├── .gitignore ├── 3rdParty ├── benchmark-1.8.3.zip └── googletest-1.12.0.zip ├── CMakeLists.txt ├── LICENSE ├── README.md ├── data ├── cones │ ├── disp2.png │ ├── disp6.png │ ├── im2.png │ └── im6.png └── teddy │ ├── disp2.png │ ├── disp6.png │ ├── im2.png │ └── im6.png ├── include ├── libStereoMatch.h ├── libStereoMatchConfig.h ├── libStereoMatchConfig.h.in └── typeDef.h ├── perf ├── CMakeLists.txt ├── perfCostAggregation.cpp ├── perfCostCompute.cpp ├── perfDispCompute.cpp ├── perfDispOptimiztion.cpp └── perfSGM.cpp ├── src ├── CMakeLists.txt ├── algorithm.h ├── costAggregation │ ├── costAggregation.h │ ├── multipathAggregation.cpp │ └── multipathAggregation.h ├── costCompute │ ├── adCensusCost.cpp │ ├── adCensusCost.h │ ├── adCost.cpp │ ├── adCost.h │ ├── censusCost.cpp │ ├── censusCost.h │ └── costCompute.h ├── dispCompute │ ├── dispCompute.cpp │ └── dispCompute.h ├── dispOptimiztion │ ├── dispOptimiztion.cpp │ └── dispOptimiztion.h ├── sgm.cpp └── sgm.h ├── test ├── CMakeLists.txt ├── testCostAggregation.cpp ├── testCostCompute.cpp ├── testDispCompute.cpp ├── testDispOptimiztion.cpp └── testSGM.cpp └── uml ├── costAggregation.png ├── costAggregation.vsdx ├── costCompute.png ├── costCompute.vsdx └── dispCompute.vsdx /.gitignore: -------------------------------------------------------------------------------- 1 | # Folder 2 | build 3 | .vs 4 | 5 | # No used File 6 | CMakeSettings.json 7 | 8 | # Prerequisites 9 | *.d 10 | 11 | # Compiled Object files 12 | *.slo 13 | *.lo 14 | *.o 15 | *.obj 16 | 17 | # Precompiled Headers 18 | *.gch 19 | *.pch 20 | 21 | # Compiled Dynamic libraries 22 | *.so 23 | *.dylib 24 | *.dll 25 | 26 | # Fortran module files 27 | *.mod 28 | *.smod 29 | 30 | # Compiled Static libraries 31 | *.lai 32 | *.la 33 | *.a 34 | *.lib 35 | 36 | # Executables 37 | *.exe 38 | *.out 39 | *.app -------------------------------------------------------------------------------- /3rdParty/benchmark-1.8.3.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Practice3DVision/libStereoMatch/70c681e49c862e9e2b04e71d107a664c90d824f7/3rdParty/benchmark-1.8.3.zip -------------------------------------------------------------------------------- /3rdParty/googletest-1.12.0.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Practice3DVision/libStereoMatch/70c681e49c862e9e2b04e71d107a664c90d824f7/3rdParty/googletest-1.12.0.zip -------------------------------------------------------------------------------- /CMakeLists.txt: -------------------------------------------------------------------------------- 1 | cmake_minimum_required(VERSION 3.20) 2 | 3 | project(libStereoMatch VERSION 0.1.0) 4 | 5 | set(CMAKE_EXPORT_COMPILE_COMMANDS TRUE) 6 | 7 | option(BUILD_SHARED "compile libStereoMatch as a dynamic library." OFF) 8 | option(BUILD_TEST "perform accuracy testing." ON) 9 | option(BUILD_PERF "perform performance testing." ON) 10 | 11 | configure_file( 12 | ${CMAKE_CURRENT_SOURCE_DIR}/include/libStereoMatchConfig.h.in 13 | ${CMAKE_CURRENT_SOURCE_DIR}/include/libStereoMatchConfig.h 14 | ) 15 | 16 | message("Version of libStereoMatch: ${PROJECT_VERSION}") 17 | add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/src) 18 | 19 | if(BUILD_TEST) 20 | message("Perform accuracy testing.") 21 | add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/test) 22 | endif() 23 | 24 | if(BUILD_PERF) 25 | message("Perform performance testing.") 26 | add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/perf) 27 | endif() -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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It is safest 630 | to attach them to the start of each source file to most effectively 631 | state the exclusion of warranty; and each file should have at least 632 | the "copyright" line and a pointer to where the full notice is found. 633 | 634 | 635 | Copyright (C) 636 | 637 | This program is free software: you can redistribute it and/or modify 638 | it under the terms of the GNU General Public License as published by 639 | the Free Software Foundation, either version 3 of the License, or 640 | (at your option) any later version. 641 | 642 | This program is distributed in the hope that it will be useful, 643 | but WITHOUT ANY WARRANTY; without even the implied warranty of 644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 645 | GNU General Public License for more details. 646 | 647 | You should have received a copy of the GNU General Public License 648 | along with this program. If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # libStereoMatch 2 | libStereoMatch is a universal stereo matching library. This library is developed using C++and divides the stereo matching steps into four steps: cost calculation, cost aggregation, disparity calculation, and disparity optimization. Users can build their own stereo matching algorithms through combination and combination. 3 | -------------------------------------------------------------------------------- /data/cones/disp2.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Practice3DVision/libStereoMatch/70c681e49c862e9e2b04e71d107a664c90d824f7/data/cones/disp2.png -------------------------------------------------------------------------------- /data/cones/disp6.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Practice3DVision/libStereoMatch/70c681e49c862e9e2b04e71d107a664c90d824f7/data/cones/disp6.png -------------------------------------------------------------------------------- /data/cones/im2.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Practice3DVision/libStereoMatch/70c681e49c862e9e2b04e71d107a664c90d824f7/data/cones/im2.png -------------------------------------------------------------------------------- /data/cones/im6.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Practice3DVision/libStereoMatch/70c681e49c862e9e2b04e71d107a664c90d824f7/data/cones/im6.png -------------------------------------------------------------------------------- /data/teddy/disp2.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Practice3DVision/libStereoMatch/70c681e49c862e9e2b04e71d107a664c90d824f7/data/teddy/disp2.png -------------------------------------------------------------------------------- /data/teddy/disp6.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Practice3DVision/libStereoMatch/70c681e49c862e9e2b04e71d107a664c90d824f7/data/teddy/disp6.png -------------------------------------------------------------------------------- /data/teddy/im2.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Practice3DVision/libStereoMatch/70c681e49c862e9e2b04e71d107a664c90d824f7/data/teddy/im2.png -------------------------------------------------------------------------------- /data/teddy/im6.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Practice3DVision/libStereoMatch/70c681e49c862e9e2b04e71d107a664c90d824f7/data/teddy/im6.png -------------------------------------------------------------------------------- /include/libStereoMatch.h: -------------------------------------------------------------------------------- 1 | /** 2 | * @file libStereoMatch.h 3 | * @author Liu Yunhuang (1369215984@qq.com) 4 | * @brief 5 | * @version 0.1 6 | * @date 2024-03-06 7 | * 8 | * @copyright Copyright (c) 2024 9 | * 10 | */ 11 | 12 | #ifndef __LIB_STEREO_MATCH_H_ 13 | #define __LIB_STEREO_MATCH_H_ 14 | 15 | #include 16 | #include 17 | #include 18 | #include 19 | 20 | #include 21 | #include 22 | 23 | #include 24 | 25 | #include 26 | 27 | #include 28 | 29 | #endif //!__LIB_STEREO_MATCH_H_ -------------------------------------------------------------------------------- /include/libStereoMatchConfig.h: -------------------------------------------------------------------------------- 1 | /** 2 | * @file libStereoMatchConfig.h.in 3 | * @author Liu Yunhuang (1369215984@qq.com) 4 | * @brief 5 | * @version 0.1 6 | * @date 2024-03-06 7 | * 8 | * @copyright Copyright (c) 2024 9 | * 10 | */ 11 | 12 | #ifndef __LIB_STEREO_MATCH_CONFIG_H_ 13 | #define __LIB_STEREO_MATCH_CONFIG_H_ 14 | 15 | /* #undef BUILD_SHARED */ 16 | 17 | #define LIB_STEREO_MATCH_VERSION 0.1.0 18 | #define LIB_STEREO_MATCH_VERSION_MAJOR 0 19 | #define LIB_STEREO_MATCH_VERSION_MINOR 1 20 | #define LIB_STEREO_MATCH_VERSION_PATCH 0 21 | 22 | #endif //!__LIB_STEREO_MATCH_CONFIG_H_ 23 | -------------------------------------------------------------------------------- /include/libStereoMatchConfig.h.in: -------------------------------------------------------------------------------- 1 | /** 2 | * @file libStereoMatchConfig.h.in 3 | * @author Liu Yunhuang (1369215984@qq.com) 4 | * @brief 5 | * @version 0.1 6 | * @date 2024-03-06 7 | * 8 | * @copyright Copyright (c) 2024 9 | * 10 | */ 11 | 12 | #ifndef __LIB_STEREO_MATCH_CONFIG_H_ 13 | #define __LIB_STEREO_MATCH_CONFIG_H_ 14 | 15 | #cmakedefine BUILD_SHARED 16 | 17 | #define LIB_STEREO_MATCH_VERSION @libStereoMatch_VERSION@ 18 | #define LIB_STEREO_MATCH_VERSION_MAJOR @libStereoMatch_VERSION_MAJOR@ 19 | #define LIB_STEREO_MATCH_VERSION_MINOR @libStereoMatch_VERSION_MINOR@ 20 | #define LIB_STEREO_MATCH_VERSION_PATCH @libStereoMatch_VERSION_PATCH@ 21 | 22 | #endif //!__LIB_STEREO_MATCH_CONFIG_H_ -------------------------------------------------------------------------------- /include/typeDef.h: -------------------------------------------------------------------------------- 1 | /** 2 | * @file typeDef.h 3 | * @author Liu Yunhuang (1369215984@qq.com) 4 | * @brief 5 | * @version 0.1 6 | * @date 2024-03-06 7 | * 8 | * @copyright Copyright (c) 2024 9 | * 10 | */ 11 | 12 | #ifndef __TYPE_DEF_H_ 13 | #define __TYPE_DEF_H_ 14 | 15 | #include "libStereoMatchConfig.h" 16 | 17 | #include 18 | 19 | #define IN 20 | #define OUT 21 | 22 | #ifdef BUILD_SHARED 23 | #ifdef WIN32 24 | #define LIBSM_API __declspec(dllexport) 25 | #else 26 | #define LIBSM_API __declspec(dllimport) 27 | #endif 28 | #else 29 | #define LIBSM_API 30 | #endif 31 | 32 | #define OCCLUDED_PIXEL -0.111f 33 | #define MISMATCHED_PIXEL 0.111f 34 | #define NONE_PIXEL 0.f 35 | #define IS_OCCLUDED_PIXEL(val) (std::abs(val - OCCLUDED_PIXEL) < 0.0001f) 36 | #define IS_MISMATCHED_PIXEL(val) (std::abs(val - MISMATCHED_PIXEL) < 0.0001f) 37 | #define IS_NONE_PIXEL(val) (std::abs(val - NONE_PIXEL) < 0.0001f) 38 | 39 | namespace libSM { 40 | template 41 | using Ptr = std::shared_ptr; 42 | } 43 | 44 | #endif //!__TYPE_DEF_H_ -------------------------------------------------------------------------------- /perf/CMakeLists.txt: -------------------------------------------------------------------------------- 1 | cmake_minimum_required(VERSION 3.20) 2 | 3 | include(FetchContent) 4 | FetchContent_Declare( 5 | benchmark 6 | URL ${PROJECT_SOURCE_DIR}/3rdParty/benchmark-1.8.3.zip 7 | ) 8 | 9 | project(PerfermanceTest) 10 | 11 | set(gtest_force_shared_crt ON CACHE BOOL "" FORCE) 12 | 13 | FetchContent_MakeAvailable(benchmark) 14 | 15 | add_executable( 16 | PerfermanceCostCompute 17 | ${CMAKE_CURRENT_SOURCE_DIR}/perfCostCompute.cpp 18 | ) 19 | 20 | target_link_libraries( 21 | PerfermanceCostCompute 22 | PRIVATE 23 | benchmark::benchmark 24 | StereoMatch 25 | ) 26 | 27 | add_executable( 28 | PerfermanceDispCompute 29 | ${CMAKE_CURRENT_SOURCE_DIR}/perfDispCompute.cpp 30 | ) 31 | 32 | target_link_libraries( 33 | PerfermanceDispCompute 34 | PRIVATE 35 | benchmark::benchmark 36 | StereoMatch 37 | ) 38 | 39 | add_executable( 40 | PerfermanceCostAggregation 41 | ${CMAKE_CURRENT_SOURCE_DIR}/perfCostAggregation.cpp 42 | ) 43 | 44 | target_link_libraries( 45 | PerfermanceCostAggregation 46 | PRIVATE 47 | benchmark::benchmark 48 | StereoMatch 49 | ) 50 | 51 | add_executable( 52 | PerfermanceDispOptimiztion 53 | ${CMAKE_CURRENT_SOURCE_DIR}/perfDispOptimiztion.cpp 54 | ) 55 | 56 | target_link_libraries( 57 | PerfermanceDispOptimiztion 58 | PRIVATE 59 | benchmark::benchmark 60 | StereoMatch 61 | ) 62 | 63 | add_executable( 64 | PerfermanceSGM 65 | ${CMAKE_CURRENT_SOURCE_DIR}/perfSGM.cpp 66 | ) 67 | 68 | target_link_libraries( 69 | PerfermanceSGM 70 | PRIVATE 71 | benchmark::benchmark 72 | StereoMatch 73 | ) -------------------------------------------------------------------------------- /perf/perfCostAggregation.