactorSimpleCamera rangeFactorSimpleCamera(a13, b13, 2.0, model1); + RangeFactorPinholeCameraCal3_S2 rangeFactorPinholeCameraCal3_S2(a13, b13, 2.0, model1); BearingRangeFactor2D bearingRangeFactor2D(a08, a03, rot2, 2.0, model2); @@ -405,9 +402,9 @@ TEST (testSerializationSLAM, factors) { graph += rangeFactorPose2; graph += rangeFactorPose3; graph += rangeFactorCalibratedCameraPoint; - graph += rangeFactorSimpleCameraPoint; + graph += rangeFactorPinholeCameraCal3_S2Point; graph += rangeFactorCalibratedCamera; - graph += rangeFactorSimpleCamera; + graph += rangeFactorPinholeCameraCal3_S2; graph += bearingRangeFactor2D; @@ -463,9 +460,9 @@ TEST (testSerializationSLAM, factors) { EXPECT(equalsObj(rangeFactorPose2)); EXPECT(equalsObj(rangeFactorPose3)); EXPECT(equalsObj(rangeFactorCalibratedCameraPoint)); - EXPECT(equalsObj(rangeFactorSimpleCameraPoint)); + EXPECT(equalsObj(rangeFactorPinholeCameraCal3_S2Point)); EXPECT(equalsObj(rangeFactorCalibratedCamera)); - EXPECT(equalsObj(rangeFactorSimpleCamera)); + EXPECT(equalsObj(rangeFactorPinholeCameraCal3_S2)); EXPECT(equalsObj(bearingRangeFactor2D)); @@ -521,9 +518,9 @@ TEST (testSerializationSLAM, factors) { EXPECT(equalsXML(rangeFactorPose2)); EXPECT(equalsXML(rangeFactorPose3)); EXPECT(equalsXML(rangeFactorCalibratedCameraPoint)); - EXPECT(equalsXML(rangeFactorSimpleCameraPoint)); + EXPECT(equalsXML(rangeFactorPinholeCameraCal3_S2Point)); EXPECT(equalsXML(rangeFactorCalibratedCamera)); - EXPECT(equalsXML(rangeFactorSimpleCamera)); + EXPECT(equalsXML(rangeFactorPinholeCameraCal3_S2)); EXPECT(equalsXML(bearingRangeFactor2D)); @@ -579,9 +576,9 @@ TEST (testSerializationSLAM, factors) { EXPECT(equalsBinary(rangeFactorPose2)); EXPECT(equalsBinary(rangeFactorPose3)); EXPECT(equalsBinary(rangeFactorCalibratedCameraPoint)); - EXPECT(equalsBinary(rangeFactorSimpleCameraPoint)); + EXPECT(equalsBinary(rangeFactorPinholeCameraCal3_S2Point)); EXPECT(equalsBinary(rangeFactorCalibratedCamera)); - EXPECT(equalsBinary(rangeFactorSimpleCamera)); + EXPECT(equalsBinary(rangeFactorPinholeCameraCal3_S2)); EXPECT(equalsBinary(bearingRangeFactor2D)); diff --git a/tests/testTranslationRecovery.cpp b/tests/testTranslationRecovery.cpp index eb34ba803..7260fd5af 100644 --- a/tests/testTranslationRecovery.cpp +++ b/tests/testTranslationRecovery.cpp @@ -11,19 +11,29 @@ /** * @file testTranslationRecovery.cpp - * @author Frank Dellaert + * @author Frank Dellaert, Akshay Krishnan * @date March 2020 * @brief test recovering translations when rotations are given. */ -#include - #include + +#include #include using namespace std; using namespace gtsam; +// Returns the Unit3 direction as measured in the binary measurement, but +// computed from the input poses. Helper function used in the unit tests. +Unit3 GetDirectionFromPoses(const Values& poses, + const BinaryMeasurement& unitTranslation) { + const Pose3 wTa = poses.at(unitTranslation.key1()), + wTb = poses.at(unitTranslation.key2()); + const Point3 Ta = wTa.translation(), Tb = wTb.translation(); + return Unit3(Tb - Ta); +} + /* ************************************************************************* */ // We read the BAL file, which has 3 cameras in it, with poses. We then assume // the rotations are correct, but translations have to be estimated from @@ -48,43 +58,186 @@ TEST(TranslationRecovery, BAL) { const auto relativeTranslations = TranslationRecovery::SimulateMeasurements( poses, {{0, 1}, {0, 2}, {1, 2}}); - // Check - Unit3 w_aZb_stored; // measurement between 0 and 1 stored for next unit test - for(auto& unitTranslation : relativeTranslations) { - const Pose3 wTa = poses.at(unitTranslation.key1()), - wTb = poses.at(unitTranslation.key2()); - const Point3 Ta = wTa.translation(), Tb = wTb.translation(); - const Unit3 w_aZb = unitTranslation.measured(); - EXPECT(assert_equal(Unit3(Tb - Ta), w_aZb)); - if(unitTranslation.key1() == 0 && unitTranslation.key2() == 1) { - w_aZb_stored = unitTranslation.measured(); - } + // Check simulated measurements. + for (auto& unitTranslation : relativeTranslations) { + EXPECT(assert_equal(GetDirectionFromPoses(poses, unitTranslation), + unitTranslation.measured())); } TranslationRecovery algorithm(relativeTranslations); const auto graph = algorithm.buildGraph(); EXPECT_LONGS_EQUAL(3, graph.size()); - // Translation recovery, version 1 + // Run translation recovery const double scale = 2.0; const auto result = algorithm.run(scale); // Check result for first two translations, determined by prior EXPECT(assert_equal(Point3(0, 0, 0), result.at(0))); - EXPECT(assert_equal(Point3(2 * w_aZb_stored.point3()), result.at(1))); + EXPECT(assert_equal( + Point3(2 * GetDirectionFromPoses(poses, relativeTranslations[0])), + result.at(1))); // Check