├── py-faster-rcnn ├── lib │ ├── nms │ │ ├── __init__.py │ │ ├── .gitignore │ │ └── gpu_nms.hpp │ ├── transform │ │ └── __init__.py │ ├── utils │ │ ├── .gitignore │ │ └── __init__.py │ ├── pycocotools │ │ ├── __init__.py │ │ └── UPSTREAM_REV │ ├── Makefile │ ├── datasets │ │ ├── __init__.py │ │ └── VOCdevkit-matlab-wrapper │ │ │ ├── get_voc_opts.m │ │ │ └── xVOCap.m │ ├── fast_rcnn │ │ ├── __init__.py │ │ └── nms_wrapper.py │ ├── roi_data_layer │ │ └── __init__.py │ └── rpn │ │ ├── __init__.py │ │ └── README.md ├── caffe-fast-rcnn │ ├── __init__.py │ ├── docs │ │ ├── tutorial │ │ │ ├── fig │ │ │ │ ├── .gitignore │ │ │ │ ├── layer.jpg │ │ │ │ ├── backward.jpg │ │ │ │ ├── forward.jpg │ │ │ │ ├── logreg.jpg │ │ │ │ └── forward_backward.png │ │ │ ├── layers │ │ │ │ ├── filter.md │ │ │ │ ├── silence.md │ │ │ │ ├── batchreindex.md │ │ │ │ ├── rnn.md │ │ │ │ ├── input.md │ │ │ │ ├── argmax.md │ │ │ │ ├── im2col.md │ │ │ │ ├── tanh.md │ │ │ │ ├── spp.md │ │ │ │ ├── windowdata.md │ │ │ │ ├── dummydata.md │ │ │ │ ├── hingeloss.md │ │ │ │ ├── threshold.md │ │ │ │ ├── split.md │ │ │ │ ├── sigmoidcrossentropyloss.md │ │ │ │ ├── log.md │ │ │ │ ├── absval.md │ │ │ │ ├── bias.md │ │ │ │ ├── crop.md │ │ │ │ ├── tile.md │ │ │ │ ├── embed.md │ │ │ │ ├── parameter.md │ │ │ │ ├── prelu.md │ │ │ │ ├── scale.md │ │ │ │ ├── bnll.md │ │ │ │ ├── euclideanloss.md │ │ │ │ ├── flatten.md │ │ │ │ ├── multinomiallogisticloss.md │ │ │ │ ├── sigmoid.md │ │ │ │ ├── dropout.md │ │ │ │ └── eltwise.md │ │ │ └── convolution.md │ │ ├── CNAME │ │ ├── images │ │ │ ├── caffeine-icon.png │ │ │ └── GitHub-Mark-64px.png │ │ ├── _config.yml │ │ ├── README.md │ │ └── stylesheets │ │ │ └── reset.css │ ├── python │ │ ├── caffe │ │ │ ├── proto │ │ │ │ └── __init__.py │ │ │ ├── imagenet │ │ │ │ └── ilsvrc_2012_mean.npy │ │ │ ├── test │ │ │ │ └── test_layer_type_list.py │ │ │ └── __init__.py │ │ └── requirements.txt │ ├── matlab │ │ ├── hdf5creation │ │ │ └── .gitignore │ │ └── +caffe │ │ │ ├── private │ │ │ ├── CHECK.m │ │ │ └── CHECK_FILE_EXIST.m │ │ │ ├── set_mode_cpu.m │ │ │ ├── set_mode_gpu.m │ │ │ ├── version.m │ │ │ ├── imagenet │ │ │ └── ilsvrc_2012_mean.mat │ │ │ ├── reset_all.m │ │ │ ├── set_device.m │ │ │ ├── get_solver.m │ │ │ ├── run_tests.m │ │ │ └── +test │ │ │ └── test_io.m │ ├── src │ │ ├── caffe │ │ │ ├── test │ │ │ │ └── test_data │ │ │ │ │ ├── solver_data_list.txt │ │ │ │ │ ├── sample_data_list.txt │ │ │ │ │ ├── sample_data.h5 │ │ │ │ │ ├── solver_data.h5 │ │ │ │ │ └── sample_data_2_gzip.h5 │ │ │ ├── layer.cpp │ │ │ ├── layers │ │ │ │ ├── parameter_layer.cpp │ │ │ │ ├── neuron_layer.cpp │ │ │ │ ├── silence_layer.cpp │ │ │ │ ├── silence_layer.cu │ │ │ │ ├── loss_layer.cpp │ │ │ │ └── base_data_layer.cu │ │ │ ├── util │ │ │ │ ├── cudnn.cpp │ │ │ │ └── db_leveldb.cpp │ │ │ └── solvers │ │ │ │ ├── sgd_solver.cu │ │ │ │ └── adagrad_solver.cu │ │ └── gtest │ │ │ └── CMakeLists.txt │ ├── examples │ │ ├── web_demo │ │ │ └── requirements.txt │ │ ├── images │ │ │ ├── cat.jpg │ │ │ ├── cat gray.jpg │ │ │ ├── cat_gray.jpg │ │ │ └── fish-bike.jpg │ │ ├── mnist │ │ │ ├── train_lenet.sh │ │ │ ├── train_lenet_adam.sh │ │ │ ├── train_lenet_rmsprop.sh │ │ │ ├── train_lenet_consolidated.sh │ │ │ ├── train_mnist_autoencoder.sh │ │ │ ├── train_mnist_autoencoder_adadelta.sh │ │ │ ├── train_mnist_autoencoder_adagrad.sh │ │ │ ├── train_mnist_autoencoder_nesterov.sh │ │ │ ├── mnist_autoencoder_solver_adagrad.prototxt │ │ │ ├── mnist_autoencoder_solver.prototxt │ │ │ ├── mnist_autoencoder_solver_adadelta.prototxt │ │ │ ├── mnist_autoencoder_solver_nesterov.prototxt │ │ │ ├── create_mnist.sh │ │ │ ├── lenet_auto_solver.prototxt │ │ │ ├── lenet_adadelta_solver.prototxt │ │ │ └── lenet_solver.prototxt │ │ ├── imagenet │ │ │ ├── train_caffenet.sh │ │ │ ├── resume_training.sh │ │ │ └── make_imagenet_mean.sh │ │ ├── siamese │ │ │ ├── train_mnist_siamese.sh │ │ │ ├── create_mnist_siamese.sh │ │ │ └── mnist_siamese_solver.prototxt │ │ ├── finetune_flickr_style │ │ │ ├── flickr_style.csv.gz │ │ │ └── style_names.txt │ │ ├── cifar10 │ │ │ ├── train_full_sigmoid.sh │ │ │ ├── train_full_sigmoid_bn.sh │ │ │ ├── train_quick.sh │ │ │ ├── create_cifar10.sh │ │ │ └── train_full.sh │ │ ├── finetune_pascal_detection │ │ │ └── pascal_finetune_solver.prototxt │ │ └── net_surgery │ │ │ └── conv.prototxt │ ├── cmake │ │ ├── CMakeFiles │ │ │ ├── cmake.check_cache │ │ │ ├── a.out │ │ │ └── 2.8.12.2 │ │ │ │ ├── CompilerIdC │ │ │ │ └── a.out │ │ │ │ ├── CompilerIdCXX │ │ │ │ └── a.out │ │ │ │ └── CMakeSystem.cmake │ │ ├── detect_cuda_archs.cu │ │ ├── Templates │ │ │ └── CaffeConfigVersion.cmake.in │ │ └── Modules │ │ │ └── FindNCCL.cmake │ ├── tools │ │ ├── test_net.cpp │ │ ├── device_query.cpp │ │ ├── finetune_net.cpp │ │ ├── train_net.cpp │ │ ├── net_speed_benchmark.cpp │ │ └── CMakeLists.txt │ ├── INSTALL.md │ ├── scripts │ │ ├── travis │ │ │ ├── configure.sh │ │ │ ├── defaults.sh │ │ │ ├── build.sh │ │ │ ├── install-python-deps.sh │ │ │ ├── test.sh │ │ │ ├── setup-venv.sh │ │ │ └── configure-cmake.sh │ │ ├── build_docs.sh │ │ └── download_model_from_gist.sh │ ├── detect_cuda_archs.cu │ ├── data │ │ ├── mnist │ │ │ └── get_mnist.sh │ │ ├── cifar10 │ │ │ └── get_cifar10.sh │ │ └── ilsvrc12 │ │ │ └── get_ilsvrc_aux.sh │ ├── include │ │ └── caffe │ │ │ ├── util │ │ │ ├── format.hpp │ │ │ ├── signal_handler.h │ │ │ └── nccl.hpp │ │ │ └── caffe.hpp │ └── CONTRIBUTORS.md ├── tools │ ├── README.md │ └── _init_paths.py └── cfgs │ ├── faster_rcnn_alt_opt.yml │ ├── faster_rcnn_end2end.yml │ ├── faster_rcnn_endmod.yml │ ├── faster_rcnn_oneh.yml │ ├── faster_rcnn_coco.yml │ └── faster_rcnn_posenet.yml ├── ros ├── sptam │ ├── plotters │ │ ├── parsers │ │ │ ├── __init__.py │ │ │ ├── mit_gt.py │ │ │ └── ground_truth_loader.py │ │ └── utils │ │ │ ├── __init__.py │ │ │ └── colors.py │ ├── src │ │ ├── standAlone │ │ │ ├── .gitignore │ │ │ └── Test │ │ │ │ ├── opencv3_feature_extraction │ │ │ │ └── parameters.yaml │ │ │ │ └── ReadImagesFromDir │ │ │ │ ├── CMakeLists.txt │ │ │ │ └── ReadImagesFromDir.cpp │ │ ├── ros │ │ │ ├── stereo_driver.cpp │ │ │ └── sptam_nodelet.cpp │ │ └── sptam │ │ │ ├── ObjectEdge.cpp │ │ │ ├── match_to_points.hpp │ │ │ ├── loopclosing │ │ │ └── LCDetector.hpp │ │ │ └── utils │ │ │ ├── timer.h │ │ │ ├── timer.cpp │ │ │ └── projection_derivatives.hpp │ ├── msg │ │ └── StereoKFwithPose.msg │ ├── configurationFiles │ │ ├── tsukuba_cam.yaml │ │ ├── fantasy_cam.yaml │ │ ├── kitti_cam_03.yaml │ │ ├── kitti_cam_04_to_12.yaml │ │ ├── kitti_cam_00_to_02_13_to_21.yaml │ │ ├── KITTI00_left.yaml │ │ ├── KITTI00_right.yaml │ │ ├── kitti_sift.yaml │ │ ├── mit.yaml │ │ ├── sfu.yaml │ │ ├── newCollege.yaml │ │ ├── kitti_fast_brief.yaml │ │ ├── kitti_agast_latch.yaml │ │ ├── kitti_fast_latch.yaml │ │ ├── kitti_agast_brief.yaml │ │ ├── tsukuba.yaml │ │ ├── kitti_star_brief.yaml │ │ ├── kitti_surf.yaml │ │ ├── mobius.yaml │ │ ├── zed_vga.yaml │ │ ├── firefly.yaml │ │ ├── kitti_star_latch.yaml │ │ ├── bumblebee.yaml │ │ ├── kitti_orb.yaml │ │ ├── euroc_fast_brief.yaml │ │ ├── kitti_gftt_latch.yaml │ │ ├── level7.yaml │ │ ├── vrep_quad.yaml │ │ ├── euroc_odroid_fast_brief.yaml │ │ ├── euroc_star_brief.yaml │ │ ├── euroc_odroid_star_brief.yaml │ │ ├── kitti_gftt_lucid.yaml │ │ ├── euroc_orb_brief.yaml │ │ ├── euroc_odroid_orb_brief.yaml │ │ ├── kitti_surf_freak.yaml │ │ ├── euroc_gftt_brief.yaml │ │ ├── euroc_odroid_gftt_brief.yaml │ │ ├── kitti.yaml │ │ ├── kitti_agast_brisk.yaml │ │ ├── kitti_fast_brisk.yaml │ │ ├── euroc_orb.yaml │ │ ├── euroc_odroid_orb.yaml │ │ ├── kitti_gftt_brisk.yaml │ │ ├── kitti_star_brisk.yaml │ │ ├── kitti_akaze.yaml │ │ └── calibrations │ │ │ └── 00b09d0100626e63_left.yaml │ ├── sptam_plugin.xml │ ├── Doxyfile │ ├── LICENSE.txt │ ├── launch │ │ └── msf.launch │ ├── cmake-modules │ │ └── FindOpenGV.cmake │ └── README.md ├── dl_node │ ├── msg │ │ ├── Ints.msg │ │ ├── Detection.msg │ │ ├── DetectionList.msg │ │ ├── DetectionWithPoseList.msg │ │ └── DetectionWithPose.msg │ └── src │ │ ├── _init_paths.py │ │ └── _init_paths_softnms.py └── ros-utils │ └── package.xml ├── dependencies ├── pugixml │ ├── tests │ │ ├── data │ │ │ ├── empty.xml │ │ │ ├── small.xml │ │ │ ├── тест.xml │ │ │ ├── multiline.xml │ │ │ ├── latintest_latin1.xml │ │ │ ├── utftest_utf16_be.xml │ │ │ ├── utftest_utf16_le.xml │ │ │ ├── utftest_utf32_be.xml │ │ │ ├── utftest_utf32_le.xml │ │ │ ├── utftest_utf16_be_bom.xml │ │ │ ├── utftest_utf16_le_bom.xml │ │ │ ├── utftest_utf32_be_bom.xml │ │ │ ├── utftest_utf32_le_bom.xml │ │ │ ├── utftest_utf16_be_clean.xml │ │ │ ├── utftest_utf16_le_clean.xml │ │ │ ├── utftest_utf32_be_clean.xml │ │ │ ├── utftest_utf32_le_clean.xml │ │ │ ├── utftest_utf16_be_nodecl.xml │ │ │ ├── utftest_utf16_le_nodecl.xml │ │ │ ├── utftest_utf32_be_nodecl.xml │ │ │ ├── utftest_utf32_le_nodecl.xml │ │ │ ├── truncation.xml │ │ │ └── latintest_utf8.xml │ │ ├── data_fuzz_xpath │ │ │ ├── basic.xpath │ │ │ ├── math.xpath │ │ │ ├── path.xpath │ │ │ ├── predicate.xpath │ │ │ └── functions.xpath │ │ ├── data_fuzz_parse │ │ │ ├── basic.xml │ │ │ ├── utf16.xml │ │ │ ├── utf32.xml │ │ │ ├── types.xml │ │ │ ├── refs.xml │ │ │ └── doctype.xml │ │ ├── test_header_guard.cpp │ │ ├── test_header_iosfwd_1.cpp │ │ ├── test_header_iosfwd_2.cpp │ │ ├── test_header_string_1.cpp │ │ ├── test_header_string_2.cpp │ │ ├── test_header_iostream_1.cpp │ │ ├── test_header_iostream_2.cpp │ │ ├── test_version.cpp │ │ ├── common.hpp │ │ ├── test_header_string_iostream.cpp │ │ ├── allocator.hpp │ │ ├── fuzz_parse.cpp │ │ ├── fuzz_setup.sh │ │ ├── test_header_only_1.cpp │ │ ├── test_header_only_2.cpp │ │ └── fuzz_xpath.cpp │ ├── .codecov.yml │ ├── docs │ │ ├── images │ │ │ ├── dom_tree.png │ │ │ ├── vs2005_pch1.png │ │ │ ├── vs2005_pch2.png │ │ │ ├── vs2005_pch3.png │ │ │ ├── vs2005_pch4.png │ │ │ ├── vs2005_link1.png │ │ │ ├── vs2005_link2.png │ │ │ ├── vs2010_link1.png │ │ │ └── vs2010_link2.png │ │ ├── samples │ │ │ ├── weekly-utf-16.xml │ │ │ ├── weekly-shift_jis.xml │ │ │ ├── character.xml │ │ │ ├── transitions.xml │ │ │ ├── tree.xml │ │ │ ├── load_file.cpp │ │ │ ├── save_file.cpp │ │ │ ├── save_stream.cpp │ │ │ ├── custom_memory_management.cpp │ │ │ ├── traverse_iter.cpp │ │ │ ├── xgconsole.xml │ │ │ ├── save_declaration.cpp │ │ │ ├── modify_remove.cpp │ │ │ ├── traverse_rangefor.cpp │ │ │ ├── modify_add.cpp │ │ │ ├── save_subtree.cpp │ │ │ ├── xpath_select.cpp │ │ │ └── traverse_walker.cpp │ │ └── config.adoc │ ├── scripts │ │ ├── cocoapods_push.sh │ │ ├── pugixml_airplay.mkf │ │ └── pugixml.pc.in │ ├── .travis.yml │ └── appveyor.yml └── meta │ ├── test │ └── CMakeLists.txt │ ├── example │ ├── examples.hpp │ └── CMakeLists.txt │ ├── install_libcxx.sh │ └── readme.md ├── _config.yml ├── data └── caffeModels │ └── getCaffeModel.sh ├── .gitmodules ├── models_trained ├── coco │ ├── VGG16 │ │ ├── fast_rcnn │ │ │ └── solver.prototxt │ │ └── faster_rcnn_end2end │ │ │ └── solver.prototxt │ └── VGG_CNN_M_1024 │ │ ├── faster_rcnn_end2end │ │ └── solver.prototxt │ │ └── fast_rcnn │ │ └── solver.prototxt ├── pascal_voc │ ├── ZF │ │ ├── faster_rcnn_alt_opt │ │ │ ├── stage1_rpn_solver60k80k.pt │ │ │ ├── stage2_rpn_solver60k80k.pt │ │ │ ├── stage1_fast_rcnn_solver30k40k.pt │ │ │ └── stage2_fast_rcnn_solver30k40k.pt │ │ ├── fast_rcnn │ │ │ └── solver.prototxt │ │ └── faster_rcnn_end2end │ │ │ └── solver.prototxt │ ├── VGG16 │ │ ├── fast_rcnn │ │ │ └── solver.prototxt │ │ ├── faster_rcnn_alt_opt │ │ │ ├── stage1_rpn_solver60k80k.pt │ │ │ ├── stage2_rpn_solver60k80k.pt │ │ │ ├── stage1_fast_rcnn_solver30k40k.pt │ │ │ └── stage2_fast_rcnn_solver30k40k.pt │ │ └── faster_rcnn_end2end │ │ │ └── solver.prototxt │ └── VGG_CNN_M_1024 │ │ ├── fast_rcnn │ │ └── solver.prototxt │ │ ├── faster_rcnn_end2end │ │ └── solver.prototxt │ │ └── faster_rcnn_alt_opt │ │ ├── stage1_rpn_solver60k80k.pt │ │ ├── stage2_rpn_solver60k80k.pt │ │ ├── stage1_fast_rcnn_solver30k40k.pt │ │ └── stage2_fast_rcnn_solver30k40k.pt ├── modelnet │ └── VGG16 │ │ └── faster_rcnn_end2end │ │ ├── solver.working.prototxt │ │ └── solver.prototxt ├── modeloneh │ └── VGG16 │ │ └── faster_rcnn_end2end │ │ ├── solver.working.prototxt │ │ └── solver.prototxt └── modelpose │ └── VGG16 │ └── faster_rcnn_end2end │ ├── solver.working.prototxt │ └── solver.prototxt └── FromMaxwellToOther.dockerfile /py-faster-rcnn/lib/nms/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /ros/sptam/plotters/parsers/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /ros/sptam/plotters/utils/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/data/empty.xml: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /py-faster-rcnn/lib/transform/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /ros/dl_node/msg/Ints.msg: -------------------------------------------------------------------------------- 1 | int32[] data 2 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/data/small.xml: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/data/тест.xml: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /ros/sptam/src/standAlone/.gitignore: -------------------------------------------------------------------------------- 1 | build 2 | -------------------------------------------------------------------------------- /py-faster-rcnn/lib/utils/.gitignore: -------------------------------------------------------------------------------- 1 | *.c 2 | *.so 3 | -------------------------------------------------------------------------------- /dependencies/pugixml/.codecov.yml: -------------------------------------------------------------------------------- 1 | comment: false 2 | 3 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/data_fuzz_xpath/basic.xpath: -------------------------------------------------------------------------------- 1 | a/b/c -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/fig/.gitignore: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/python/caffe/proto/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /py-faster-rcnn/lib/nms/.gitignore: -------------------------------------------------------------------------------- 1 | *.c 2 | *.cpp 3 | *.so 4 | -------------------------------------------------------------------------------- /py-faster-rcnn/lib/pycocotools/__init__.py: -------------------------------------------------------------------------------- 1 | __author__ = 'tylin' 2 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/data_fuzz_xpath/math.xpath: -------------------------------------------------------------------------------- 1 | 1+2*3 div 4 mod 5-6 -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/CNAME: -------------------------------------------------------------------------------- 1 | caffe.berkeleyvision.org 2 | -------------------------------------------------------------------------------- /_config.yml: -------------------------------------------------------------------------------- 1 | theme: jekyll-theme-slate 2 | exclude: 3 | - py-faster-rcnn 4 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/data_fuzz_parse/basic.xml: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/matlab/hdf5creation/.gitignore: -------------------------------------------------------------------------------- 1 | *.h5 2 | list.txt 3 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/data/multiline.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | -------------------------------------------------------------------------------- /py-faster-rcnn/lib/Makefile: -------------------------------------------------------------------------------- 1 | all: 2 | python setup.py build_ext --inplace 3 | rm -rf build 4 | -------------------------------------------------------------------------------- /dependencies/meta/test/CMakeLists.txt: -------------------------------------------------------------------------------- 1 | add_executable(meta meta.cpp) 2 | add_test(test.meta, meta) 3 | -------------------------------------------------------------------------------- /py-faster-rcnn/tools/README.md: -------------------------------------------------------------------------------- 1 | Tools for training, testing, and compressing Fast R-CNN networks. 2 | -------------------------------------------------------------------------------- /ros/dl_node/msg/Detection.msg: -------------------------------------------------------------------------------- 1 | int32 cls 2 | int32 x1 3 | int32 y1 4 | int32 x2 5 | int32 y2 6 | 7 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/data_fuzz_xpath/path.xpath: -------------------------------------------------------------------------------- 1 | @*/ancestor::*/near-north/*[4]/@*/preceding::text() -------------------------------------------------------------------------------- /ros/dl_node/msg/DetectionList.msg: -------------------------------------------------------------------------------- 1 | Header header 2 | Detection[] data 3 | geometry_msgs/Pose pose 4 | 5 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/data_fuzz_xpath/predicate.xpath: -------------------------------------------------------------------------------- 1 | library/nodes[@id=12]/element[@type='translate'][1] -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/src/caffe/test/test_data/solver_data_list.txt: -------------------------------------------------------------------------------- 1 | src/caffe/test/test_data/solver_data.h5 2 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/data_fuzz_xpath/functions.xpath: -------------------------------------------------------------------------------- 1 | sum(nodes) + round(concat(//a[translate(@id, 'abc', '012')])) 2 | -------------------------------------------------------------------------------- /py-faster-rcnn/lib/pycocotools/UPSTREAM_REV: -------------------------------------------------------------------------------- 1 | https://github.com/pdollar/coco/commit/3ac47c77ebd5a1ed4254a98b7fbf2ef4765a3574 2 | -------------------------------------------------------------------------------- /ros/sptam/msg/StereoKFwithPose.msg: -------------------------------------------------------------------------------- 1 | Header header 2 | ##geometry_msgs/Pose pose 3 | sensor_msgs/Image img_l 4 | uint64 kf_id 5 | -------------------------------------------------------------------------------- /ros/dl_node/msg/DetectionWithPoseList.msg: -------------------------------------------------------------------------------- 1 | Header header 2 | DetectionWithPose[] data 3 | ##geometry_msgs/Pose pose 4 | uint64 kf_id 5 | -------------------------------------------------------------------------------- /ros/sptam/src/ros/stereo_driver.cpp: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CIFASIS/object-detection-sptam/HEAD/ros/sptam/src/ros/stereo_driver.cpp -------------------------------------------------------------------------------- /dependencies/pugixml/tests/test_header_guard.cpp: -------------------------------------------------------------------------------- 1 | // Tests header guards 2 | #include "../src/pugixml.hpp" 3 | #include "../src/pugixml.hpp" 4 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/examples/web_demo/requirements.txt: -------------------------------------------------------------------------------- 1 | werkzeug 2 | flask 3 | tornado 4 | numpy 5 | pandas 6 | pillow 7 | pyyaml 8 | -------------------------------------------------------------------------------- /py-faster-rcnn/cfgs/faster_rcnn_alt_opt.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: faster_rcnn_alt_opt 2 | TRAIN: 3 | BG_THRESH_LO: 0.0 4 | TEST: 5 | HAS_RPN: True 6 | -------------------------------------------------------------------------------- /data/caffeModels/getCaffeModel.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | wget https://cifasis-conicet.gov.ar/~erica/caffeModels/pose_coco_Allconst_iter16000.caffemodel 3 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/test_header_iosfwd_1.cpp: -------------------------------------------------------------------------------- 1 | // Tests compatibility with iosfwd 2 | #include "../src/pugixml.hpp" 3 | #include 4 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/test_header_iosfwd_2.cpp: -------------------------------------------------------------------------------- 1 | // Tests compatibility with iosfwd 2 | #include 3 | #include "../src/pugixml.hpp" 4 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/test_header_string_1.cpp: -------------------------------------------------------------------------------- 1 | // Tests compatibility with string 2 | #include "../src/pugixml.hpp" 3 | #include 4 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/test_header_string_2.cpp: -------------------------------------------------------------------------------- 1 | // Tests compatibility with string 2 | #include 3 | #include "../src/pugixml.hpp" 4 | -------------------------------------------------------------------------------- /dependencies/meta/example/examples.hpp: -------------------------------------------------------------------------------- 1 | /// \file examples.hpp List of all examples 2 | 3 | /// \example tuple_cat.cpp Tuple concatenation example: 4 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/test_header_iostream_1.cpp: -------------------------------------------------------------------------------- 1 | // Tests compatibility with iostream 2 | #include "../src/pugixml.hpp" 3 | #include 4 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/test_header_iostream_2.cpp: -------------------------------------------------------------------------------- 1 | // Tests compatibility with iostream 2 | #include 3 | #include "../src/pugixml.hpp" 4 | -------------------------------------------------------------------------------- /dependencies/pugixml/docs/images/dom_tree.png: 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/py-faster-rcnn/caffe-fast-rcnn/matlab/+caffe/set_mode_gpu.m: -------------------------------------------------------------------------------- 1 | function set_mode_gpu() 2 | % set_mode_gpu() 3 | % set Caffe to GPU mode 4 | 5 | caffe_('set_mode_gpu'); 6 | 7 | end 8 | -------------------------------------------------------------------------------- /py-faster-rcnn/lib/nms/gpu_nms.hpp: -------------------------------------------------------------------------------- 1 | void _nms(int* keep_out, int* num_out, const float* boxes_host, int boxes_num, 2 | int boxes_dim, float nms_overlap_thresh, int device_id); 3 | -------------------------------------------------------------------------------- /ros/dl_node/msg/DetectionWithPose.msg: -------------------------------------------------------------------------------- 1 | int32 cls 2 | int32 x1 3 | int32 y1 4 | int32 x2 5 | int32 y2 6 | float32 yaw 7 | float32 dimX 8 | float32 dimY 9 | float32 dimZ 10 | 11 | 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./build/tools/caffe train \ 5 | --solver=models/bvlc_reference_caffenet/solver.prototxt $@ 6 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/examples/mnist/train_lenet_rmsprop.