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | 3 | #include 4 | 5 | #include 6 | 7 | using namespace libSM; 8 | using namespace cv; 9 | using namespace std; 10 | 11 | const string CONES_DATA_SET_PATH = "../../data/cones/"; 12 | const string TEDDY_DATA_SET_PATH = "../../data/teddy/"; 13 | 14 | class Cones : public benchmark::Fixture { 15 | protected: 16 | void SetUp(const benchmark::State &) override { 17 | left = imread(CONES_DATA_SET_PATH + "im2.png", IMREAD_UNCHANGED); 18 | right = imread(CONES_DATA_SET_PATH + "im6.png", IMREAD_UNCHANGED); 19 | } 20 | 21 | public: 22 | Mat left; 23 | Mat right; 24 | void transformToGray() { 25 | if (left.type() == CV_8UC3) 26 | cvtColor(left, left, COLOR_BGR2GRAY); 27 | 28 | if (right.type() == CV_8UC3) 29 | cvtColor(right, right, COLOR_BGR2GRAY); 30 | } 31 | }; 32 | 33 | BENCHMARK_DEFINE_F(Cones, perfWinnerTakesAll)(benchmark::State& state) { 34 | transformToGray(); 35 | 36 | Mat cost; 37 | { 38 | auto params = CensusCost::Params(); 39 | params.windowWidth = 9; 40 | params.windowHeight = 7; 41 | params.minDisp = 0; 42 | params.maxDisp = state.range(0); 43 | 44 | auto adCensusComputer = CensusCost::create(params); 45 | adCensusComputer->compute(left, right, cost); 46 | } 47 | 48 | Mat aggregatedCost; 49 | { 50 | auto params = MultipathAggregation::Params(); 51 | params.P1 = 10.f; 52 | params.P2 = 150.f; 53 | params.enableHonrizon = true; 54 | params.enableNegtive45 = true; 55 | params.enablePostive45 = true; 56 | params.enableVertiacl = true; 57 | 58 | auto multipathAggregator = MultipathAggregation::create(params); 59 | 60 | for (auto _ : state) { 61 | multipathAggregator->aggregation(left, cost, aggregatedCost); 62 | } 63 | } 64 | 65 | Mat disp; 66 | { 67 | auto params = DispComputeParams(); 68 | params.enableLRCheck = true; 69 | params.enableUniqueCheck = true; 70 | params.enableSubpixelFitting = true; 71 | params.lrCheckThreshod = 1; 72 | params.uniquenessRatio = 0.95f; 73 | params.minDisp = 0; 74 | params.maxDisp = 64; 75 | 76 | winnerTakesAll(aggregatedCost, disp, params); 77 | } 78 | } 79 | 80 | BENCHMARK_REGISTER_F(Cones, perfWinnerTakesAll)->MeasureProcessCPUTime()->UseRealTime()->Unit(benchmark::TimeUnit::kSecond)->DenseRange(32, 256, 32); 81 | 82 | BENCHMARK_MAIN(); -------------------------------------------------------------------------------- /perf/perfCostCompute.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | 3 | #include 4 | 5 | #include 6 | 7 | using namespace libSM; 8 | using namespace cv; 9 | using namespace std; 10 | 11 | const string CONES_DATA_SET_PATH = "../../data/cones/"; 12 | const string TEDDY_DATA_SET_PATH = "../../data/teddy/"; 13 | 14 | class Cones : public benchmark::Fixture { 15 | protected: 16 | void SetUp(const benchmark::State &) override { 17 | left = imread(CONES_DATA_SET_PATH + "im2.png", IMREAD_UNCHANGED); 18 | right = imread(CONES_DATA_SET_PATH + "im6.png", IMREAD_UNCHANGED); 19 | } 20 | 21 | public: 22 | Mat left; 23 | Mat right; 24 | void transformToGray() { 25 | if (left.type() == CV_8UC3) 26 | cvtColor(left, left, COLOR_BGR2GRAY); 27 | 28 | if (right.type() == CV_8UC3) 29 | cvtColor(right, right, COLOR_BGR2GRAY); 30 | } 31 | }; 32 | 33 | BENCHMARK_DEFINE_F(Cones, perfADCostColor)(benchmark::State &state) { 34 | auto params = ADCost::Params(); 35 | params.windowWidth = 9; 36 | params.windowHeight = 7; 37 | params.minDisp = 0; 38 | params.maxDisp = state.range(0); 39 | auto adCostComputer = ADCost::create(params); 40 | Mat out; 41 | for (auto _ : state) { 42 | adCostComputer->compute(left, right, out); 43 | } 44 | }; 45 | 46 | BENCHMARK_DEFINE_F(Cones, perfADCostGray)(benchmark::State &state) { 47 | auto params = ADCost::Params(); 48 | params.windowWidth = 9; 49 | params.windowHeight = 7; 50 | params.minDisp = 0; 51 | params.maxDisp = state.range(0); 52 | auto adCostComputer = ADCost::create(params); 53 | Mat out; 54 | transformToGray(); 55 | for (auto _ : state) { 56 | adCostComputer->compute(left, right, out); 57 | } 58 | }; 59 | 60 | BENCHMARK_DEFINE_F(Cones, perfCensusCost)(benchmark::State& state) { 61 | auto params = CensusCost::Params(); 62 | params.windowWidth = 9; 63 | params.windowHeight = 7; 64 | params.minDisp = 0; 65 | params.maxDisp = state.range(0); 66 | auto censusCostComputer = CensusCost::create(params); 67 | Mat out; 68 | transformToGray(); 69 | for (auto _ : state) { 70 | censusCostComputer->compute(left, right, out); 71 | } 72 | } 73 | 74 | BENCHMARK_DEFINE_F(Cones, perfADCensusCost)(benchmark::State& state) { 75 | auto params = ADCensusCost::Params(); 76 | params.windowWidth = 9; 77 | params.windowHeight = 7; 78 | params.minDisp = 0; 79 | params.maxDisp = state.range(0); 80 | params.adWeight = 10.f; 81 | params.censusWeight = 30.f; 82 | auto adcensusCostComputer = ADCensusCost::create(params); 83 | Mat out; 84 | transformToGray(); 85 | for (auto _ : state) { 86 | adcensusCostComputer->compute(left, right, out); 87 | } 88 | } 89 | 90 | BENCHMARK_REGISTER_F(Cones, perfADCostColor)->MeasureProcessCPUTime()->UseRealTime()->Unit(benchmark::TimeUnit::kSecond)->DenseRange(32, 256, 32); 91 | BENCHMARK_REGISTER_F(Cones, perfADCostGray)->MeasureProcessCPUTime()->UseRealTime()->Unit(benchmark::TimeUnit::kSecond)->DenseRange(32, 256, 32); 92 | BENCHMARK_REGISTER_F(Cones, perfCensusCost)->MeasureProcessCPUTime()->UseRealTime()->Unit(benchmark::TimeUnit::kSecond)->DenseRange(32, 256, 32); 93 | BENCHMARK_REGISTER_F(Cones, perfADCensusCost)->MeasureProcessCPUTime()->UseRealTime()->Unit(benchmark::TimeUnit::kSecond)->DenseRange(32, 256, 32); 94 | 95 | BENCHMARK_MAIN(); -------------------------------------------------------------------------------- /perf/perfDispCompute.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | 3 | #include 4 | 5 | #include 6 | 7 | using namespace libSM; 8 | using namespace cv; 9 | using namespace std; 10 | 11 | const string CONES_DATA_SET_PATH = "../../data/cones/"; 12 | const string TEDDY_DATA_SET_PATH = "../../data/teddy/"; 13 | 14 | class Cones : public benchmark::Fixture { 15 | protected: 16 | void SetUp(const benchmark::State &) override { 17 | left = imread(CONES_DATA_SET_PATH + "im2.png", IMREAD_UNCHANGED); 18 | right = imread(CONES_DATA_SET_PATH + "im6.png", IMREAD_UNCHANGED); 19 | } 20 | 21 | public: 22 | Mat left; 23 | Mat right; 24 | void transformToGray() { 25 | if (left.type() == CV_8UC3) 26 | cvtColor(left, left, COLOR_BGR2GRAY); 27 | 28 | if (right.type() == CV_8UC3) 29 | cvtColor(right, right, COLOR_BGR2GRAY); 30 | } 31 | }; 32 | 33 | BENCHMARK_DEFINE_F(Cones, perfWinnerTakesAll)(benchmark::State& state) { 34 | Mat cost; 35 | { 36 | auto params = ADCensusCost::Params(); 37 | params.windowWidth = 9; 38 | params.windowHeight = 7; 39 | params.minDisp = 0; 40 | params.maxDisp = 128; 41 | params.adWeight = 10.f; 42 | params.censusWeight = 30.f; 43 | 44 | transformToGray(); 45 | 46 | auto adCensusComputer = ADCensusCost::create(params); 47 | adCensusComputer->compute(left, right, cost); 48 | } 49 | 50 | Mat disp; 51 | { 52 | auto params = DispComputeParams(); 53 | params.enableLRCheck = true; 54 | params.enableUniqueCheck = true; 55 | params.enableSubpixelFitting = true; 56 | params.lrCheckThreshod = 1; 57 | params.uniquenessRatio = 0.98f; 58 | params.minDisp = 0; 59 | params.maxDisp = state.range(0); 60 | 61 | for (auto _ : state) { 62 | winnerTakesAll(cost, disp, params); 63 | } 64 | } 65 | } 66 | 67 | BENCHMARK_REGISTER_F(Cones, perfWinnerTakesAll)->MeasureProcessCPUTime()->UseRealTime()->Unit(benchmark::TimeUnit::kSecond)->DenseRange(32, 256, 32); 68 | 69 | BENCHMARK_MAIN(); -------------------------------------------------------------------------------- /perf/perfDispOptimiztion.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | 3 | #include 4 | 5 | #include 6 | 7 | using namespace libSM; 8 | using namespace cv; 9 | using namespace std; 10 | 11 | const string CONES_DATA_SET_PATH = "../../data/cones/"; 12 | const string TEDDY_DATA_SET_PATH = "../../data/teddy/"; 13 | 14 | class Cones : public benchmark::Fixture { 15 | protected: 16 | void SetUp(const benchmark::State &) override { 17 | left = imread(CONES_DATA_SET_PATH + "im2.png", IMREAD_UNCHANGED); 18 | right = imread(CONES_DATA_SET_PATH + "im6.png", IMREAD_UNCHANGED); 19 | } 20 | 21 | public: 22 | Mat left; 23 | Mat right; 24 | void transformToGray() { 25 | if (left.type() == CV_8UC3) 26 | cvtColor(left, left, COLOR_BGR2GRAY); 27 | 28 | if (right.type() == CV_8UC3) 29 | cvtColor(right, right, COLOR_BGR2GRAY); 30 | } 31 | }; 32 | 33 | BENCHMARK_DEFINE_F(Cones, perfDispOptimiztion)(benchmark::State& state) { 34 | transformToGray(); 35 | 36 | Mat cost; 37 | { 38 | auto params = CensusCost::Params(); 39 | params.windowWidth = 9; 40 | params.windowHeight = 7; 41 | params.minDisp = 0; 42 | params.maxDisp = 64; 43 | 44 | auto adCensusComputer = CensusCost::create(params); 45 | adCensusComputer->compute(left, right, cost); 46 | } 47 | 48 | Mat aggregatedCost; 49 | { 50 | auto params = MultipathAggregation::Params(); 51 | params.P1 = 10.f; 52 | params.P2 = 150.f; 53 | params.enableHonrizon = true; 54 | params.enableNegtive45 = true; 55 | params.enablePostive45 = true; 56 | params.enableVertiacl = true; 57 | 58 | auto multipathAggregator = MultipathAggregation::create(params); 59 | multipathAggregator->aggregation(left, cost, aggregatedCost); 60 | } 61 | 62 | Mat disp; 63 | { 64 | auto params = DispComputeParams(); 65 | params.enableLRCheck = true; 66 | params.enableUniqueCheck = true; 67 | params.enableSubpixelFitting = true; 68 | params.lrCheckThreshod = 1; 69 | params.uniquenessRatio = 0.95f; 70 | params.minDisp = 0; 71 | params.maxDisp = 64; 72 | 73 | winnerTakesAll(aggregatedCost, disp, params); 74 | } 75 | 76 | 77 | Mat optimizedDisp; 78 | { 79 | auto params = DispOptParams(); 80 | params.enableRemoveSmallArea = true; 81 | params.dispDomainThreshold = 2; 82 | params.smallAreaThreshold = 10; 83 | params.enableBilateralFilter = true; 84 | params.d = 10; 85 | params.sigmaColor = 10; 86 | params.sigmaSpace = 20; 87 | 88 | for (auto _ : state) { 89 | dispOptimiz(disp, optimizedDisp, params); 90 | } 91 | } 92 | } 93 | 94 | BENCHMARK_REGISTER_F(Cones, perfDispOptimiztion)->MeasureProcessCPUTime()->UseRealTime()->Unit(benchmark::TimeUnit::kSecond)->DenseRange(32, 256, 32); 95 | 96 | BENCHMARK_MAIN(); -------------------------------------------------------------------------------- /perf/perfSGM.