that the third translations is correct Point3 Ta = poses.at(0).translation(); Point3 Tb = poses.at(1).translation(); Point3 Tc = poses.at(2).translation(); - Point3 expected = - (Tc - Ta) * (scale / (Tb - Ta).norm()); + Point3 expected = (Tc - Ta) * (scale / (Tb - Ta).norm()); EXPECT(assert_equal(expected, result.at(2), 1e-4)); // TODO(frank): how to get stats back? // EXPECT_DOUBLES_EQUAL(0.0199833, actualError, 1e-5); } +TEST(TranslationRecovery, TwoPoseTest) { + // Create a dataset with 2 poses. + // __ __ + // \/ \/ + // 0 _____ 1 + // + // 0 and 1 face in the same direction but have a translation offset. + Values poses; + poses.insert(0, Pose3(Rot3(), Point3(0, 0, 0))); + poses.insert(1, Pose3(Rot3(), Point3(2, 0, 0))); + + auto relativeTranslations = + TranslationRecovery::SimulateMeasurements(poses, {{0, 1}}); + + // Check simulated measurements. + for (auto& unitTranslation : relativeTranslations) { + EXPECT(assert_equal(GetDirectionFromPoses(poses, unitTranslation), + unitTranslation.measured())); + } + + TranslationRecovery algorithm(relativeTranslations); + const auto graph = algorithm.buildGraph(); + EXPECT_LONGS_EQUAL(1, graph.size()); + + // Run translation recovery + const auto result = algorithm.run(/*scale=*/3.0); + + // Check result for first two translations, determined by prior + EXPECT(assert_equal(Point3(0, 0, 0), result.at(0))); + EXPECT(assert_equal(Point3(3, 0, 0), result.at(1))); +} + +TEST(TranslationRecovery, ThreePoseTest) { + // Create a dataset with 3 poses. + // __ __ + // \/ \/ + // 0 _____ 1 + // \ __ / + // \\// + // 3 + // + // 0 and 1 face in the same direction but have a translation offset. 3 is in + // the same direction as 0 and 1, in between 0 and 1, with some Y axis offset. + + Values poses; + poses.insert(0, Pose3(Rot3(), Point3(0, 0, 0))); + poses.insert(1, Pose3(Rot3(), Point3(2, 0, 0))); + poses.insert(3, Pose3(Rot3(), Point3(1, -1, 0))); + + auto relativeTranslations = TranslationRecovery::SimulateMeasurements( + poses, {{0, 1}, {1, 3}, {3, 0}}); + + // Check simulated measurements. + for (auto& unitTranslation : relativeTranslations) { + EXPECT(assert_equal(GetDirectionFromPoses(poses, unitTranslation), + unitTranslation.measured())); + } + + TranslationRecovery algorithm(relativeTranslations); + const auto graph = algorithm.buildGraph(); + EXPECT_LONGS_EQUAL(3, graph.size()); + + const auto result = algorithm.run(/*scale=*/3.0); + + // Check result + EXPECT(assert_equal(Point3(0, 0, 0), result.at(0))); + EXPECT(assert_equal(Point3(3, 0, 0), result.at(1))); + EXPECT(assert_equal(Point3(1.5, -1.5, 0), result.at(3))); +} + +TEST(TranslationRecovery, ThreePosesIncludingZeroTranslation) { + // Create a dataset with 3 poses. + // __ __ + // \/ \/ + // 0 _____ 1 + // 2 <| + // + // 0 and 1 face in the same direction but have a translation offset. 2 is at + // the same point as 1 but is rotated, with little FOV overlap. + Values poses; + poses.insert(0, Pose3(Rot3(), Point3(0, 0, 0))); + poses.insert(1, Pose3(Rot3(), Point3(2, 0, 0))); + poses.insert(2, Pose3(Rot3::RzRyRx(-M_PI / 2, 0, 0), Point3(2, 0, 0))); + + auto relativeTranslations = + TranslationRecovery::SimulateMeasurements(poses, {{0, 1}, {1, 2}}); + + // Check simulated measurements. + for (auto& unitTranslation : relativeTranslations) { + EXPECT(assert_equal(GetDirectionFromPoses(poses, unitTranslation), + unitTranslation.measured())); + } + + TranslationRecovery algorithm(relativeTranslations); + const auto graph = algorithm.buildGraph(); + // There is only 1 non-zero translation edge. + EXPECT_LONGS_EQUAL(1, graph.size()); + + // Run translation recovery + const auto result = algorithm.run(/*scale=*/3.0); + + // Check result + EXPECT(assert_equal(Point3(0, 0, 0), result.at(0))); + EXPECT(assert_equal(Point3(3, 0, 0), result.at(1))); + EXPECT(assert_equal(Point3(3, 0, 0), result.at(2))); +} + +TEST(TranslationRecovery, FourPosesIncludingZeroTranslation) { + // Create a dataset with 4 poses. + // __ __ + // \/ \/ + // 0 _____ 1 + // \ __ 2 <| + // \\// + // 3 + // + // 0 and 1 face in the same direction but have a translation offset. 2 is at + // the same point as 1 but is rotated, with very little FOV overlap. 