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | ./build/tools/caffe train \ 5 | --solver=examples/mnist/lenet_solver_rmsprop.prototxt $@ 6 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/data_fuzz_parse/refs.xml: -------------------------------------------------------------------------------- 1 | pcdata < > & " ' « &unknown; %entity; -------------------------------------------------------------------------------- /dependencies/pugixml/tests/test_header_string_iostream.cpp: -------------------------------------------------------------------------------- 1 | // Tests compatibility with string/iostream 2 | #include 3 | #include "../src/pugixml.hpp" 4 | #include 5 | #include 6 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/_config.yml: -------------------------------------------------------------------------------- 1 | defaults: 2 | - 3 | scope: 4 | path: "" # an empty string here means all files in the project 5 | values: 6 | layout: "default" 7 | 8 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/fig/forward_backward.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CIFASIS/object-detection-sptam/HEAD/py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/fig/forward_backward.png -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/src/caffe/test/test_data/sample_data.h5: 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"../src" 4 | } 5 | 6 | files 7 | { 8 | ("../src") 9 | pugiconfig.hpp 10 | pugixml.cpp 11 | pugixml.hpp 12 | } 13 | 14 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/cmake/CMakeFiles/2.8.12.2/CompilerIdC/a.out: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CIFASIS/object-detection-sptam/HEAD/py-faster-rcnn/caffe-fast-rcnn/cmake/CMakeFiles/2.8.12.2/CompilerIdC/a.out -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/cmake/CMakeFiles/2.8.12.2/CompilerIdCXX/a.out: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CIFASIS/object-detection-sptam/HEAD/py-faster-rcnn/caffe-fast-rcnn/cmake/CMakeFiles/2.8.12.2/CompilerIdCXX/a.out -------------------------------------------------------------------------------- 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--solver=examples/mnist/mnist_autoencoder_solver_adadelta.prototxt $@ 6 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/examples/mnist/train_mnist_autoencoder_adagrad.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | set -e 3 | 4 | ./build/tools/caffe train \ 5 | --solver=examples/mnist/mnist_autoencoder_solver_adagrad.prototxt $@ 6 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/examples/mnist/train_mnist_autoencoder_nesterov.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | set -e 3 | 4 | ./build/tools/caffe train \ 5 | --solver=examples/mnist/mnist_autoencoder_solver_nesterov.prototxt $@ 6 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/examples/siamese/train_mnist_siamese.sh: 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/py-faster-rcnn/caffe-fast-rcnn/tools/test_net.cpp: -------------------------------------------------------------------------------- 1 | #include "caffe/caffe.hpp" 2 | 3 | int main(int argc, char** argv) { 4 | LOG(FATAL) << "Deprecated. Use caffe test --model=... " 5 | "--weights=... instead."; 6 | return 0; 7 | } 8 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/examples/cifar10/train_full_sigmoid_bn.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | TOOLS=./build/tools 5 | 6 | $TOOLS/caffe train \ 7 | --solver=examples/cifar10/cifar10_full_sigmoid_solver_bn.prototxt $@ 8 | 9 | -------------------------------------------------------------------------------- /dependencies/meta/example/CMakeLists.txt: -------------------------------------------------------------------------------- 1 | add_executable(tutorial_snippets tutorial_snippets.cpp) 2 | add_test(example.tutorial_snippets, tutorial_snippets) 3 | 4 | add_executable(tuple_cat tuple_cat.cpp) 5 | add_test(example.tuple_cat, tuple_cat) 6 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/src/gtest/CMakeLists.txt: -------------------------------------------------------------------------------- 1 | add_library(gtest STATIC EXCLUDE_FROM_ALL gtest.h gtest-all.cpp) 2 | caffe_default_properties(gtest) 3 | 4 | #add_library(gtest_main gtest_main.cc) 5 | #target_link_libraries(gtest_main gtest) 6 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/src/caffe/layers/parameter_layer.cpp: -------------------------------------------------------------------------------- 1 | #include "caffe/layers/parameter_layer.hpp" 2 | 3 | namespace caffe { 4 | 5 | INSTANTIATE_CLASS(ParameterLayer); 6 | REGISTER_LAYER_CLASS(Parameter); 7 | 8 | } // namespace caffe 9 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/tools/device_query.cpp: -------------------------------------------------------------------------------- 1 | #include "caffe/common.hpp" 2 | 3 | int main(int argc, char** argv) { 4 | LOG(FATAL) << "Deprecated. Use caffe device_query " 5 | "[--device_id=0] instead."; 6 | return 0; 7 | } 8 | -------------------------------------------------------------------------------- /dependencies/pugixml/docs/samples/character.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/matlab/+caffe/reset_all.m: -------------------------------------------------------------------------------- 1 | function reset_all() 2 | % reset_all() 3 | % clear all solvers and stand-alone nets and reset Caffe to initial status 4 | 5 | caffe_('reset'); 6 | is_valid_handle('get_new_init_key'); 7 | 8 | end 9 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/tools/finetune_net.cpp: -------------------------------------------------------------------------------- 1 | #include "caffe/caffe.hpp" 2 | 3 | int main(int argc, char** argv) { 4 | LOG(FATAL) << "Deprecated. Use caffe train --solver=... " 5 | "[--weights=...] instead."; 6 | return 0; 7 | } 8 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/tools/train_net.cpp: -------------------------------------------------------------------------------- 1 | #include "caffe/caffe.hpp" 2 | 3 | int main(int argc, char** argv) { 4 | LOG(FATAL) << "Deprecated. Use caffe train --solver=... " 5 | "[--snapshot=...] instead."; 6 | return 0; 7 | } 8 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/tsukuba_cam.yaml: -------------------------------------------------------------------------------- 1 | %YAML:1.0 2 | 3 | image_width: 640 4 | image_height: 480 5 | 6 | camera_matrix: !!opencv-matrix 7 | rows: 3 8 | cols: 3 9 | dt: d 10 | data: [ 615, 0, 320, 0, 615, 240, 0, 0, 1] 11 | 12 | baseline: 0.1 13 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/fantasy_cam.yaml: -------------------------------------------------------------------------------- 1 | %YAML:1.0 2 | 3 | image_width: 1000 4 | image_height: 1000 5 | 6 | camera_matrix: !!opencv-matrix 7 | rows: 3 8 | cols: 3 9 | dt: d 10 | data: [ 1000, 0, 500, 0, 1000, 500, 0, 0, 1 ] 11 | 12 | baseline: 1 13 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/INSTALL.md: -------------------------------------------------------------------------------- 1 | # Installation 2 | 3 | See http://caffe.berkeleyvision.org/installation.html for the latest 4 | installation instructions. 5 | 6 | Check the users group in case you need help: 7 | https://groups.google.com/forum/#!forum/caffe-users 8 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/tools/net_speed_benchmark.cpp: -------------------------------------------------------------------------------- 1 | #include "caffe/caffe.hpp" 2 | 3 | int main(int argc, char** argv) { 4 | LOG(FATAL) << "Deprecated. Use caffe time --model=... " 5 | "[--iterations=50] [--gpu] [--device_id=0]"; 6 | return 0; 7 | } 8 | -------------------------------------------------------------------------------- /dependencies/pugixml/docs/samples/transitions.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | -------------------------------------------------------------------------------- /ros/sptam/sptam_plugin.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | S-PTAM nodelet. 6 | 7 | 8 | 9 | 10 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/allocator.hpp: -------------------------------------------------------------------------------- 1 | #ifndef HEADER_TEST_ALLOCATOR_HPP 2 | #define HEADER_TEST_ALLOCATOR_HPP 3 | 4 | #include 5 | 6 | void* memory_allocate(size_t size); 7 | size_t memory_size(void* ptr); 8 | void memory_deallocate(void* ptr); 9 | 10 | #endif 11 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/examples/imagenet/resume_training.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | ./build/tools/caffe train \ 5 | --solver=models/bvlc_reference_caffenet/solver.prototxt \ 6 | --snapshot=models/bvlc_reference_caffenet/caffenet_train_10000.solverstate.h5 \ 7 | $@ 8 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/README.md: -------------------------------------------------------------------------------- 1 | # Caffe Documentation 2 | 3 | To generate the documentation, run `$CAFFE_ROOT/scripts/build_docs.sh`. 4 | 5 | To push your changes to the documentation to the gh-pages branch of your or the BVLC repo, run `$CAFFE_ROOT/scripts/deploy_docs.sh `. 6 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/scripts/travis/configure.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | # configure the project 3 | 4 | BASEDIR=$(dirname $0) 5 | source $BASEDIR/defaults.sh 6 | 7 | if ! $WITH_CMAKE ; then 8 | source $BASEDIR/configure-make.sh 9 | else 10 | source $BASEDIR/configure-cmake.sh 11 | fi 12 | -------------------------------------------------------------------------------- /py-faster-rcnn/lib/utils/__init__.py: -------------------------------------------------------------------------------- 1 | # -------------------------------------------------------- 2 | # Fast R-CNN 3 | # Copyright (c) 2015 Microsoft 4 | # Licensed under The MIT License [see LICENSE for details] 5 | # Written by Ross Girshick 6 | # -------------------------------------------------------- 7 | -------------------------------------------------------------------------------- /py-faster-rcnn/lib/datasets/__init__.py: -------------------------------------------------------------------------------- 1 | # -------------------------------------------------------- 2 | # Fast R-CNN 3 | # Copyright (c) 2015 Microsoft 4 | # Licensed under The MIT License [see LICENSE for details] 5 | # Written by Ross Girshick 6 | # -------------------------------------------------------- 7 | -------------------------------------------------------------------------------- /py-faster-rcnn/lib/fast_rcnn/__init__.py: -------------------------------------------------------------------------------- 1 | # -------------------------------------------------------- 2 | # Fast R-CNN 3 | # Copyright (c) 2015 Microsoft 4 | # Licensed under The MIT License [see LICENSE for details] 5 | # Written by Ross Girshick 6 | # -------------------------------------------------------- 7 | -------------------------------------------------------------------------------- /py-faster-rcnn/lib/roi_data_layer/__init__.py: -------------------------------------------------------------------------------- 1 | # -------------------------------------------------------- 2 | # Fast R-CNN 3 | # Copyright (c) 2015 Microsoft 4 | # Licensed under The MIT License [see LICENSE for details] 5 | # Written by Ross Girshick 6 | # -------------------------------------------------------- 7 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/scripts/travis/defaults.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | # set default environment variables 3 | 4 | set -e 5 | 6 | WITH_CMAKE=${WITH_CMAKE:-false} 7 | WITH_PYTHON3=${WITH_PYTHON3:-false} 8 | WITH_IO=${WITH_IO:-true} 9 | WITH_CUDA=${WITH_CUDA:-false} 10 | WITH_CUDNN=${WITH_CUDNN:-false} 11 | -------------------------------------------------------------------------------- /py-faster-rcnn/lib/rpn/__init__.py: -------------------------------------------------------------------------------- 1 | # -------------------------------------------------------- 2 | # Fast R-CNN 3 | # Copyright (c) 2015 Microsoft 4 | # Licensed under The MIT License [see LICENSE for details] 5 | # Written by Ross Girshick and Sean Bell 6 | # -------------------------------------------------------- 7 | -------------------------------------------------------------------------------- /py-faster-rcnn/cfgs/faster_rcnn_end2end.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: faster_rcnn_end2end 2 | TRAIN: 3 | HAS_RPN: True 4 | IMS_PER_BATCH: 1 5 | BBOX_NORMALIZE_TARGETS_PRECOMPUTED: True 6 | RPN_POSITIVE_OVERLAP: 0.7 7 | RPN_BATCHSIZE: 256 8 | PROPOSAL_METHOD: gt 9 | BG_THRESH_LO: 0.0 10 | TEST: 11 | HAS_RPN: True 12 | -------------------------------------------------------------------------------- /py-faster-rcnn/cfgs/faster_rcnn_endmod.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: faster_rcnn_end2end 2 | TRAIN: 3 | HAS_RPN: True 4 | IMS_PER_BATCH: 1 5 | BBOX_NORMALIZE_TARGETS_PRECOMPUTED: True 6 | RPN_POSITIVE_OVERLAP: 0.7 7 | RPN_BATCHSIZE: 256 8 | PROPOSAL_METHOD: gt 9 | BG_THRESH_LO: 0.0 10 | TEST: 11 | HAS_RPN: True 12 | -------------------------------------------------------------------------------- /ros/sptam/Doxyfile: -------------------------------------------------------------------------------- 1 | PROJECT_NAME="SPTAM" 2 | OUTPUT_DIRECTORY=doc 3 | EXTRACT_ALL=YES 4 | EXTRACT_PRIVATE=YES 5 | INPUT=src README.md 6 | RECURSIVE=YES 7 | GENERATE_LATEX=NO 8 | USE_MDFILE_AS_MAINPAGE=README.md 9 | HAVE_DOT=YES 10 | CALL_GRAPH=YES 11 | INLINE_SOURCES=YES 12 | REFERENCED_BY_RELATION=YES 13 | REFERENCES_RELATION=YES 14 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/kitti_cam_03.yaml: -------------------------------------------------------------------------------- 1 | %YAML:1.0 2 | 3 | image_width: 1242 4 | image_height: 375 5 | 6 | camera_matrix: !!opencv-matrix 7 | rows: 3 8 | cols: 3 9 | dt: d 10 | data: [ 7.215377000000e+02, 0, 6.095593000000e+02, 0, 7.215377000000e+02, 1.728540000000e+02, 0, 0, 1 ] 11 | 12 | baseline: 5.3715058825e-01 13 | -------------------------------------------------------------------------------- /dependencies/pugixml/docs/samples/tree.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | some text 5 | 6 | some more text 7 | 8 | 9 | 10 | 11 | 12 | 13 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/examples/finetune_flickr_style/style_names.txt: -------------------------------------------------------------------------------- 1 | Detailed 2 | Pastel 3 | Melancholy 4 | Noir 5 | HDR 6 | Vintage 7 | Long Exposure 8 | Horror 9 | Sunny 10 | Bright 11 | Hazy 12 | Bokeh 13 | Serene 14 | Texture 15 | Ethereal 16 | Macro 17 | Depth of Field 18 | Geometric Composition 19 | Minimal 20 | Romantic 21 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/scripts/travis/build.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | # build the project 3 | 4 | BASEDIR=$(dirname $0) 5 | source $BASEDIR/defaults.sh 6 | 7 | if ! $WITH_CMAKE ; then 8 | make --jobs $NUM_THREADS all test pycaffe warn 9 | else 10 | cd build 11 | make --jobs $NUM_THREADS all test.testbin 12 | fi 13 | make lint 14 | -------------------------------------------------------------------------------- /py-faster-rcnn/cfgs/faster_rcnn_oneh.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: faster_rcnn_end2end 2 | TRAIN: 3 | HAS_RPN: True 4 | IMS_PER_BATCH: 1 5 | BBOX_NORMALIZE_TARGETS_PRECOMPUTED: True 6 | RPN_POSITIVE_OVERLAP: 0.7 7 | RPN_BATCHSIZE: 256 8 | PROPOSAL_METHOD: gt 9 | BG_THRESH_LO: 0.0 10 | USE_FLIPPED: False 11 | TEST: 12 | HAS_RPN: True 13 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/kitti_cam_04_to_12.yaml: -------------------------------------------------------------------------------- 1 | %YAML:1.0 2 | 3 | image_width: 1226 4 | image_height: 370 5 | 6 | camera_matrix: !!opencv-matrix 7 | rows: 3 8 | cols: 3 9 | dt: d 10 | data: [ 7.070912000000e+02, 0, 6.018873000000e+02, 0, 7.070912000000e+02, 1.831104000000e+02, 0, 0, 1 ] 11 | 12 | baseline: 5.3715065326e-01 13 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/matlab/+caffe/set_device.m: -------------------------------------------------------------------------------- 1 | function set_device(device_id) 2 | % set_device(device_id) 3 | % set Caffe's GPU device ID 4 | 5 | CHECK(isscalar(device_id) && device_id >= 0, ... 6 | 'device_id must be non-negative integer'); 7 | device_id = double(device_id); 8 | 9 | caffe_('set_device', device_id); 10 | 11 | end 12 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/kitti_cam_00_to_02_13_to_21.yaml: -------------------------------------------------------------------------------- 1 | %YAML:1.0 2 | 3 | image_width: 1241 4 | image_height: 376 5 | 6 | camera_matrix: !!opencv-matrix 7 | rows: 3 8 | cols: 3 9 | dt: d 10 | data: [ 7.188560000000e+02, 0, 6.071928000000e+02, 0, 7.188560000000e+02, 1.852157000000e+02, 0, 0, 1 ] 11 | 12 | baseline: 5.3716571886e-01 13 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/scripts/travis/install-python-deps.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | # install extra Python dependencies 3 | # (must come after setup-venv) 4 | 5 | BASEDIR=$(dirname $0) 6 | source $BASEDIR/defaults.sh 7 | 8 | if ! $WITH_PYTHON3 ; then 9 | # Python2 10 | : 11 | else 12 | # Python3 13 | pip install --pre protobuf==3.0.0b3 14 | fi 15 | -------------------------------------------------------------------------------- /py-faster-rcnn/lib/datasets/VOCdevkit-matlab-wrapper/get_voc_opts.m: -------------------------------------------------------------------------------- 1 | function VOCopts = get_voc_opts(path) 2 | 3 | tmp = pwd; 4 | cd(path); 5 | try 6 | addpath('VOCcode'); 7 | VOCinit; 8 | catch 9 | rmpath('VOCcode'); 10 | cd(tmp); 11 | error(sprintf('VOCcode directory not found under %s', path)); 12 | end 13 | rmpath('VOCcode'); 14 | cd(tmp); 15 | -------------------------------------------------------------------------------- /py-faster-rcnn/lib/datasets/VOCdevkit-matlab-wrapper/xVOCap.m: -------------------------------------------------------------------------------- 1 | function ap = xVOCap(rec,prec) 2 | % From the PASCAL VOC 2011 devkit 3 | 4 | mrec=[0 ; rec ; 1]; 5 | mpre=[0 ; prec ; 0]; 6 | for i=numel(mpre)-1:-1:1 7 | mpre(i)=max(mpre(i),mpre(i+1)); 8 | end 9 | i=find(mrec(2:end)~=mrec(1:end-1))+1; 10 | ap=sum((mrec(i)-mrec(i-1)).*mpre(i)); 11 | -------------------------------------------------------------------------------- /ros/sptam/src/sptam/ObjectEdge.cpp: -------------------------------------------------------------------------------- 1 | #include "ObjectEdge.hpp" 2 | 3 | ObjectEdge::ObjectEdge(const sptam::Map::SharedKeyFrame& kf, const Eigen::Vector3d& T, const Eigen::Matrix3d& R, const Eigen::Vector3d& D,const Eigen::Vector3d& world_normal) : kf_(kf), 4 | T_(T), 5 | R_(R), 6 | D_(D), 7 | world_normal_(world_normal) 8 | { 9 | } 10 | 11 | 12 | 13 | -------------------------------------------------------------------------------- /ros/sptam/LICENSE.txt: -------------------------------------------------------------------------------- 1 | S-PTAM is released under a GPLv3 license (see COPYING.txt). 2 | 3 | For a closed-source version of S-PTAM for commercial purposes, please contact the authors. 4 | 5 | If you use S-PTAM in an academic work, please cite the most relevant publication associated by visiting: 6 | http://robotica.dc.uba.ar/index.php/publicaciones/?lang=en 7 | 8 | 9 | 10 | 11 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/python/requirements.txt: -------------------------------------------------------------------------------- 1 | Cython>=0.19.2 2 | numpy>=1.7.1 3 | scipy>=0.13.2 4 | scikit-image>=0.9.3 5 | matplotlib>=1.3.1 6 | ipython>=3.0.0 7 | h5py>=2.2.0 8 | leveldb>=0.191 9 | networkx>=1.8.1 10 | nose>=1.3.0 11 | pandas>=0.12.0 12 | python-dateutil>=1.4,<2 13 | protobuf>=2.5.0 14 | python-gflags>=2.0 15 | pyyaml>=3.10 16 | Pillow>=2.3.0 17 | six>=1.1.0 -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/matlab/+caffe/get_solver.m: -------------------------------------------------------------------------------- 1 | function solver = get_solver(solver_file) 2 | % solver = get_solver(solver_file) 3 | % Construct a Solver object from solver_file 4 | 5 | CHECK(ischar(solver_file), 'solver_file must be a string'); 6 | CHECK_FILE_EXIST(solver_file); 7 | pSolver = caffe_('get_solver', solver_file); 8 | solver = caffe.Solver(pSolver); 9 | 10 | end 11 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/scripts/travis/test.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | # test the project 3 | 4 | BASEDIR=$(dirname $0) 5 | source $BASEDIR/defaults.sh 6 | 7 | if $WITH_CUDA ; then 8 | echo "Skipping tests for CUDA build" 9 | exit 0 10 | fi 11 | 12 | if ! $WITH_CMAKE ; then 13 | make runtest 14 | make pytest 15 | else 16 | cd build 17 | make runtest 18 | make pytest 19 | fi 20 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/fuzz_parse.cpp: -------------------------------------------------------------------------------- 1 | #include "../src/pugixml.hpp" 2 | 3 | #include 4 | 5 | extern "C" int LLVMFuzzerTestOneInput(const uint8_t *Data, size_t Size) 6 | { 7 | pugi::xml_document doc; 8 | 9 | doc.load_buffer(Data, Size); 10 | doc.load_buffer(Data, Size, pugi::parse_minimal); 11 | doc.load_buffer(Data, Size, pugi::parse_full); 12 | 13 | return 0; 14 | } 15 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/examples/imagenet/make_imagenet_mean.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | # Compute the mean image from the imagenet training lmdb 3 | # N.B. this is available in data/ilsvrc12 4 | 5 | EXAMPLE=examples/imagenet 6 | DATA=data/ilsvrc12 7 | TOOLS=build/tools 8 | 9 | $TOOLS/compute_image_mean $EXAMPLE/ilsvrc12_train_lmdb \ 10 | $DATA/imagenet_mean.binaryproto 11 | 12 | echo "Done." 13 | -------------------------------------------------------------------------------- /py-faster-rcnn/cfgs/faster_rcnn_coco.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: faster_rcnn_end2end 2 | TRAIN: 3 | HAS_RPN: True 4 | IMS_PER_BATCH: 1 5 | BBOX_NORMALIZE_TARGETS_PRECOMPUTED: True 6 | RPN_POSITIVE_OVERLAP: 0.7 7 | RPN_BATCHSIZE: 256 8 | PROPOSAL_METHOD: gt 9 | BG_THRESH_LO: 0.0 10 | HAS_POSE: True 11 | USE_FLIPPED: False 12 | ASPECT_GROUPING: False 13 | SNAPSHOT_ITERS: 500 14 | TEST: 15 | HAS_RPN: True 16 | -------------------------------------------------------------------------------- /py-faster-rcnn/cfgs/faster_rcnn_posenet.