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | 3 | #include 4 | 5 | #include 6 | 7 | using namespace libSM; 8 | using namespace cv; 9 | using namespace std; 10 | 11 | const string CONES_DATA_SET_PATH = "../../data/cones/"; 12 | const string TEDDY_DATA_SET_PATH = "../../data/teddy/"; 13 | 14 | class Cones : public benchmark::Fixture { 15 | protected: 16 | void SetUp(const benchmark::State &) override { 17 | left = imread(CONES_DATA_SET_PATH + "im2.png", IMREAD_UNCHANGED); 18 | right = imread(CONES_DATA_SET_PATH + "im6.png", IMREAD_UNCHANGED); 19 | } 20 | 21 | public: 22 | Mat left; 23 | Mat right; 24 | void transformToGray() { 25 | if (left.type() == CV_8UC3) 26 | cvtColor(left, left, COLOR_BGR2GRAY); 27 | 28 | if (right.type() == CV_8UC3) 29 | cvtColor(right, right, COLOR_BGR2GRAY); 30 | } 31 | }; 32 | 33 | BENCHMARK_DEFINE_F(Cones, perfDispOptimiztion)(benchmark::State& state) { 34 | transformToGray(); 35 | 36 | auto params = SGM::Params(); 37 | params.maxDisp = state.range(0); 38 | auto sgm = SGM::create(params); 39 | 40 | Mat disparityMap; 41 | 42 | for (auto _ : state) { 43 | sgm->match(left, right, disparityMap); 44 | } 45 | } 46 | 47 | BENCHMARK_REGISTER_F(Cones, perfDispOptimiztion)->MeasureProcessCPUTime()->UseRealTime()->Unit(benchmark::TimeUnit::kSecond)->DenseRange(32, 256, 32); 48 | 49 | BENCHMARK_MAIN(); -------------------------------------------------------------------------------- /src/CMakeLists.txt: -------------------------------------------------------------------------------- 1 | cmake_minimum_required(VERSION 3.20) 2 | 3 | set(PROJECT_ROOT_HEADER_DIR ${PROJECT_SOURCE_DIR}/include) 4 | 5 | project(StereoMatch LANGUAGES CXX) 6 | 7 | find_package(OpenCV REQUIRED) 8 | 9 | file(GLOB_RECURSE HEADERS ${CMAKE_CURRENT_SOURCE_DIR}/*.h ${PROJECT_ROOT_HEADER_DIR}/*.h) 10 | file(GLOB_RECURSE SOURCES ${CMAKE_CURRENT_SOURCE_DIR}/*.cpp ${CMAKE_CURRENT_SOURCE_DIR}/*.hpp) 11 | source_group("Headers" FILES ${HEADERS}) 12 | source_group("Sources" FILES ${SOURCES}) 13 | 14 | if(BUILD_SHARED) 15 | add_library(${PROJECT_NAME} SHARED) 16 | else() 17 | add_library(${PROJECT_NAME} STATIC) 18 | endif() 19 | 20 | target_sources(${PROJECT_NAME} PUBLIC ${HEADERS} PRIVATE ${SOURCES}) 21 | target_compile_options(${PROJECT_NAME} PRIVATE /openmp) 22 | target_link_libraries(${PROJECT_NAME} PUBLIC ${OpenCV_LIBRARIES}) 23 | target_include_directories(${PROJECT_NAME} PUBLIC ${PROJECT_ROOT_HEADER_DIR} ${CMAKE_CURRENT_SOURCE_DIR}) -------------------------------------------------------------------------------- /src/algorithm.h: -------------------------------------------------------------------------------- 1 | /** 2 | * @file algorithm.h 3 | * @author Liu Yunhuang (1369215984@qq.com) 4 | * @brief 5 | * @version 0.1 6 | * @date 2024-03-08 7 | * 8 | * @copyright Copyright (c) 2024 9 | * 10 | */ 11 | 12 | #ifndef __ALGORITHM_H_ 13 | #define __ALGORITHM_H_ 14 | 15 | #include 16 | 17 | namespace cv { 18 | class Mat; 19 | } 20 | 21 | namespace libSM { 22 | class Algorithm { 23 | public: 24 | virtual ~Algorithm() {} 25 | /** 26 | * @brief perform stereo matching 27 | * 28 | * @param left left image 29 | * @param right right image 30 | * @param dispMap disparity Map 31 | */ 32 | virtual void match(IN const cv::Mat& left, IN const cv::Mat& right, OUT cv::Mat& dispMap) = 0; 33 | }; 34 | } 35 | 36 | #endif //!__ALGORITHM_H_ -------------------------------------------------------------------------------- /src/costAggregation/costAggregation.h: -------------------------------------------------------------------------------- 1 | /** 2 | * @file costAggregation.h 3 | * @author Liu Yunhuang (1369215984@qq.com) 4 | * @brief 5 | * @version 0.1 6 | * @date 2024-03-07 7 | * 8 | * @copyright Copyright (c) 2024 9 | * 10 | */ 11 | 12 | #ifndef __COST_AGGREGATION_H_ 13 | #define __COST_AGGREGATION_H_ 14 | 15 | #include 16 | 17 | namespace cv { 18 | class Mat; 19 | } 20 | 21 | namespace libSM { 22 | /** 23 | * @brief cost aggregator 24 | * 25 | */ 26 | class LIBSM_API CostAggregation { 27 | public: 28 | virtual ~CostAggregation() {} 29 | /** 30 | * @brief aggregation cost 31 | * 32 | * @param left left image 33 | * @param cost cost space 34 | * @param aggregationCost aggregated cost 35 | */ 36 | virtual void aggregation(IN const cv::Mat &left, 37 | IN const cv::Mat &cost, 38 | OUT cv::Mat &aggregationCost) = 0; 39 | }; 40 | } // namespace libSM 41 | 42 | #endif //!__COST_AGGREGATION_H_ -------------------------------------------------------------------------------- /src/costAggregation/multipathAggregation.cpp: -------------------------------------------------------------------------------- 1 | #include "multipathAggregation.h" 2 | 3 | #include 4 | 5 | using namespace cv; 6 | using namespace std; 7 | 8 | namespace libSM { 9 | class MultipathAggregationImpl : public MultipathAggregation { 10 | public: 11 | MultipathAggregationImpl(const Params params) : params_(params){}; 12 | void aggregation(const cv::Mat &left, const cv::Mat &cost, 13 | cv::Mat &aggregationCost) override; 14 | 15 | private: 16 | /** 17 | * @brief aggregation cost horizontally 18 | * 19 | * @param left left image 20 | * @param cost cost space 21 | * @param aggregationCost aggregated cost 22 | * @param leftToRight from left to right 23 | */ 24 | void aggregationHorizontal(const cv::Mat &left, const Mat &cost, 25 | Mat &aggregationCost, bool leftToRight = true); 26 | /** 27 | * @brief aggregation cost vertically 28 | * 29 | * @param left left image 30 | * @param cost cost space 31 | * @param aggregationCost aggregated cost 32 | * @param leftToRight from up to bottom 33 | */ 34 | void aggregationVertical(const cv::Mat &left, const Mat &cost, 35 | Mat &aggregationCost, bool upToBottom = true); 36 | /** 37 | * @brief aggregation cost on the negative 45-degree line 38 | * 39 | * @param left left image 40 | * @param cost cost space 41 | * @param aggregationCost aggregated cost 42 | * @param topLeftToBottomRight from top-left to bottom-right 43 | */ 44 | void aggregationNegative45(const cv::Mat &left, const Mat &cost, 45 | Mat &aggregationCost, 46 | bool topLeftToBottomRight = true); 47 | /** 48 | * @brief aggregation cost on the 45-degree line 49 | * 50 | * @param left left image 51 | * @param cost cost space 52 | * @param aggregationCost aggregated cost 53 | * @param topRightToBottomLeft from top-right to bottom-left 54 | */ 55 | void aggregationPostive45(const cv::Mat &left, const Mat &cost, 56 | Mat &aggregationCost, 57 | bool topRightToBottomLeft = true); 58 | Params params_; 59 | }; 60 | 61 | void MultipathAggregationImpl::aggregationHorizontal(const cv::Mat &left, 62 | const Mat &cost, 63 | Mat &aggregationCost, 64 | bool leftToRight) { 65 | const int beginLoc = leftToRight ? 0 : cost.cols - 1; 66 | const int endLoc = leftToRight ? cost.cols : 0; 67 | const int direction = leftToRight ? 1 : -1; 68 | 69 | #pragma omp parallel for schedule(dynamic) default(shared) 70 | for (int i = 0; i < cost.rows; ++i) { 71 | auto ptrCost = cost.ptr(i); 72 | auto ptrAggregationCost = aggregationCost.ptr(i); 73 | auto ptrLeft = left.ptr(i); 74 | 75 | vector lastCost(cost.channels() + 2, FLT_MAX); 76 | float lastMin = FLT_MAX; 77 | 78 | for (int d = 0; d < cost.channels(); ++d) { 79 | auto curCost = ptrCost[cost.channels() * beginLoc + d]; 80 | lastMin = min(lastMin, curCost); 81 | lastCost[d + 1] = curCost; 82 | } 83 | 84 | for (int j = beginLoc + direction; j != endLoc; j += direction) { 85 | float curLocMinCost = FLT_MAX; 86 | 87 | for (int d = 0; d < cost.channels(); ++d) { 88 | auto lastCurDispCost = lastCost[d + 1]; 89 | auto lastPreDispCost = lastCost[d] + params_.P1; 90 | auto lastAftDispCost = lastCost[d + 2] + params_.P1; 91 | auto lastElseDispCost = 92 | lastMin + 93 | max(params_.P2 / 94 | (max(abs(ptrLeft[j] - ptrLeft[j - direction]), 1)), 95 | params_.P1); 96 | 97 | auto curCost = ptrCost[cost.channels() * j + d] + 98 | min(min(lastCurDispCost, lastPreDispCost), 99 | min(lastAftDispCost, lastElseDispCost)) - 100 | lastMin; 101 | 102 | curLocMinCost = min(curLocMinCost, curCost); 103 | ptrAggregationCost[cost.channels() * j + d] = curCost; 104 | } 105 | 106 | for (int d = 0; d < cost.channels(); ++d) { 107 | lastCost[d + 1] = ptrAggregationCost[cost.channels() * j + d]; 108 | } 109 | 110 | lastMin = curLocMinCost; 111 | } 112 | } 113 | } 114 | 115 | void MultipathAggregationImpl::aggregationVertical(const cv::Mat &left, 116 | const Mat &cost, 117 | Mat &aggregationCost, 118 | bool upToBottom) { 119 | const int beginLoc = upToBottom ? 0 : cost.rows - 1; 120 | const int endLoc = upToBottom ? cost.rows : 0; 121 | const int direction = upToBottom ? 1 : -1; 122 | 123 | #pragma omp parallel for schedule(dynamic) default(shared) 124 | for (int j = 0; j < cost.cols; ++j) { 125 | vector lastCost(cost.channels() + 2, FLT_MAX); 126 | float lastMin = FLT_MAX; 127 | uchar lastPixel = left.ptr(beginLoc)[j]; 128 | 129 | for (int d = 0; d < cost.channels(); ++d) { 130 | auto curCost = cost.ptr(beginLoc)[cost.channels() * j + d]; 131 | lastCost[d + 1] = curCost; 132 | 133 | if (curCost < lastMin) { 134 | lastMin = curCost; 135 | } 136 | } 137 | 138 | for (int i = beginLoc + direction; i != endLoc; i = i + direction) { 139 | auto ptrCurCost = cost.ptr(i); 140 | auto ptrCurLeft = left.ptr(i); 141 | auto ptrAggregationCost = aggregationCost.ptr(i); 142 | float curLocMinCost = FLT_MAX; 143 | 144 | for (int d = 0; d < cost.channels(); ++d) { 145 | auto lastCurDispCost = lastCost[d + 1]; 146 | auto lastPreDispCost = lastCost[d] + params_.P1; 147 | auto lastAftDispCost = lastCost[d + 2] + params_.P1; 148 | auto lastElseDispCost = 149 | lastMin + 150 | max(params_.P2 / (max(abs(ptrCurLeft[j] - lastPixel), 1)), 151 | params_.P1); 152 | 153 | auto curCost = ptrCurCost[cost.channels() * j + d] + 154 | min(min(lastCurDispCost, lastPreDispCost), 155 | min(lastAftDispCost, lastElseDispCost)) - 156 | lastMin; 157 | 158 | curLocMinCost = min(curLocMinCost, curCost); 159 | ptrAggregationCost[cost.channels() * j + d] = curCost; 160 | } 161 | 162 | for (int d = 0; d < cost.channels(); ++d) { 163 | lastCost[d + 1] = ptrAggregationCost[cost.channels() * j + d]; 164 | } 165 | 166 | lastMin = curLocMinCost; 167 | lastPixel = ptrCurLeft[j]; 168 | } 169 | } 170 | } 171 | 172 | void MultipathAggregationImpl::aggregationPostive45(const cv::Mat &left, 173 | const Mat &cost, 174 | Mat &aggregationCost, 175 | bool topRightToBottomLeft) { 176 | const int beginLocY = topRightToBottomLeft ? 0 : cost.rows - 1; 177 | const int endLocY = topRightToBottomLeft ? cost.rows : 0; 178 | const int directionY = topRightToBottomLeft ? 1 : -1; 179 | const int beginLocX = topRightToBottomLeft ? cost.cols - 1 : 0; 180 | const int endLocX = topRightToBottomLeft ? 0 : cost.cols; 181 | const int directionX = topRightToBottomLeft ? -1 : 1; 182 | 183 | // Not directly using '!=' to avoid OpenMP's inability to statically 184 | // determine the iteration count. 185 | #pragma omp parallel for schedule(dynamic) default(shared) 186 | for (int indexX = 0; indexX < cost.cols; ++indexX) { 187 | int j = beginLocX + indexX * directionX; 188 | vector lastCost(cost.channels() + 2, FLT_MAX); 189 | float lastMin = FLT_MAX; 190 | uchar lastPixel = left.ptr(beginLocY)[j]; 191 | 192 | for (int d = 0; d < cost.channels(); ++d) { 193 | auto curCost = cost.ptr(beginLocY)[cost.channels() * j + d]; 194 | lastCost[d + 1] = curCost; 195 | 196 | if (curCost < lastMin) { 197 | lastMin = curCost; 198 | } 199 | } 200 | 201 | int curLinej = j + directionX; 202 | 203 | if (curLinej < 0) { 204 | curLinej = cost.cols - 1; 205 | } else if (curLinej > cost.cols - 1) { 206 | curLinej = 0; 207 | } 208 | 209 | for (int i = beginLocY + directionY; i != endLocY; i += directionY) { 210 | auto ptrCurCost = cost.ptr(i); 211 | auto ptrCurLeft = left.ptr(i); 212 | auto ptrAggregationCost = aggregationCost.ptr(i); 213 | float curLocMinCost = FLT_MAX; 214 | 215 | for (int d = 0; d < cost.channels(); ++d) { 216 | auto lastCurDispCost = lastCost[d + 1]; 217 | auto lastPreDispCost = lastCost[d] + params_.P1; 218 | auto lastAftDispCost = lastCost[d + 2] + params_.P1; 219 | auto lastElseDispCost = 220 | lastMin + 221 | max(params_.P2 / 222 | (max(abs(ptrCurLeft[curLinej] - lastPixel), 1)), 223 | params_.P1); 224 | 225 | auto curCost = ptrCurCost[cost.channels() * curLinej + d] + 226 | min(min(lastCurDispCost, lastPreDispCost), 227 | min(lastAftDispCost, lastElseDispCost)) - 228 | lastMin; 229 | 230 | curLocMinCost = min(curLocMinCost, curCost); 231 | ptrAggregationCost[cost.channels() * curLinej + d] = curCost; 232 | } 233 | 234 | for (int d = 0; d < cost.channels(); ++d) { 235 | lastCost[d + 1] = 236 | ptrAggregationCost[cost.channels() * curLinej + d]; 237 | } 238 | 239 | lastMin = curLocMinCost; 240 | lastPixel = ptrCurLeft[curLinej]; 241 | curLinej += directionX; 242 | 243 | if (curLinej < 0) { 244 | curLinej = cost.cols - 1; 245 | } else if (curLinej > cost.cols - 1) { 246 | curLinej = 0; 247 | } 248 | } 249 | } 250 | } 251 | 252 | void MultipathAggregationImpl::aggregationNegative45( 253 | const cv::Mat &left, const Mat &cost, Mat &aggregationCost, 254 | bool topLeftToBottomRight) { 255 | const int beginLocY = topLeftToBottomRight ? 