3 is in + // the same direction as 0 and 1, in between 0 and 1, with some Y axis offset. + + Values poses; + poses.insert(0, Pose3(Rot3(), Point3(0, 0, 0))); + poses.insert(1, Pose3(Rot3(), Point3(2, 0, 0))); + poses.insert(2, Pose3(Rot3::RzRyRx(-M_PI / 2, 0, 0), Point3(2, 0, 0))); + poses.insert(3, Pose3(Rot3(), Point3(1, -1, 0))); + + auto relativeTranslations = TranslationRecovery::SimulateMeasurements( + poses, {{0, 1}, {1, 2}, {1, 3}, {3, 0}}); + + // Check simulated measurements. + for (auto& unitTranslation : relativeTranslations) { + EXPECT(assert_equal(GetDirectionFromPoses(poses, unitTranslation), + unitTranslation.measured())); + } + + TranslationRecovery algorithm(relativeTranslations); + const auto graph = algorithm.buildGraph(); + EXPECT_LONGS_EQUAL(3, graph.size()); + + // Run translation recovery + const auto result = algorithm.run(/*scale=*/4.0); + + // Check result + EXPECT(assert_equal(Point3(0, 0, 0), result.at(0))); + EXPECT(assert_equal(Point3(4, 0, 0), result.at(1))); + EXPECT(assert_equal(Point3(4, 0, 0), result.at(2))); + EXPECT(assert_equal(Point3(2, -2, 0), result.at(3))); +} + /* ************************************************************************* */ int main() { TestResult tr; diff --git a/wrap/.gitignore b/wrap/.gitignore index 38da6d9d1..4fd660b95 100644 --- a/wrap/.gitignore +++ b/wrap/.gitignore @@ -1,2 +1,5 @@ __pycache__/ .vscode/ +*build* +*dist* +*.egg-info diff --git a/wrap/CMakeLists.txt b/wrap/CMakeLists.txt new file mode 100644 index 000000000..d363c7161 --- /dev/null +++ b/wrap/CMakeLists.txt @@ -0,0 +1,59 @@ +cmake_minimum_required(VERSION 3.9) + +# Set the project name and version +project(GTwrap VERSION 1.0) + +# ############################################################################## +# General configuration + +set(WRAP_PYTHON_VERSION + "Default" + CACHE STRING "The Python version to use for wrapping") + +include(${CMAKE_CURRENT_SOURCE_DIR}/cmake/GtwrapUtils.cmake) +gtwrap_get_python_version(${WRAP_PYTHON_VERSION}) + +# ############################################################################## +# Install the CMake file to be used by other projects +if(WIN32 AND NOT CYGWIN) + set(SCRIPT_INSTALL_DIR "${CMAKE_INSTALL_PREFIX}/CMake") +else() + set(SCRIPT_INSTALL_DIR "${CMAKE_INSTALL_PREFIX}/lib/cmake") +endif() + +# Install scripts to the standard CMake script directory. +install(FILES cmake/gtwrapConfig.cmake cmake/PybindWrap.cmake + cmake/GtwrapUtils.cmake + DESTINATION "${SCRIPT_INSTALL_DIR}/gtwrap") + +# Install wrapping scripts as binaries to `CMAKE_INSTALL_PREFIX/bin` so they can +# be invoked for wrapping. +# We use DESTINATION (instead of TYPE) so we can support older CMake versions. +install(PROGRAMS scripts/pybind_wrap.py scripts/matlab_wrap.py + DESTINATION ${CMAKE_INSTALL_BINDIR}) + +# Install pybind11 directory to `CMAKE_INSTALL_PREFIX/lib/pybind11` This will +# allow the gtwrapConfig.cmake file to load it later. +# We use DESTINATION (instead of TYPE) so we can support older CMake versions. +install(DIRECTORY pybind11 + DESTINATION ${CMAKE_INSTALL_LIBDIR}) + +# ############################################################################## +# Install the Python package +find_package( + Python ${WRAP_PYTHON_VERSION} + COMPONENTS Interpreter + EXACT) + +# Detect virtualenv and set Pip args accordingly +# https://www.scivision.dev/cmake-install-python-package/ +if(DEFINED ENV{VIRTUAL_ENV} OR DEFINED ENV{CONDA_PREFIX}) + set(_pip_args) +else() + set(_pip_args "--user") +endif() +#TODO add correct flags for virtualenv + +# Finally install the gtwrap python package. +execute_process(COMMAND ${Python_EXECUTABLE} -m pip install . ${_pip_args} + WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}) diff --git a/wrap/LICENSE b/wrap/LICENSE new file mode 100644 index 000000000..406b266b7 --- /dev/null +++ b/wrap/LICENSE @@ -0,0 +1,13 @@ +Copyright (c) 2010, Georgia Tech Research Corporation +Atlanta, Georgia 30332-0415 +All Rights Reserved + +Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: + +1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. + +2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. + +3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. \ No newline at end of file diff --git a/wrap/README.md b/wrap/README.md index f72c3f652..347cca601 100644 --- a/wrap/README.md +++ b/wrap/README.md @@ -8,9 +8,40 @@ It was designed to be more general than just wrapping GTSAM. For notes on creati 1. This library uses `pybind11`, which is included as a subdirectory in GTSAM. 