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: faster_rcnn_end2end 2 | TRAIN: 3 | HAS_RPN: True 4 | IMS_PER_BATCH: 1 5 | BBOX_NORMALIZE_TARGETS_PRECOMPUTED: True 6 | RPN_POSITIVE_OVERLAP: 0.7 7 | RPN_BATCHSIZE: 256 8 | PROPOSAL_METHOD: gt 9 | BG_THRESH_LO: 0.0 10 | HAS_POSE: True 11 | USE_FLIPPED: False 12 | SNAPSHOT_ITERS: 10000 13 | 14 | TEST: 15 | HAS_RPN: True 16 | HAS_POSE: True 17 | 18 | 19 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/src/caffe/layers/neuron_layer.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | 3 | #include "caffe/layers/neuron_layer.hpp" 4 | 5 | namespace caffe { 6 | 7 | template 8 | void NeuronLayer::Reshape(const vector*>& bottom, 9 | const vector*>& top) { 10 | top[0]->ReshapeLike(*bottom[0]); 11 | } 12 | 13 | INSTANTIATE_CLASS(NeuronLayer); 14 | 15 | } // namespace caffe 16 | -------------------------------------------------------------------------------- /ros/sptam/src/sptam/match_to_points.hpp: -------------------------------------------------------------------------------- 1 | #include 2 | #include "Match.hpp" 3 | 4 | // Used in MapMaker.cpp 5 | std::list matchToPoints( 6 | const StereoFrame& frame, 7 | Iterable&& mapPoints, 8 | const cv::Ptr descriptorMatcher, 9 | const size_t matchingNeighborhoodThreshold, 10 | const double matchingDistanceThreshold, 11 | const Measurement::Source source 12 | ); 13 | -------------------------------------------------------------------------------- /dependencies/pugixml/docs/samples/load_file.cpp: -------------------------------------------------------------------------------- 1 | #include "pugixml.hpp" 2 | 3 | #include 4 | 5 | int main() 6 | { 7 | // tag::code[] 8 | pugi::xml_document doc; 9 | 10 | pugi::xml_parse_result result = doc.load_file("tree.xml"); 11 | 12 | std::cout << "Load result: " << result.description() << ", mesh name: " << doc.child("mesh").attribute("name").value() << std::endl; 13 | // end::code[] 14 | } 15 | 16 | // vim:et 17 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/data_fuzz_parse/doctype.xml: -------------------------------------------------------------------------------- 1 | ]> ]]> ]> ]> -------------------------------------------------------------------------------- /dependencies/pugixml/docs/samples/save_file.cpp: -------------------------------------------------------------------------------- 1 | #include "pugixml.hpp" 2 | 3 | #include 4 | 5 | int main() 6 | { 7 | // get a test document 8 | pugi::xml_document doc; 9 | doc.load_string("hey"); 10 | 11 | // tag::code[] 12 | // save document to file 13 | std::cout << "Saving result: " << doc.save_file("save_file_output.xml") << std::endl; 14 | // end::code[] 15 | } 16 | 17 | // vim:et 18 | -------------------------------------------------------------------------------- /dependencies/pugixml/docs/samples/save_stream.cpp: -------------------------------------------------------------------------------- 1 | #include "pugixml.hpp" 2 | 3 | #include 4 | 5 | int main() 6 | { 7 | // get a test document 8 | pugi::xml_document doc; 9 | doc.load_string("hey"); 10 | 11 | // tag::code[] 12 | // save document to standard output 13 | std::cout << "Document:\n"; 14 | doc.save(std::cout); 15 | // end::code[] 16 | } 17 | 18 | // vim:et 19 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/examples/cifar10/train_quick.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | TOOLS=./build/tools 5 | 6 | $TOOLS/caffe train \ 7 | --solver=examples/cifar10/cifar10_quick_solver.prototxt $@ 8 | 9 | # reduce learning rate by factor of 10 after 8 epochs 10 | $TOOLS/caffe train \ 11 | --solver=examples/cifar10/cifar10_quick_solver_lr1.prototxt \ 12 | --snapshot=examples/cifar10/cifar10_quick_iter_4000.solverstate.h5 $@ 13 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/python/caffe/test/test_layer_type_list.py: -------------------------------------------------------------------------------- 1 | import unittest 2 | 3 | import caffe 4 | 5 | class TestLayerTypeList(unittest.TestCase): 6 | 7 | def test_standard_types(self): 8 | #removing 'Data' from list 9 | for type_name in ['Data', 'Convolution', 'InnerProduct']: 10 | self.assertIn(type_name, caffe.layer_type_list(), 11 | '%s not in layer_type_list()' % type_name) 12 | -------------------------------------------------------------------------------- /dependencies/pugixml/scripts/pugixml.pc.in: -------------------------------------------------------------------------------- 1 | prefix=@CMAKE_INSTALL_PREFIX@ 2 | exec_prefix=${prefix} 3 | includedir=${prefix}/include/pugixml-@PUGIXML_VERSION_STRING@ 4 | libdir=${exec_prefix}/lib/pugixml-@PUGIXML_VERSION_STRING@ 5 | 6 | Name: pugixml 7 | Description: Light-weight, simple and fast XML parser for C++ with XPath support. 8 | URL: http://pugixml.org/ 9 | Version: @PUGIXML_VERSION_STRING@ 10 | Cflags: -I${includedir} 11 | Libs: -L${libdir} -lpugixml -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/detect_cuda_archs.cu: -------------------------------------------------------------------------------- 1 | #include 2 | int main() 3 | { 4 | int count = 0; 5 | if (cudaSuccess != cudaGetDeviceCount(&count)) return -1; 6 | if (count == 0) return -1; 7 | for (int device = 0; device < count; ++device) 8 | { 9 | cudaDeviceProp prop; 10 | if (cudaSuccess == cudaGetDeviceProperties(&prop, device)) 11 | std::printf("%d.%d ", prop.major, prop.minor); 12 | } 13 | return 0; 14 | } 15 | -------------------------------------------------------------------------------- /ros/sptam/launch/msf.launch: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/cmake/detect_cuda_archs.cu: -------------------------------------------------------------------------------- 1 | #include 2 | int main() 3 | { 4 | int count = 0; 5 | if (cudaSuccess != cudaGetDeviceCount(&count)) return -1; 6 | if (count == 0) return -1; 7 | for (int device = 0; device < count; ++device) 8 | { 9 | cudaDeviceProp prop; 10 | if (cudaSuccess == cudaGetDeviceProperties(&prop, device)) 11 | std::printf("%d.%d ", prop.major, prop.minor); 12 | } 13 | return 0; 14 | } 15 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/examples/finetune_pascal_detection/pascal_finetune_solver.prototxt: -------------------------------------------------------------------------------- 1 | net: "examples/finetune_pascal_detection/pascal_finetune_trainval_test.prototxt" 2 | test_iter: 100 3 | test_interval: 1000 4 | base_lr: 0.001 5 | lr_policy: "step" 6 | gamma: 0.1 7 | stepsize: 20000 8 | display: 20 9 | max_iter: 100000 10 | momentum: 0.9 11 | weight_decay: 0.0005 12 | snapshot: 10000 13 | snapshot_prefix: "examples/finetune_pascal_detection/pascal_det_finetune" 14 | -------------------------------------------------------------------------------- /ros/sptam/plotters/utils/colors.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | 3 | """ 4 | Colores facheros para usar en los plots 5 | """ 6 | 7 | colors = [ 8 | (0, 0.4470, 0.7410), 9 | (0.8500, 0.3250, 0.0980), 10 | (0.9290, 0.6940, 0.1250), 11 | (0.4940, 0.1840, 0.5560), 12 | (0.4660, 0.6740, 0.1880), 13 | (0.3010, 0.7450, 0.9330), 14 | (0.6350, 0.0780, 0.1840), 15 | (0.6290, 0.4940, 0.1250), 16 | (0.4660, 0.6740, 0.5880) 17 | ] 18 | 19 | ground_truth_color = (1, 0, 0) 20 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/cmake/Templates/CaffeConfigVersion.cmake.in: -------------------------------------------------------------------------------- 1 | set(PACKAGE_VERSION "@Caffe_VERSION@") 2 | 3 | # Check whether the requested PACKAGE_FIND_VERSION is compatible 4 | if("${PACKAGE_VERSION}" VERSION_LESS "${PACKAGE_FIND_VERSION}") 5 | set(PACKAGE_VERSION_COMPATIBLE FALSE) 6 | else() 7 | set(PACKAGE_VERSION_COMPATIBLE TRUE) 8 | if ("${PACKAGE_VERSION}" VERSION_EQUAL "${PACKAGE_FIND_VERSION}") 9 | set(PACKAGE_VERSION_EXACT TRUE) 10 | endif() 11 | endif() 12 | -------------------------------------------------------------------------------- /ros/sptam/plotters/parsers/mit_gt.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | import numpy as np 3 | import tf.transformations 4 | 5 | from utils import mathHelpers as mh 6 | 7 | class MIT_GT: 8 | 9 | def __init__(self, filename): 10 | 11 | raise RuntimeError("not implemented...") 12 | 13 | def align(self, sptam_frame_ids, sptam_timestamps, sptam_poses, interpolate=False): 14 | 15 | raise RuntimeError("not implemented...") 16 | 17 | def load( filename ): 18 | return MIT_GT( filename ) 19 | -------------------------------------------------------------------------------- /models_trained/coco/VGG16/fast_rcnn/solver.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/coco/VGG16/fast_rcnn/train.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 200000 6 | display: 20 7 | average_loss: 100 8 | # iter_size: 1 9 | momentum: 0.9 10 | weight_decay: 0.0005 11 | # We disable standard caffe solver snapshotting and implement our own snapshot 12 | # function 13 | snapshot: 0 14 | # We still use the snapshot prefix, though 15 | snapshot_prefix: "vgg16_fast_rcnn" 16 | #debug_info: true 17 | -------------------------------------------------------------------------------- /models_trained/pascal_voc/ZF/faster_rcnn_alt_opt/stage1_rpn_solver60k80k.pt: -------------------------------------------------------------------------------- 1 | train_net: "models/pascal_voc/ZF/faster_rcnn_alt_opt/stage1_rpn_train.pt" 2 | 3 | base_lr: 0.001 4 | lr_policy: "step" 5 | gamma: 0.1 6 | stepsize: 60000 7 | display: 20 8 | average_loss: 100 9 | momentum: 0.9 10 | weight_decay: 0.0005 11 | 12 | # We disable standard caffe solver snapshotting and implement our own snapshot 13 | # function 14 | snapshot: 0 15 | # We still use the snapshot prefix, though 16 | snapshot_prefix: "zf_rpn" 17 | -------------------------------------------------------------------------------- /models_trained/pascal_voc/ZF/faster_rcnn_alt_opt/stage2_rpn_solver60k80k.pt: -------------------------------------------------------------------------------- 1 | train_net: "models/pascal_voc/ZF/faster_rcnn_alt_opt/stage2_rpn_train.pt" 2 | 3 | base_lr: 0.001 4 | lr_policy: "step" 5 | gamma: 0.1 6 | stepsize: 60000 7 | display: 20 8 | average_loss: 100 9 | momentum: 0.9 10 | weight_decay: 0.0005 11 | 12 | # We disable standard caffe solver snapshotting and implement our own snapshot 13 | # function 14 | snapshot: 0 15 | # We still use the snapshot prefix, though 16 | snapshot_prefix: "zf_rpn" 17 | -------------------------------------------------------------------------------- /models_trained/coco/VGG16/faster_rcnn_end2end/solver.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/coco/VGG16/faster_rcnn_end2end/train.onlycls.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 350000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "coco_15kr_250ks_" 15 | iter_size: 2 16 | -------------------------------------------------------------------------------- /models_trained/coco/VGG_CNN_M_1024/faster_rcnn_end2end/solver.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/coco/VGG_CNN_M_1024/faster_rcnn_end2end/train.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 350000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg_cnn_m_1024_faster_rcnn" 15 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/fuzz_setup.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | sudo apt-get --yes install subversion screen gcc g++ cmake ninja-build golang autoconf libtool apache2 python-dev pkg-config zlib1g-dev libgcrypt11-dev 4 | 5 | mkdir -p clang 6 | cd clang 7 | git clone https://chromium.googlesource.com/chromium/src/tools/clang 8 | cd .. 9 | clang/clang/scripts/update.py 10 | sudo cp -rf third_party/llvm-build/Release+Asserts/lib/* /usr/local/lib/ 11 | sudo cp -rf third_party/llvm-build/Release+Asserts/bin/* /usr/local/bin 12 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/test_header_only_1.cpp: -------------------------------------------------------------------------------- 1 | #define PUGIXML_HEADER_ONLY 2 | #define pugi pugih 3 | 4 | #include "common.hpp" 5 | 6 | // Check header guards 7 | #include "../src/pugixml.hpp" 8 | #include "../src/pugixml.hpp" 9 | 10 | TEST(header_only_1) 11 | { 12 | xml_document doc; 13 | CHECK(doc.load_string(STR(""))); 14 | CHECK_STRING(doc.first_child().name(), STR("node")); 15 | 16 | #ifndef PUGIXML_NO_XPATH 17 | CHECK(doc.first_child() == doc.select_node(STR("//*")).node()); 18 | #endif 19 | } 20 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/test_header_only_2.cpp: -------------------------------------------------------------------------------- 1 | #define PUGIXML_HEADER_ONLY 2 | #define pugi pugih 3 | 4 | #include "common.hpp" 5 | 6 | // Check header guards 7 | #include "../src/pugixml.hpp" 8 | #include "../src/pugixml.hpp" 9 | 10 | TEST(header_only_2) 11 | { 12 | xml_document doc; 13 | CHECK(doc.load_string(STR(""))); 14 | CHECK_STRING(doc.first_child().name(), STR("node")); 15 | 16 | #ifndef PUGIXML_NO_XPATH 17 | CHECK(doc.first_child() == doc.select_node(STR("//*")).node()); 18 | #endif 19 | } 20 | -------------------------------------------------------------------------------- /models_trained/coco/VGG_CNN_M_1024/fast_rcnn/solver.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/coco/VGG_CNN_M_1024/fast_rcnn/train.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 200000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg_cnn_m_1024_fast_rcnn" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /models_trained/pascal_voc/VGG16/fast_rcnn/solver.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/pascal_voc/VGG16/fast_rcnn/train.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | # iter_size: 1 9 | momentum: 0.9 10 | weight_decay: 0.0005 11 | # We disable standard caffe solver snapshotting and implement our own snapshot 12 | # function 13 | snapshot: 0 14 | # We still use the snapshot prefix, though 15 | snapshot_prefix: "vgg16_fast_rcnn" 16 | #debug_info: true 17 | -------------------------------------------------------------------------------- /models_trained/pascal_voc/VGG16/faster_rcnn_alt_opt/stage1_rpn_solver60k80k.pt: -------------------------------------------------------------------------------- 1 | train_net: "models/pascal_voc/VGG16/faster_rcnn_alt_opt/stage1_rpn_train.pt" 2 | 3 | base_lr: 0.001 4 | lr_policy: "step" 5 | gamma: 0.1 6 | stepsize: 60000 7 | display: 20 8 | average_loss: 100 9 | momentum: 0.9 10 | weight_decay: 0.0005 11 | 12 | # We disable standard caffe solver snapshotting and implement our own snapshot 13 | # function 14 | snapshot: 0 15 | # We still use the snapshot prefix, though 16 | snapshot_prefix: "vgg16_rpn" 17 | -------------------------------------------------------------------------------- /models_trained/pascal_voc/VGG16/faster_rcnn_alt_opt/stage2_rpn_solver60k80k.pt: -------------------------------------------------------------------------------- 1 | train_net: "models/pascal_voc/VGG16/faster_rcnn_alt_opt/stage2_rpn_train.pt" 2 | 3 | base_lr: 0.001 4 | lr_policy: "step" 5 | gamma: 0.1 6 | stepsize: 60000 7 | display: 20 8 | average_loss: 100 9 | momentum: 0.9 10 | weight_decay: 0.0005 11 | 12 | # We disable standard caffe solver snapshotting and implement our own snapshot 13 | # function 14 | snapshot: 0 15 | # We still use the snapshot prefix, though 16 | snapshot_prefix: "vgg16_rpn" 17 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/data/mnist/get_mnist.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | # This scripts downloads the mnist data and unzips it. 3 | 4 | DIR="$( cd "$(dirname "$0")" ; pwd -P )" 5 | cd "$DIR" 6 | 7 | echo "Downloading..." 8 | 9 | for fname in train-images-idx3-ubyte train-labels-idx1-ubyte t10k-images-idx3-ubyte t10k-labels-idx1-ubyte 10 | do 11 | if [ ! -e $fname ]; then 12 | wget --no-check-certificate http://yann.lecun.com/exdb/mnist/${fname}.gz 13 | gunzip ${fname}.gz 14 | fi 15 | done 16 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/data/truncation.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | some text 7 | 8 | some more text 9 | 10 | 11 | <汉语 名字="name" 价值="value">世界有很多语言𤭢 12 | 13 | 14 | <氏名> 15 | <氏>山田 16 | <名>太郎 17 | 18 | 19 | -------------------------------------------------------------------------------- /models_trained/pascal_voc/ZF/fast_rcnn/solver.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/pascal_voc/ZF/fast_rcnn/train.prototxt" 2 | 3 | base_lr: 0.001 4 | lr_policy: "step" 5 | gamma: 0.1 6 | stepsize: 30000 7 | display: 20 8 | average_loss: 100 9 | momentum: 0.9 10 | weight_decay: 0.0005 11 | 12 | # We disable standard caffe solver snapshotting and implement our own snapshot 13 | # function 14 | snapshot: 0 15 | # We still use the snapshot prefix, though 16 | snapshot_prefix: "zf_fast_rcnn" 17 | #debug_info: true 18 | #iter_size: 2 19 | -------------------------------------------------------------------------------- /models_trained/pascal_voc/VGG_CNN_M_1024/fast_rcnn/solver.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/pascal_voc/VGG_CNN_M_1024/fast_rcnn/train.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg_cnn_m_1024_fast_rcnn" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /models_trained/pascal_voc/VGG_CNN_M_1024/faster_rcnn_end2end/solver.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/pascal_voc/VGG_CNN_M_1024/faster_rcnn_end2end/train.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 50000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg_cnn_m_1024_faster_rcnn" 15 | -------------------------------------------------------------------------------- /models_trained/pascal_voc/ZF/faster_rcnn_alt_opt/stage1_fast_rcnn_solver30k40k.pt: -------------------------------------------------------------------------------- 1 | train_net: "models/pascal_voc/ZF/faster_rcnn_alt_opt/stage1_fast_rcnn_train.pt" 2 | 3 | base_lr: 0.001 4 | lr_policy: "step" 5 | gamma: 0.1 6 | stepsize: 30000 7 | display: 20 8 | average_loss: 100 9 | momentum: 0.9 10 | weight_decay: 0.0005 11 | 12 | # We disable standard caffe solver snapshotting and implement our own snapshot 13 | # function 14 | snapshot: 0 15 | # We still use the snapshot prefix, though 16 | snapshot_prefix: "zf_fast_rcnn" 17 | -------------------------------------------------------------------------------- /models_trained/pascal_voc/ZF/faster_rcnn_alt_opt/stage2_fast_rcnn_solver30k40k.pt: -------------------------------------------------------------------------------- 1 | train_net: "models/pascal_voc/ZF/faster_rcnn_alt_opt/stage2_fast_rcnn_train.pt" 2 | 3 | base_lr: 0.001 4 | lr_policy: "step" 5 | gamma: 0.1 6 | stepsize: 30000 7 | display: 20 8 | average_loss: 100 9 | momentum: 0.9 10 | weight_decay: 0.0005 11 | 12 | # We disable standard caffe solver snapshotting and implement our own snapshot 13 | # function 14 | snapshot: 0 15 | # We still use the snapshot prefix, though 16 | snapshot_prefix: "zf_fast_rcnn" 17 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/matlab/+caffe/run_tests.m: -------------------------------------------------------------------------------- 1 | function results = run_tests() 2 | % results = run_tests() 3 | % run all tests in this caffe matlab wrapper package 4 | 5 | % use CPU for testing 6 | caffe.set_mode_cpu(); 7 | 8 | % reset caffe before testing 9 | caffe.reset_all(); 10 | 11 | % put all test cases here 12 | results = [... 13 | run(caffe.test.test_net) ... 14 | run(caffe.test.test_solver) ... 15 | run(caffe.test.test_io) ]; 16 | 17 | % reset caffe after testing 18 | caffe.reset_all(); 19 | 20 | end 21 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/scripts/travis/setup-venv.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | # setup a Python virtualenv 3 | # (must come after install-deps) 4 | 5 | BASEDIR=$(dirname $0) 6 | source $BASEDIR/defaults.sh 7 | 8 | VENV_DIR=${1:-~/venv} 9 | 10 | # setup our own virtualenv 11 | if $WITH_PYTHON3; then 12 | PYTHON_EXE='/usr/bin/python3' 13 | else 14 | PYTHON_EXE='/usr/bin/python2' 15 | fi 16 | 17 | # use --system-site-packages so that Python will use deb packages 18 | virtualenv $VENV_DIR -p $PYTHON_EXE --system-site-packages 19 | -------------------------------------------------------------------------------- /models_trained/pascal_voc/VGG16/faster_rcnn_alt_opt/stage1_fast_rcnn_solver30k40k.pt: -------------------------------------------------------------------------------- 1 | train_net: "models/pascal_voc/VGG16/faster_rcnn_alt_opt/stage1_fast_rcnn_train.pt" 2 | 3 | base_lr: 0.001 4 | lr_policy: "step" 5 | gamma: 0.1 6 | stepsize: 30000 7 | display: 20 8 | average_loss: 100 9 | momentum: 0.9 10 | weight_decay: 0.0005 11 | 12 | # We disable standard caffe solver snapshotting and implement our own snapshot 13 | # function 14 | snapshot: 0 15 | # We still use the snapshot prefix, though 16 | snapshot_prefix: "vgg16_fast_rcnn" 17 | -------------------------------------------------------------------------------- /models_trained/pascal_voc/VGG16/faster_rcnn_alt_opt/stage2_fast_rcnn_solver30k40k.pt: -------------------------------------------------------------------------------- 1 | train_net: "models/pascal_voc/VGG16/faster_rcnn_alt_opt/stage2_fast_rcnn_train.pt" 2 | 3 | base_lr: 0.001 4 | lr_policy: "step" 5 | gamma: 0.1 6 | stepsize: 30000 7 | display: 20 8 | average_loss: 100 9 | momentum: 0.9 10 | weight_decay: 0.0005 11 | 12 | # We disable standard caffe solver snapshotting and implement our own snapshot 13 | # function 14 | snapshot: 0 15 | # We still use the snapshot prefix, though 16 | snapshot_prefix: "vgg16_fast_rcnn" 17 | -------------------------------------------------------------------------------- /models_trained/pascal_voc/VGG16/faster_rcnn_end2end/solver.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/pascal_voc/VGG16/faster_rcnn_end2end/train.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 50000 6 | display: 20 7 | average_loss: 100 8 | # iter_size: 1 9 | momentum: 0.9 10 | weight_decay: 0.0005 11 | # We disable standard caffe solver snapshotting and implement our own snapshot 12 | # function 13 | snapshot: 0 14 | # We still use the snapshot prefix, though 15 | snapshot_prefix: "vgg16_faster_rcnn" 16 | iter_size: 2 17 | -------------------------------------------------------------------------------- /models_trained/modelnet/VGG16/faster_rcnn_end2end/solver.working.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/modelnet/VGG16/faster_rcnn_end2end/train.