0 : cost.rows - 1; 256 | const int endLocY = topLeftToBottomRight ? cost.rows : 0; 257 | const int directionY = topLeftToBottomRight ? 1 : -1; 258 | const int beginLocX = topLeftToBottomRight ? 0 : cost.cols - 1; 259 | const int endLocX = topLeftToBottomRight ? cost.cols : 0; 260 | const int directionX = topLeftToBottomRight ? 1 : -1; 261 | 262 | // Not directly using '!=' to avoid OpenMP's inability to statically 263 | // determine the iteration count. 264 | #pragma omp parallel for schedule(dynamic) default(shared) 265 | for (int indexX = 0; indexX < cost.cols; ++indexX) { 266 | int j = beginLocX + indexX * directionX; 267 | vector lastCost(cost.channels() + 2, FLT_MAX); 268 | float lastMin = FLT_MAX; 269 | uchar lastPixel = left.ptr(beginLocY)[j]; 270 | 271 | for (int d = 0; d < cost.channels(); ++d) { 272 | auto curCost = cost.ptr(beginLocY)[cost.channels() * j + d]; 273 | lastCost[d + 1] = curCost; 274 | 275 | if (curCost < lastMin) { 276 | lastMin = curCost; 277 | } 278 | } 279 | 280 | int curLinej = j + directionX; 281 | 282 | if (curLinej < 0) { 283 | curLinej = cost.cols - 1; 284 | } else if (curLinej > cost.cols - 1) { 285 | curLinej = 0; 286 | } 287 | 288 | for (int i = beginLocY + directionY; i < endLocY; i += directionY) { 289 | auto ptrCurCost = cost.ptr(i); 290 | auto ptrCurLeft = left.ptr(i); 291 | auto ptrAggregationCost = aggregationCost.ptr(i); 292 | float curLocMinCost = FLT_MAX; 293 | 294 | for (int d = 0; d < cost.channels(); ++d) { 295 | auto lastCurDispCost = lastCost[d + 1]; 296 | auto lastPreDispCost = lastCost[d] + params_.P1; 297 | auto lastAftDispCost = lastCost[d + 2] + params_.P1; 298 | auto lastElseDispCost = 299 | lastMin + 300 | max(params_.P2 / 301 | (max(abs(ptrCurLeft[curLinej] - lastPixel), 1)), 302 | params_.P1); 303 | 304 | auto curCost = ptrCurCost[cost.channels() * curLinej + d] + 305 | min(min(lastCurDispCost, lastPreDispCost), 306 | min(lastAftDispCost, lastElseDispCost)) - 307 | lastMin; 308 | 309 | curLocMinCost = min(curLocMinCost, curCost); 310 | ptrAggregationCost[cost.channels() * curLinej + d] = curCost; 311 | } 312 | 313 | for (int d = 0; d < cost.channels(); ++d) { 314 | lastCost[d + 1] = 315 | ptrAggregationCost[cost.channels() * curLinej + d]; 316 | } 317 | 318 | lastPixel = ptrCurLeft[curLinej]; 319 | lastMin = curLocMinCost; 320 | curLinej += directionX; 321 | 322 | if (curLinej < 0) { 323 | curLinej = cost.cols - 1; 324 | } else if (curLinej > cost.cols - 1) { 325 | curLinej = 0; 326 | } 327 | } 328 | } 329 | } 330 | 331 | void MultipathAggregationImpl::aggregation(const cv::Mat &left, 332 | const cv::Mat &cost, 333 | cv::Mat &aggregationCost) { 334 | CV_Assert(!cost.empty()); 335 | 336 | if(!params_.enableHonrizon && !params_.enableVertiacl && !params_.enableNegtive45 && !params_.enablePostive45) { 337 | aggregationCost = cost; 338 | return; 339 | } 340 | else { 341 | aggregationCost = Mat(cost.size(), cost.type(), Scalar(0.f)); 342 | } 343 | 344 | if (params_.enableHonrizon) { 345 | Mat temp = Mat(cost.size(), cost.type(), Scalar(0.f)); 346 | aggregationHorizontal(left, cost, temp, true); 347 | aggregationCost += temp; 348 | aggregationHorizontal(left, cost, temp, false); 349 | aggregationCost += temp; 350 | } 351 | 352 | if (params_.enableVertiacl) { 353 | Mat temp = Mat(cost.size(), cost.type(), Scalar(0.f)); 354 | aggregationVertical(left, cost, temp, true); 355 | aggregationCost += temp; 356 | aggregationVertical(left, cost, temp, false); 357 | aggregationCost += temp; 358 | } 359 | 360 | if (params_.enablePostive45) { 361 | Mat temp = Mat(cost.size(), cost.type(), Scalar(0.f)); 362 | aggregationPostive45(left, cost, temp, true); 363 | aggregationCost += temp; 364 | aggregationPostive45(left, cost, temp, false); 365 | aggregationCost += temp; 366 | } 367 | 368 | if (params_.enableNegtive45) { 369 | Mat temp = Mat(cost.size(), cost.type(), Scalar(0.f)); 370 | aggregationNegative45(left, cost, temp, true); 371 | aggregationCost += temp; 372 | aggregationNegative45(left, cost, temp, false); 373 | aggregationCost += temp; 374 | } 375 | } 376 | 377 | Ptr MultipathAggregation::create(const Params params) { 378 | return Ptr(new MultipathAggregationImpl(params)); 379 | } 380 | 381 | } // namespace libSM -------------------------------------------------------------------------------- /src/costAggregation/multipathAggregation.h: -------------------------------------------------------------------------------- 1 | /** 2 | * @file multipathAggregation.h 3 | * @author Liu Yunhuang (1369215984@qq.com) 4 | * @brief 5 | * @version 0.1 6 | * @date 2024-03-07 7 | * 8 | * @copyright Copyright (c) 2024 9 | * 10 | */ 11 | 12 | #ifndef __MULTI_PATH_AGGREGATION_H_ 13 | #define __MULTI_PATH_AGGREGATION_H_ 14 | 15 | #include "costAggregation.h" 16 | 17 | namespace libSM { 18 | /** 19 | * @brief multi-path cost aggregator(which is used in SGM) 20 | * 21 | */ 22 | class LIBSM_API MultipathAggregation : public CostAggregation { 23 | public: 24 | /** 25 | * @brief cost aggregation parameters 26 | * 27 | */ 28 | struct Params { 29 | Params() : enableHonrizon(true), enableVertiacl(true), enableNegtive45(true), enablePostive45(true), P1(10.f), P2(150.f) {} 30 | bool enableHonrizon; // enable aggregation on horizontal line 31 | bool enableVertiacl; // enable aggregation on vertical line 32 | bool enablePostive45; // enable aggregation on postive 45 line 33 | bool enableNegtive45; // enable aggregation on negtive 45 line 34 | float P1; // penalty coefficient for disparity continuity 35 | float P2; // penalty coefficient for disparity no continuity 36 | }; 37 | virtual ~MultipathAggregation() {} 38 | /** 39 | * @brief create MultiPathAggregation 40 | * 41 | * @param params cost aggregation parameters 42 | * @return Ptr CostAggregation's Ptr 43 | */ 44 | static Ptr create(IN const Params params); 45 | /** 46 | * @brief aggregation cost 47 | * 48 | * @param left left image 49 | * @param cost cost space 50 | * @param aggregationCost aggregated cost 51 | */ 52 | virtual void aggregation(IN const cv::Mat &left, 53 | IN const cv::Mat &cost, 54 | OUT cv::Mat &aggregationCost) override = 0; 55 | }; 56 | } // namespace libSM 57 | 58 | #endif //!__MULTI_PATH_AGGREGATION_H_ -------------------------------------------------------------------------------- /src/costCompute/adCensusCost.cpp: -------------------------------------------------------------------------------- 1 | #include "adCensusCost.h" 2 | #include "adCost.h" 3 | #include "censusCost.h" 4 | 5 | #include 6 | 7 | #include 8 | 9 | using namespace cv; 10 | 11 | namespace libSM { 12 | /** 13 | * @brief implementation class for the ADCensus Cost interface. 14 | * 15 | */ 16 | class ADCensusCostImpl : public ADCensusCost { 17 | public: 18 | ADCensusCostImpl(const Params params) : params_(params) {} 19 | void compute(const Mat &left, const Mat &right, Mat &out) override; 20 | 21 | private: 22 | Params params_; 23 | }; 24 | 25 | void ADCensusCostImpl::compute(const Mat &left, const Mat &right, Mat &out) { 26 | CV_Assert_N(!left.empty(), !right.empty(), left.size == right.size); 27 | 28 | Mat adCost, censusCost; 29 | 30 | { 31 | ADCost::Params adParams; 32 | adParams.minDisp = params_.minDisp; 33 | adParams.maxDisp = params_.maxDisp; 34 | adParams.minDisp = params_.minDisp; 35 | adParams.maxDisp = params_.maxDisp; 36 | auto adCostComputor = ADCost::create(adParams); 37 | adCostComputor->compute(left, right, adCost); 38 | } 39 | 40 | { 41 | CensusCost::Params censusParams; 42 | censusParams.minDisp = params_.minDisp; 43 | censusParams.maxDisp = params_.maxDisp; 44 | censusParams.minDisp = params_.minDisp; 45 | censusParams.maxDisp = params_.maxDisp; 46 | auto censusCostComputor = CensusCost::create(censusParams); 47 | censusCostComputor->compute(left, right, censusCost); 48 | } 49 | 50 | const int halfWidth = params_.windowWidth / 2; 51 | const int halfHeight = params_.windowHeight / 2; 52 | const int dispRange = params_.maxDisp - params_.minDisp; 53 | 54 | if (out.empty()) 55 | out = Mat(left.size(), CV_32FC(dispRange)); 56 | 57 | #pragma omp parallel for default(shared) schedule(static) 58 | for (int i = 0; i < out.rows; ++i) { 59 | for (int j = 0; j < out.cols; ++j) { 60 | 61 | if (j < halfWidth || j > out.cols - halfWidth - 1 || 62 | i < halfHeight || i > out.rows - halfHeight - 1) { 63 | for (int d = 0; d < dispRange; ++d) { 64 | out.ptr(i)[dispRange * j + d] = FLT_MAX; 65 | } 66 | continue; 67 | } 68 | 69 | for (int d = 0; d < dispRange; ++d) { 70 | out.ptr(i)[dispRange * j + d] = 71 | 1 - 72 | exp(-adCost.ptr(i)[dispRange * j + d] / 73 | params_.adWeight) + 74 | 1 - 75 | exp(-censusCost.ptr(i)[dispRange * j + d] / 76 | params_.censusWeight); 77 | } 78 | } 79 | } 80 | } 81 | 82 | Ptr ADCensusCost::create(const Params params) { 83 | return Ptr(new ADCensusCostImpl(params)); 84 | } 85 | } // namespace libSM -------------------------------------------------------------------------------- /src/costCompute/adCensusCost.h: -------------------------------------------------------------------------------- 1 | /** 2 | * @file adCensusCost.h 3 | * @author Liu Yunhuang (1369215984@qq.com) 4 | * @brief 5 | * @version 0.1 6 | * @date 2024-03-06 7 | * 8 | * @copyright Copyright (c) 2024 9 | * 10 | */ 11 | 12 | #ifndef __AD_CENSUS_COST_H_ 13 | #define __AD_CENSUS_COST_H_ 14 | 15 | #include 16 | 17 | #include "costCompute.h" 18 | 19 | namespace libSM { 20 | /** 21 | * @brief ADCensus Cost Calculator 22 | * 23 | */ 24 | class LIBSM_API ADCensusCost : public CostComputer { 25 | public: 26 | /** 27 | * @brief parameters in the ADCensus cost calculator. 28 | * 29 | */ 30 | struct Params { 31 | Params() 32 | : windowWidth(9), windowHeight(7), minDisp(0), maxDisp(128), 33 | adWeight(10), censusWeight(30) {} 34 | int windowWidth; // the width of the cost calculation window 35 | int windowHeight; // the height of the cost calculation window 36 | int minDisp; // minimum disparity value 37 | int maxDisp; // maximum disparity value. 38 | float adWeight; // weight of ad 39 | float censusWeight; // weight of census 40 | }; 41 | virtual ~ADCensusCost() {} 42 | /** 43 | * @brief create a cost calculator 44 | * 45 | * @param params parameters 46 | * @return Ptr cost calculator 47 | */ 48 | static Ptr 49 | create(IN const Params params); // create a cost calculator 50 | /** 51 | * @brief cost calculation 52 | * 53 | * @param left rectified left image 54 | * @param right rectified right image 55 | * @param out cost three-dimensional space 56 | */ 57 | virtual void compute(IN const cv::Mat &left, IN const cv::Mat &right, 58 | OUT cv::Mat &out) override = 0; 59 | }; 60 | } // namespace libSM 61 | 62 | #endif //! __AD_CENSUS_COST_H_ -------------------------------------------------------------------------------- /src/costCompute/adCost.cpp: -------------------------------------------------------------------------------- 1 | #include "adCost.h" 2 | 3 | #include 4 | 5 | #include 6 | 7 | using namespace cv; 8 | 9 | namespace libSM { 10 | /** 11 | * @brief implementation class for the ADCost interface. 