2. The `interface_parser.py` in this library uses `pyparsing` to parse the interface file `gtsam.h`. Please install it first in your current Python environment before attempting the build. - ``` - python3 -m pip install pyparsing - ``` + +``` +python3 -m pip install pyparsing +``` + +## Getting Started + +Clone this repository to your local machine and perform the standard CMake install: + +```sh +mkdir build && cd build +cmake .. +make install # use sudo if needed +``` + +Using `wrap` in your project is straightforward from here. In you `CMakeLists.txt` file, you just need to add the following: + +```cmake +include(PybindWrap) + +pybind_wrap(${PROJECT_NAME}_py # target + ${PROJECT_SOURCE_DIR}/cpp/${PROJECT_NAME}.h # interface header file + "${PROJECT_NAME}.cpp" # the generated cpp + "${PROJECT_NAME}" # module_name + "gtsam" # top namespace in the cpp file + "${ignore}" # ignore classes + ${PROJECT_BINARY_DIR}/${PROJECT_NAME}.tpl + ${PROJECT_NAME} # libs + "${PROJECT_NAME}" # dependencies + ON # use boost + ) +``` + +For more information, please follow our [tutorial](https://github.com/borglab/gtsam-project-python). ## GTSAM Python wrapper @@ -45,32 +76,3 @@ It was designed to be more general than just wrapping GTSAM. For notes on creati python setup.py install ``` - NOTE: It's a good idea to create a virtual environment otherwise it will be installed in your system Python's site-packages. - - -## Old GTSAM Wrapper - -*Outdated note from the original wrap.* - -TODO: Update this. - -It was designed to be more general than just wrapping GTSAM, but a small amount of GTSAM specific code exists in `matlab.h`, the include file that is included by the `mex` files. The GTSAM-specific functionality consists primarily of handling of Eigen Matrix and Vector classes. - -For notes on creating a wrap interface, see `gtsam.h` for what features can be wrapped into a toolbox, as well as the current state of the toolbox for GTSAM. For more technical details on the interface, please read comments in `matlab.h` - -Some good things to know: - -OBJECT CREATION - -- Classes are created by special constructors, e.g., `new_GaussianFactorGraph_.cpp`. - These constructors are called from the MATLAB class `@GaussianFactorGraph`. - `new_GaussianFactorGraph_` calls wrap_constructed in `matlab.h`, see documentation there - -METHOD (AND CONSTRUCTOR) ARGUMENTS - -- Simple argument types of methods, such as "double", will be converted in the - `mex` wrappers by calling unwrap, defined in matlab.h -- Vector and Matrix arguments are normally passed by reference in GTSAM, but - in `gtsam.h` you need to pretend they are passed by value, to trigger the - generation of the correct conversion routines `unwrap` and `unwrap` -- passing classes as arguments works, provided they are passed by reference. - This triggers a call to unwrap_shared_ptr diff --git a/wrap/cmake/GtwrapUtils.cmake b/wrap/cmake/GtwrapUtils.cmake new file mode 100644 index 000000000..acf075c5b --- /dev/null +++ b/wrap/cmake/GtwrapUtils.cmake @@ -0,0 +1,74 @@ +# Utilities to help with wrapping. + +macro(get_python_version) + if(${CMAKE_VERSION} VERSION_LESS "3.12.0") + # Use older version of cmake's find_python + find_package(PythonInterp) + + if(NOT ${PYTHONINTERP_FOUND}) + message( + FATAL_ERROR + "Cannot find Python interpreter. Please install Python>=3.5.") + endif() + + find_package(PythonLibs ${PYTHON_VERSION_STRING}) + + set(Python_VERSION_MAJOR + ${PYTHON_VERSION_MAJOR} + PARENT_SCOPE) + set(Python_VERSION_MINOR + ${PYTHON_VERSION_MINOR} + PARENT_SCOPE) + set(Python_VERSION_PATCH + ${PYTHON_VERSION_PATCH} + PARENT_SCOPE) + set(Python_EXECUTABLE + ${PYTHON_EXECUTABLE} + PARENT_SCOPE) + + else() + # Get info about the Python interpreter + # https://cmake.org/cmake/help/latest/module/FindPython.html#module:FindPython + find_package(Python COMPONENTS Interpreter Development) + + if(NOT ${Python_FOUND}) + message( + FATAL_ERROR + "Cannot find Python interpreter. Please install Python>=3.5.") + endif() + + endif() +endmacro() + +# Set the Python version for the wrapper and set the paths to the executable and +# include/library directories. WRAP_PYTHON_VERSION can be "Default" or a +# specific major.minor version. +macro(gtwrap_get_python_version WRAP_PYTHON_VERSION) + # Unset these cached variables to avoid surprises when the python in the + # current environment are different from the cached! + unset(Python_EXECUTABLE CACHE) + unset(Python_INCLUDE_DIRS CACHE) + unset(Python_VERSION_MAJOR CACHE) + unset(Python_VERSION_MINOR CACHE) + unset(Python_VERSION_PATCH CACHE) + + # Allow override + if(${WRAP_PYTHON_VERSION} STREQUAL "Default") + # Check for Python3 or Python2 in order + get_python_version() + + # Set the wrapper python version + set(WRAP_PYTHON_VERSION + "${Python_VERSION_MAJOR}.${Python_VERSION_MINOR}.