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 50000 6 | display: 20 7 | average_loss: 100 8 | # iter_size: 1 9 | momentum: 0.9 10 | weight_decay: 0.0005 11 | # We disable standard caffe solver snapshotting and implement our own snapshot 12 | # function 13 | snapshot: 0 14 | # We still use the snapshot prefix, though 15 | snapshot_prefix: "vgg16_faster_rcnn" 16 | iter_size: 2 17 | -------------------------------------------------------------------------------- /models_trained/modeloneh/VGG16/faster_rcnn_end2end/solver.working.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/modelnet/VGG16/faster_rcnn_end2end/train.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 50000 6 | display: 20 7 | average_loss: 100 8 | # iter_size: 1 9 | momentum: 0.9 10 | weight_decay: 0.0005 11 | # We disable standard caffe solver snapshotting and implement our own snapshot 12 | # function 13 | snapshot: 0 14 | # We still use the snapshot prefix, though 15 | snapshot_prefix: "vgg16_faster_rcnn" 16 | iter_size: 2 17 | -------------------------------------------------------------------------------- /models_trained/modelpose/VGG16/faster_rcnn_end2end/solver.working.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/modelnet/VGG16/faster_rcnn_end2end/train.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 50000 6 | display: 20 7 | average_loss: 100 8 | # iter_size: 1 9 | momentum: 0.9 10 | weight_decay: 0.0005 11 | # We disable standard caffe solver snapshotting and implement our own snapshot 12 | # function 13 | snapshot: 0 14 | # We still use the snapshot prefix, though 15 | snapshot_prefix: "vgg16_faster_rcnn" 16 | iter_size: 2 17 | -------------------------------------------------------------------------------- /models_trained/pascal_voc/VGG_CNN_M_1024/faster_rcnn_alt_opt/stage1_rpn_solver60k80k.pt: -------------------------------------------------------------------------------- 1 | train_net: "models/pascal_voc/VGG_CNN_M_1024/faster_rcnn_alt_opt/stage1_rpn_train.pt" 2 | 3 | base_lr: 0.001 4 | lr_policy: "step" 5 | gamma: 0.1 6 | stepsize: 60000 7 | display: 20 8 | average_loss: 100 9 | momentum: 0.9 10 | weight_decay: 0.0005 11 | 12 | # We disable standard caffe solver snapshotting and implement our own snapshot 13 | # function 14 | snapshot: 0 15 | # We still use the snapshot prefix, though 16 | snapshot_prefix: "vgg_cnn_m_1024_rpn" 17 | -------------------------------------------------------------------------------- /models_trained/pascal_voc/VGG_CNN_M_1024/faster_rcnn_alt_opt/stage2_rpn_solver60k80k.pt: -------------------------------------------------------------------------------- 1 | train_net: "models/pascal_voc/VGG_CNN_M_1024/faster_rcnn_alt_opt/stage2_rpn_train.pt" 2 | 3 | base_lr: 0.001 4 | lr_policy: "step" 5 | gamma: 0.1 6 | stepsize: 60000 7 | display: 20 8 | average_loss: 100 9 | momentum: 0.9 10 | weight_decay: 0.0005 11 | 12 | # We disable standard caffe solver snapshotting and implement our own snapshot 13 | # function 14 | snapshot: 0 15 | # We still use the snapshot prefix, though 16 | snapshot_prefix: "vgg_cnn_m_1024_rpn" 17 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/include/caffe/util/format.hpp: -------------------------------------------------------------------------------- 1 | #ifndef CAFFE_UTIL_FORMAT_H_ 2 | #define CAFFE_UTIL_FORMAT_H_ 3 | 4 | #include // NOLINT(readability/streams) 5 | #include // NOLINT(readability/streams) 6 | #include 7 | 8 | namespace caffe { 9 | 10 | inline std::string format_int(int n, int numberOfLeadingZeros = 0 ) { 11 | std::ostringstream s; 12 | s << std::setw(numberOfLeadingZeros) << std::setfill('0') << n; 13 | return s.str(); 14 | } 15 | 16 | } 17 | 18 | #endif // CAFFE_UTIL_FORMAT_H_ 19 | -------------------------------------------------------------------------------- /dependencies/pugixml/.travis.yml: -------------------------------------------------------------------------------- 1 | language: cpp 2 | sudo: required 3 | dist: trusty 4 | os: 5 | - linux 6 | - osx 7 | env: 8 | - DEFINES=standard 9 | - DEFINES=PUGIXML_WCHAR_MODE 10 | - DEFINES=PUGIXML_COMPACT 11 | - DEFINES=PUGIXML_NO_EXCEPTIONS 12 | script: 13 | - make test cxxstd=c++11 defines=$DEFINES config=coverage -j2 14 | - make test cxxstd=c++11 defines=$DEFINES config=release -j2 15 | - make test cxxstd=c++98 defines=$DEFINES config=debug -j2 16 | 17 | after_success: bash <(curl -s https://codecov.io/bash) -f pugixml.cpp.gcov 18 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/fuzz_xpath.cpp: -------------------------------------------------------------------------------- 1 | #include "../src/pugixml.hpp" 2 | 3 | #include 4 | #include 5 | 6 | extern "C" int LLVMFuzzerTestOneInput(const uint8_t *Data, size_t Size) 7 | { 8 | char* text = new char[Size + 1]; 9 | memcpy(text, Data, Size); 10 | text[Size] = 0; 11 | 12 | #ifdef PUGIXML_NO_EXCEPTIONS 13 | pugi::xpath_query q(text); 14 | #else 15 | try 16 | { 17 | pugi::xpath_query q(text); 18 | } 19 | catch (pugi::xpath_exception&) 20 | { 21 | } 22 | #endif 23 | 24 | delete[] text; 25 | return 0; 26 | } 27 | -------------------------------------------------------------------------------- /models_trained/pascal_voc/VGG_CNN_M_1024/faster_rcnn_alt_opt/stage1_fast_rcnn_solver30k40k.pt: -------------------------------------------------------------------------------- 1 | train_net: "models/pascal_voc/VGG_CNN_M_1024/faster_rcnn_alt_opt/stage1_fast_rcnn_train.pt" 2 | 3 | base_lr: 0.001 4 | lr_policy: "step" 5 | gamma: 0.1 6 | stepsize: 30000 7 | display: 20 8 | average_loss: 100 9 | momentum: 0.9 10 | weight_decay: 0.0005 11 | 12 | # We disable standard caffe solver snapshotting and implement our own snapshot 13 | # function 14 | snapshot: 0 15 | # We still use the snapshot prefix, though 16 | snapshot_prefix: "vgg_cnn_m_1024_fast_rcnn" 17 | -------------------------------------------------------------------------------- /models_trained/pascal_voc/VGG_CNN_M_1024/faster_rcnn_alt_opt/stage2_fast_rcnn_solver30k40k.pt: -------------------------------------------------------------------------------- 1 | train_net: "models/pascal_voc/VGG_CNN_M_1024/faster_rcnn_alt_opt/stage2_fast_rcnn_train.pt" 2 | 3 | base_lr: 0.001 4 | lr_policy: "step" 5 | gamma: 0.1 6 | stepsize: 30000 7 | display: 20 8 | average_loss: 100 9 | momentum: 0.9 10 | weight_decay: 0.0005 11 | 12 | # We disable standard caffe solver snapshotting and implement our own snapshot 13 | # function 14 | snapshot: 0 15 | # We still use the snapshot prefix, though 16 | snapshot_prefix: "vgg_cnn_m_1024_fast_rcnn" 17 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/cmake/CMakeFiles/2.8.12.2/CMakeSystem.cmake: -------------------------------------------------------------------------------- 1 | set(CMAKE_HOST_SYSTEM "Linux-2.6.32-431.11.2.el6.x86_64") 2 | set(CMAKE_HOST_SYSTEM_NAME "Linux") 3 | set(CMAKE_HOST_SYSTEM_VERSION "2.6.32-431.11.2.el6.x86_64") 4 | set(CMAKE_HOST_SYSTEM_PROCESSOR "x86_64") 5 | 6 | 7 | 8 | set(CMAKE_SYSTEM "Linux-2.6.32-431.11.2.el6.x86_64") 9 | set(CMAKE_SYSTEM_NAME "Linux") 10 | set(CMAKE_SYSTEM_VERSION "2.6.32-431.11.2.el6.x86_64") 11 | set(CMAKE_SYSTEM_PROCESSOR "x86_64") 12 | 13 | set(CMAKE_CROSSCOMPILING "FALSE") 14 | 15 | set(CMAKE_SYSTEM_LOADED 1) 16 | -------------------------------------------------------------------------------- /dependencies/pugixml/tests/data/latintest_utf8.xml: -------------------------------------------------------------------------------- 1 |
00000535351010MüllerJörg
<Test>
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<Test 2>
20
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 -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/examples/mnist/mnist_autoencoder_solver_adagrad.prototxt: -------------------------------------------------------------------------------- 1 | net: "examples/mnist/mnist_autoencoder.prototxt" 2 | test_state: { stage: 'test-on-train' } 3 | test_iter: 500 4 | test_state: { stage: 'test-on-test' } 5 | test_iter: 100 6 | test_interval: 500 7 | test_compute_loss: true 8 | base_lr: 0.01 9 | lr_policy: "fixed" 10 | display: 100 11 | max_iter: 65000 12 | weight_decay: 0.0005 13 | snapshot: 10000 14 | snapshot_prefix: "examples/mnist/mnist_autoencoder_adagrad_train" 15 | # solver mode: CPU or GPU 16 | solver_mode: GPU 17 | type: "AdaGrad" 18 | -------------------------------------------------------------------------------- /models_trained/modelnet/VGG16/faster_rcnn_end2end/solver.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/modelnet/VGG16/faster_rcnn_end2end/train.prototxt" 2 | ##test_iter: 100 3 | ##test_interval: 100 4 | base_lr: 0.001 5 | lr_policy: "step" 6 | gamma: 0.1 7 | stepsize: 50000 8 | display: 20 9 | average_loss: 100 10 | # iter_size: 1 11 | momentum: 0.9 12 | weight_decay: 0.0005 13 | # We disable standard caffe solver snapshotting and implement our own snapshot 14 | # function 15 | snapshot: 0 16 | # We still use the snapshot prefix, though 17 | snapshot_prefix: "vgg16_faster_rcnn" 18 | iter_size: 2 19 | -------------------------------------------------------------------------------- /models_trained/modeloneh/VGG16/faster_rcnn_end2end/solver.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/modeloneh/VGG16/faster_rcnn_end2end/train.prototxt" 2 | ##test_iter: 100 3 | ##test_interval: 100 4 | base_lr: 0.001 5 | lr_policy: "step" 6 | gamma: 0.1 7 | stepsize: 50000 8 | display: 20 9 | average_loss: 100 10 | # iter_size: 1 11 | momentum: 0.9 12 | weight_decay: 0.0005 13 | # We disable standard caffe solver snapshotting and implement our own snapshot 14 | # function 15 | snapshot: 0 16 | # We still use the snapshot prefix, though 17 | snapshot_prefix: "vggimnet_onehot" 18 | iter_size: 2 19 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/examples/mnist/mnist_autoencoder_solver.prototxt: -------------------------------------------------------------------------------- 1 | net: "examples/mnist/mnist_autoencoder.prototxt" 2 | test_state: { stage: 'test-on-train' } 3 | test_iter: 500 4 | test_state: { stage: 'test-on-test' } 5 | test_iter: 100 6 | test_interval: 500 7 | test_compute_loss: true 8 | base_lr: 0.01 9 | lr_policy: "step" 10 | gamma: 0.1 11 | stepsize: 10000 12 | display: 100 13 | max_iter: 65000 14 | weight_decay: 0.0005 15 | snapshot: 10000 16 | snapshot_prefix: "examples/mnist/mnist_autoencoder" 17 | momentum: 0.9 18 | # solver mode: CPU or GPU 19 | solver_mode: GPU 20 | -------------------------------------------------------------------------------- /dependencies/pugixml/docs/samples/custom_memory_management.cpp: -------------------------------------------------------------------------------- 1 | #include "pugixml.hpp" 2 | 3 | #include 4 | 5 | // tag::decl[] 6 | void* custom_allocate(size_t size) 7 | { 8 | return new (std::nothrow) char[size]; 9 | } 10 | 11 | void custom_deallocate(void* ptr) 12 | { 13 | delete[] static_cast(ptr); 14 | } 15 | // end::decl[] 16 | 17 | int main() 18 | { 19 | // tag::call[] 20 | pugi::set_memory_management_functions(custom_allocate, custom_deallocate); 21 | // end::call[] 22 | 23 | pugi::xml_document doc; 24 | doc.load_string(""); 25 | } 26 | 27 | // vim:et 28 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/examples/cifar10/create_cifar10.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | # This script converts the cifar data into leveldb format. 3 | set -e 4 | 5 | EXAMPLE=examples/cifar10 6 | DATA=data/cifar10 7 | DBTYPE=lmdb 8 | 9 | echo "Creating $DBTYPE..." 10 | 11 | rm -rf $EXAMPLE/cifar10_train_$DBTYPE $EXAMPLE/cifar10_test_$DBTYPE 12 | 13 | ./build/examples/cifar10/convert_cifar_data.bin $DATA $EXAMPLE $DBTYPE 14 | 15 | echo "Computing image mean..." 16 | 17 | ./build/tools/compute_image_mean -backend=$DBTYPE \ 18 | $EXAMPLE/cifar10_train_$DBTYPE $EXAMPLE/mean.binaryproto 19 | 20 | echo "Done." 21 | -------------------------------------------------------------------------------- /ros/sptam/src/standAlone/Test/ReadImagesFromDir/CMakeLists.txt: -------------------------------------------------------------------------------- 1 | cmake_minimum_required (VERSION 2.6) 2 | 3 | # nombre del proyecto 4 | project (ReadImagesFromDir) 5 | 6 | # defininos algunas opciones de compilación 7 | set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -g -Wall -std=c++11") 8 | 9 | # Encontrar los componentes necesarios de la librería OpenCV 10 | FIND_PACKAGE(OpenCV REQUIRED) 11 | 12 | # agregar un ejecutable al proyecto 13 | add_executable(ReadImagesFromDir ReadImagesFromDir.cpp) 14 | 15 | # linkear las librerías necesarias al ejecutable 16 | target_link_libraries(ReadImagesFromDir ${OpenCV_LIBS}) 17 | -------------------------------------------------------------------------------- /models_trained/modelpose/VGG16/faster_rcnn_end2end/solver.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/modelpose/VGG16/faster_rcnn_end2end/train.onlyCLSandPose.prototxt" 2 | ##test_iter: 100 3 | ##test_interval: 100 4 | base_lr: 0.001 ##o 0.0001 5 | lr_policy: "step" 6 | gamma: 0.1 7 | stepsize: 200000 8 | display: 20 9 | average_loss: 100 10 | # iter_size: 1 11 | momentum: 0.9 12 | weight_decay: 0.0005 13 | # We disable standard caffe solver snapshotting and implement our own snapshot 14 | # function 15 | snapshot: 0 16 | # We still use the snapshot prefix, though 17 | snapshot_prefix: "pose_cls_15k250k5k_dyp_20+" 18 | iter_size: 2 19 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/examples/mnist/mnist_autoencoder_solver_adadelta.prototxt: -------------------------------------------------------------------------------- 1 | net: "examples/mnist/mnist_autoencoder.prototxt" 2 | test_state: { stage: 'test-on-train' } 3 | test_iter: 500 4 | test_state: { stage: 'test-on-test' } 5 | test_iter: 100 6 | test_interval: 500 7 | test_compute_loss: true 8 | base_lr: 1.0 9 | lr_policy: "fixed" 10 | momentum: 0.95 11 | delta: 1e-8 12 | display: 100 13 | max_iter: 65000 14 | weight_decay: 0.0005 15 | snapshot: 10000 16 | snapshot_prefix: "examples/mnist/mnist_autoencoder_adadelta_train" 17 | # solver mode: CPU or GPU 18 | solver_mode: GPU 19 | type: "AdaDelta" 20 | -------------------------------------------------------------------------------- /FromMaxwellToOther.dockerfile: -------------------------------------------------------------------------------- 1 | FROM eevidal/object-detection-sptam-kinetic:ros-base-xenial-sptam-kinetic-maxwell 2 | 3 | LABEL maintainer="Erica Vidal ericavidal@gmail.com" 4 | 5 | RUN cd $HOME/object-detection-sptam && git pull \ 6 | && cd $HOME/object-detection-sptam/py-faster-rcnn \ 7 | && rm -Rf lib \ 8 | && git checkout lib 9 | 10 | # the rigth arch have to be set on setup.py file (line 135) 11 | COPY ./py-faster-rcnn/lib/setup.py /root/object-detection-sptam/py-faster-rcnn/lib/ 12 | 13 | RUN cd $HOME/object-detection-sptam/py-faster-rcnn/lib && make 14 | 15 | CMD ["bash"] 16 | 17 | WORKDIR catkin_ws -------------------------------------------------------------------------------- /dependencies/pugixml/appveyor.yml: -------------------------------------------------------------------------------- 1 | version: "{branch}-{build}" 2 | 3 | install: 4 | - ps: (new-object net.webclient).DownloadFile('http://coapp.org/files/CoApp.Tools.Powershell.msi', 'C:\CoApp.Tools.Powershell.msi') 5 | - ps: Start-Process -FilePath msiexec -ArgumentList /i, 'C:\CoApp.Tools.Powershell.msi', /quiet -Wait 6 | - ps: $env:PSModulePath = $env:PSModulePath + ';C:\Program Files (x86)\Outercurve Foundation\Modules' 7 | - ps: Import-Module CoApp 8 | 9 | build_script: 10 | - ps: .\scripts\nuget_build.bat 11 | 12 | test_script: 13 | - ps: .\tests\autotest-appveyor.ps1 14 | 15 | artifacts: 16 | - path: .\scripts\*.nupkg -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/examples/mnist/mnist_autoencoder_solver_nesterov.prototxt: -------------------------------------------------------------------------------- 1 | net: "examples/mnist/mnist_autoencoder.prototxt" 2 | test_state: { stage: 'test-on-train' } 3 | test_iter: 500 4 | test_state: { stage: 'test-on-test' } 5 | test_iter: 100 6 | test_interval: 500 7 | test_compute_loss: true 8 | base_lr: 0.01 9 | lr_policy: "step" 10 | gamma: 0.1 11 | stepsize: 10000 12 | display: 100 13 | max_iter: 65000 14 | weight_decay: 0.0005 15 | snapshot: 10000 16 | snapshot_prefix: "examples/mnist/mnist_autoencoder_nesterov_train" 17 | momentum: 0.95 18 | # solver mode: CPU or GPU 19 | solver_mode: GPU 20 | type: "Nesterov" 21 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/scripts/build_docs.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | # Build documentation for display in web browser. 3 | 4 | PORT=${1:-4000} 5 | 6 | echo "usage: build_docs.sh [port]" 7 | 8 | # Find the docs dir, no matter where the script is called 9 | ROOT_DIR="$( cd "$(dirname "$0")"/.. ; pwd -P )" 10 | cd $ROOT_DIR 11 | 12 | # Gather docs. 13 | scripts/gather_examples.sh 14 | 15 | # Split caffe.proto for inclusion by layer catalogue. 16 | scripts/split_caffe_proto.py 17 | 18 | # Generate developer docs. 19 | make docs 20 | 21 | # Display docs using web server. 22 | cd docs 23 | jekyll serve -w -s . -d _site --port=$PORT 24 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/data/cifar10/get_cifar10.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | # This scripts downloads the CIFAR10 (binary version) data and unzips it. 3 | 4 | DIR="$( cd "$(dirname "$0")" ; pwd -P )" 5 | cd "$DIR" 6 | 7 | echo "Downloading..." 8 | 9 | wget --no-check-certificate http://www.cs.toronto.edu/~kriz/cifar-10-binary.tar.gz 10 | 11 | echo "Unzipping..." 12 | 13 | tar -xf cifar-10-binary.tar.gz && rm -f cifar-10-binary.tar.gz 14 | mv cifar-10-batches-bin/* . && rm -rf cifar-10-batches-bin 15 | 16 | # Creation is split out because leveldb sometimes causes segfault 17 | # and needs to be re-created. 18 | 19 | echo "Done." 20 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/examples/cifar10/train_full.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | TOOLS=./build/tools 5 | 6 | $TOOLS/caffe train \ 7 | --solver=examples/cifar10/cifar10_full_solver.prototxt $@ 8 | 9 | # reduce learning rate by factor of 10 10 | $TOOLS/caffe train \ 11 | --solver=examples/cifar10/cifar10_full_solver_lr1.prototxt \ 12 | --snapshot=examples/cifar10/cifar10_full_iter_60000.solverstate.h5 $@ 13 | 14 | # reduce learning rate by factor of 10 15 | $TOOLS/caffe train \ 16 | --solver=examples/cifar10/cifar10_full_solver_lr2.prototxt \ 17 | --snapshot=examples/cifar10/cifar10_full_iter_65000.solverstate.h5 $@ 18 | -------------------------------------------------------------------------------- /ros/sptam/src/ros/sptam_nodelet.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | #include 3 | #include "stereo_driver.hpp" 4 | 5 | namespace sptam 6 | { 7 | class sptam_nodelet : public nodelet::Nodelet 8 | { 9 | public: 10 | 11 | void onInit() 12 | { 13 | NODELET_DEBUG("Initializing sptam nodelet..."); 14 | sptam_interface_.reset( new sptam::stereo_driver( getNodeHandle(), getPrivateNodeHandle() ) ); 15 | } 16 | 17 | private: 18 | 19 | std::unique_ptr sptam_interface_; 20 | }; 21 | } 22 | 23 | PLUGINLIB_EXPORT_CLASS(sptam::sptam_nodelet, nodelet::Nodelet) 24 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/examples/net_surgery/conv.prototxt: -------------------------------------------------------------------------------- 1 | # Simple single-layer network to showcase editing model parameters. 2 | name: "convolution" 3 | layer { 4 | name: "data" 5 | type: "Input" 6 | top: "data" 7 | input_param { shape: { dim: 1 dim: 1 dim: 100 dim: 100 } } 8 | } 9 | layer { 10 | name: "conv" 11 | type: "Convolution" 12 | bottom: "data" 13 | top: "conv" 14 | convolution_param { 15 | num_output: 3 16 | kernel_size: 5 17 | stride: 1 18 | weight_filler { 19 | type: "gaussian" 20 | std: 0.01 21 | } 22 | bias_filler { 23 | type: "constant" 24 | value: 0 25 | } 26 | } 27 | } 28 | -------------------------------------------------------------------------------- /ros/sptam/cmake-modules/FindOpenGV.cmake: -------------------------------------------------------------------------------- 1 | FIND_PATH(OPENGV_INCLUDE_DIR opengv/types.hpp 2 | ${OPENGV_ROOT}/include 3 | $ENV{OPENGV_ROOT}/include 4 | /usr/include 5 | /opt/local/include 6 | /usr/local/include 7 | /sw/include 8 | ) 9 | 10 | FIND_LIBRARY(OPENGV_LIBRARY opengv 11 | ${OPENGV_ROOT}/lib 12 | $ENV{OPENGV_ROOT}/lib 13 | /usr/lib 14 | /usr/local/lib 15 | /opt/local/lib 16 | /sw/lib 17 | ) 18 | 19 | IF(OPENGV_INCLUDE_DIR AND OPENGV_LIBRARY) 20 | SET(OPENGV_FOUND TRUE) 21 | ELSE(OPENGV_INCLUDE_DIR AND OPENGV_LIBRARY) 22 | SET(OPENGV_FOUND FALSE) 23 | ENDIF(OPENGV_INCLUDE_DIR AND OPENGV_LIBRARY) 24 | -------------------------------------------------------------------------------- /ros/sptam/src/sptam/loopclosing/LCDetector.hpp: -------------------------------------------------------------------------------- 1 | #pragma once 2 | 3 | #include "../Map.hpp" 4 | 5 | /// Result of a detection 6 | struct DetectionMatch 7 | { 8 | /// Detection status. 9 | bool status; 10 | /// Query id 11 | size_t query; 12 | /// Matched id if loop detected, otherwise, best candidate 13 | size_t match; 14 | /// Matched score 15 | double score; 16 | 17 | /** Checks if the loop was detected */ 18 | inline bool detection() const 19 | { return status; } 20 | }; 21 | 22 | class LCDetector 23 | { 24 | public: 25 | virtual ~LCDetector(){} 26 | virtual DetectionMatch detectloop(const sptam::Map::SharedKeyFrame& stereo_frame) = 0; 27 | }; 28 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/KITTI00_left.yaml: -------------------------------------------------------------------------------- 1 | %YAML:1.0 2 | 3 | image_width: 1241 4 | image_height: 376 5 | camera_name: left_camera 6 | frame_id: stereo 7 | camera_matrix: 8 | rows: 3 9 | cols: 3 10 | data: [ 7.188560000000e+02, 0, 6.071928000000e+02, 0, 7.188560000000e+02, 1.852157000000e+02, 0, 0, 1] 11 | distortion_model: plumb_bob 12 | distortion_coefficients: 13 | rows: 1 14 | cols: 5 15 | data: [ 0, 0, 0, 0, 0 ] 16 | rectification_matrix: 17 | rows: 3 18 | cols: 3 19 | data: [1, 0, 0, 0, 1, 0, 0, 0, 1] 20 | projection_matrix: 21 | rows: 3 22 | cols: 4 23 | data: [7.188560000000e+02, 0, 6.071928000000e+02, 0, 0, 7.188560000000e+02, 1.852157000000e+02, 0, 0, 0, 1, 0] 24 | -------------------------------------------------------------------------------- /models_trained/pascal_voc/ZF/faster_rcnn_end2end/solver.