12 | * 13 | */ 14 | class ADCostImpl : public ADCost { 15 | public: 16 | ADCostImpl(const Params params) : params_(params) {} 17 | void compute(const Mat &left, const Mat &right, Mat &out) override; 18 | 19 | private: 20 | /** 21 | * @brief clculate the AD cost within the window 22 | * 23 | * @param leftROI Left image ROI 24 | * @param right right image 25 | * @param rx right image x-coordinate 26 | * @param ry right image y-coordinate 27 | * @return float ad cost of the window 28 | */ 29 | float getWindowPixelsCost(const Mat &leftROI, const Mat &right, 30 | const int rx, const int ry); 31 | Params params_; 32 | }; 33 | 34 | float ADCostImpl::getWindowPixelsCost(const Mat &leftROI, const Mat &right, 35 | const int rx, const int ry) { 36 | const int halfWidth = params_.windowWidth / 2; 37 | const int halfHeight = params_.windowHeight / 2; 38 | 39 | float cost = 0.f; 40 | 41 | for (int i = -halfHeight; i <= halfHeight; ++i) { 42 | for (int j = -halfWidth; j <= halfWidth; ++j) { 43 | if (leftROI.type() == CV_8UC3) { 44 | auto leftPixel = 45 | leftROI.ptr(halfHeight + i)[halfWidth + j]; 46 | auto rightPixel = right.ptr(ry + i)[rx + j]; 47 | cost += 48 | (abs(static_cast(leftPixel[0]) - rightPixel[0]) + 49 | abs(static_cast(leftPixel[1]) - rightPixel[1]) + 50 | abs(static_cast(leftPixel[2]) - rightPixel[2])) / 51 | 3.f; 52 | } else { 53 | cost += abs(static_cast(leftROI.ptr( 54 | halfHeight + i)[halfWidth + j]) - 55 | right.ptr(ry + i)[rx + j]); 56 | } 57 | } 58 | } 59 | 60 | return cost; 61 | } 62 | 63 | void ADCostImpl::compute(const Mat &left, const Mat &right, Mat &out) { 64 | CV_Assert_N(!left.empty(), !right.empty(), left.size == right.size); 65 | 66 | const int dispRange = params_.maxDisp - params_.minDisp; 67 | 68 | if (out.empty()) 69 | out = Mat(left.size(), CV_32FC(dispRange), Scalar(0.f)); 70 | 71 | const int halfWidth = params_.windowWidth / 2; 72 | const int halfHeight = params_.windowHeight / 2; 73 | 74 | #pragma omp parallel for default(shared) schedule(static) 75 | for (int i = 0; i < out.rows; ++i) { 76 | for (int j = 0; j < out.cols; ++j) { 77 | 78 | if (j < halfWidth || j > out.cols - halfWidth - 1 || 79 | i < halfHeight || i > out.rows - halfHeight - 1) { 80 | for (int d = 0; d < dispRange; ++d) { 81 | out.ptr(i)[dispRange * j + d] = FLT_MAX; 82 | } 83 | continue; 84 | } 85 | 86 | auto leftROI = 87 | left(Rect(j - halfWidth, i - halfHeight, params_.windowWidth, 88 | params_.windowHeight)); 89 | 90 | for (int d = 0; d < dispRange; ++d) { 91 | if (j - d < halfWidth || j - d > out.cols - halfWidth) { 92 | out.ptr(i)[dispRange * j + d] = FLT_MAX; 93 | continue; 94 | } 95 | 96 | out.ptr(i)[dispRange * j + d] = 97 | getWindowPixelsCost(leftROI, right, j - d, i); 98 | } 99 | } 100 | } 101 | } 102 | 103 | Ptr ADCost::create(const Params params) { 104 | return Ptr(new ADCostImpl(params)); 105 | } 106 | } // namespace libSM -------------------------------------------------------------------------------- /src/costCompute/adCost.h: -------------------------------------------------------------------------------- 1 | /** 2 | * @file adCost.h 3 | * @author Liu Yunhuang (1369215984@qq.com) 4 | * @brief 5 | * @version 0.1 6 | * @date 2024-03-06 7 | * 8 | * @copyright Copyright (c) 2024 9 | * 10 | */ 11 | 12 | #ifndef __AD_COST_H_ 13 | #define __AD_COST_H_ 14 | 15 | #include 16 | 17 | #include "costCompute.h" 18 | 19 | namespace libSM { 20 | /** 21 | * @brief AD Cost Calculator 22 | * 23 | */ 24 | class LIBSM_API ADCost : public CostComputer { 25 | public: 26 | /** 27 | * @brief parameters in the AD cost calculator. 28 | * 29 | */ 30 | struct Params { 31 | Params() : windowWidth(9), windowHeight(7), minDisp(0), maxDisp(128) {} 32 | int windowWidth; // the width of the cost calculation window 33 | int windowHeight; // the height of the cost calculation window 34 | int minDisp; // minimum disparity value 35 | int maxDisp; // maximum disparity value 36 | }; 37 | virtual ~ADCost() {} 38 | /** 39 | * @brief create a cost calculator 40 | * 41 | * @param params parameters 42 | * @return Ptr cost calculator 43 | */ 44 | static Ptr 45 | create(IN const Params params); // create a cost calculator 46 | /** 47 | * @brief cost calculation 48 | * 49 | * @param left rectified left image 50 | * @param right rectified right image 51 | * @param out cost three-dimensional space 52 | */ 53 | virtual void compute(IN const cv::Mat &left, IN const cv::Mat &right, 54 | OUT cv::Mat &out) override = 0; 55 | }; 56 | } // namespace libSM 57 | 58 | #endif //! AD_COST_H_ -------------------------------------------------------------------------------- /src/costCompute/censusCost.cpp: -------------------------------------------------------------------------------- 1 | #include "censusCost.h" 2 | 3 | #include 4 | 5 | #include 6 | 7 | using namespace cv; 8 | 9 | namespace libSM { 10 | /** 11 | * @brief implementation class for the CensusCost interface. 12 | * 13 | */ 14 | class CensusCostImpl : public CensusCost { 15 | public: 16 | CensusCostImpl(const Params params) : params_(params) {} 17 | void compute(const Mat &left, const Mat &right, Mat &out) override; 18 | 19 | private: 20 | /** 21 | * @brief clculate the AD cost within the window 22 | * 23 | * @param img image 24 | * @param x image x-coordinate 25 | * @param y image y-coordinate 26 | * @return uint64_t census of the window 27 | */ 28 | uint64_t getWindowPixelsCensus(const Mat &img, const int x, const int y); 29 | /** 30 | * @brief calculate hamming distance 31 | * 32 | * @param lhs left census 33 | * @param rhs right census 34 | * @return uint64_t 35 | */ 36 | uint8_t hammingDistance(uint64_t lhs, uint64_t rhs); 37 | Params params_; 38 | }; 39 | 40 | uint64_t CensusCostImpl::getWindowPixelsCensus(const Mat &img, const int x, 41 | const int y) { 42 | const int halfWidth = params_.windowWidth / 2; 43 | const int halfHeight = params_.windowHeight / 2; 44 | 45 | const uchar centerGray = img.ptr(y)[x]; 46 | uint64_t census = 0; 47 | 48 | for (int i = -halfHeight; i <= halfHeight; ++i) { 49 | for (int j = -halfWidth; j <= halfWidth; ++j) { 50 | census += (img.ptr(y + i)[x + j] > centerGray); 51 | if (i != halfHeight || j != halfWidth) { 52 | census <<= 1; 53 | } 54 | } 55 | } 56 | 57 | return census; 58 | } 59 | 60 | uint8_t CensusCostImpl::hammingDistance(uint64_t lhs, uint64_t rhs) { 61 | uint8_t distance = 0; 62 | const int itemCount = params_.windowHeight * params_.windowWidth; 63 | int iterationCount = 0; 64 | 65 | while (iterationCount++ < itemCount) { 66 | distance += (lhs & 0x01) ^ (rhs & 0x01); 67 | lhs >>= 1; 68 | rhs >>= 1; 69 | } 70 | 71 | return distance; 72 | } 73 | 74 | void CensusCostImpl::compute(const Mat &left, const Mat &right, Mat &out) { 75 | CV_Assert_N(!left.empty(), !right.empty(), left.size == right.size, 76 | left.type() == CV_8UC1, right.type() == CV_8UC1); 77 | 78 | const int dispRange = params_.maxDisp - params_.minDisp; 79 | 80 | if (out.empty()) 81 | out = Mat(left.size(), CV_32FC(dispRange), Scalar(0.f)); 82 | 83 | Mat leftCensus = Mat(left.size(), CV_8UC(8), Scalar(0)); 84 | Mat rightCensus = Mat(right.size(), CV_8UC(8), Scalar(0)); 85 | 86 | const int halfWidth = params_.windowWidth / 2; 87 | const int halfHeight = params_.windowHeight / 2; 88 | 89 | #pragma omp parallel for default(shared) schedule(static) 90 | for (int i = halfHeight; i < out.rows - halfHeight; ++i) { 91 | auto ptrLeftCensus = leftCensus.ptr(i); 92 | auto ptrRightCensus = rightCensus.ptr(i); 93 | for (int j = halfWidth; j < out.cols - halfWidth; ++j) { 94 | ptrLeftCensus[j] = getWindowPixelsCensus(left, j, i); 95 | ptrRightCensus[j] = getWindowPixelsCensus(right, j, i); 96 | } 97 | } 98 | 99 | #pragma omp parallel for default(shared) schedule(static) 100 | for (int i = 0; i < out.rows; ++i) { 101 | auto ptrLeftCensus = leftCensus.ptr(i); 102 | auto ptrRightCensus = rightCensus.ptr(i); 103 | 104 | for (int j = 0; j < out.cols; ++j) { 105 | 106 | if (j < halfWidth || j > out.cols - halfWidth - 1 || 107 | i < halfHeight || i > out.rows - halfHeight - 1) { 108 | for (int d = 0; d < dispRange; ++d) { 109 | out.ptr(i)[dispRange * j + d] = FLT_MAX; 110 | } 111 | continue; 112 | } 113 | 114 | auto leftCensusVal = ptrLeftCensus[j]; 115 | 116 | for (int d = 0; d < dispRange; ++d) { 117 | 118 | if (j - d < halfWidth || j - d > out.cols - halfWidth) { 119 | out.ptr(i)[dispRange * j + d] = FLT_MAX; 120 | continue; 121 | } 122 | 123 | out.ptr(i)[dispRange * j + d] = 124 | hammingDistance(leftCensusVal, ptrRightCensus[j - d]); 125 | } 126 | } 127 | } 128 | } 129 | 130 | Ptr CensusCost::create(const Params params) { 131 | return Ptr(new CensusCostImpl(params)); 132 | } 133 | } // namespace libSM -------------------------------------------------------------------------------- /src/costCompute/censusCost.h: -------------------------------------------------------------------------------- 1 | /** 2 | * @file censusCost.h 3 | * @author Liu Yunhuang (1369215984@qq.com) 4 | * @brief 5 | * @version 0.1 6 | * @date 2024-03-06 7 | * 8 | * @copyright Copyright (c) 2024 9 | * 10 | */ 11 | 12 | #ifndef __CENSUS_COST_H_ 13 | #define __CENSUS_COST_H_ 14 | 15 | #include 16 | 17 | #include "costCompute.h" 18 | 19 | namespace libSM { 20 | /** 21 | * @brief Census Cost Calculator 22 | * 23 | */ 24 | class LIBSM_API CensusCost : public CostComputer { 25 | public: 26 | /** 27 | * @brief parameters in the Census cost calculator. 28 | * 29 | */ 30 | struct Params { 31 | Params() : windowWidth(9), windowHeight(7), minDisp(0), maxDisp(128) {} 32 | int windowWidth; // the width of the cost calculation window 33 | int windowHeight; // the height of the cost calculation window 34 | int minDisp; // minimum disparity value 35 | int maxDisp; // maximum disparity value. 36 | }; 37 | virtual ~CensusCost() {} 38 | /** 39 | * @brief create a cost calculator 40 | * 41 | * @param params parameters 42 | * @return Ptr cost calculator 43 | */ 44 | static Ptr 45 | create(IN const Params params); // create a cost calculator 46 | /** 47 | * @brief cost calculation 48 | * 49 | * @param left rectified left image 50 | * @param right rectified right image 51 | * @param out cost three-dimensional space 52 | */ 53 | virtual void compute(IN const cv::Mat &left, IN const cv::Mat &right, 54 | OUT cv::Mat &out) override = 0; 55 | }; 56 | } // namespace libSM 57 | 58 | #endif //! __CENSUS_COST_H_ -------------------------------------------------------------------------------- /src/costCompute/costCompute.h: -------------------------------------------------------------------------------- 1 | /** 2 | * @file costCompute.h 3 | * @author Liu Yunhuang (1369215984@qq.com) 4 | * @brief 5 | * @version 0.1 6 | * @date 2024-03-06 7 | * 8 | * @copyright Copyright (c) 2024 9 | * 10 | */ 11 | 12 | #ifndef __COST_COMPUTE_H_ 13 | #define __COST_COMPUTE_H_ 14 | 15 | #include 16 | 17 | namespace cv { 18 | class Mat; 19 | } 20 | 21 | namespace libSM { 22 | /** 23 | * @brief abstract base class for cost calculation 24 | * 25 | */ 26 | class LIBSM_API CostComputer { 27 | public: 28 | virtual ~CostComputer() {} 29 | /** 30 | * @brief cost calculation 31 | * 32 | * @param left rectified left image 33 | * @param right rectified right image 34 | * @param out cost three-dimensional space 35 | */ 36 | virtual void compute(IN const cv::Mat &left, IN const cv::Mat &right, 37 | OUT cv::Mat &out) = 0; 38 | }; 39 | } // namespace libSM 40 | 41 | #endif //!