${Python_VERSION_PATCH}" + CACHE STRING "The version of Python to build the wrappers against." + FORCE) + + else() + # Find the Python that best matches the python version specified. + find_package( + Python ${WRAP_PYTHON_VERSION} + COMPONENTS Interpreter Development + EXACT) + endif() + +endmacro() diff --git a/wrap/cmake/PybindWrap.cmake b/wrap/cmake/PybindWrap.cmake index ff69b5aed..a92a78a93 100644 --- a/wrap/cmake/PybindWrap.cmake +++ b/wrap/cmake/PybindWrap.cmake @@ -1,32 +1,5 @@ -# Unset these cached variables to avoid surprises when the python in the current -# environment are different from the cached! -unset(PYTHON_EXECUTABLE CACHE) -unset(PYTHON_INCLUDE_DIR CACHE) -unset(PYTHON_MAJOR_VERSION CACHE) - -# Allow override from command line -if(NOT DEFINED WRAP_USE_CUSTOM_PYTHON_LIBRARY) - if(WRAP_PYTHON_VERSION STREQUAL "Default") - find_package(PythonInterp REQUIRED) - find_package(PythonLibs REQUIRED) - else() - find_package(PythonInterp - ${WRAP_PYTHON_VERSION} - EXACT - REQUIRED) - find_package(PythonLibs - ${WRAP_PYTHON_VERSION} - EXACT - REQUIRED) - endif() -endif() - -set(DIR_OF_WRAP_PYBIND_CMAKE ${CMAKE_CURRENT_LIST_DIR}) - set(PYBIND11_PYTHON_VERSION ${WRAP_PYTHON_VERSION}) -add_subdirectory(${CMAKE_CURRENT_LIST_DIR}/../pybind11 pybind11) - # User-friendly Pybind11 wrapping and installing function. # Builds a Pybind11 module from the provided interface_header. # For example, for the interface header gtsam.h, this will @@ -65,7 +38,7 @@ function(pybind_wrap add_custom_command(OUTPUT ${generated_cpp} COMMAND ${PYTHON_EXECUTABLE} - ${CMAKE_SOURCE_DIR}/wrap/pybind_wrapper.py + ${PYBIND_WRAP_SCRIPT} --src ${interface_header} --out @@ -89,9 +62,9 @@ function(pybind_wrap # ~~~ add_custom_command(OUTPUT ${generated_cpp} DEPENDS ${interface_header} - ${CMAKE_SOURCE_DIR}/wrap/interface_parser.py - ${CMAKE_SOURCE_DIR}/wrap/pybind_wrapper.py - ${CMAKE_SOURCE_DIR}/wrap/template_instantiator.py + # @GTWRAP_SOURCE_DIR@/gtwrap/interface_parser.py + # @GTWRAP_SOURCE_DIR@/gtwrap/pybind_wrapper.py + # @GTWRAP_SOURCE_DIR@/gtwrap/template_instantiator.py APPEND) pybind11_add_module(${target} ${generated_cpp}) diff --git a/wrap/cmake/gtwrapConfig.cmake b/wrap/cmake/gtwrapConfig.cmake new file mode 100644 index 000000000..48bd4772d --- /dev/null +++ b/wrap/cmake/gtwrapConfig.cmake @@ -0,0 +1,27 @@ +# This config file modifies CMAKE_MODULE_PATH so that the wrap cmake files may +# be included This file also allows the use of `find_package(gtwrap)` in CMake. + +set(GTWRAP_DIR "${CMAKE_CURRENT_LIST_DIR}") +list(APPEND CMAKE_MODULE_PATH "${CMAKE_CURRENT_LIST_DIR}") + +if(WIN32 AND NOT CYGWIN) + set(SCRIPT_INSTALL_DIR "${CMAKE_INSTALL_PREFIX}/CMake") +else() + set(SCRIPT_INSTALL_DIR "${CMAKE_INSTALL_PREFIX}/lib/cmake") +endif() + +# Standard includes +include(GNUInstallDirs) +include(CMakePackageConfigHelpers) +include(CMakeDependentOption) + +# Load all the CMake scripts from the standard location +include(${SCRIPT_INSTALL_DIR}/gtwrap/PybindWrap.cmake) +include(${SCRIPT_INSTALL_DIR}/gtwrap/GtwrapUtils.cmake) + +# Set the variables for the wrapping scripts to be used in the build. +set(PYBIND_WRAP_SCRIPT "${CMAKE_INSTALL_FULL_BINDIR}/pybind_wrap.py") +set(MATLAB_WRAP_SCRIPT "${CMAKE_INSTALL_FULL_BINDIR}/matlab_wrap.py") + +# Load the pybind11 code from the library installation path +add_subdirectory(${CMAKE_INSTALL_FULL_LIBDIR}/pybind11 pybind11) diff --git a/wrap/gtwrap/__init__.py b/wrap/gtwrap/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/wrap/interface_parser.py b/wrap/gtwrap/interface_parser.py similarity index 100% rename from wrap/interface_parser.py rename to wrap/gtwrap/interface_parser.py diff --git a/wrap/matlab_wrapper.py b/wrap/gtwrap/matlab_wrapper.py similarity index 96% rename from wrap/matlab_wrapper.py rename to wrap/gtwrap/matlab_wrapper.py index 1b6b75a49..355913ba7 100755 --- a/wrap/matlab_wrapper.py +++ b/wrap/gtwrap/matlab_wrapper.py @@ -2,8 +2,8 @@ import os import argparse import textwrap -import interface_parser as parser -import template_instantiator as instantiator +import gtwrap.interface_parser as parser +import gtwrap.template_instantiator as instantiator from functools import reduce from functools import partial @@ -1666,7 +1666,7 @@ class MatlabWrapper(object): return self.content -def _generate_content(cc_content, path, verbose=False): +def generate_content(cc_content, path, verbose=False): """Generate files and folders from matlab wrapper content. Keyword arguments: @@ -1698,7 +1698,7 @@ def _generate_content(cc_content, path, verbose=False): for sub_content in c: import sys _debug("sub object: {}".format(sub_content[1][0][0])) - _generate_content(sub_content[1], path_to_folder) + generate_content(sub_content[1], path_to_folder) elif type(c[1]) == list: path_to_folder = path + '/' + c[0] @@ -1726,53 +1726,3 @@ def _generate_content(cc_content, path, verbose=False): with open(path_to_file, 'w') as f: f.write(c[1]) - - -if __name__ == "__main__": - arg_parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter) - arg_parser.add_argument("--src", type=str, required=True, help="Input interface .h file.") - arg_parser.add_argument("--module_name", type=str, required=True, help="Name of the C++ class being wrapped.") - arg_parser.add_argument("--out", type=str, required=True, help="Name of the output folder.") - arg_parser.add_argument("--top_module_namespaces", - type=str, - default="", - help="C++ namespace for the top module, e.g. `ns1::ns2::ns3`. " - "Only the content within this namespace and its sub-namespaces " - "will be wrapped. The content of this namespace will be available at " - "the top module level, and its sub-namespaces' in the submodules.