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/pascal_voc/ZF/faster_rcnn_end2end/train.prototxt" 2 | 3 | base_lr: 0.001 4 | lr_policy: "step" 5 | gamma: 0.1 6 | stepsize: 50000 7 | display: 20 8 | average_loss: 100 9 | momentum: 0.9 10 | weight_decay: 0.0005 11 | 12 | #base_lr: 0.001 13 | #lr_policy: "exp" 14 | #gamma: 0.999539589 # (0.00001/0.001)^(1/10000) 15 | #display: 1 16 | #average_loss: 100 17 | #momentum: 0.9 18 | #weight_decay: 0.0005 19 | 20 | # We disable standard caffe solver snapshotting and implement our own snapshot 21 | # function 22 | snapshot: 0 23 | # We still use the snapshot prefix, though 24 | snapshot_prefix: "zf_faster_rcnn" 25 | iter_size: 2 26 | -------------------------------------------------------------------------------- /ros/sptam/src/sptam/utils/timer.h: -------------------------------------------------------------------------------- 1 | #pragma once 2 | 3 | #include 4 | 5 | namespace sptam 6 | { 7 | class Timer 8 | { 9 | public: 10 | Timer(void); 11 | 12 | void start(void); /* measures initial time */ 13 | void stop(void); /* measures elapsed time */ 14 | double elapsed(void) const; /* returns elapsed time in seconds */ 15 | 16 | static double now(void); /* returns seconds since epoch */ 17 | 18 | private: 19 | typedef std::chrono::high_resolution_clock clock_t; 20 | std::chrono::time_point t; 21 | double elapsed_seconds; 22 | }; 23 | } 24 | 25 | std::ostream& operator<< (std::ostream& stream, const sptam::Timer& t); 26 | 27 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/KITTI00_right.yaml: -------------------------------------------------------------------------------- 1 | %YAML:1.0 2 | 3 | image_width: 1241 4 | image_height: 376 5 | camera_name: right_camera 6 | frame_id: stereo 7 | camera_matrix: 8 | rows: 3 9 | cols: 3 10 | data: [ 7.188560000000e+02, 0, 6.071928000000e+02, 0, 7.188560000000e+02, 1.852157000000e+02, 0, 0, 1] 11 | distortion_model: plumb_bob 12 | distortion_coefficients: 13 | rows: 1 14 | cols: 5 15 | data: [ 0, 0, 0, 0, 0 ] 16 | rectification_matrix: 17 | rows: 3 18 | cols: 3 19 | data: [1, 0, 0, 0, 1, 0, 0, 0, 1] 20 | projection_matrix: 21 | rows: 3 22 | cols: 4 23 | data: [7.188560000000e+02, 0, 6.071928000000e+02, -386.1448, 0, 7.188560000000e+02, 1.852157000000e+02, 0, 0, 0, 1, 0] 24 | 25 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/data/ilsvrc12/get_ilsvrc_aux.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | # 3 | # N.B. This does not download the ilsvrcC12 data set, as it is gargantuan. 4 | # This script downloads the imagenet example auxiliary files including: 5 | # - the ilsvrc12 image mean, binaryproto 6 | # - synset ids and words 7 | # - Python pickle-format data of ImageNet graph structure and relative infogain 8 | # - the training splits with labels 9 | 10 | DIR="$( cd "$(dirname "$0")" ; pwd -P )" 11 | cd "$DIR" 12 | 13 | echo "Downloading..." 14 | 15 | wget -c http://dl.caffe.berkeleyvision.org/caffe_ilsvrc12.tar.gz 16 | 17 | echo "Unzipping..." 18 | 19 | tar -xf caffe_ilsvrc12.tar.gz && rm -f caffe_ilsvrc12.tar.gz 20 | 21 | echo "Done." 22 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/CONTRIBUTORS.md: -------------------------------------------------------------------------------- 1 | # Contributors 2 | 3 | Caffe is developed by a core set of BVLC members and the open-source community. 4 | 5 | We thank all of our [contributors](https://github.com/BVLC/caffe/graphs/contributors)! 6 | 7 | **For the detailed history of contributions** of a given file, try 8 | 9 | git blame file 10 | 11 | to see line-by-line credits and 12 | 13 | git log --follow file 14 | 15 | to see the change log even across renames and rewrites. 16 | 17 | Please refer to the [acknowledgements](http://caffe.berkeleyvision.org/#acknowledgements) on the Caffe site for further details. 18 | 19 | **Copyright** is held by the original contributor according to the versioning history; see LICENSE. 20 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/scripts/download_model_from_gist.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | 3 | GIST=$1 4 | DIRNAME=${2:-./models} 5 | 6 | if [ -z $GIST ]; then 7 | echo "usage: download_model_from_gist.sh " 8 | exit 9 | fi 10 | 11 | GIST_DIR=$(echo $GIST | tr '/' '-') 12 | MODEL_DIR="$DIRNAME/$GIST_DIR" 13 | 14 | if [ -d $MODEL_DIR ]; then 15 | echo "$MODEL_DIR already exists! Please make sure you're not overwriting anything important!" 16 | exit 17 | fi 18 | 19 | echo "Downloading Caffe model info to $MODEL_DIR ..." 20 | mkdir -p $MODEL_DIR 21 | wget https://gist.github.com/$GIST/download -O $MODEL_DIR/gist.zip 22 | unzip -j $MODEL_DIR/gist.zip -d $MODEL_DIR 23 | rm $MODEL_DIR/gist.zip 24 | echo "Done" 25 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/stylesheets/reset.css: -------------------------------------------------------------------------------- 1 | /* MeyerWeb Reset */ 2 | 3 | html, body, div, span, applet, object, iframe, 4 | h1, h2, h3, h4, h5, h6, p, blockquote, pre, 5 | a, abbr, acronym, address, big, cite, code, 6 | del, dfn, em, img, ins, kbd, q, s, samp, 7 | small, strike, strong, sub, sup, tt, var, 8 | b, u, i, center, 9 | dl, dt, dd, ol, ul, li, 10 | fieldset, form, label, legend, 11 | table, caption, tbody, tfoot, thead, tr, th, td, 12 | article, aside, canvas, details, embed, 13 | figure, figcaption, footer, header, hgroup, 14 | menu, nav, output, ruby, section, summary, 15 | time, mark, audio, video { 16 | margin: 0; 17 | padding: 0; 18 | border: 0; 19 | font: inherit; 20 | vertical-align: baseline; 21 | } 22 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/filter.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Filter Layer 3 | --- 4 | 5 | # Filter Layer 6 | 7 | * Layer type: `Filter` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1FilterLayer.html) 9 | * Header: [`./include/caffe/layers/filter_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/filter_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/filter_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/filter_layer.cpp) 11 | * CUDA GPU implementation: [`./src/caffe/layers/filter_layer.cu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/filter_layer.cu) 12 | 13 | ## Parameters 14 | 15 | Does not take any parameters. 16 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/kitti_sift.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | Name: 'SIFT' 3 | nOctaveLayers: 1 4 | 5 | DescriptorExtractor: 6 | Name: 'SIFT' 7 | nOctaveLayers: 1 8 | 9 | DescriptorMatcher: 10 | # normType: use 11 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 12 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 13 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 14 | # use L2 norm type as default when it is not especified 15 | Name: 'BruteForce' 16 | crossCheck: false 17 | 18 | MatchingCellSize: 15 19 | MatchingNeighborhood: 1 20 | MatchingDistance: 100 21 | EpipolarDistance: 1 22 | FrustumNearPlaneDist: 0.1 23 | FrustumFarPlaneDist: 10000.0 24 | BundleAdjustmentActiveKeyframes: 10 25 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/mit.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'GFTT' 4 | 5 | nfeatures: 1000 6 | minDistance: 15.0 7 | qualityLevel: 0.01 8 | useHarrisDetector: false 9 | 10 | DescriptorExtractor: 11 | Name: 'BRIEF' 12 | bytes: 32 13 | 14 | DescriptorMatcher: 15 | # normType: use 16 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 17 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 18 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 19 | Name: 'BruteForce-Hamming' 20 | crossCheck: false 21 | 22 | MatchingCellSize: 30 23 | MatchingNeighborhood: 1 24 | MatchingDistance: 25 25 | EpipolarDistance: 0 26 | FrustumNearPlaneDist: 0.1 27 | FrustumFarPlaneDist: 10000.0 28 | BundleAdjustmentActiveKeyframes: 10 29 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/sfu.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'GFTT' 4 | 5 | nfeatures: 10000 6 | minDistance: 5.0 7 | qualityLevel: 0.001 8 | useHarrisDetector: false 9 | 10 | DescriptorExtractor: 11 | Name: 'BRIEF' 12 | bytes: 32 13 | 14 | DescriptorMatcher: 15 | # normType: use 16 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 17 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 18 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 19 | Name: 'BruteForce-Hamming' 20 | crossCheck: false 21 | 22 | MatchingCellSize: 15 23 | MatchingNeighborhood: 1 24 | MatchingDistance: 25 25 | EpipolarDistance: 1 26 | FrustumNearPlaneDist: 0.1 27 | FrustumFarPlaneDist: 10000.0 28 | BundleAdjustmentActiveKeyframes: 10 29 | -------------------------------------------------------------------------------- /py-faster-rcnn/lib/fast_rcnn/nms_wrapper.py: -------------------------------------------------------------------------------- 1 | # -------------------------------------------------------- 2 | # Fast R-CNN 3 | # Copyright (c) 2015 Microsoft 4 | # Licensed under The MIT License [see LICENSE for details] 5 | # Written by Ross Girshick 6 | # -------------------------------------------------------- 7 | 8 | from fast_rcnn.config import cfg 9 | from nms.gpu_nms import gpu_nms 10 | from nms.cpu_nms import cpu_nms 11 | 12 | def nms(dets, thresh, force_cpu=False): 13 | """Dispatch to either CPU or GPU NMS implementations.""" 14 | 15 | if dets.shape[0] == 0: 16 | return [] 17 | if cfg.USE_GPU_NMS and not force_cpu: 18 | return gpu_nms(dets, thresh, device_id=cfg.GPU_ID) 19 | else: 20 | return cpu_nms(dets, thresh) 21 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/newCollege.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'GFTT' 4 | 5 | nfeatures: 2000 6 | minDistance: 15.0 7 | qualityLevel: 0.01 8 | useHarrisDetector: false 9 | 10 | DescriptorExtractor: 11 | Name: 'BRIEF' 12 | bytes: 32 13 | 14 | DescriptorMatcher: 15 | # normType: use 16 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 17 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 18 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 19 | Name: 'BruteForce-Hamming' 20 | crossCheck: false 21 | 22 | MatchingCellSize: 15 23 | MatchingNeighborhood: 1 24 | MatchingDistance: 25 25 | EpipolarDistance: 0 26 | FrustumNearPlaneDist: 0.1 27 | FrustumFarPlaneDist: 10000.0 28 | BundleAdjustmentActiveKeyframes: 10 29 | -------------------------------------------------------------------------------- /dependencies/pugixml/docs/samples/traverse_iter.cpp: -------------------------------------------------------------------------------- 1 | #include "pugixml.hpp" 2 | 3 | #include 4 | 5 | int main() 6 | { 7 | pugi::xml_document doc; 8 | if (!doc.load_file("xgconsole.xml")) return -1; 9 | 10 | pugi::xml_node tools = doc.child("Profile").child("Tools"); 11 | 12 | // tag::code[] 13 | for (pugi::xml_node_iterator it = tools.begin(); it != tools.end(); ++it) 14 | { 15 | std::cout << "Tool:"; 16 | 17 | for (pugi::xml_attribute_iterator ait = it->attributes_begin(); ait != it->attributes_end(); ++ait) 18 | { 19 | std::cout << " " << ait->name() << "=" << ait->value(); 20 | } 21 | 22 | std::cout << std::endl; 23 | } 24 | // end::code[] 25 | } 26 | 27 | // vim:et 28 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/kitti_fast_brief.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'FAST' 4 | 5 | threshold: 60 6 | nonmaxSuppression: true 7 | 8 | DescriptorExtractor: 9 | Name: 'BRIEF' 10 | bytes: 32 11 | 12 | # OpenCV3 13 | # use_orientation: false 14 | 15 | DescriptorMatcher: 16 | # normType: use 17 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 18 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 19 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 20 | Name: 'BruteForce-Hamming' 21 | crossCheck: false 22 | 23 | MatchingCellSize: 15 24 | MatchingNeighborhood: 1 25 | MatchingDistance: 25 26 | EpipolarDistance: 0 27 | FrustumNearPlaneDist: 0.1 28 | FrustumFarPlaneDist: 10000.0 29 | BundleAdjustmentActiveKeyframes: 10 30 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/include/caffe/caffe.hpp: -------------------------------------------------------------------------------- 1 | // caffe.hpp is the header file that you need to include in your code. It wraps 2 | // all the internal caffe header files into one for simpler inclusion. 3 | 4 | #ifndef CAFFE_CAFFE_HPP_ 5 | #define CAFFE_CAFFE_HPP_ 6 | 7 | #include "caffe/blob.hpp" 8 | #include "caffe/common.hpp" 9 | #include "caffe/filler.hpp" 10 | #include "caffe/layer.hpp" 11 | #include "caffe/layer_factory.hpp" 12 | #include "caffe/net.hpp" 13 | #include "caffe/parallel.hpp" 14 | #include "caffe/proto/caffe.pb.h" 15 | #include "caffe/solver.hpp" 16 | #include "caffe/solver_factory.hpp" 17 | #include "caffe/util/benchmark.hpp" 18 | #include "caffe/util/io.hpp" 19 | #include "caffe/util/upgrade_proto.hpp" 20 | 21 | #endif // CAFFE_CAFFE_HPP_ 22 | -------------------------------------------------------------------------------- /py-faster-rcnn/tools/_init_paths.py: -------------------------------------------------------------------------------- 1 | # -------------------------------------------------------- 2 | # Fast R-CNN 3 | # Copyright (c) 2015 Microsoft 4 | # Licensed under The MIT License [see LICENSE for details] 5 | # Written by Ross Girshick 6 | # -------------------------------------------------------- 7 | 8 | """Set up paths for Fast R-CNN.""" 9 | 10 | import os.path as osp 11 | import sys 12 | 13 | def add_path(path): 14 | if path not in sys.path: 15 | sys.path.insert(0, path) 16 | 17 | this_dir = osp.dirname(__file__) 18 | 19 | # Add caffe to PYTHONPATH 20 | caffe_path = osp.join(this_dir, '..', 'caffe-fast-rcnn', 'python') 21 | add_path(caffe_path) 22 | 23 | # Add lib to PYTHONPATH 24 | lib_path = osp.join(this_dir, '..', 'lib') 25 | add_path(lib_path) 26 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/kitti_agast_latch.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'AGAST' 4 | 5 | threshold: 60 6 | nonmaxSuppression: true 7 | 8 | DescriptorExtractor: 9 | Name: 'LATCH' 10 | bytes: 32 11 | rotationInvariance: false 12 | half_ssd_size: 3 13 | 14 | DescriptorMatcher: 15 | # normType: use 16 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 17 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 18 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 19 | Name: 'BruteForce-Hamming' 20 | crossCheck: false 21 | 22 | MatchingCellSize: 15 23 | MatchingNeighborhood: 1 24 | MatchingDistance: 45 25 | EpipolarDistance: 0 26 | FrustumNearPlaneDist: 0.1 27 | FrustumFarPlaneDist: 10000.0 28 | BundleAdjustmentActiveKeyframes: 10 29 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/kitti_fast_latch.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'FAST' 4 | 5 | threshold: 60 6 | nonmaxSuppression: true 7 | 8 | DescriptorExtractor: 9 | Name: 'LATCH' 10 | bytes: 32 11 | rotationInvariance: false 12 | half_ssd_size: 3 13 | 14 | DescriptorMatcher: 15 | # normType: use 16 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 17 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 18 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 19 | Name: 'BruteForce-Hamming' 20 | crossCheck: false 21 | 22 | MatchingCellSize: 15 23 | MatchingNeighborhood: 1 24 | MatchingDistance: 45 25 | EpipolarDistance: 0 26 | FrustumNearPlaneDist: 0.1 27 | FrustumFarPlaneDist: 10000.0 28 | BundleAdjustmentActiveKeyframes: 10 29 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/examples/siamese/create_mnist_siamese.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | # This script converts the mnist data into leveldb format. 3 | set -e 4 | 5 | EXAMPLES=./build/examples/siamese 6 | DATA=./data/mnist 7 | 8 | echo "Creating leveldb..." 9 | 10 | rm -rf ./examples/siamese/mnist_siamese_train_leveldb 11 | rm -rf ./examples/siamese/mnist_siamese_test_leveldb 12 | 13 | $EXAMPLES/convert_mnist_siamese_data.bin \ 14 | $DATA/train-images-idx3-ubyte \ 15 | $DATA/train-labels-idx1-ubyte \ 16 | ./examples/siamese/mnist_siamese_train_leveldb 17 | $EXAMPLES/convert_mnist_siamese_data.bin \ 18 | $DATA/t10k-images-idx3-ubyte \ 19 | $DATA/t10k-labels-idx1-ubyte \ 20 | ./examples/siamese/mnist_siamese_test_leveldb 21 | 22 | echo "Done." 23 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/matlab/+caffe/+test/test_io.m: -------------------------------------------------------------------------------- 1 | classdef test_io < matlab.unittest.TestCase 2 | methods (Test) 3 | function test_read_write_mean(self) 4 | % randomly generate mean data 5 | width = 200; 6 | height = 300; 7 | channels = 3; 8 | mean_data_write = 255 * rand(width, height, channels, 'single'); 9 | % write mean data to binary proto 10 | mean_proto_file = tempname(); 11 | caffe.io.write_mean(mean_data_write, mean_proto_file); 12 | % read mean data from saved binary proto and test whether they are equal 13 | mean_data_read = caffe.io.read_mean(mean_proto_file); 14 | self.verifyEqual(mean_data_write, mean_data_read) 15 | delete(mean_proto_file); 16 | end 17 | end 18 | end 19 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/kitti_agast_brief.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'AGAST' 4 | 5 | threshold: 60 6 | nonmaxSuppression: true 7 | 8 | DescriptorExtractor: 9 | Name: 'BRIEF' 10 | bytes: 32 11 | 12 | # OpenCV3 13 | # use_orientation: false 14 | 15 | DescriptorMatcher: 16 | # normType: use 17 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 18 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 19 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 20 | Name: 'BruteForce-Hamming' 21 | crossCheck: false 22 | 23 | MatchingCellSize: 15 24 | MatchingNeighborhood: 1 25 | MatchingDistance: 25 26 | EpipolarDistance: 0 27 | FrustumNearPlaneDist: 0.1 28 | FrustumFarPlaneDist: 10000.0 29 | BundleAdjustmentActiveKeyframes: 10 30 | 31 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/convolution.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Convolution 3 | --- 4 | # Caffeinated Convolution 5 | 6 | The Caffe strategy for convolution is to reduce the problem to matrix-matrix multiplication. 7 | This linear algebra computation is highly-tuned in BLAS libraries and efficiently computed on GPU devices. 8 | 9 | For more details read Yangqing's [Convolution in Caffe: a memo](https://github.com/Yangqing/caffe/wiki/Convolution-in-Caffe:-a-memo). 10 | 11 | As it turns out, this same reduction was independently explored in the context of conv. nets by 12 | 13 | > K. Chellapilla, S. Puri, P. Simard, et al. High performance convolutional neural networks for document processing. In Tenth International Workshop on Frontiers in Handwriting Recognition, 2006. 14 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/examples/mnist/create_mnist.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | # This script converts the mnist data into lmdb/leveldb format, 3 | # depending on the value assigned to $BACKEND. 4 | set -e 5 | 6 | EXAMPLE=examples/mnist 7 | DATA=data/mnist 8 | BUILD=build/examples/mnist 9 | 10 | BACKEND="lmdb" 11 | 12 | echo "Creating ${BACKEND}..." 13 | 14 | rm -rf $EXAMPLE/mnist_train_${BACKEND} 15 | rm -rf $EXAMPLE/mnist_test_${BACKEND} 16 | 17 | $BUILD/convert_mnist_data.bin $DATA/train-images-idx3-ubyte \ 18 | $DATA/train-labels-idx1-ubyte $EXAMPLE/mnist_train_${BACKEND} --backend=${BACKEND} 19 | $BUILD/convert_mnist_data.bin $DATA/t10k-images-idx3-ubyte \ 20 | $DATA/t10k-labels-idx1-ubyte $EXAMPLE/mnist_test_${BACKEND} --backend=${BACKEND} 21 | 22 | echo "Done." 23 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/tsukuba.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'GFTT' 4 | 5 | nfeatures: 2000 6 | minDistance: 5.0 7 | qualityLevel: 0.01 8 | useHarrisDetector: false 9 | 10 | DescriptorExtractor: 11 | Name: 'BRIEF' 12 | bytes: 32 13 | 14 | DescriptorMatcher: 15 | # normType: use 16 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 17 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 18 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 19 | Name: 'BruteForce-Hamming' 20 | crossCheck: false 21 | 22 | MatchingCellSize: 30 23 | MatchingNeighborhood: 1 24 | MatchingDistance: 25 25 | EpipolarDistance: 0 26 | FrustumNearPlaneDist: 0.1 27 | FrustumFarPlaneDist: 20 28 | BundleAdjustmentActiveKeyframes: 10 29 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/src/caffe/layers/silence_layer.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | 3 | #include "caffe/layers/silence_layer.hpp" 4 | #include "caffe/util/math_functions.hpp" 5 | 6 | namespace caffe { 7 | 8 | template 9 | void SilenceLayer::Backward_cpu(const vector*>& top, 10 | const vector& propagate_down, const vector*>& bottom) { 11 | for (int i = 0; i < bottom.size(); ++i) { 12 | if (propagate_down[i]) { 13 | caffe_set(bottom[i]->count(), Dtype(0), 14 | bottom[i]->mutable_cpu_diff()); 15 | } 16 | } 17 | } 18 | 19 | #ifdef CPU_ONLY 20 | STUB_GPU(SilenceLayer); 21 | #endif 22 | 23 | INSTANTIATE_CLASS(SilenceLayer); 24 | REGISTER_LAYER_CLASS(Silence); 25 | 26 | } // namespace caffe 27 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/silence.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Silence Layer 3 | --- 4 | 5 | # Silence Layer 6 | 7 | * Layer type: `Silence` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1SilenceLayer.html) 9 | * Header: [`./include/caffe/layers/silence_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/silence_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/silence_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/silence_layer.cpp) 11 | * CUDA GPU implementation: [`./src/caffe/layers/silence_layer.cu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/silence_layer.cu) 12 | 13 | Silences a blob, so that it is not printed. 14 | 15 | ## Parameters 16 | 17 | No parameters. 18 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/src/caffe/util/cudnn.cpp: -------------------------------------------------------------------------------- 1 | #ifdef USE_CUDNN 2 | #include "caffe/util/cudnn.hpp" 3 | 4 | namespace caffe { 5 | namespace cudnn { 6 | 7 | float dataType::oneval = 1.0; 8 | float dataType::zeroval = 0.0; 9 | const void* dataType::one = 10 | static_cast(&dataType::oneval); 11 | const void* dataType::zero = 12 | static_cast(&dataType::zeroval); 13 | 14 | double dataType::oneval = 1.0; 15 | double dataType::zeroval = 0.0; 16 | const void* dataType::one = 17 | static_cast(&dataType::oneval); 18 | const void* dataType::zero = 19 | static_cast(&dataType::zeroval); 20 | 21 | } // namespace cudnn 22 | } // namespace caffe 23 | #endif 24 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/scripts/travis/configure-cmake.sh: -------------------------------------------------------------------------------- 1 | # CMake configuration 2 | 3 | mkdir -p build 4 | cd build 5 | 6 | ARGS="-DCMAKE_BUILD_TYPE=Release -DBLAS=Open" 7 | 8 | if $WITH_PYTHON3 ; then 9 | ARGS="$ARGS -Dpython_version=3" 10 | fi 11 | 12 | if $WITH_IO ; then 13 | ARGS="$ARGS -DUSE_OPENCV=On -DUSE_LMDB=On -DUSE_LEVELDB=On" 14 | else 15 | ARGS="$ARGS -DUSE_OPENCV=Off -DUSE_LMDB=Off -DUSE_LEVELDB=Off" 16 | fi 17 | 18 | if $WITH_CUDA ; then 19 | # Only build SM50 20 | ARGS="$ARGS -DCPU_ONLY=Off -DCUDA_ARCH_NAME=Manual -DCUDA_ARCH_BIN=\"50\" -DCUDA_ARCH_PTX=\"\"" 21 | else 22 | ARGS="$ARGS -DCPU_ONLY=On" 23 | fi 24 | 25 | if $WITH_CUDNN ; then 26 | ARGS="$ARGS -DUSE_CUDNN=On" 27 | else 28 | ARGS="$ARGS -DUSE_CUDNN=Off" 29 | fi 30 | 31 | cmake .. $ARGS 32 | 33 | -------------------------------------------------------------------------------- /ros/ros-utils/package.