__COST_COMPUTE_H_ -------------------------------------------------------------------------------- /src/dispCompute/dispCompute.cpp: -------------------------------------------------------------------------------- 1 | #include "dispCompute.h" 2 | 3 | #include 4 | 5 | using namespace cv; 6 | using namespace std; 7 | 8 | namespace libSM { 9 | /** 10 | * @brief check if the difference in value is too small 11 | * 12 | * @param majorMinCost minimum cost 13 | * @param minorMinCost sub minimum cost 14 | * @param uniquenessRatio uniqueness ratio 15 | * @return true pass 16 | * @return false not passed 17 | */ 18 | bool uniqueCheck(const float majorMinCost, const float minorMinCost, 19 | const float uniquenessRatio = 0.8f) { 20 | return (minorMinCost - majorMinCost) > 21 | majorMinCost * (1.f - uniquenessRatio); 22 | } 23 | 24 | /** 25 | * @brief left and right consistency test 26 | * 27 | * @param ptrCostMap the cost of the current line 28 | * @param leftBestDisp left image best parallax 29 | * @param lx left image x-coordinate 30 | * @param rx matched right image x-coordinate 31 | * @param dispRange parallax interval 32 | * @param cols number of image columns 33 | * @param lrCheckThreshod left and right consistency threshold 34 | * @return pair first: pass or no pass, second: is occlusions or 35 | * mismatches 36 | */ 37 | pair lrCheck(const float *ptrCostMap, const int lx, const int rx, 38 | const int minDisp, const int maxDisp, const int cols, 39 | const int lrCheckThreshod = 1) { 40 | int rightBestDisp = lx - rx; 41 | float minCost = FLT_MAX; 42 | const int dispRange = maxDisp - minDisp; 43 | 44 | for (int d = -dispRange + 1; d <= 0; ++d) { 45 | auto curLx = rx - d + minDisp; 46 | if (curLx < 0 || curLx > cols - 1) { 47 | continue; 48 | } 49 | 50 | auto curCost = ptrCostMap[dispRange * curLx - d]; 51 | if (curCost < minCost) { 52 | minCost = curCost; 53 | rightBestDisp = d; 54 | } 55 | } 56 | 57 | return make_pair(abs(rx - rightBestDisp + minDisp - lx) <= lrCheckThreshod, 58 | (lx - rx) < abs(rightBestDisp)); 59 | } 60 | 61 | /** 62 | * @brief sub-pixel fitting 63 | * 64 | * @param ptrCostMap the cost of the current line 65 | * @param lx left image x-coordinate 66 | * @param disp parallax of current left image pixels 67 | * @param minCost the minimum cost of pixels in the current left image 68 | * @param dispRange parallax interval 69 | * @return float sub-pixel parallax 70 | */ 71 | float subpixelFitting(const float *ptrCostMap, const int lx, const int disp, 72 | const float minCost, const int dispRange) { 73 | auto preCost = ptrCostMap[dispRange * lx + disp - 1]; 74 | auto aftCost = ptrCostMap[dispRange * lx + disp + 1]; 75 | auto denom = max(0.001f, preCost + aftCost - 2 * minCost); 76 | return disp + (preCost - aftCost) / (denom * 2.f); 77 | } 78 | 79 | void winnerTakesAll(const Mat &costMap, Mat &dispMap, 80 | const DispComputeParams params) { 81 | CV_Assert_N(!costMap.empty()); 82 | 83 | if (dispMap.empty()) 84 | dispMap = Mat(costMap.size(), CV_32FC1, cv::Scalar(0.f)); 85 | 86 | #pragma omp parallel for schedule(dynamic) default(shared) 87 | for (int i = 0; i < costMap.rows; ++i) { 88 | 89 | auto ptrCostMap = costMap.ptr(i); 90 | auto ptrDispMap = dispMap.ptr(i); 91 | 92 | for (int j = 0; j < costMap.cols; ++j) { 93 | 94 | float majorMinCost = FLT_MAX, minorMinCost = FLT_MAX; 95 | int majorDisp = 0; 96 | 97 | for (int d = 0; d < costMap.channels(); ++d) { 98 | auto curCost = ptrCostMap[costMap.channels() * j + d]; 99 | if (curCost < majorMinCost) { 100 | minorMinCost = majorMinCost; 101 | majorMinCost = curCost; 102 | majorDisp = d; 103 | } 104 | } 105 | 106 | if (params.enableUniqueCheck && 107 | !uniqueCheck(majorMinCost, minorMinCost, 108 | params.uniquenessRatio)) { 109 | ptrDispMap[j] = NONE_PIXEL; 110 | continue; 111 | } 112 | 113 | if (params.enableLRCheck) { 114 | auto lrCheckResult = 115 | lrCheck(ptrCostMap, j, j - (majorDisp + params.minDisp), 116 | params.minDisp, params.maxDisp, costMap.cols, 117 | params.lrCheckThreshod); 118 | 119 | if (!lrCheckResult.first) { 120 | ptrDispMap[j] = lrCheckResult.second ? OCCLUDED_PIXEL 121 | : MISMATCHED_PIXEL; 122 | continue; 123 | } 124 | } 125 | 126 | if (params.enableSubpixelFitting && 127 | (majorDisp != 0 && majorDisp != costMap.channels() - 1)) { 128 | ptrDispMap[j] = 129 | subpixelFitting(ptrCostMap, j, majorDisp, majorMinCost, 130 | costMap.channels()) + 131 | params.minDisp; 132 | } else { 133 | ptrDispMap[j] = majorDisp + params.minDisp; 134 | } 135 | } 136 | } 137 | } 138 | } // namespace libSM -------------------------------------------------------------------------------- /src/dispCompute/dispCompute.h: -------------------------------------------------------------------------------- 1 | /** 2 | * @file dispCompute.h 3 | * @author Liu Yunhuang (1369215984@qq.com) 4 | * @brief 5 | * @version 0.1 6 | * @date 2024-03-06 7 | * 8 | * @copyright Copyright (c) 2024 9 | * 10 | */ 11 | 12 | #ifndef __DISP_COMPUTE_H_ 13 | #define __DISP_COMPUTE_H_ 14 | 15 | #include 16 | 17 | namespace cv { 18 | class Mat; 19 | } 20 | 21 | namespace libSM { 22 | /** 23 | * @brief disparity computation control parameters 24 | * 25 | */ 26 | struct DispComputeParams { 27 | DispComputeParams() 28 | : enableLRCheck(true), enableUniqueCheck(true), enableSubpixelFitting(true), minDisp(0), 29 | maxDisp(64), uniquenessRatio(0.95f), lrCheckThreshod(1) {} 30 | bool enableLRCheck; // left-right consistency check 31 | bool enableUniqueCheck; // consistency check 32 | bool enableSubpixelFitting; // subpixel fitting 33 | float uniquenessRatio; // uniqueness ratio 34 | int lrCheckThreshod; // left and right consistency threshold 35 | int minDisp; // minimum disparity value 36 | int maxDisp; // maximum disparity value 37 | }; 38 | 39 | /** 40 | * @brief winner-takes-all algorithm 41 | * 42 | * @param costMap //cost space 43 | * @param dispMap //disparity map 44 | * @param params //disparity computation control parameters 45 | */ 46 | void LIBSM_API winnerTakesAll(IN const cv::Mat &costMap, OUT cv::Mat &dispMap, 47 | IN const DispComputeParams params); 48 | } // namespace libSM 49 | 50 | #endif //!__DISP_COMPUTE_H_ -------------------------------------------------------------------------------- /src/dispOptimiztion/dispOptimiztion.cpp: -------------------------------------------------------------------------------- 1 | #include "dispOptimiztion.h" 2 | 3 | #include 4 | 5 | #include 6 | 7 | using namespace cv; 8 | using namespace std; 9 | 10 | namespace libSM { 11 | 12 | /** 13 | * @brief remove small connected domains 14 | * 15 | * @param dispMap //disparity map 16 | * @param out //out disparity map 17 | * @param dispDomainThreshold //parallax map connectivity threshold 18 | * @param smallAreaThreshold //threshold for the number of pixels in a small 19 | * connected domain 20 | */ 21 | void removeSmallArea(const Mat &dispMap, Mat &out, 22 | const float dispDomainThreshold, 23 | const int smallAreaThreshold) { 24 | CV_Assert(!dispMap.empty()); 25 | 26 | if (out.empty()) 27 | out = dispMap.clone(); 28 | 29 | vector visited(dispMap.rows * dispMap.cols, false); 30 | 31 | for (int i = 0; i < dispMap.rows; ++i) { 32 | auto ptrDispMap = dispMap.ptr(i); 33 | 34 | for (int j = 0; j < dispMap.cols; ++j) { 35 | if (visited[dispMap.cols * i + j] || abs(ptrDispMap[j]) < 0.001f) { 36 | continue; 37 | } 38 | 39 | vector> area; 40 | int areaSize = area.size(); 41 | area.emplace_back(make_pair(j, i)); 42 | visited[dispMap.cols * i + j] = true; 43 | 44 | do { 45 | int preSize = areaSize; 46 | areaSize = area.size(); 47 | 48 | for (int k = preSize; k < areaSize; ++k) { 49 | auto curPixelX = area[k].first; 50 | auto curPixelY = area[k].second; 51 | auto curPixelDisp = 52 | dispMap.ptr(curPixelY)[curPixelX]; 53 | 54 | for (int y = -1; y <= 1; ++y) { 55 | for (int x = -1; x <= 1; ++x) { 56 | auto visitPixelX = curPixelX + x; 57 | auto visitPixelY = curPixelY + y; 58 | 59 | if (visitPixelX < 0 || 60 | visitPixelX > dispMap.cols - 1 || 61 | visitPixelY < 0 || 62 | visitPixelY > dispMap.rows - 1) { 63 | continue; 64 | } 65 | 66 | if (visited[dispMap.cols * visitPixelY + 67 | visitPixelX] || 68 | abs(dispMap.ptr( 69 | visitPixelY)[visitPixelX]) < 0.001f) { 70 | continue; 71 | } 72 | 73 | if (abs(dispMap.ptr( 74 | visitPixelY)[visitPixelX] - 75 | curPixelDisp) < dispDomainThreshold) { 76 | area.push_back( 77 | make_pair(visitPixelX, visitPixelY)); 78 | visited[dispMap.cols * visitPixelY + 79 | visitPixelX] = true; 80 | } 81 | } 82 | } 83 | } 84 | } while (areaSize < area.size()); 85 | 86 | if (area.size() < smallAreaThreshold) { 87 | for (auto loc : area) { 88 | out.ptr(loc.second)[loc.first] = NONE_PIXEL; 89 | } 90 | } 91 | } 92 | } 93 | } 94 | 95 | /** 96 | * @brief median filter for float-type image 97 | * 98 | * @param dispMap disparity map 99 | * @param out filtered disparity map 100 | * @param k kernel size 101 | */ 102 | void medianFilter(const Mat &dispMap, Mat &out, const int k) { 103 | const int halfSize = k / 2; 104 | const int medianIndex = (k * k) / 2; 105 | 106 | #pragma omp parallel for schedule(dynamic) default(shared) 107 | for (int i = halfSize; i < dispMap.rows - halfSize; ++i) { 108 | auto ptrOut = out.ptr(i); 109 | 110 | for (int j = halfSize; j < dispMap.cols - halfSize; ++j) { 111 | vector disp; 112 | 113 | for (int y = -halfSize; y <= halfSize; ++y) { 114 | for (int x = -halfSize; x <= halfSize; ++x) { 115 | disp.emplace_back(dispMap.ptr(i + y)[j + x]); 116 | } 117 | } 118 | 119 | std::sort(disp.begin(), disp.end()); 120 | ptrOut[j] = disp[medianIndex]; 121 | } 122 | } 123 | } 124 | 125 | /** 126 | * @brief fill disparity map 127 | * 128 | * @param dispMap disparity map 129 | * @param out filled disparity map 130 | */ 131 | void dispFill(const Mat &dispMap, Mat &out) { 132 | const vector> direction = { 133 | make_pair(0, -1), make_pair(1, -1), make_pair(1, 0), 134 | make_pair(1, 1), make_pair(0, 1), make_pair(-1, 1), 135 | make_pair(-1, 0), make_pair(-1, -1)}; 136 | 137 | #pragma omp parallel for schedule(dynamic) default(shared) 138 | for (int i = 0; i < dispMap.rows; ++i) { 139 | auto ptrDispMap = dispMap.ptr(i); 140 | auto ptrOut = out.ptr(i); 141 | 142 | for (int j = 0; j < dispMap.cols; ++j) { 143 | auto state = make_pair(IS_OCCLUDED_PIXEL(ptrDispMap[j]), 144 | IS_MISMATCHED_PIXEL(ptrDispMap[j]) || IS_NONE_PIXEL(ptrDispMap[j])); 145 | if (state.first || state.second) { 146 | vector disp; 147 | 148 | for (int d = 0; d < direction.size(); ++d) { 149 | auto curLocX = j; 150 | auto curLocY = i; 151 | bool isFind = false; 152 | 153 | do { 154 | curLocX += direction[d].first; 155 | curLocY += direction[d].second; 156 | 157 | if (curLocX < 0 || curLocX > dispMap.cols - 1 || 158 | curLocY < 0 || curLocY > dispMap.rows - 1) { 159 | break; 160 | } 161 | 162 | auto curVal = dispMap.ptr(curLocY)[curLocX]; 163 | 164 | if (!IS_OCCLUDED_PIXEL(curVal) && 165 | !IS_MISMATCHED_PIXEL(curVal) && 166 | !IS_NONE_PIXEL(curVal)) { 167 | disp.emplace_back(curVal); 168 | isFind = true; 169 | break; 170 | } 171 | } while (true); 172 | 173 | if (!isFind) { 174 | disp.emplace_back(0); 175 | } 176 | } 177 | 178 | std::sort(disp.begin(), disp.end()); 179 | 180 | ptrOut[j] = state.first ? disp[1] : disp[disp.size() / 2]; 181 | } 182 | } 183 | } 184 | } 185 | 186 | void dispOptimiz(const Mat &dispMap, Mat &out, const DispOptParams params) { 187 | CV_Assert(!dispMap.empty()); 188 | 189 | if (out.empty()) 190 | out = dispMap.clone(); 191 | 192 | if (params.enableRemoveSmallArea) { 193 | removeSmallArea(dispMap, out, params.dispDomainThreshold, 194 | params.smallAreaThreshold); 195 | } 196 | 197 | if (params.enableDispFill) { 198 | Mat temp = out.clone(); 199 | dispFill(temp, out); 200 | } 201 | 202 | if (params.enableMedianFilter) { 203 | Mat temp = out.clone(); 204 | medianFilter(temp, out, params.k); 205 | } else if (params.enableBilateralFilter) { 206 | Mat temp = out.clone(); 207 | bilateralFilter(temp, out, params.d, params.sigmaColor, 208 | params.sigmaSpace); 209 | } 210 | } 211 | 212 | } // namespace libSM -------------------------------------------------------------------------------- /src/dispOptimiztion/dispOptimiztion.h: -------------------------------------------------------------------------------- 1 | /** 2 | * @file dispOptimiztion.h 3 | * @author Liu Yunhuang (1369215984@qq.com) 4 | * @brief 5 | * @version 0.1 6 | * @date 2024-03-07 7 | * 8 | * @copyright Copyright (c) 2024 9 | * 10 | */ 11 | 12 | #ifndef __DISP_OPTIMIZTION_H_ 13 | #define __DISP_OPTIMIZTION_H_ 14 | 15 | #include 16 | 17 | namespace cv { 18 | class Mat; 19 | } 20 | 21 | namespace libSM { 22 | /** 23 | * @brief parallax optimization parameters 24 | * 25 | */ 26 | struct DispOptParams { 27 | DispOptParams() 28 | : enableBilateralFilter(false), enableRemoveSmallArea(true), 29 | enableDispFill(true), enableMedianFilter(true), 30 | smallAreaThreshold(20), dispDomainThreshold(1), k(3), d(10), 31 | sigmaColor(10), sigmaSpace(10) {} 32 | bool enableBilateralFilter; // enable bilateral filter 33 | bool enableRemoveSmallArea; // enable remove small area 34 | bool enableMedianFilter; // enable median filter 35 | bool enableDispFill; // enable fill the background or prospect 36 | int smallAreaThreshold; // small area threshild 37 | int dispDomainThreshold; // parallax connected domain threshold 38 | int k; // median filtering filter kernel size 39 | int d; // bilateral filtering filter field diameter 40 | float sigmaColor; // standard deviation of Gaussian function in color space 41 | float sigmaSpace; // standard deviation of Gaussian function in coordinate 42 | // space 43 | }; 44 | 45 | /** 46 | * @brief optimize disparity map 47 | * 48 | * @param dispMap disparity map 49 | * @param out out disparity map 50 | * @param params parallax optimization parameters 51 | */ 52 | void LIBSM_API dispOptimiz(IN const cv::Mat &dispMap, OUT cv::Mat &out, 53 | IN const DispOptParams params); 54 | } // namespace libSM 55 | 56 | #endif //!