\n" - "For example, `import ` gives you access to a Python " - "`.Class` of the corresponding C++ `ns1::ns2::ns3::Class`" - ", and `from import ns4` gives you access to a Python " - "`ns4.Class` of the C++ `ns1::ns2::ns3::ns4::Class`. ") - arg_parser.add_argument("--ignore", - nargs='*', - type=str, - help="A space-separated list of classes to ignore. " - "Class names must include their full namespaces.") - args = arg_parser.parse_args() - - top_module_namespaces = args.top_module_namespaces.split("::") - if top_module_namespaces[0]: - top_module_namespaces = [''] + top_module_namespaces - - with open(args.src, 'r') as f: - content = f.read() - - if not os.path.exists(args.src): - os.mkdir(args.src) - - module = parser.Module.parseString(content) - - instantiator.instantiate_namespace_inplace(module) - - import sys - - print("Ignoring classes: {}".format(args.ignore), file=sys.stderr) - wrapper = MatlabWrapper(module=module, - module_name=args.module_name, - top_module_namespace=top_module_namespaces, - ignore_classes=args.ignore) - - cc_content = wrapper.wrap() - - _generate_content(cc_content, args.out) diff --git a/wrap/pybind_wrapper.py b/wrap/gtwrap/pybind_wrapper.py similarity index 84% rename from wrap/pybind_wrapper.py rename to wrap/gtwrap/pybind_wrapper.py index 326d9be52..c0e88e37a 100755 --- a/wrap/pybind_wrapper.py +++ b/wrap/gtwrap/pybind_wrapper.py @@ -9,12 +9,11 @@ See LICENSE for the license information Code generator for wrapping a C++ module with Pybind11 Author: Duy Nguyen Ta, Fan Jiang, Matthew Sklar and Frank Dellaert """ -import argparse import re import textwrap -import interface_parser as parser -import template_instantiator as instantiator +import gtwrap.interface_parser as parser +import gtwrap.template_instantiator as instantiator class PybindWrapper(object): @@ -319,76 +318,3 @@ class PybindWrapper(object): wrapped_namespace=wrapped_namespace, boost_class_export=boost_class_export, ) - - -def main(): - arg_parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter) - arg_parser.add_argument("--src", type=str, required=True, help="Input interface .h file") - arg_parser.add_argument( - "--module_name", - type=str, - required=True, - help="Name of the Python module to be generated and " - "used in the Python `import` statement.", - ) - arg_parser.add_argument( - "--out", - type=str, - required=True, - help="Name of the output pybind .cc file", - ) - arg_parser.add_argument( - "--use-boost", - action="store_true", - help="using boost's shared_ptr instead of std's", - ) - arg_parser.add_argument( - "--top_module_namespaces", - type=str, - default="", - help="C++ namespace for the top module, e.g. `ns1::ns2::ns3`. " - "Only the content within this namespace and its sub-namespaces " - "will be wrapped. The content of this namespace will be available at " - "the top module level, and its sub-namespaces' in the submodules.\n" - "For example, `import ` gives you access to a Python " - "`.Class` of the corresponding C++ `ns1::ns2::ns3::Class`" - "and `from import ns4` gives you access to a Python " - "`ns4.Class` of the C++ `ns1::ns2::ns3::ns4::Class`. ", - ) - arg_parser.add_argument( - "--ignore", - nargs='*', - type=str, - help="A space-separated list of classes to ignore. " - "Class names must include their full namespaces.", - ) - arg_parser.add_argument("--template", type=str, help="The module template file") - args = arg_parser.parse_args() - - top_module_namespaces = args.top_module_namespaces.split("::") - if top_module_namespaces[0]: - top_module_namespaces = [''] + top_module_namespaces - - with open(args.src, "r") as f: - content = f.read() - module = parser.Module.parseString(content) - instantiator.instantiate_namespace_inplace(module) - - with open(args.template, "r") as f: - template_content = f.read() - wrapper = PybindWrapper( - module=module, - module_name=args.module_name, - use_boost=args.use_boost, - top_module_namespaces=top_module_namespaces, - ignore_classes=args.ignore, - module_template=template_content, - ) - - cc_content = wrapper.wrap() - with open(args.out, "w") as f: - f.write(cc_content) - - -if __name__ == "__main__": - main() diff --git a/wrap/template_instantiator.py b/wrap/gtwrap/template_instantiator.py similarity index 99% rename from wrap/template_instantiator.py rename to wrap/gtwrap/template_instantiator.py index 3d98e9699..6032beac4 100644 --- a/wrap/template_instantiator.py +++ b/wrap/gtwrap/template_instantiator.py @@ -1,4 +1,4 @@ -import interface_parser as parser +import gtwrap.interface_parser as parser def instantiate_type(ctype, template_typenames, instantiations, cpp_typename, instantiated_class=None): diff --git a/wrap/scripts/matlab_wrap.py b/wrap/scripts/matlab_wrap.py new file mode 100644 index 000000000..232e93490 --- /dev/null +++ b/wrap/scripts/matlab_wrap.py @@ -0,0 +1,68 @@ +#!