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | ros_utils 5 | 0.0.1 6 | Some useful nodes to work with ROS 7 | 8 | Thomas Fischer 9 | 10 | GPLv3 11 | 12 | catkin 13 | 14 | roscpp 15 | geometry_msgs 16 | nav_msgs 17 | cmake_modules 18 | 19 | roscpp 20 | geometry_msgs 21 | nav_msgs 22 | cmake_modules 23 | 24 | 25 | 26 | 27 | 28 | 29 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/kitti_star_brief.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'STAR' 4 | 5 | maxSize: 16 6 | responseThreshold: 20 7 | suppressNonmaxSize: 5 8 | 9 | DescriptorExtractor: 10 | Name: 'BRIEF' 11 | bytes: 32 12 | 13 | # OpenCV3 14 | # use_orientation: false 15 | 16 | DescriptorMatcher: 17 | # normType: use 18 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 19 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 20 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 21 | Name: 'BruteForce-Hamming' 22 | crossCheck: 'false' 23 | 24 | MatchingCellSize: 15 25 | MatchingNeighborhood: 1 26 | MatchingDistance: 25 27 | EpipolarDistance: 0 28 | FrustumNearPlaneDist: 0.1 29 | FrustumFarPlaneDist: 10000.0 30 | BundleAdjustmentActiveKeyframes: 10 31 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/include/caffe/util/signal_handler.h: -------------------------------------------------------------------------------- 1 | #ifndef INCLUDE_CAFFE_UTIL_SIGNAL_HANDLER_H_ 2 | #define INCLUDE_CAFFE_UTIL_SIGNAL_HANDLER_H_ 3 | 4 | #include "caffe/proto/caffe.pb.h" 5 | #include "caffe/solver.hpp" 6 | 7 | namespace caffe { 8 | 9 | class SignalHandler { 10 | public: 11 | // Contructor. Specify what action to take when a signal is received. 12 | SignalHandler(SolverAction::Enum SIGINT_action, 13 | SolverAction::Enum SIGHUP_action); 14 | ~SignalHandler(); 15 | ActionCallback GetActionFunction(); 16 | private: 17 | SolverAction::Enum CheckForSignals() const; 18 | SolverAction::Enum SIGINT_action_; 19 | SolverAction::Enum SIGHUP_action_; 20 | }; 21 | 22 | } // namespace caffe 23 | 24 | #endif // INCLUDE_CAFFE_UTIL_SIGNAL_HANDLER_H_ 25 | -------------------------------------------------------------------------------- /dependencies/pugixml/docs/samples/xgconsole.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | Jamplus build system 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/batchreindex.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Batch Reindex Layer 3 | --- 4 | 5 | # Batch Reindex Layer 6 | 7 | * Layer type: `BatchReindex` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1BatchReindexLayer.html) 9 | * Header: [`./include/caffe/layers/batch_reindex_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/batch_reindex_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/batch_reindex_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/batch_reindex_layer.cpp) 11 | * CUDA GPU implementation: [`./src/caffe/layers/batch_reindex_layer.cu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/batch_reindex_layer.cu) 12 | 13 | 14 | ## Parameters 15 | 16 | No parameters. 17 | -------------------------------------------------------------------------------- /dependencies/meta/install_libcxx.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env bash 2 | 3 | set -e 4 | 5 | # Checkout LLVM sources 6 | git clone --depth=1 https://github.com/llvm-mirror/llvm.git llvm-source 7 | git clone --depth=1 https://github.com/llvm-mirror/libcxx.git llvm-source/projects/libcxx 8 | git clone --depth=1 https://github.com/llvm-mirror/libcxxabi.git llvm-source/projects/libcxxabi 9 | 10 | # Build and install libc++ (Use unstable ABI for better sanitizer coverage) 11 | mkdir llvm-build && cd llvm-build 12 | cmake -DCMAKE_C_COMPILER=${C_COMPILER} -DCMAKE_CXX_COMPILER=${COMPILER} \ 13 | -DCMAKE_BUILD_TYPE=RelWithDebInfo -DCMAKE_INSTALL_PREFIX=/usr \ 14 | -DLIBCXX_ABI_UNSTABLE=ON \ 15 | -DLLVM_USE_SANITIZER=${SANITIZER} \ 16 | ../llvm-source 17 | make cxx -j2 18 | sudo make install-cxxabi install-cxx 19 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/kitti_surf.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | Name: 'SURF' 3 | hessianThreshold: 1000 4 | nOctaves: 1 5 | 6 | DescriptorExtractor: 7 | Name: 'SURF' 8 | hessianThreshold: 1000 9 | nOctaves: 1 10 | 11 | 12 | DescriptorMatcher: 13 | # normType: use 14 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 15 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 16 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 17 | # use L2 norm type as default when it is not especified 18 | Name: 'BruteForce' 19 | crossCheck: false 20 | 21 | MatchingCellSize: 15 22 | MatchingNeighborhood: 1 23 | MatchingDistance: 0.2 24 | EpipolarDistance: 1 25 | FrustumNearPlaneDist: 0.1 26 | FrustumFarPlaneDist: 10000.0 27 | BundleAdjustmentActiveKeyframes: 10 28 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/mobius.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'GFTT' 4 | 5 | nfeatures: 2000 6 | minDistance: 15.0 7 | qualityLevel: 0.01 8 | useHarrisDetector: false 9 | 10 | DescriptorExtractor: 11 | Name: 'BRIEF' 12 | bytes: 32 13 | 14 | # OpenCV3 15 | # use_orientation: false 16 | 17 | DescriptorMatcher: 18 | # normType: use 19 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 20 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 21 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 22 | Name: 'BruteForce-Hamming' 23 | crossCheck: false 24 | 25 | MatchingCellSize: 15 26 | MatchingNeighborhood: 1 27 | MatchingDistance: 30 28 | EpipolarDistance: 2 29 | FrustumNearPlaneDist: 0.1 30 | FrustumFarPlaneDist: 100.0 31 | BundleAdjustmentActiveKeyframes: 10 32 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/zed_vga.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'GFTT' 4 | 5 | nfeatures: 1000 6 | minDistance: 5.0 7 | qualityLevel: 0.01 8 | useHarrisDetector: false 9 | 10 | DescriptorExtractor: 11 | Name: 'BRIEF' 12 | bytes: 32 13 | 14 | # OpenCV3 15 | # use_orientation: false 16 | 17 | DescriptorMatcher: 18 | # normType: use 19 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 20 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 21 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 22 | Name: 'BruteForce-Hamming' 23 | crossCheck: false 24 | 25 | MatchingCellSize: 30 26 | MatchingNeighborhood: 2 27 | MatchingDistance: 20 28 | EpipolarDistance: 0 29 | FrustumNearPlaneDist: 0.1 30 | FrustumFarPlaneDist: 1000.0 31 | BundleAdjustmentActiveKeyframes: 10 32 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/rnn.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: RNN Layer 3 | --- 4 | 5 | # RNN Layer 6 | 7 | * Layer type: `RNN` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1RNNLayer.html) 9 | * Header: [`./include/caffe/layers/rnn_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/rnn_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/rnn_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/rnn_layer.cpp) 11 | 12 | ## Parameters 13 | 14 | * Parameters (`RecurrentParameter recurrent_param`) 15 | * From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto): 16 | 17 | {% highlight Protobuf %} 18 | {% include proto/RecurrentParameter.txt %} 19 | {% endhighlight %} 20 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/firefly.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'GFTT' 4 | 5 | nfeatures: 2000 6 | minDistance: 15.0 7 | qualityLevel: 0.01 8 | useHarrisDetector: false 9 | 10 | DescriptorExtractor: 11 | Name: 'BRIEF' 12 | bytes: 32 13 | 14 | # OpenCV3 15 | # use_orientation: false 16 | 17 | DescriptorMatcher: 18 | # normType: use 19 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 20 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 21 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 22 | Name: 'BruteForce-Hamming' 23 | crossCheck: false 24 | 25 | MatchingCellSize: 30 26 | MatchingNeighborhood: 1 27 | MatchingDistance: 25 28 | EpipolarDistance: 4 29 | FrustumNearPlaneDist: 0.1 30 | FrustumFarPlaneDist: 1000.0 31 | BundleAdjustmentActiveKeyframes: 10 32 | 33 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/kitti_star_latch.yaml: -------------------------------------------------------------------------------- 1 | %YAML:1.0 2 | 3 | FeatureDetector: 4 | 5 | Name: 'STAR' 6 | 7 | maxSize: 16 8 | responseThreshold: 20 9 | suppressNonmaxSize: 5 10 | 11 | DescriptorExtractor: 12 | Name: 'LATCH' 13 | bytes: 32 14 | rotationInvariance: false 15 | half_ssd_size: 3 16 | 17 | DescriptorMatcher: 18 | # normType: use 19 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 20 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 21 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 22 | Name: 'BruteForce-Hamming' 23 | crossCheck: false 24 | 25 | MatchingCellSize: 15 26 | MatchingNeighborhood: 1 27 | MatchingDistance: 45 28 | EpipolarDistance: 0 29 | FrustumNearPlaneDist: 0.1 30 | FrustumFarPlaneDist: 10000.0 31 | BundleAdjustmentActiveKeyframes: 10 32 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/cmake/Modules/FindNCCL.cmake: -------------------------------------------------------------------------------- 1 | set(NCCL_INC_PATHS 2 | /usr/include 3 | /usr/local/include 4 | $ENV{NCCL_DIR}/include 5 | ) 6 | 7 | set(NCCL_LIB_PATHS 8 | /lib 9 | /lib64 10 | /usr/lib 11 | /usr/lib64 12 | /usr/local/lib 13 | /usr/local/lib64 14 | $ENV{NCCL_DIR}/lib 15 | ) 16 | 17 | find_path(NCCL_INCLUDE_DIR NAMES nccl.h PATHS ${NCCL_INC_PATHS}) 18 | find_library(NCCL_LIBRARIES NAMES nccl PATHS ${NCCL_LIB_PATHS}) 19 | 20 | include(FindPackageHandleStandardArgs) 21 | find_package_handle_standard_args(NCCL DEFAULT_MSG NCCL_INCLUDE_DIR NCCL_LIBRARIES) 22 | 23 | if (NCCL_FOUND) 24 | message(STATUS "Found NCCL (include: ${NCCL_INCLUDE_DIR}, library: ${NCCL_LIBRARIES})") 25 | mark_as_advanced(NCCL_INCLUDE_DIR NCCL_LIBRARIES) 26 | endif () 27 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/input.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Input Layer 3 | --- 4 | 5 | # Input Layer 6 | 7 | * Layer type: `Input` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1InputLayer.html) 9 | * Header: [`./include/caffe/layers/input_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/input_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/input_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/input_layer.cpp) 11 | 12 | ## Parameters 13 | 14 | * Parameters (`InputParameter input_param`) 15 | * From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto)): 16 | 17 | {% highlight Protobuf %} 18 | {% include proto/InputParameter.txt %} 19 | {% endhighlight %} 20 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/bumblebee.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'GFTT' 4 | 5 | nfeatures: 2000 6 | minDistance: 15.0 7 | qualityLevel: 0.01 8 | useHarrisDetector: false 9 | 10 | DescriptorExtractor: 11 | Name: 'BRIEF' 12 | bytes: 32 13 | 14 | # OpenCV3 15 | # use_orientation: false 16 | 17 | DescriptorMatcher: 18 | # normType: use 19 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 20 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 21 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 22 | Name: 'BruteForce-Hamming' 23 | crossCheck: false 24 | 25 | MatchingCellSize: 15 26 | MatchingNeighborhood: 1 27 | MatchingDistance: 25 28 | EpipolarDistance: 0 29 | FrustumNearPlaneDist: 0.1 30 | FrustumFarPlaneDist: 100.0 31 | BundleAdjustmentActiveKeyframes: 10 32 | 33 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/kitti_orb.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'ORB' 4 | 5 | nFeatures: 2000 6 | scaleFactor: 1.2 7 | nLevels: 1 8 | edgeThreshold: 31 9 | 10 | DescriptorExtractor: 11 | Name: 'ORB' 12 | 13 | nFeatures: 2000 14 | scaleFactor: 1.2 15 | nLevels: 1 16 | edgeThreshold: 31 17 | 18 | DescriptorMatcher: 19 | # normType: use 20 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 21 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 22 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 23 | Name: 'BruteForce-Hamming' 24 | crossCheck: false 25 | 26 | MatchingCellSize: 15 27 | MatchingNeighborhood: 1 28 | MatchingDistance: 50 29 | EpipolarDistance: 0 30 | FrustumNearPlaneDist: 0.1 31 | FrustumFarPlaneDist: 10000.0 32 | BundleAdjustmentActiveKeyframes: 10 33 | -------------------------------------------------------------------------------- /dependencies/pugixml/docs/samples/save_declaration.cpp: -------------------------------------------------------------------------------- 1 | #include "pugixml.hpp" 2 | 3 | #include 4 | 5 | int main() 6 | { 7 | // tag::code[] 8 | // get a test document 9 | pugi::xml_document doc; 10 | doc.load_string("hey"); 11 | 12 | // add a custom declaration node 13 | pugi::xml_node decl = doc.prepend_child(pugi::node_declaration); 14 | decl.append_attribute("version") = "1.0"; 15 | decl.append_attribute("encoding") = "UTF-8"; 16 | decl.append_attribute("standalone") = "no"; 17 | 18 | // 19 | // 20 | // hey 21 | // 22 | doc.save(std::cout); 23 | std::cout << std::endl; 24 | // end::code[] 25 | } 26 | 27 | // vim:et 28 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/argmax.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: ArgMax Layer 3 | --- 4 | 5 | # ArgMax Layer 6 | 7 | * Layer type: `ArgMax` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1ArgMaxLayer.html) 9 | * Header: [`./include/caffe/layers/argmax_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/argmax_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/argmax_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/argmax_layer.cpp) 11 | 12 | ## Parameters 13 | * Parameters (`ArgMaxParameter argmax_param`) 14 | * From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto)): 15 | 16 | {% highlight Protobuf %} 17 | {% include proto/ArgMaxParameter.txt %} 18 | {% endhighlight %} 19 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/im2col.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Im2col Layer 3 | --- 4 | 5 | # im2col 6 | 7 | * File type: `Im2col` 8 | * Header: [`./include/caffe/layers/im2col_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/im2col_layer.hpp) 9 | * CPU implementation: [`./src/caffe/layers/im2col_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/im2col_layer.cpp) 10 | * CUDA GPU implementation: [`./src/caffe/layers/im2col_layer.cu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/im2col_layer.cu) 11 | 12 | `Im2col` is a helper for doing the image-to-column transformation that you most 13 | likely do not need to know about. This is used in Caffe's original convolution 14 | to do matrix multiplication by laying out all patches into a matrix. 15 | 16 | 17 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/tanh.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: TanH Layer 3 | --- 4 | 5 | # TanH Layer 6 | 7 | * Header: [`./include/caffe/layers/tanh_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/tanh_layer.hpp) 8 | * CPU implementation: [`./src/caffe/layers/tanh_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/tanh_layer.cpp) 9 | * CUDA GPU implementation: [`./src/caffe/layers/tanh_layer.cu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/tanh_layer.cu) 10 | 11 | ## Parameters 12 | 13 | * Parameters (`TanHParameter tanh_param`) 14 | * From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto): 15 | 16 | {% highlight Protobuf %} 17 | {% include proto/TanHParameter.txt %} 18 | {% endhighlight %} 19 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/src/caffe/util/db_leveldb.cpp: -------------------------------------------------------------------------------- 1 | #ifdef USE_LEVELDB 2 | #include "caffe/util/db_leveldb.hpp" 3 | 4 | #include 5 | 6 | namespace caffe { namespace db { 7 | 8 | void LevelDB::Open(const string& source, Mode mode) { 9 | leveldb::Options options; 10 | options.block_size = 65536; 11 | options.write_buffer_size = 268435456; 12 | options.max_open_files = 100; 13 | options.error_if_exists = mode == NEW; 14 | options.create_if_missing = mode != READ; 15 | leveldb::Status status = leveldb::DB::Open(options, source, &db_); 16 | CHECK(status.ok()) << "Failed to open leveldb " << source 17 | << std::endl << status.ToString(); 18 | LOG(INFO) << "Opened leveldb " << source; 19 | } 20 | 21 | } // namespace db 22 | } // namespace caffe 23 | #endif // USE_LEVELDB 24 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/euroc_fast_brief.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'FAST' 4 | 5 | threshold: 60 6 | nonmaxSuppression: true 7 | 8 | DescriptorExtractor: 9 | Name: 'BRIEF' 10 | bytes: 32 11 | 12 | DescriptorMatcher: 13 | # normType: use 14 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 15 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 16 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 17 | Name: 'BruteForce-Hamming' 18 | crossCheck: false 19 | 20 | MatchingCellSize: 30 21 | MatchingNeighborhood: 1 22 | MatchingDistance: 25 23 | EpipolarDistance: 1 24 | FrustumNearPlaneDist: 0.1 25 | FrustumFarPlaneDist: 50.0 26 | BundleAdjustmentActiveKeyframes: 10 27 | minimumTrackedPointsRatio: 0.7 28 | 29 | 30 | LoopDetectorVocabulary: '/home/gcastro/mit_malaga_vocabulary.yml.gz' 31 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/kitti_gftt_latch.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'GFTT' 4 | 5 | nfeatures: 2000 6 | minDistance: 15.0 7 | qualityLevel: 0.01 8 | useHarrisDetector: false 9 | 10 | DescriptorExtractor: 11 | Name: 'LATCH' 12 | bytes: 32 13 | rotationInvariance: false 14 | half_ssd_size: 3 15 | 16 | 17 | DescriptorMatcher: 18 | # normType: use 19 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 20 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 21 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 22 | Name: 'BruteForce-Hamming' 23 | crossCheck: false 24 | 25 | MatchingCellSize: 15 26 | MatchingNeighborhood: 1 27 | MatchingDistance: 45 28 | EpipolarDistance: 0 29 | FrustumNearPlaneDist: 0.1 30 | FrustumFarPlaneDist: 10000.0 31 | BundleAdjustmentActiveKeyframes: 10 32 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/level7.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'GFTT' 4 | 5 | nfeatures: 1000 6 | minDistance: 15.0 7 | qualityLevel: 0.01 8 | useHarrisDetector: false 9 | 10 | DescriptorExtractor: 11 | Name: 'BRIEF' 12 | bytes: 32 13 | 14 | DescriptorMatcher: 15 | # normType: use 16 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 17 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 18 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 19 | Name: 'BruteForce-Hamming' 20 | crossCheck: false 21 | 22 | MatchingCellSize: 30 23 | MatchingNeighborhood: 1 24 | MatchingDistance: 25 25 | EpipolarDistance: 0 26 | FrustumNearPlaneDist: 0.1 27 | FrustumFarPlaneDist: 10000.0 28 | BundleAdjustmentActiveKeyframes: 10 29 | 30 | LoopDetectorVocabulary: '/home/gcastro/mit_malaga_vocabulary.yml.gz' 31 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/vrep_quad.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'GFTT' 4 | 5 | nfeatures: 200 6 | minDistance: 15.0 7 | qualityLevel: 0.01 8 | useHarrisDetector: false 9 | 10 | DescriptorExtractor: 11 | Name: 'BRIEF' 12 | bytes: 32 13 | 14 | DescriptorMatcher: 15 | # normType: use 16 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 17 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 18 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 19 | Name: 'BruteForce-Hamming' 20 | crossCheck: false 21 | 22 | MatchingCellSize: 20 23 | MatchingNeighborhood: 1 24 | MatchingDistance: 30 25 | EpipolarDistance: 3 26 | FrustumNearPlaneDist: 0.1 27 | FrustumFarPlaneDist: 1000.0 28 | BundleAdjustmentActiveKeyframes: 10 29 | 30 | LoopDetectorVocabulary: '/home/gcastro/mit_malaga_vocabulary.yml.gz' 31 | -------------------------------------------------------------------------------- /dependencies/pugixml/docs/samples/modify_remove.cpp: -------------------------------------------------------------------------------- 1 | #include "pugixml.hpp" 2 | 3 | #include 4 | 5 | int main() 6 | { 7 | pugi::xml_document doc; 8 | if (!doc.load_string("Simple node")) return -1; 9 | 10 | // tag::code[] 11 | // remove description node with the whole subtree 12 | pugi::xml_node node = doc.child("node"); 13 | node.remove_child("description"); 14 | 15 | // remove id attribute 16 | pugi::xml_node param = node.child("param"); 17 | param.remove_attribute("value"); 18 | 19 | // we can also remove nodes/attributes by handles 20 | pugi::xml_attribute id = param.attribute("name"); 21 | param.remove_attribute(id); 22 | // end::code[] 23 | 24 | doc.print(std::cout); 25 | } 26 | 27 | // vim:et 28 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/spp.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Spatial Pyramid Pooling Layer 3 | --- 4 | 5 | # Spatial Pyramid Pooling Layer 6 | 7 | * Layer type: `SPP` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1SPPLayer.html) 9 | * Header: [`./include/caffe/layers/spp_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/spp_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/spp_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/spp_layer.cpp) 11 | 12 | 13 | ## Parameters 14 | 15 | * Parameters (`SPPParameter spp_param`) 16 | * From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto): 17 | 18 | {% highlight Protobuf %} 19 | {% include proto/SPPParameter.txt %} 20 | {% endhighlight %} 21 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/euroc_odroid_fast_brief.