__DISP_OPTIMIZTION_H_ -------------------------------------------------------------------------------- /src/sgm.cpp: -------------------------------------------------------------------------------- 1 | #include "sgm.h" 2 | #include "costCompute/censusCost.h" 3 | #include "costAggregation/multipathAggregation.h" 4 | #include "dispCompute/dispCompute.h" 5 | #include "dispOptimiztion/dispOptimiztion.h" 6 | 7 | #include 8 | 9 | using namespace cv; 10 | using namespace std; 11 | 12 | namespace libSM { 13 | /** 14 | * @brief SGM algorithm's implement 15 | * 16 | */ 17 | class SGMImpl : public SGM { 18 | public: 19 | SGMImpl(const Params params) : params_(params) {} 20 | void match(const cv::Mat &left, const cv::Mat &right, 21 | cv::Mat &dispMap) override; 22 | private: 23 | Params params_; 24 | }; 25 | 26 | void SGMImpl::match(const cv::Mat &left, const cv::Mat &right, cv::Mat &dispMap) { 27 | CV_Assert_N(!left.empty(), !right.empty(), left.type() == CV_8UC1 || left.type() == CV_8UC3, right.type() == CV_8UC1 || right.type() == CV_8UC3); 28 | 29 | Mat leftProcess, rightProcess; 30 | 31 | if(left.type() == CV_8UC3) 32 | cvtColor(left, leftProcess, COLOR_BGR2GRAY); 33 | else 34 | leftProcess = left; 35 | 36 | if(right.type() == CV_8UC3) 37 | cvtColor(right, rightProcess, COLOR_BGR2GRAY); 38 | else 39 | rightProcess = right; 40 | 41 | //cost compute 42 | Mat cost; 43 | { 44 | auto params = CensusCost::Params(); 45 | params.windowWidth = params_.windowWidth; 46 | params.windowHeight = params_.windowHeight; 47 | params.minDisp = params_.minDisp; 48 | params.maxDisp = params_.maxDisp; 49 | 50 | auto adCensusComputer = CensusCost::create(params); 51 | adCensusComputer->compute(leftProcess, rightProcess, cost); 52 | } 53 | 54 | //cost aggregation 55 | Mat aggregatedCost; 56 | { 57 | auto params = MultipathAggregation::Params(); 58 | params.P1 = params_.P1; 59 | params.P2 = params_.P2; 60 | params.enableHonrizon = params_.enableHonrizon; 61 | params.enableVertiacl = params.enableVertiacl; 62 | params.enableNegtive45 = params_.enableNegtive45; 63 | params.enablePostive45 = params_.enablePostive45; 64 | 65 | auto multipathAggregator = MultipathAggregation::create(params); 66 | multipathAggregator->aggregation(leftProcess, cost, aggregatedCost); 67 | } 68 | 69 | cost.release(); 70 | 71 | //disparity compute 72 | Mat disp; 73 | { 74 | auto params = DispComputeParams(); 75 | params.enableLRCheck = params_.enableLRCheck; 76 | params.enableUniqueCheck = params_.enableUniqueCheck; 77 | params.enableSubpixelFitting = params_.enableSubpixelFitting; 78 | params.lrCheckThreshod = params_.lrCheckThreshod; 79 | params.uniquenessRatio = params_.uniquenessRatio; 80 | params.minDisp = params_.minDisp; 81 | params.maxDisp = params_.maxDisp; 82 | 83 | winnerTakesAll(aggregatedCost, disp, params); 84 | } 85 | 86 | aggregatedCost.release(); 87 | 88 | //disparity optimiztion 89 | { 90 | auto params = DispOptParams(); 91 | params.enableRemoveSmallArea = params_.enableRemoveSmallArea; 92 | params.dispDomainThreshold = params_.dispDomainThreshold; 93 | params.smallAreaThreshold = params_.smallAreaThreshold; 94 | params.enableBilateralFilter = params_.enableBilateralFilter; 95 | params.d = params_.d; 96 | params.sigmaColor = params_.sigmaColor; 97 | params.sigmaSpace = params_.sigmaSpace; 98 | params.enableMedianFilter = params_.enableMedianFilter; 99 | params.k = params_.k; 100 | params.enableDispFill = params_.enableDispFill; 101 | 102 | dispOptimiz(disp, dispMap, params); 103 | } 104 | } 105 | 106 | Ptr SGM::create(const Params params) { 107 | return Ptr(new SGMImpl(params)); 108 | } 109 | 110 | } // namespace libSM -------------------------------------------------------------------------------- /src/sgm.h: -------------------------------------------------------------------------------- 1 | /** 2 | * @file sgm.h 3 | * @author Liu Yunhuang (1369215984@qq.com) 4 | * @brief 5 | * @version 0.1 6 | * @date 2024-03-08 7 | * 8 | * @copyright Copyright (c) 2024 9 | * 10 | */ 11 | 12 | #ifndef __SGM_H_ 13 | #define __SGM_H_ 14 | 15 | #include "algorithm.h" 16 | 17 | namespace cv { 18 | class Mat; 19 | } 20 | 21 | namespace libSM { 22 | /** 23 | * @brief Semi Global Matching Algorithm 24 | * 25 | * @paper H. Hirschmuller, "Stereo Processing by Semiglobal Matching and Mutual 26 | * Information," in IEEE Transactions on Pattern Analysis and Machine 27 | * Intelligence, vol. 30, no. 2, pp. 328-341, Feb. 2008, 28 | * doi: 10.1109/TPAMI.2007.1166. 29 | * 30 | */ 31 | class LIBSM_API SGM : public Algorithm { 32 | public: 33 | /** 34 | * @brief control parameters 35 | * 36 | */ 37 | struct Params { 38 | Params() 39 | : enableHonrizon(true), enableVertiacl(true), enablePostive45(true), 40 | enableNegtive45(true), enableBilateralFilter(false), 41 | enableRemoveSmallArea(true), enableLRCheck(true), 42 | enableUniqueCheck(true), enableSubpixelFitting(true), 43 | enableMedianFilter(true), enableDispFill(true), windowWidth(9), 44 | windowHeight(7), minDisp(0), maxDisp(64), P1(10), P2(150), 45 | lrCheckThreshod(1), uniquenessRatio(0.95), smallAreaThreshold(20), 46 | dispDomainThreshold(1), k(3), d(10), sigmaColor(10), 47 | sigmaSpace(10) {} 48 | bool enableHonrizon; // enable aggregation on horizontal line 49 | bool enableVertiacl; // enable aggregation on vertical line 50 | bool enablePostive45; // enable aggregation on postive 45 line 51 | bool enableNegtive45; // enable aggregation on negtive 45 line 52 | bool enableBilateralFilter; // enable bilateral filter 53 | bool enableRemoveSmallArea; // enable remove small area 54 | bool enableLRCheck; // left-right consistency check 55 | bool enableUniqueCheck; // consistency check 56 | bool enableSubpixelFitting; // subpixel fitting 57 | bool enableMedianFilter; // enable median filter 58 | bool enableDispFill; // enable fill the background or prospect 59 | int windowWidth; // the width of the cost calculation window 60 | int windowHeight; // the height of the cost calculation window 61 | int minDisp; // minimum disparity value 62 | int maxDisp; // maximum disparity value. 63 | float P1; // penalty coefficient for disparity continuity 64 | float P2; // penalty coefficient for disparity no continuity 65 | int lrCheckThreshod; // left and right consistency threshold 66 | float uniquenessRatio; // uniqueness ratio 67 | int smallAreaThreshold; // small area threshild 68 | int dispDomainThreshold; // parallax connected domain threshold 69 | int k; // median filtering filter kernel size 70 | int d; // bilateral filtering filter field diameter 71 | float sigmaColor; // standard deviation of Gaussian function in color 72 | // space 73 | float sigmaSpace; // standard deviation of Gaussian function in 74 | // coordinate space 75 | }; 76 | virtual ~SGM() {} 77 | /** 78 | * @brief create the SGM algorithm 79 | * 80 | * @param params control params 81 | * @return Ptr SGM algorithm 82 | */ 83 | static Ptr create(const Params params); 84 | /** 85 | * @brief perform stereo matching 86 | * 87 | * @param left left image 88 | * @param right right image 89 | * @param dispMap disparity Map 90 | */ 91 | virtual void match(IN const cv::Mat &left, IN const cv::Mat &right, 92 | OUT cv::Mat &dispMap) override = 0; 93 | }; 94 | } // namespace libSM 95 | 96 | #endif //!__SGM_H_ -------------------------------------------------------------------------------- /test/CMakeLists.txt: -------------------------------------------------------------------------------- 1 | cmake_minimum_required(VERSION 3.20) 2 | 3 | include(FetchContent) 4 | FetchContent_Declare( 5 | googletest 6 | URL ${PROJECT_SOURCE_DIR}/3rdParty/googletest-1.12.0.zip 7 | ) 8 | 9 | project(PrecisionTest) 10 | 11 | set(gtest_force_shared_crt ON CACHE BOOL "" FORCE) 12 | 13 | FetchContent_MakeAvailable(googletest) 14 | enable_testing() 15 | 16 | add_executable( 17 | TestCostCompute 18 | ${CMAKE_CURRENT_SOURCE_DIR}/testCostCompute.cpp 19 | ) 20 | 21 | target_link_libraries( 22 | TestCostCompute 23 | PRIVATE 24 | gtest_main 25 | StereoMatch 26 | ) 27 | 28 | add_executable( 29 | TestDispCompute 30 | ${CMAKE_CURRENT_SOURCE_DIR}/testDispCompute.cpp 31 | ) 32 | 33 | target_link_libraries( 34 | TestDispCompute 35 | PRIVATE 36 | gtest_main 37 | StereoMatch 38 | ) 39 | 40 | add_executable( 41 | TestCostAggregation 42 | ${CMAKE_CURRENT_SOURCE_DIR}/testCostAggregation.cpp 43 | ) 44 | 45 | target_link_libraries( 46 | TestCostAggregation 47 | PRIVATE 48 | gtest_main 49 | StereoMatch 50 | ) 51 | 52 | add_executable( 53 | TestDispOptimiztion 54 | ${CMAKE_CURRENT_SOURCE_DIR}/testDispOptimiztion.cpp 55 | ) 56 | 57 | target_link_libraries( 58 | TestDispOptimiztion 59 | PRIVATE 60 | gtest_main 61 | StereoMatch 62 | ) 63 | 64 | add_executable( 65 | TestSGM 66 | ${CMAKE_CURRENT_SOURCE_DIR}/testSGM.cpp 67 | ) 68 | 69 | target_link_libraries( 70 | TestSGM 71 | PRIVATE 72 | gtest_main 73 | StereoMatch 74 | ) 75 | 76 | 77 | include(GoogleTest) 78 | gtest_discover_tests(TestCostCompute) 79 | gtest_discover_tests(TestDispCompute) 80 | gtest_discover_tests(TestCostAggregation) 81 | gtest_discover_tests(TestDispOptimiztion) 82 | gtest_discover_tests(TestSGM) -------------------------------------------------------------------------------- /test/testCostAggregation.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | 3 | #include 4 | 5 | #include 6 | 7 | using namespace cv; 8 | using namespace std; 9 | using namespace libSM; 10 | 11 | const string CONES_DATA_SET_PATH = "../../data/cones/"; 12 | const string TEDDY_DATA_SET_PATH = "../../data/teddy/"; 13 | 14 | class Cones : public testing::Test { 15 | protected: 16 | void SetUp() override { 17 | left = imread(CONES_DATA_SET_PATH + "im2.png", IMREAD_UNCHANGED); 18 | right = imread(CONES_DATA_SET_PATH + "im6.png", IMREAD_UNCHANGED); 19 | } 20 | 21 | public: 22 | Mat left; 23 | Mat right; 24 | void transformToGray() { 25 | if(left.type() == CV_8UC3) 26 | cvtColor(left, left, COLOR_BGR2GRAY); 27 | 28 | if(right.type() == CV_8UC3) 29 | cvtColor(right, right, COLOR_BGR2GRAY); 30 | } 31 | }; 32 | 33 | class Teddy : public testing::Test { 34 | protected: 35 | void SetUp() override { 36 | left = imread(TEDDY_DATA_SET_PATH + "im2.png", IMREAD_UNCHANGED); 37 | right = imread(TEDDY_DATA_SET_PATH + "im6.png", IMREAD_UNCHANGED); 38 | } 39 | public: 40 | Mat left; 41 | Mat right; 42 | void transformToGray() { 43 | if(left.type() == CV_8UC3) 44 | cvtColor(left, left, COLOR_BGR2GRAY); 45 | 46 | if(right.type() == CV_8UC3) 47 | cvtColor(right, right, COLOR_BGR2GRAY); 48 | } 49 | }; 50 | 51 | TEST_F(Cones, testMultipathAggregation) { 52 | transformToGray(); 53 | 54 | Mat cost; 55 | { 56 | auto params = CensusCost::Params(); 57 | params.windowWidth = 9; 58 | params.windowHeight = 7; 59 | params.minDisp = 0; 60 | params.maxDisp = 64; 61 | 62 | auto adCensusComputer = CensusCost::create(params); 63 | adCensusComputer->compute(left, right, cost); 64 | } 65 | 66 | Mat aggregatedCost; 67 | { 68 | auto params = MultipathAggregation::Params(); 69 | params.P1 = 10.f; 70 | params.P2 = 150.f; 71 | params.enableHonrizon = true; 72 | params.enableNegtive45 = true; 73 | params.enablePostive45 = true; 74 | params.enableVertiacl = true; 75 | 76 | auto multipathAggregator = MultipathAggregation::create(params); 77 | multipathAggregator->aggregation(left, cost, aggregatedCost); 78 | } 79 | 80 | Mat disp; 81 | { 82 | auto params = DispComputeParams(); 83 | params.enableLRCheck = true; 84 | params.enableUniqueCheck = true; 85 | params.enableSubpixelFitting = true; 86 | params.lrCheckThreshod = 1; 87 | params.uniquenessRatio = 0.95f; 88 | params.minDisp = 0; 89 | params.maxDisp = 64; 90 | 91 | winnerTakesAll(aggregatedCost, disp, params); 92 | } 93 | 94 | ASSERT_LE(abs(disp.ptr(301)[308] - 40), 1.f); 95 | } -------------------------------------------------------------------------------- /test/testCostCompute.