/usr/bin/env python3 + +""" +Helper script to wrap C++ to Matlab. +This script is installed via CMake to the user's binary directory +and invoked during the wrapping by CMake. +""" + +import argparse +import os + +import gtwrap.interface_parser as parser +import gtwrap.template_instantiator as instantiator +from gtwrap.matlab_wrapper import MatlabWrapper, generate_content + +if __name__ == "__main__": + arg_parser = argparse.ArgumentParser( + formatter_class=argparse.ArgumentDefaultsHelpFormatter) + arg_parser.add_argument("--src", type=str, required=True, + help="Input interface .h file.") + arg_parser.add_argument("--module_name", type=str, required=True, + help="Name of the C++ class being wrapped.") + arg_parser.add_argument("--out", type=str, required=True, + help="Name of the output folder.") + arg_parser.add_argument( + "--top_module_namespaces", + type=str, + default="", + help="C++ namespace for the top module, e.g. `ns1::ns2::ns3`. " + "Only the content within this namespace and its sub-namespaces " + "will be wrapped. The content of this namespace will be available at " + "the top module level, and its sub-namespaces' in the submodules.\n" + "For example, `import ` gives you access to a Python " + "`.Class` of the corresponding C++ `ns1::ns2::ns3::Class`" + ", and `from import ns4` gives you access to a Python " + "`ns4.Class` of the C++ `ns1::ns2::ns3::ns4::Class`. ") + arg_parser.add_argument("--ignore", + nargs='*', + type=str, + help="A space-separated list of classes to ignore. " + "Class names must include their full namespaces.") + args = arg_parser.parse_args() + + top_module_namespaces = args.top_module_namespaces.split("::") + if top_module_namespaces[0]: + top_module_namespaces = [''] + top_module_namespaces + + with open(args.src, 'r') as f: + content = f.read() + + if not os.path.exists(args.src): + os.mkdir(args.src) + + module = parser.Module.parseString(content) + + instantiator.instantiate_namespace_inplace(module) + + import sys + + print("Ignoring classes: {}".format(args.ignore), file=sys.stderr) + wrapper = MatlabWrapper(module=module, + module_name=args.module_name, + top_module_namespace=top_module_namespaces, + ignore_classes=args.ignore) + + cc_content = wrapper.wrap() + + generate_content(cc_content, args.out) diff --git a/wrap/scripts/pybind_wrap.py b/wrap/scripts/pybind_wrap.py new file mode 100644 index 000000000..e641cfaaf --- /dev/null +++ b/wrap/scripts/pybind_wrap.py @@ -0,0 +1,93 @@ +#!/usr/bin/env python3 + +""" +Helper script to wrap C++ to Python with Pybind. +This script is installed via CMake to the user's binary directory +and invoked during the wrapping by CMake. +""" + +import argparse + +import gtwrap.interface_parser as parser +import gtwrap.template_instantiator as instantiator +from gtwrap.pybind_wrapper import PybindWrapper + + +def main(): + """Main runner.""" + arg_parser = argparse.ArgumentParser( + formatter_class=argparse.ArgumentDefaultsHelpFormatter) + arg_parser.add_argument( + "--src", + type=str, + required=True, + help="Input interface .i/.h file") + arg_parser.add_argument( + "--module_name", + type=str, + required=True, + help="Name of the Python module to be generated and " + "used in the Python `import` statement.", + ) + arg_parser.add_argument( + "--out", + type=str, + required=True, + help="Name of the output pybind .cc file", + ) + arg_parser.add_argument( + "--use-boost", + action="store_true", + help="using boost's shared_ptr instead of std's", + ) + arg_parser.add_argument( + "--top_module_namespaces", + type=str, + default="", + help="C++ namespace for the top module, e.g. `ns1::ns2::ns3`. " + "Only the content within this namespace and its sub-namespaces " + "will be wrapped. The content of this namespace will be available at " + "the top module level, and its sub-namespaces' in the submodules.