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'FAST' 4 | 5 | threshold: 60 6 | nonmaxSuppression: true 7 | 8 | DescriptorExtractor: 9 | Name: 'BRIEF' 10 | bytes: 32 11 | 12 | DescriptorMatcher: 13 | # normType: use 14 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 15 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 16 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 17 | Name: 'BruteForce-Hamming' 18 | crossCheck: false 19 | 20 | MatchingCellSize: 30 21 | MatchingNeighborhood: 1 22 | MatchingDistance: 25 23 | EpipolarDistance: 1 24 | FrustumNearPlaneDist: 0.1 25 | FrustumFarPlaneDist: 50.0 26 | BundleAdjustmentActiveKeyframes: 10 27 | minimumTrackedPointsRatio: 0.7 28 | 29 | 30 | LoopDetectorVocabulary: '/home/gcastro/mit_malaga_vocabulary.yml.gz' 31 | -------------------------------------------------------------------------------- /dependencies/pugixml/docs/samples/traverse_rangefor.cpp: -------------------------------------------------------------------------------- 1 | #include "pugixml.hpp" 2 | 3 | #include 4 | 5 | int main() 6 | { 7 | pugi::xml_document doc; 8 | if (!doc.load_file("xgconsole.xml")) return -1; 9 | 10 | pugi::xml_node tools = doc.child("Profile").child("Tools"); 11 | 12 | // tag::code[] 13 | for (pugi::xml_node tool: tools.children("Tool")) 14 | { 15 | std::cout << "Tool:"; 16 | 17 | for (pugi::xml_attribute attr: tool.attributes()) 18 | { 19 | std::cout << " " << attr.name() << "=" << attr.value(); 20 | } 21 | 22 | for (pugi::xml_node child: tool.children()) 23 | { 24 | std::cout << ", child " << child.name(); 25 | } 26 | 27 | std::cout << std::endl; 28 | } 29 | // end::code[] 30 | } 31 | 32 | // vim:et 33 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/euroc_star_brief.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'STAR' 4 | 5 | maxSize: 16 6 | responseThreshold: 30 7 | suppressNonmaxSize: 5 8 | 9 | DescriptorExtractor: 10 | Name: 'BRIEF' 11 | bytes: 32 12 | 13 | DescriptorMatcher: 14 | # normType: use 15 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 16 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 17 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 18 | Name: 'BruteForce-Hamming' 19 | crossCheck: false 20 | 21 | MatchingCellSize: 30 22 | MatchingNeighborhood: 1 23 | MatchingDistance: 25 24 | EpipolarDistance: 1 25 | FrustumNearPlaneDist: 0.1 26 | FrustumFarPlaneDist: 50.0 27 | BundleAdjustmentActiveKeyframes: 10 28 | minimumTrackedPointsRatio: 0.7 29 | 30 | LoopDetectorVocabulary: '/home/gcastro/mit_malaga_vocabulary.yml.gz' 31 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/euroc_odroid_star_brief.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'STAR' 4 | 5 | maxSize: 16 6 | responseThreshold: 40 7 | suppressNonmaxSize: 5 8 | 9 | DescriptorExtractor: 10 | Name: 'BRIEF' 11 | bytes: 32 12 | 13 | DescriptorMatcher: 14 | # normType: use 15 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 16 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 17 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 18 | Name: 'BruteForce-Hamming' 19 | crossCheck: false 20 | 21 | MatchingCellSize: 30 22 | MatchingNeighborhood: 1 23 | MatchingDistance: 25 24 | EpipolarDistance: 1 25 | FrustumNearPlaneDist: 0.1 26 | FrustumFarPlaneDist: 50.0 27 | BundleAdjustmentActiveKeyframes: 10 28 | minimumTrackedPointsRatio: 0.7 29 | 30 | LoopDetectorVocabulary: '/home/gcastro/mit_malaga_vocabulary.yml.gz' 31 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/kitti_gftt_lucid.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'GFTT' 4 | 5 | nfeatures: 2000 6 | minDistance: 15.0 7 | qualityLevel: 0.01 8 | useHarrisDetector: false 9 | 10 | DescriptorExtractor: 11 | Name: 'LUCID' 12 | 13 | lucid_kernel: 3 14 | blur_kernel: 3 15 | 16 | # OpenCV3 17 | # use_orientation: false 18 | 19 | DescriptorMatcher: 20 | # normType: use 21 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 22 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 23 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 24 | Name: 'BruteForce-Hamming' 25 | crossCheck: false 26 | 27 | MatchingCellSize: 15 28 | MatchingNeighborhood: 1 29 | MatchingDistance: 300 30 | EpipolarDistance: 1 31 | FrustumNearPlaneDist: 0.1 32 | FrustumFarPlaneDist: 10000.0 33 | BundleAdjustmentActiveKeyframes: 10 34 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/euroc_orb_brief.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'ORB' 4 | 5 | nFeatures: 200 6 | scaleFactor: 1.2 7 | nLevels: 1 8 | edgeThreshold: 31 9 | 10 | DescriptorExtractor: 11 | Name: 'BRIEF' 12 | bytes: 32 13 | 14 | DescriptorMatcher: 15 | # normType: use 16 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 17 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 18 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 19 | Name: 'BruteForce-Hamming' 20 | crossCheck: false 21 | 22 | MatchingCellSize: 15 23 | MatchingNeighborhood: 1 24 | MatchingDistance: 25 25 | EpipolarDistance: 1 26 | FrustumNearPlaneDist: 0.1 27 | FrustumFarPlaneDist: 50.0 28 | BundleAdjustmentActiveKeyframes: 10 29 | minimumTrackedPointsRatio: 0.7 30 | 31 | LoopDetectorVocabulary: '/home/gcastro/mit_malaga_vocabulary.yml.gz' 32 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/windowdata.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: WindowData Layer 3 | --- 4 | 5 | # WindowData Layer 6 | 7 | * Layer type: `WindowData` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1WindowDataLayer.html) 9 | * Header: [`./include/caffe/layers/window_data_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/window_data_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/window_data_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/window_data_layer.cpp) 11 | 12 | ## Parameters 13 | 14 | * Parameters (`WindowDataParameter`) 15 | * From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto): 16 | 17 | {% highlight Protobuf %} 18 | {% include proto/WindowDataParameter.txt %} 19 | {% endhighlight %} 20 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/include/caffe/util/nccl.hpp: -------------------------------------------------------------------------------- 1 | #ifndef CAFFE_UTIL_NCCL_H_ 2 | #define CAFFE_UTIL_NCCL_H_ 3 | #ifdef USE_NCCL 4 | 5 | #include 6 | 7 | #include "caffe/common.hpp" 8 | 9 | #define NCCL_CHECK(condition) \ 10 | { \ 11 | ncclResult_t result = condition; \ 12 | CHECK_EQ(result, ncclSuccess) << " " \ 13 | << ncclGetErrorString(result); \ 14 | } 15 | 16 | namespace caffe { 17 | 18 | namespace nccl { 19 | 20 | template class dataType; 21 | 22 | template<> class dataType { 23 | public: 24 | static const ncclDataType_t type = ncclFloat; 25 | }; 26 | template<> class dataType { 27 | public: 28 | static const ncclDataType_t type = ncclDouble; 29 | }; 30 | 31 | } // namespace nccl 32 | 33 | } // namespace caffe 34 | 35 | #endif // end USE_NCCL 36 | 37 | #endif // CAFFE_UTIL_NCCL_H_ 38 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/euroc_odroid_orb_brief.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'ORB' 4 | 5 | nFeatures: 200 6 | scaleFactor: 1.2 7 | nLevels: 1 8 | edgeThreshold: 31 9 | 10 | DescriptorExtractor: 11 | Name: 'BRIEF' 12 | bytes: 32 13 | 14 | DescriptorMatcher: 15 | # normType: use 16 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 17 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 18 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 19 | Name: 'BruteForce-Hamming' 20 | crossCheck: false 21 | 22 | MatchingCellSize: 15 23 | MatchingNeighborhood: 1 24 | MatchingDistance: 25 25 | EpipolarDistance: 1 26 | FrustumNearPlaneDist: 0.1 27 | FrustumFarPlaneDist: 50.0 28 | BundleAdjustmentActiveKeyframes: 5 29 | minimumTrackedPointsRatio: 0.7 30 | 31 | LoopDetectorVocabulary: '/home/gcastro/mit_malaga_vocabulary.yml.gz' 32 | -------------------------------------------------------------------------------- /ros/sptam/src/sptam/utils/timer.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | #include 3 | #include "timer.h" 4 | 5 | sptam::Timer::Timer(void) : 6 | elapsed_seconds(0) 7 | { 8 | 9 | } 10 | 11 | void sptam::Timer::start(void) 12 | { 13 | t = clock_t::now(); 14 | } 15 | 16 | void sptam::Timer::stop(void) 17 | { 18 | elapsed_seconds = std::chrono::duration(clock_t::now() - t).count() * 1e-3; 19 | } 20 | 21 | double sptam::Timer::elapsed(void) const 22 | { 23 | return elapsed_seconds; 24 | } 25 | 26 | double sptam::Timer::now() 27 | { 28 | return std::chrono::duration_cast(clock_t::now().time_since_epoch()).count() * 1e-6; 29 | } 30 | 31 | 32 | std::ostream& operator<< (std::ostream& stream, const sptam::Timer& t) 33 | { 34 | stream << std::setprecision(16) << std::fixed << t.elapsed(); 35 | return stream; 36 | } 37 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/kitti_surf_freak.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'SURF' 4 | hessianThreshold: 100 5 | nOctaves: 8 6 | nOctaveLayers: 7 7 | extended: false 8 | upright: false 9 | 10 | 11 | DescriptorExtractor: 12 | Name: 'FREAK' 13 | patternScale: 42.0 14 | orientationNormalized: true 15 | scaleNormalized: true 16 | nOctaves: 8 17 | 18 | DescriptorMatcher: 19 | # normType: use 20 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 21 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 22 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 23 | Name: 'BruteForce-Hamming' 24 | crossCheck: false 25 | 26 | MatchingCellSize: 15 27 | MatchingNeighborhood: 1 28 | MatchingDistance: 125 29 | EpipolarDistance: 1 30 | FrustumNearPlaneDist: 0.1 31 | FrustumFarPlaneDist: 10000.0 32 | BundleAdjustmentActiveKeyframes: 10 33 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/dummydata.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Dummy Data Layer 3 | --- 4 | 5 | # Dummy Data Layer 6 | 7 | * Layer type: `DummyData` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1DummyDataLayer.html) 9 | * Header: [`./include/caffe/layers/dummy_data_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/dummy_data_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/dummy_data_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/dummy_data_layer.cpp) 11 | 12 | 13 | ## Parameters 14 | 15 | * Parameters (`DummyDataParameter dummy_data_param`) 16 | * From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto)): 17 | 18 | {% highlight Protobuf %} 19 | {% include proto/DummyDataParameter.txt %} 20 | {% endhighlight %} 21 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/euroc_gftt_brief.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'GFTT' 4 | 5 | nfeatures: 2000 6 | minDistance: 15.0 7 | qualityLevel: 0.001 8 | useHarrisDetector: false 9 | 10 | DescriptorExtractor: 11 | Name: 'BRIEF' 12 | bytes: 32 13 | 14 | DescriptorMatcher: 15 | # normType: use 16 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 17 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 18 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 19 | Name: 'BruteForce-Hamming' 20 | crossCheck: false 21 | 22 | MatchingCellSize: 15 23 | MatchingNeighborhood: 2 24 | MatchingDistance: 25 25 | EpipolarDistance: 1 26 | FrustumNearPlaneDist: 0.1 27 | FrustumFarPlaneDist: 50.0 28 | BundleAdjustmentActiveKeyframes: 10 29 | minimumTrackedPointsRatio: 0.7 30 | 31 | LoopDetectorVocabulary: '/home/gcastro/mit_malaga_vocabulary.yml.gz' 32 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/hingeloss.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Hinge Loss Layer 3 | --- 4 | 5 | # Hinge (L1, L2) Loss Layer 6 | 7 | * Layer type: `HingeLoss` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1HingeLossLayer.html) 9 | * Header: [`./include/caffe/layers/hinge_loss_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/hinge_loss_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/hinge_loss_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/hinge_loss_layer.cpp) 11 | 12 | ## Parameters 13 | 14 | * Parameters (`HingeLossParameter hinge_loss_param`) 15 | * From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto): 16 | 17 | {% highlight Protobuf %} 18 | {% include proto/HingeLossParameter.txt %} 19 | {% endhighlight %} 20 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/threshold.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Threshold Layer 3 | --- 4 | 5 | # Threshold Layer 6 | 7 | * Header: [`./include/caffe/layers/threshold_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/threshold_layer.hpp) 8 | * CPU implementation: [`./src/caffe/layers/threshold_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/threshold_layer.cpp) 9 | * CUDA GPU implementation: [`./src/caffe/layers/threshold_layer.cu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/threshold_layer.cu) 10 | 11 | ## Parameters 12 | 13 | * Parameters (`ThresholdParameter threshold_param`) 14 | * From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto): 15 | 16 | {% highlight Protobuf %} 17 | {% include proto/ThresholdParameter.txt %} 18 | {% endhighlight %} 19 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/euroc_odroid_gftt_brief.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'GFTT' 4 | 5 | nfeatures: 200 6 | minDistance: 32.0 7 | qualityLevel: 0.001 8 | useHarrisDetector: false 9 | 10 | DescriptorExtractor: 11 | Name: 'BRIEF' 12 | bytes: 32 13 | 14 | DescriptorMatcher: 15 | # normType: use 16 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 17 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 18 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 19 | Name: 'BruteForce-Hamming' 20 | crossCheck: false 21 | 22 | MatchingCellSize: 15 23 | MatchingNeighborhood: 1 24 | MatchingDistance: 25 25 | EpipolarDistance: 1 26 | FrustumNearPlaneDist: 0.1 27 | FrustumFarPlaneDist: 50.0 28 | BundleAdjustmentActiveKeyframes: 5 29 | minimumTrackedPointsRatio: 0.7 30 | 31 | LoopDetectorVocabulary: '/home/gcastro/mit_malaga_vocabulary.yml.gz' 32 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/split.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Split Layer 3 | --- 4 | 5 | # Split Layer 6 | 7 | * Layer type: `Split` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1SplitLayer.html) 9 | * Header: [`./include/caffe/layers/split_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/split_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/split_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/split_layer.cpp) 11 | * CUDA GPU implementation: [`./src/caffe/layers/split_layer.cu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/split_layer.cu) 12 | 13 | The `Split` layer is a utility layer that splits an input blob to multiple output blobs. This is used when a blob is fed into multiple output layers. 14 | 15 | ## Parameters 16 | 17 | Does not take any parameters. 18 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/src/caffe/layers/silence_layer.cu: -------------------------------------------------------------------------------- 1 | #include 2 | 3 | #include "caffe/layers/silence_layer.hpp" 4 | #include "caffe/util/math_functions.hpp" 5 | 6 | namespace caffe { 7 | 8 | template 9 | void SilenceLayer::Forward_gpu(const vector*>& bottom, 10 | const vector*>& top) { 11 | // Do nothing. 12 | } 13 | 14 | template 15 | void SilenceLayer::Backward_gpu(const vector*>& top, 16 | const vector& propagate_down, const vector*>& bottom) { 17 | for (int i = 0; i < bottom.size(); ++i) { 18 | if (propagate_down[i]) { 19 | caffe_gpu_set(bottom[i]->count(), Dtype(0), 20 | bottom[i]->mutable_gpu_diff()); 21 | } 22 | } 23 | } 24 | 25 | INSTANTIATE_LAYER_GPU_FUNCS(SilenceLayer); 26 | 27 | } // namespace caffe 28 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/src/caffe/solvers/sgd_solver.cu: -------------------------------------------------------------------------------- 1 | #include "caffe/util/math_functions.hpp" 2 | 3 | 4 | namespace caffe { 5 | 6 | template 7 | __global__ void SGDUpdate(int N, Dtype* g, Dtype* h, 8 | Dtype momentum, Dtype local_rate) { 9 | CUDA_KERNEL_LOOP(i, N) { 10 | g[i] = h[i] = momentum*h[i] + local_rate*g[i]; 11 | } 12 | } 13 | template 14 | void sgd_update_gpu(int N, Dtype* g, Dtype* h, Dtype momentum, 15 | Dtype local_rate) { 16 | SGDUpdate // NOLINT_NEXT_LINE(whitespace/operators) 17 | <<>>( 18 | N, g, h, momentum, local_rate); 19 | CUDA_POST_KERNEL_CHECK; 20 | } 21 | template void sgd_update_gpu(int, float*, float*, float, float); 22 | template void sgd_update_gpu(int, double*, double*, double, double); 23 | 24 | } // namespace caffe 25 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/kitti.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'GFTT' 4 | 5 | nfeatures: 2000 6 | minDistance: 15.0 7 | qualityLevel: 0.01 8 | useHarrisDetector: false 9 | 10 | DescriptorExtractor: 11 | Name: 'BRIEF' 12 | bytes: 32 13 | 14 | # OpenCV3 15 | # use_orientation: false 16 | 17 | DescriptorMatcher: 18 | # normType: use 19 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 20 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 21 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 22 | Name: 'BruteForce-Hamming' 23 | crossCheck: false 24 | 25 | MatchingCellSize: 15 26 | MatchingNeighborhood: 1 27 | MatchingDistance: 25 28 | EpipolarDistance: 0 29 | FrustumNearPlaneDist: 0.1 30 | FrustumFarPlaneDist: 10000.0 31 | BundleAdjustmentActiveKeyframes: 10 32 | 33 | LoopDetectorVocabulary: '/home/gcastro/mit_malaga_vocabulary.yml.gz' 34 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/sigmoidcrossentropyloss.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Sigmoid Cross-Entropy Loss Layer 3 | --- 4 | 5 | # Sigmoid Cross-Entropy Loss Layer 6 | 7 | * Layer type: `SigmoidCrossEntropyLoss` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1SigmoidCrossEntropyLossLayer.html) 9 | * Header: [`./include/caffe/layers/sigmoid_cross_entropy_loss_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/sigmoid_cross_entropy_loss_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/sigmoid_cross_entropy_loss_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/sigmoid_cross_entropy_loss_layer.cpp) 11 | * CUDA GPU implementation: [`./src/caffe/layers/sigmoid_cross_entropy_loss_layer.cu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/sigmoid_cross_entropy_loss_layer.cu) 12 | 13 | To-do. 14 | -------------------------------------------------------------------------------- /py-faster-rcnn/lib/rpn/README.md: -------------------------------------------------------------------------------- 1 | ### `rpn` module overview 2 | 3 | ##### `generate_anchors.py` 4 | 5 | Generates a regular grid of multi-scale, multi-aspect anchor boxes. 6 | 7 | ##### `proposal_layer.py` 8 | 9 | Converts RPN outputs (per-anchor scores and bbox regression estimates) into object proposals. 10 | 11 | ##### `anchor_target_layer.py` 12 | 13 | Generates training targets/labels for each anchor. Classification labels are 1 (object), 0 (not object) or -1 (ignore). 14 | Bbox regression targets are specified when the classification label is > 0. 15 | 16 | ##### `proposal_target_layer.py` 17 | 18 | Generates training targets/labels for each object proposal: classification labels 0 - K (bg or object class 1, ... , K) 19 | and bbox regression targets in that case that the label is > 0. 20 | 21 | ##### `generate.py` 22 | 23 | Generate object detection proposals from an imdb using an RPN. 24 | -------------------------------------------------------------------------------- /ros/sptam/src/sptam/utils/projection_derivatives.hpp: -------------------------------------------------------------------------------- 1 | //////////////////////////////////////////////////////////////////////////////// 2 | // Jacobian computation functions. functions with a '2' suffix are the versions 3 | // using my own calculations for what should be the projection derivatives. 4 | // The other functions are the versions given and used by by g2o for BA. 5 | 6 | #include 7 | 8 | namespace Eigen 9 | { 10 | typedef Matrix Matrix9d; 11 | } 12 | 13 | Eigen::Matrix jacobianXj(const Eigen::Matrix& camera_transform, const Eigen::Matrix3d& Kcam, const Eigen::Vector3d& point_world); 14 | 15 | Eigen::Matrix jacobianXi(const Eigen::Matrix& camera_transform, const Eigen::Matrix3d& Kcam, const Eigen::Vector3d& point_world); 16 | 17 | //////////////////////////////////////////////////////////////////////////////// 18 | -------------------------------------------------------------------------------- /dependencies/pugixml/docs/samples/modify_add.cpp: -------------------------------------------------------------------------------- 1 | #include "pugixml.hpp" 2 | 3 | #include 4 | 5 | int main() 6 | { 7 | pugi::xml_document doc; 8 | 9 | // tag::code[] 10 | // add node with some name 11 | pugi::xml_node node = doc.append_child("node"); 12 | 13 | // add description node with text child 14 | pugi::xml_node descr = node.append_child("description"); 15 | descr.append_child(pugi::node_pcdata).set_value("Simple node"); 16 | 17 | // add param node before the description 18 | pugi::xml_node param = node.insert_child_before("param", descr); 19 | 20 | // add attributes to param node 21 | param.append_attribute("name") = "version"; 22 | param.append_attribute("value") = 1.1; 23 | param.insert_attribute_after("type", param.attribute("name")) = "float"; 24 | // end::code[] 25 | 26 | doc.print(std::cout); 27 | } 28 | 29 | // vim:et 30 | -------------------------------------------------------------------------------- /dependencies/pugixml/docs/samples/save_subtree.cpp: -------------------------------------------------------------------------------- 1 | #include "pugixml.hpp" 2 | 3 | #include 4 | 5 | int main() 6 | { 7 | // tag::code[] 8 | // get a test document 9 | pugi::xml_document doc; 10 | doc.load_string("hey"); 11 | 12 | // print document to standard output (prints hey) 13 | doc.save(std::cout, "", pugi::format_raw); 14 | std::cout << std::endl; 15 | 16 | // print document to standard output as a regular node (prints hey) 17 | doc.print(std::cout, "", pugi::format_raw); 18 | std::cout << std::endl; 19 | 20 | // print a subtree to standard output (prints hey) 21 | doc.child("foo").child("call").print(std::cout, "", pugi::format_raw); 22 | std::cout << std::endl; 23 | // end::code[] 24 | } 25 | 26 | // vim:et 27 | -------------------------------------------------------------------------------- /ros/dl_node/src/_init_paths.py: -------------------------------------------------------------------------------- 1 | # -------------------------------------------------------- 2 | # Fast R-CNN 3 | # Copyright (c) 2015 Microsoft 4 | # Licensed under The MIT License [see LICENSE for details] 5 | # Written by Ross Girshick 6 | # -------------------------------------------------------- 7 | 8 | """Set up paths for Fast R-CNN.""" 9 | 10 | import os.path as osp 11 | import sys 12 | 13 | def add_path(path): 14 | if path not in sys.path: 15 | sys.path.insert(0, path) 16 | 17 | ##this_dir = osp.dirname(__file__) 18 | 19 | # Add caffe to PYTHONPATH 20 | ## Hardcoded 21 | caffe_path = osp.join('/','usr','local','python', 'caffe') 22 | add_path(caffe_path) 23 | 24 | # Add lib to PYTHONPATH 25 | ## Hardcoded 26 | lib_path = osp.join('/','usr','local','lib') 27 | add_path(lib_path) 28 | 29 | #tools_path = osp.join('/','home','javier','rcnn','py-faster-rcnn' ,'tools') 30 | #add_path(tools_path) 31 | 32 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/kitti_agast_brisk.