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | 3 | #include 4 | 5 | #include 6 | 7 | using namespace cv; 8 | using namespace std; 9 | using namespace libSM; 10 | 11 | const string CONES_DATA_SET_PATH = "../../data/cones/"; 12 | const string TEDDY_DATA_SET_PATH = "../../data/teddy/"; 13 | 14 | class Cones : public testing::Test { 15 | protected: 16 | void SetUp() override { 17 | left = imread(CONES_DATA_SET_PATH + "im2.png", IMREAD_UNCHANGED); 18 | right = imread(CONES_DATA_SET_PATH + "im6.png", IMREAD_UNCHANGED); 19 | } 20 | 21 | public: 22 | Mat left; 23 | Mat right; 24 | void transformToGray() { 25 | if(left.type() == CV_8UC3) 26 | cvtColor(left, left, COLOR_BGR2GRAY); 27 | 28 | if(right.type() == CV_8UC3) 29 | cvtColor(right, right, COLOR_BGR2GRAY); 30 | } 31 | }; 32 | 33 | class Teddy : public testing::Test { 34 | protected: 35 | void SetUp() override { 36 | left = imread(TEDDY_DATA_SET_PATH + "im2.png", IMREAD_UNCHANGED); 37 | right = imread(TEDDY_DATA_SET_PATH + "im6.png", IMREAD_UNCHANGED); 38 | } 39 | public: 40 | Mat left; 41 | Mat right; 42 | void transformToGray() { 43 | if(left.type() == CV_8UC3) 44 | cvtColor(left, left, COLOR_BGR2GRAY); 45 | 46 | if(right.type() == CV_8UC3) 47 | cvtColor(right, right, COLOR_BGR2GRAY); 48 | } 49 | }; 50 | 51 | TEST_F(Cones, testADCostColor) { 52 | auto params = ADCost::Params(); 53 | params.windowWidth = 9; 54 | params.windowHeight = 7; 55 | params.minDisp = 0; 56 | params.maxDisp = 4; 57 | auto adCostComputer = ADCost::create(params); 58 | Mat out; 59 | adCostComputer->compute(left, right, out); 60 | 61 | ASSERT_LE(abs(out.ptr(9)[9][0] - 1671.3), 1); 62 | } 63 | 64 | TEST_F(Cones, testADCostGray) { 65 | auto params = ADCost::Params(); 66 | params.windowWidth = 9; 67 | params.windowHeight = 7; 68 | params.minDisp = 0; 69 | params.maxDisp = 4; 70 | auto adCostComputer = ADCost::create(params); 71 | Mat out; 72 | transformToGray(); 73 | adCostComputer->compute(left, right, out); 74 | 75 | ASSERT_LE(abs(out.ptr(17)[17][0] - 860), 1); 76 | } 77 | 78 | TEST_F(Cones, testCensusCost) { 79 | auto params = CensusCost::Params(); 80 | params.windowWidth = 9; 81 | params.windowHeight = 7; 82 | params.minDisp = 0; 83 | params.maxDisp = 4; 84 | auto censusCostComputer = CensusCost::create(params); 85 | Mat out; 86 | transformToGray(); 87 | censusCostComputer->compute(left, right, out); 88 | 89 | ASSERT_EQ(out.ptr(25)[25][0], 24); 90 | ASSERT_EQ(out.ptr(25)[25][1], 24); 91 | } 92 | 93 | TEST_F(Cones, testADCensusCost) { 94 | auto params = ADCensusCost::Params(); 95 | params.windowWidth = 9; 96 | params.windowHeight = 7; 97 | params.minDisp = 0; 98 | params.maxDisp = 4; 99 | params.adWeight = 10.f; 100 | params.censusWeight = 30.f; 101 | auto adCensusComputer = ADCensusCost::create(params); 102 | Mat out; 103 | transformToGray(); 104 | adCensusComputer->compute(left, right, out); 105 | } -------------------------------------------------------------------------------- /test/testDispCompute.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | 3 | #include 4 | 5 | #include 6 | 7 | using namespace cv; 8 | using namespace std; 9 | using namespace libSM; 10 | 11 | const string CONES_DATA_SET_PATH = "../../data/cones/"; 12 | const string TEDDY_DATA_SET_PATH = "../../data/teddy/"; 13 | 14 | class Cones : public testing::Test { 15 | protected: 16 | void SetUp() override { 17 | left = imread(CONES_DATA_SET_PATH + "im2.png", IMREAD_UNCHANGED); 18 | right = imread(CONES_DATA_SET_PATH + "im6.png", IMREAD_UNCHANGED); 19 | } 20 | 21 | public: 22 | Mat left; 23 | Mat right; 24 | void transformToGray() { 25 | if(left.type() == CV_8UC3) 26 | cvtColor(left, left, COLOR_BGR2GRAY); 27 | 28 | if(right.type() == CV_8UC3) 29 | cvtColor(right, right, COLOR_BGR2GRAY); 30 | } 31 | }; 32 | 33 | class Teddy : public testing::Test { 34 | protected: 35 | void SetUp() override { 36 | left = imread(TEDDY_DATA_SET_PATH + "im2.png", IMREAD_UNCHANGED); 37 | right = imread(TEDDY_DATA_SET_PATH + "im6.png", IMREAD_UNCHANGED); 38 | } 39 | public: 40 | Mat left; 41 | Mat right; 42 | void transformToGray() { 43 | if(left.type() == CV_8UC3) 44 | cvtColor(left, left, COLOR_BGR2GRAY); 45 | 46 | if(right.type() == CV_8UC3) 47 | cvtColor(right, right, COLOR_BGR2GRAY); 48 | } 49 | }; 50 | 51 | TEST_F(Cones, testWinnerTakesAll) { 52 | Mat cost; 53 | { 54 | auto params = ADCensusCost::Params(); 55 | params.windowWidth = 9; 56 | params.windowHeight = 7; 57 | params.minDisp = 0; 58 | params.maxDisp = 64; 59 | params.adWeight = 10.f; 60 | params.censusWeight = 30.f; 61 | 62 | transformToGray(); 63 | 64 | auto adCensusComputer = ADCensusCost::create(params); 65 | adCensusComputer->compute(left, right, cost); 66 | } 67 | 68 | Mat disp; 69 | { 70 | auto params = DispComputeParams(); 71 | params.enableLRCheck = true; 72 | params.enableUniqueCheck = true; 73 | params.enableSubpixelFitting = true; 74 | params.lrCheckThreshod = 1; 75 | params.uniquenessRatio = 0.98f; 76 | params.minDisp = 0; 77 | params.maxDisp = 64; 78 | 79 | winnerTakesAll(cost, disp, params); 80 | 81 | } 82 | 83 | ASSERT_LE(abs(disp.ptr(301)[308] - 40), 1.f); 84 | } -------------------------------------------------------------------------------- /test/testDispOptimiztion.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | 3 | #include 4 | 5 | #include 6 | 7 | using namespace cv; 8 | using namespace std; 9 | using namespace libSM; 10 | 11 | const string CONES_DATA_SET_PATH = "../../data/cones/"; 12 | const string TEDDY_DATA_SET_PATH = "../../data/teddy/"; 13 | 14 | class Cones : public testing::Test { 15 | protected: 16 | void SetUp() override { 17 | left = imread(CONES_DATA_SET_PATH + "im2.png", IMREAD_UNCHANGED); 18 | right = imread(CONES_DATA_SET_PATH + "im6.png", IMREAD_UNCHANGED); 19 | } 20 | 21 | public: 22 | Mat left; 23 | Mat right; 24 | void transformToGray() { 25 | if(left.type() == CV_8UC3) 26 | cvtColor(left, left, COLOR_BGR2GRAY); 27 | 28 | if(right.type() == CV_8UC3) 29 | cvtColor(right, right, COLOR_BGR2GRAY); 30 | } 31 | }; 32 | 33 | class Teddy : public testing::Test { 34 | protected: 35 | void SetUp() override { 36 | left = imread(TEDDY_DATA_SET_PATH + "im2.png", IMREAD_UNCHANGED); 37 | right = imread(TEDDY_DATA_SET_PATH + "im6.png", IMREAD_UNCHANGED); 38 | } 39 | public: 40 | Mat left; 41 | Mat right; 42 | void transformToGray() { 43 | if(left.type() == CV_8UC3) 44 | cvtColor(left, left, COLOR_BGR2GRAY); 45 | 46 | if(right.type() == CV_8UC3) 47 | cvtColor(right, right, COLOR_BGR2GRAY); 48 | } 49 | }; 50 | 51 | TEST_F(Cones, testMultipathAggregation) { 52 | transformToGray(); 53 | 54 | Mat cost; 55 | { 56 | auto params = CensusCost::Params(); 57 | params.windowWidth = 9; 58 | params.windowHeight = 7; 59 | params.minDisp = 0; 60 | params.maxDisp = 64; 61 | 62 | auto adCensusComputer = CensusCost::create(params); 63 | adCensusComputer->compute(left, right, cost); 64 | } 65 | 66 | Mat aggregatedCost; 67 | { 68 | auto params = MultipathAggregation::Params(); 69 | params.P1 = 10.f; 70 | params.P2 = 150.f; 71 | params.enableHonrizon = true; 72 | params.enableNegtive45 = true; 73 | params.enablePostive45 = true; 74 | params.enableVertiacl = true; 75 | 76 | auto multipathAggregator = MultipathAggregation::create(params); 77 | multipathAggregator->aggregation(left, cost, aggregatedCost); 78 | } 79 | 80 | Mat disp; 81 | { 82 | auto params = DispComputeParams(); 83 | params.enableLRCheck = true; 84 | params.enableUniqueCheck = true; 85 | params.enableSubpixelFitting = true; 86 | params.lrCheckThreshod = 1; 87 | params.uniquenessRatio = 0.95f; 88 | params.minDisp = 0; 89 | params.maxDisp = 64; 90 | 91 | winnerTakesAll(aggregatedCost, disp, params); 92 | } 93 | 94 | 95 | Mat optimizedDisp; 96 | { 97 | auto params = DispOptParams(); 98 | params.enableRemoveSmallArea = true; 99 | params.dispDomainThreshold = 2; 100 | params.smallAreaThreshold = 10; 101 | params.enableBilateralFilter = true; 102 | params.d = 10; 103 | params.sigmaColor = 10; 104 | params.sigmaSpace = 20; 105 | 106 | dispOptimiz(disp, optimizedDisp, params); 107 | } 108 | 109 | ASSERT_LE(abs(optimizedDisp.ptr(301)[308] - 40), 1.f); 110 | } -------------------------------------------------------------------------------- /test/testSGM.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | 3 | #include 4 | 5 | #include 6 | 7 | using namespace cv; 8 | using namespace std; 9 | using namespace libSM; 10 | 11 | const string CONES_DATA_SET_PATH = "../../data/cones/"; 12 | const string TEDDY_DATA_SET_PATH = "../../data/teddy/"; 13 | 14 | class Cones : public testing::Test { 15 | protected: 16 | void SetUp() override { 17 | left = imread(CONES_DATA_SET_PATH + "im2.png", IMREAD_UNCHANGED); 18 | right = imread(CONES_DATA_SET_PATH + "im6.png", IMREAD_UNCHANGED); 19 | } 20 | 21 | public: 22 | Mat left; 23 | Mat right; 24 | void transformToGray() { 25 | if(left.type() == CV_8UC3) 26 | cvtColor(left, left, COLOR_BGR2GRAY); 27 | 28 | if(right.type() == CV_8UC3) 29 | cvtColor(right, right, COLOR_BGR2GRAY); 30 | } 31 | }; 32 | 33 | class Teddy : public testing::Test { 34 | protected: 35 | void SetUp() override { 36 | left = imread(TEDDY_DATA_SET_PATH + "im2.png", IMREAD_UNCHANGED); 37 | right = imread(TEDDY_DATA_SET_PATH + "im6.png", IMREAD_UNCHANGED); 38 | } 39 | public: 40 | Mat left; 41 | Mat right; 42 | void transformToGray() { 43 | if(left.type() == CV_8UC3) 44 | cvtColor(left, left, COLOR_BGR2GRAY); 45 | 46 | if(right.type() == CV_8UC3) 47 | cvtColor(right, right, COLOR_BGR2GRAY); 48 | } 49 | }; 50 | 51 | TEST_F(Cones, testSGMGray) { 52 | transformToGray(); 53 | 54 | auto params = SGM::Params(); 55 | auto sgm = SGM::create(params); 56 | 57 | Mat disparityMap; 58 | sgm->match(left, right, disparityMap); 59 | 60 | ASSERT_LE(abs(disparityMap.ptr(301)[308] - 40), 1.f); 61 | } 62 | 63 | TEST_F(Cones, testSGMColor) { 64 | auto params = SGM::Params(); 65 | auto sgm = SGM::create(params); 66 | 67 | Mat disparityMap; 68 | sgm->match(left, right, disparityMap); 69 | 70 | ASSERT_LE(abs(disparityMap.ptr(301)[308] - 40), 1.f); 71 | } -------------------------------------------------------------------------------- /uml/costAggregation.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Practice3DVision/libStereoMatch/70c681e49c862e9e2b04e71d107a664c90d824f7/uml/costAggregation.png -------------------------------------------------------------------------------- /uml/costAggregation.vsdx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Practice3DVision/libStereoMatch/70c681e49c862e9e2b04e71d107a664c90d824f7/uml/costAggregation.vsdx -------------------------------------------------------------------------------- /uml/costCompute.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Practice3DVision/libStereoMatch/70c681e49c862e9e2b04e71d107a664c90d824f7/uml/costCompute.png -------------------------------------------------------------------------------- /uml/costCompute.vsdx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Practice3DVision/libStereoMatch/70c681e49c862e9e2b04e71d107a664c90d824f7/uml/costCompute.vsdx -------------------------------------------------------------------------------- /uml/dispCompute.vsdx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Practice3DVision/libStereoMatch/70c681e49c862e9e2b04e71d107a664c90d824f7/uml/dispCompute.vsdx --------------------------------------------------------------------------------