\n" + "For example, `import ` gives you access to a Python " + "`.Class` of the corresponding C++ `ns1::ns2::ns3::Class`" + "and `from import ns4` gives you access to a Python " + "`ns4.Class` of the C++ `ns1::ns2::ns3::ns4::Class`. ", + ) + arg_parser.add_argument( + "--ignore", + nargs='*', + type=str, + help="A space-separated list of classes to ignore. " + "Class names must include their full namespaces.", + ) + arg_parser.add_argument("--template", type=str, + help="The module template file") + args = arg_parser.parse_args() + + top_module_namespaces = args.top_module_namespaces.split("::") + if top_module_namespaces[0]: + top_module_namespaces = [''] + top_module_namespaces + + with open(args.src, "r") as f: + content = f.read() + module = parser.Module.parseString(content) + instantiator.instantiate_namespace_inplace(module) + + with open(args.template, "r") as f: + template_content = f.read() + wrapper = PybindWrapper( + module=module, + module_name=args.module_name, + use_boost=args.use_boost, + top_module_namespaces=top_module_namespaces, + ignore_classes=args.ignore, + module_template=template_content, + ) + + cc_content = wrapper.wrap() + with open(args.out, "w") as f: + f.write(cc_content) + + +if __name__ == "__main__": + main() diff --git a/wrap/setup.py b/wrap/setup.py new file mode 100644 index 000000000..8ef61f312 --- /dev/null +++ b/wrap/setup.py @@ -0,0 +1,36 @@ +"""Setup file for the GTwrap package""" + +try: + from setuptools import find_packages, setup +except ImportError: + from distutils.core import find_packages, setup + +packages = find_packages() + +setup( + name='gtwrap', + description='Library to wrap C++ with Python and Matlab', + version='1.1.0', + author="Frank Dellaert et. al.", + author_email="dellaert@gatech.edu", + license='BSD', + keywords="wrap, bindings, cpp, python", + long_description=open("README.md").read(), + long_description_content_type="text/markdown", + python_requires=">=3.5", + # https://pypi.org/classifiers + classifiers=[ + 'Development Status :: 4 - Beta', + 'Intended Audience :: Education', + 'Intended Audience :: Developers', + 'Intended Audience :: Science/Research', + 'Operating System :: MacOS', + 'Operating System :: Microsoft :: Windows', + 'Operating System :: POSIX', + 'Programming Language :: Python :: 3', + 'Topic :: Software Development :: Libraries' + ], + packages=packages, + platforms="any", + install_requires=open("requirements.txt").readlines(), +) diff --git a/wrap/tests/interface_parser_test.py b/wrap/tests/interface_parser_test.py index 3e989a519..3197b4214 100644 --- a/wrap/tests/interface_parser_test.py +++ b/wrap/tests/interface_parser_test.py @@ -4,7 +4,7 @@ import unittest import sys, os sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) -from interface_parser import * +from gtwrap.interface_parser import * class TestPyparsing(unittest.TestCase): diff --git a/wrap/tests/test_matlab_wrapper.py b/wrap/tests/test_matlab_wrapper.py index 18dc49baf..258f2da8f 100644 --- a/wrap/tests/test_matlab_wrapper.py +++ b/wrap/tests/test_matlab_wrapper.py @@ -10,9 +10,9 @@ import filecmp sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) -import template_instantiator as instantiator -import interface_parser as parser -from matlab_wrapper import MatlabWrapper +import gtwrap.template_instantiator as instantiator +import gtwrap.interface_parser as parser +from gtwrap.matlab_wrapper import MatlabWrapper class TestWrap(unittest.TestCase): @@ -20,7 +20,7 @@ class TestWrap(unittest.TestCase): MATLAB_TEST_DIR = TEST_DIR + "expected-matlab/" MATLAB_ACTUAL_DIR = TEST_DIR + "actual-matlab/" - def _generate_content(self, cc_content, path=''): + def generate_content(self, cc_content, path=''): """Generate files and folders from matlab wrapper content. Keyword arguments: @@ -48,7 +48,7 @@ class TestWrap(unittest.TestCase): for sub_content in c: import sys print("sub object: {}".format(sub_content[1][0][0]), file=sys.stderr) - self._generate_content(sub_content[1], path_to_folder) + self.generate_content(sub_content[1], path_to_folder) elif type(c[1]) == list: path_to_folder = path + '/' + c[0] @@ -104,7 +104,7 @@ class TestWrap(unittest.TestCase): cc_content = wrapper.wrap() - self._generate_content(cc_content) + self.generate_content(cc_content) def compare_and_diff(file): output = self.MATLAB_ACTUAL_DIR + file diff --git a/wrap/tests/test_pybind_wrapper.py b/wrap/tests/test_pybind_wrapper.py index 80032cbcd..d859cc99f 100644 --- a/wrap/tests/test_pybind_wrapper.py +++ b/wrap/tests/test_pybind_wrapper.py @@ -14,9 +14,9 @@ import os.path as path sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) sys.path.append(os.path.normpath(os.path.abspath(os.path.join(__file__, '../../../build/wrap')))) -from pybind_wrapper import PybindWrapper -import interface_parser as parser -import template_instantiator as instantiator +from gtwrap.pybind_wrapper import PybindWrapper +import gtwrap.interface_parser as parser +import gtwrap.template_instantiator as instantiator sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))