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'AGAST' 4 | 5 | threshold: 60 6 | nonmaxSuppression: true 7 | 8 | DescriptorExtractor: 9 | Name: 'BRISK' 10 | 11 | # OpenCV2 12 | # orientationNormalized: 'true' 13 | # scaleNormalized: 'true' 14 | # patternScale: '22.0' 15 | 16 | # OpenCV3 17 | # thresh: '30' 18 | # octaves: '3' 19 | # patternScale: '1.0' 20 | 21 | DescriptorMatcher: 22 | # normType: use 23 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 24 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 25 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 26 | Name: 'BruteForce-Hamming' 27 | crossCheck: false 28 | 29 | MatchingCellSize: 15 30 | MatchingNeighborhood: 1 31 | MatchingDistance: 100 32 | EpipolarDistance: 0 33 | FrustumNearPlaneDist: 0.1 34 | FrustumFarPlaneDist: 10000.0 35 | BundleAdjustmentActiveKeyframes: 10 36 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/kitti_fast_brisk.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'FAST' 4 | 5 | threshold: 60 6 | nonmaxSuppression: true 7 | 8 | DescriptorExtractor: 9 | Name: 'BRISK' 10 | 11 | # OpenCV2 12 | # orientationNormalized: 'true' 13 | # scaleNormalized: 'true' 14 | # patternScale: '22.0' 15 | 16 | # OpenCV3 17 | # thresh: '30' 18 | # octaves: '3' 19 | # patternScale: '1.0' 20 | 21 | DescriptorMatcher: 22 | # normType: use 23 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 24 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 25 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 26 | Name: 'BruteForce-Hamming' 27 | crossCheck: false 28 | 29 | MatchingCellSize: 15 30 | MatchingNeighborhood: 1 31 | MatchingDistance: 100 32 | EpipolarDistance: 0 33 | FrustumNearPlaneDist: 0.1 34 | FrustumFarPlaneDist: 10000.0 35 | BundleAdjustmentActiveKeyframes: 10 36 | 37 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/python/caffe/__init__.py: -------------------------------------------------------------------------------- 1 | ##<<<<<<< HEAD 2 | from .pycaffe import Net, SGDSolver, NesterovSolver, AdaGradSolver, RMSPropSolver, AdaDeltaSolver, AdamSolver 3 | from ._caffe import set_mode_cpu, set_mode_gpu, set_device, Layer, get_solver, layer_type_list, set_random_seed 4 | ##======= 5 | ##from .pycaffe import Net, SGDSolver, NesterovSolver, AdaGradSolver, RMSPropSolver, AdaDeltaSolver, AdamSolver, NCCL, Timer 6 | ##from ._caffe import init_log, log, set_mode_cpu, set_mode_gpu, set_device, Layer, get_solver, layer_type_list, set_random_seed, solver_count, set_solver_count, solver_rank, set_solver_rank, set_multiprocess, Layer, get_solver 7 | ##>>>>>>> caffe/master 8 | from ._caffe import __version__ 9 | from .proto.caffe_pb2 import TRAIN, TEST 10 | from .classifier import Classifier 11 | from .detector import Detector 12 | from . import io 13 | from .net_spec import layers, params, NetSpec, to_proto 14 | -------------------------------------------------------------------------------- /ros/sptam/README.md: -------------------------------------------------------------------------------- 1 | S-PTAM is a Stereo SLAM system able to compute the camera trajectory in real-time. It heavily exploits the parallel nature of the SLAM problem, separating the time-constrained pose estimation from less pressing matters such as map building and refinement tasks. On the other hand, the stereo setting allows to reconstruct a metric 3D map for each frame of stereo images, improving the accuracy of the mapping process with respect to monocular SLAM and avoiding the well-known bootstrapping problem. Also, the real scale of the environment is an essential feature for robots which have to interact with their surrounding workspace. 2 | 3 | You should have received this sptam version along with object-detection-sptam (https://github.com/CIFASIS/object-detection-sptam). 4 | See the original sptam library at: https://github.com/CIFASIS/sptam/tree/s-ptam-iros2015. 5 | All files included in this sptam version are GPLv3 license. 6 | 7 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/euroc_orb.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'ORB' 4 | 5 | nFeatures: 200 6 | scaleFactor: 1.2 7 | nLevels: 1 8 | edgeThreshold: 31 9 | 10 | DescriptorExtractor: 11 | Name: 'ORB' 12 | 13 | nFeatures: 200 14 | scaleFactor: 1.2 15 | nLevels: 1 16 | edgeThreshold: 31 17 | 18 | DescriptorMatcher: 19 | # normType: use 20 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 21 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 22 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 23 | Name: 'BruteForce-Hamming' 24 | crossCheck: false 25 | 26 | MatchingCellSize: 15 27 | MatchingNeighborhood: 1 28 | MatchingDistance: 50 29 | EpipolarDistance: 1 30 | FrustumNearPlaneDist: 0.1 31 | FrustumFarPlaneDist: 50.0 32 | BundleAdjustmentActiveKeyframes: 10 33 | minimumTrackedPointsRatio: 0.7 34 | 35 | LoopDetectorVocabulary: '/home/gcastro/mit_malaga_vocabulary.yml.gz' 36 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/log.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Log Layer 3 | --- 4 | 5 | # Log Layer 6 | 7 | * Layer type: `Log` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1LogLayer.html) 9 | * Header: [`./include/caffe/layers/log_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/log_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/log_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/log_layer.cpp) 11 | * CUDA GPU implementation: [`./src/caffe/layers/log_layer.cu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/log_layer.cu) 12 | 13 | ## Parameters 14 | 15 | * Parameters (`Parameter log_param`) 16 | * From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto): 17 | 18 | {% highlight Protobuf %} 19 | {% include proto/LogParameter.txt %} 20 | {% endhighlight %} 21 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/euroc_odroid_orb.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'ORB' 4 | 5 | nFeatures: 200 6 | scaleFactor: 1.2 7 | nLevels: 1 8 | edgeThreshold: 31 9 | 10 | DescriptorExtractor: 11 | Name: 'ORB' 12 | 13 | nFeatures: 200 14 | scaleFactor: 1.2 15 | nLevels: 1 16 | edgeThreshold: 31 17 | 18 | DescriptorMatcher: 19 | # normType: use 20 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 21 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 22 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 23 | Name: 'BruteForce-Hamming' 24 | crossCheck: false 25 | 26 | MatchingCellSize: 15 27 | MatchingNeighborhood: 1 28 | MatchingDistance: 50 29 | EpipolarDistance: 1 30 | FrustumNearPlaneDist: 0.1 31 | FrustumFarPlaneDist: 50.0 32 | BundleAdjustmentActiveKeyframes: 5 33 | minimumTrackedPointsRatio: 0.7 34 | 35 | LoopDetectorVocabulary: '/home/gcastro/mit_malaga_vocabulary.yml.gz' 36 | -------------------------------------------------------------------------------- /dependencies/pugixml/docs/samples/xpath_select.cpp: -------------------------------------------------------------------------------- 1 | #include "pugixml.hpp" 2 | 3 | #include 4 | 5 | int main() 6 | { 7 | pugi::xml_document doc; 8 | if (!doc.load_file("xgconsole.xml")) return -1; 9 | 10 | // tag::code[] 11 | pugi::xpath_node_set tools = doc.select_nodes("/Profile/Tools/Tool[@AllowRemote='true' and @DeriveCaptionFrom='lastparam']"); 12 | 13 | std::cout << "Tools:\n"; 14 | 15 | for (pugi::xpath_node_set::const_iterator it = tools.begin(); it != tools.end(); ++it) 16 | { 17 | pugi::xpath_node node = *it; 18 | std::cout << node.node().attribute("Filename").value() << "\n"; 19 | } 20 | 21 | pugi::xpath_node build_tool = doc.select_node("//Tool[contains(Description, 'build system')]"); 22 | 23 | if (build_tool) 24 | std::cout << "Build tool: " << build_tool.node().attribute("Filename").value() << "\n"; 25 | // end::code[] 26 | } 27 | 28 | // vim:et 29 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/absval.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Absolute Value Layer 3 | --- 4 | 5 | # Absolute Value Layer 6 | 7 | * Layer type: `AbsVal` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1AbsValLayer.html) 9 | * Header: [`./include/caffe/layers/absval_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/absval_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/absval_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/absval_layer.cpp) 11 | * CUDA GPU implementation: [`./src/caffe/layers/absval_layer.cu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/absval_layer.cu) 12 | 13 | * Sample 14 | 15 | layer { 16 | name: "layer" 17 | bottom: "in" 18 | top: "out" 19 | type: "AbsVal" 20 | } 21 | 22 | The `AbsVal` layer computes the output as abs(x) for each input element x. 23 | -------------------------------------------------------------------------------- /dependencies/pugixml/docs/samples/traverse_walker.cpp: -------------------------------------------------------------------------------- 1 | #include "pugixml.hpp" 2 | 3 | #include 4 | 5 | const char* node_types[] = 6 | { 7 | "null", "document", "element", "pcdata", "cdata", "comment", "pi", "declaration" 8 | }; 9 | 10 | // tag::impl[] 11 | struct simple_walker: pugi::xml_tree_walker 12 | { 13 | virtual bool for_each(pugi::xml_node& node) 14 | { 15 | for (int i = 0; i < depth(); ++i) std::cout << " "; // indentation 16 | 17 | std::cout << node_types[node.type()] << ": name='" << node.name() << "', value='" << node.value() << "'\n"; 18 | 19 | return true; // continue traversal 20 | } 21 | }; 22 | // end::impl[] 23 | 24 | int main() 25 | { 26 | pugi::xml_document doc; 27 | if (!doc.load_file("tree.xml")) return -1; 28 | 29 | // tag::traverse[] 30 | simple_walker walker; 31 | doc.traverse(walker); 32 | // end::traverse[] 33 | } 34 | 35 | // vim:et 36 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/bias.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Bias Layer 3 | --- 4 | 5 | # Bias Layer 6 | 7 | * Layer type: `Bias` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1BiasLayer.html) 9 | * Header: [`./include/caffe/layers/bias_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/bias_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/bias_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/bias_layer.cpp) 11 | * CUDA GPU implementation: [`./src/caffe/layers/bias_layer.cu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/bias_layer.cu) 12 | 13 | ## Parameters 14 | * Parameters (`BiasParameter bias_param`) 15 | * From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto)): 16 | 17 | {% highlight Protobuf %} 18 | {% include proto/BiasParameter.txt %} 19 | {% endhighlight %} 20 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/examples/mnist/lenet_auto_solver.prototxt: -------------------------------------------------------------------------------- 1 | # The train/test net protocol buffer definition 2 | train_net: "mnist/lenet_auto_train.prototxt" 3 | test_net: "mnist/lenet_auto_test.prototxt" 4 | # test_iter specifies how many forward passes the test should carry out. 5 | # In the case of MNIST, we have test batch size 100 and 100 test iterations, 6 | # covering the full 10,000 testing images. 7 | test_iter: 100 8 | # Carry out testing every 500 training iterations. 9 | test_interval: 500 10 | # The base learning rate, momentum and the weight decay of the network. 11 | base_lr: 0.01 12 | momentum: 0.9 13 | weight_decay: 0.0005 14 | # The learning rate policy 15 | lr_policy: "inv" 16 | gamma: 0.0001 17 | power: 0.75 18 | # Display every 100 iterations 19 | display: 100 20 | # The maximum number of iterations 21 | max_iter: 10000 22 | # snapshot intermediate results 23 | snapshot: 5000 24 | snapshot_prefix: "mnist/lenet" 25 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/crop.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Crop Layer 3 | --- 4 | 5 | # Crop Layer 6 | 7 | * Layer type: `Crop` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1CropLayer.html) 9 | * Header: [`./include/caffe/layers/crop_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/crop_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/crop_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/crop_layer.cpp) 11 | * CUDA GPU implementation: [`./src/caffe/layers/crop_layer.cu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/crop_layer.cu) 12 | 13 | ## Parameters 14 | 15 | * Parameters (`CropParameter crop_param`) 16 | * From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto)): 17 | 18 | {% highlight Protobuf %} 19 | {% include proto/CropParameter.txt %} 20 | {% endhighlight %} 21 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/tile.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Tile Layer 3 | --- 4 | 5 | # Tile Layer 6 | 7 | * Layer type: `Tile` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1TileLayer.html) 9 | * Header: [`./include/caffe/layers/tile_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/tile_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/tile_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/tile_layer.cpp) 11 | * CUDA GPU implementation: [`./src/caffe/layers/tile_layer.cu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/tile_layer.cu) 12 | 13 | ## Parameters 14 | 15 | * Parameters (`TileParameter tile_param`) 16 | * From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto): 17 | 18 | {% highlight Protobuf %} 19 | {% include proto/TileParameter.txt %} 20 | {% endhighlight %} 21 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/examples/mnist/lenet_adadelta_solver.prototxt: -------------------------------------------------------------------------------- 1 | # The train/test net protocol buffer definition 2 | net: "examples/mnist/lenet_train_test.prototxt" 3 | # test_iter specifies how many forward passes the test should carry out. 4 | # In the case of MNIST, we have test batch size 100 and 100 test iterations, 5 | # covering the full 10,000 testing images. 6 | test_iter: 100 7 | # Carry out testing every 500 training iterations. 8 | test_interval: 500 9 | # The base learning rate, momentum and the weight decay of the network. 10 | base_lr: 1.0 11 | lr_policy: "fixed" 12 | momentum: 0.95 13 | weight_decay: 0.0005 14 | # Display every 100 iterations 15 | display: 100 16 | # The maximum number of iterations 17 | max_iter: 10000 18 | # snapshot intermediate results 19 | snapshot: 5000 20 | snapshot_prefix: "examples/mnist/lenet_adadelta" 21 | # solver mode: CPU or GPU 22 | solver_mode: GPU 23 | type: "AdaDelta" 24 | delta: 1e-6 25 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/examples/mnist/lenet_solver.prototxt: -------------------------------------------------------------------------------- 1 | # The train/test net protocol buffer definition 2 | net: "examples/mnist/lenet_train_test.prototxt" 3 | # test_iter specifies how many forward passes the test should carry out. 4 | # In the case of MNIST, we have test batch size 100 and 100 test iterations, 5 | # covering the full 10,000 testing images. 6 | test_iter: 100 7 | # Carry out testing every 500 training iterations. 8 | test_interval: 500 9 | # The base learning rate, momentum and the weight decay of the network. 10 | base_lr: 0.01 11 | momentum: 0.9 12 | weight_decay: 0.0005 13 | # The learning rate policy 14 | lr_policy: "inv" 15 | gamma: 0.0001 16 | power: 0.75 17 | # Display every 100 iterations 18 | display: 100 19 | # The maximum number of iterations 20 | max_iter: 10000 21 | # snapshot intermediate results 22 | snapshot: 5000 23 | snapshot_prefix: "examples/mnist/lenet" 24 | # solver mode: CPU or GPU 25 | solver_mode: GPU 26 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/src/caffe/layers/loss_layer.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | 3 | #include "caffe/layers/loss_layer.hpp" 4 | 5 | namespace caffe { 6 | 7 | template 8 | void LossLayer::LayerSetUp( 9 | const vector*>& bottom, const vector*>& top) { 10 | // LossLayers have a non-zero (1) loss by default. 11 | if (this->layer_param_.loss_weight_size() == 0) { 12 | this->layer_param_.add_loss_weight(Dtype(1)); 13 | } 14 | } 15 | 16 | template 17 | void LossLayer::Reshape( 18 | const vector*>& bottom, const vector*>& top) { 19 | CHECK_EQ(bottom[0]->shape(0), bottom[1]->shape(0)) 20 | << "The data and label should have the same first dimension."; 21 | vector loss_shape(0); // Loss layers output a scalar; 0 axes. 22 | top[0]->Reshape(loss_shape); 23 | } 24 | 25 | INSTANTIATE_CLASS(LossLayer); 26 | 27 | } // namespace caffe 28 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/tools/CMakeLists.txt: -------------------------------------------------------------------------------- 1 | # Collect source files 2 | file(GLOB_RECURSE srcs ${CMAKE_CURRENT_SOURCE_DIR}/*.cpp) 3 | 4 | # Build each source file independently 5 | foreach(source ${srcs}) 6 | get_filename_component(name ${source} NAME_WE) 7 | 8 | # caffe target already exits 9 | if(name MATCHES "caffe") 10 | set(name ${name}.bin) 11 | endif() 12 | 13 | # target 14 | add_executable(${name} ${source}) 15 | target_link_libraries(${name} ${Caffe_LINK}) 16 | caffe_default_properties(${name}) 17 | 18 | # set back RUNTIME_OUTPUT_DIRECTORY 19 | caffe_set_runtime_directory(${name} "${PROJECT_BINARY_DIR}/tools") 20 | caffe_set_solution_folder(${name} tools) 21 | 22 | # restore output name without suffix 23 | if(name MATCHES "caffe.bin") 24 | set_target_properties(${name} PROPERTIES OUTPUT_NAME caffe) 25 | endif() 26 | 27 | # Install 28 | install(TARGETS ${name} DESTINATION bin) 29 | endforeach(source) 30 | -------------------------------------------------------------------------------- /ros/sptam/plotters/parsers/ground_truth_loader.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | import mit_gt 3 | import kitti_gt 4 | import level7_gt 5 | import euroc_gt 6 | 7 | def addProgramOptions(parser, required=False): 8 | 9 | group = parser.add_mutually_exclusive_group(required=required) 10 | 11 | group.add_argument('--mit', help='Ground truth file for the MIT dataset.') 12 | group.add_argument('--kitti', help='Ground truth file for the KITTI dataset.') 13 | group.add_argument('--level7', help='Ground truth file for the level7 dataset.') 14 | group.add_argument('--euroc', help='Ground truth file for the euroc dataset.') 15 | 16 | def load( args ): 17 | 18 | if args.kitti: 19 | return kitti_gt.load( args.kitti ) 20 | 21 | if args.level7: 22 | return level7_gt.load( args.level7 ) 23 | 24 | if args.mit: 25 | return mit_gt.load( args.mit ) 26 | 27 | if args.euroc: 28 | return euroc_gt.load( args.euroc ) 29 | 30 | return None 31 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/embed.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Embed Layer 3 | --- 4 | 5 | # Embed Layer 6 | 7 | * Layer type: `Embed` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1EmbedLayer.html) 9 | * Header: [`./include/caffe/layers/embed_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/embed_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/embed_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/embed_layer.cpp) 11 | * CUDA GPU implementation: [`./src/caffe/layers/embed_layer.cu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/embed_layer.cu) 12 | 13 | ## Parameters 14 | 15 | * Parameters (`EmbedParameter embed_param`) 16 | * From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto): 17 | 18 | {% highlight Protobuf %} 19 | {% include proto/EmbedParameter.txt %} 20 | {% endhighlight %} 21 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/parameter.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Parameter Layer 3 | --- 4 | 5 | # Parameter Layer 6 | 7 | * Layer type: `Parameter` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1ParameterLayer.html) 9 | * Header: [`./include/caffe/layers/parameter_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/parameter_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/parameter_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/parameter_layer.cpp) 11 | 12 | See [https://github.com/BVLC/caffe/pull/2079](https://github.com/BVLC/caffe/pull/2079). 13 | 14 | ## Parameters 15 | 16 | * Parameters (`ParameterParameter parameter_param`) 17 | * From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto): 18 | 19 | {% highlight Protobuf %} 20 | {% include proto/ParameterParameter.txt %} 21 | {% endhighlight %} 22 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/prelu.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: PReLU Layer 3 | --- 4 | 5 | # PReLU Layer 6 | 7 | * Layer type: `PReLU` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1PReLULayer.html) 9 | * Header: [`./include/caffe/layers/prelu_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/prelu_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/prelu_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/prelu_layer.cpp) 11 | * CUDA GPU implementation: [`./src/caffe/layers/prelu_layer.cu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/prelu_layer.cu) 12 | 13 | ## Parameters 14 | 15 | * Parameters (`PReLUParameter prelu_param`) 16 | * From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto): 17 | 18 | {% highlight Protobuf %} 19 | {% include proto/PReLUParameter.txt %} 20 | {% endhighlight %} 21 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/scale.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Scale Layer 3 | --- 4 | 5 | # Scale Layer 6 | 7 | * Layer type: `Scale` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1ScaleLayer.html) 9 | * Header: [`./include/caffe/layers/scale_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/scale_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/scale_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/scale_layer.cpp) 11 | * CUDA GPU implementation: [`./src/caffe/layers/scale_layer.cu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/scale_layer.cu) 12 | 13 | ## Parameters 14 | 15 | * Parameters (`ScaleParameter scale_param`) 16 | * From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto): 17 | 18 | {% highlight Protobuf %} 19 | {% include proto/ScaleParameter.txt %} 20 | {% endhighlight %} 21 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/src/caffe/layers/base_data_layer.cu: -------------------------------------------------------------------------------- 1 | #include 2 | 3 | #include "caffe/layers/base_data_layer.hpp" 4 | 5 | namespace caffe { 6 | 7 | template 8 | void BasePrefetchingDataLayer::Forward_gpu( 9 | const vector*>& bottom, const vector*>& top) { 10 | if (prefetch_current_) { 11 | prefetch_free_.push(prefetch_current_); 12 | } 13 | prefetch_current_ = prefetch_full_.pop("Waiting for data"); 14 | // Reshape to loaded data. 15 | top[0]->ReshapeLike(prefetch_current_->data_); 16 | top[0]->set_gpu_data(prefetch_current_->data_.mutable_gpu_data()); 17 | if (this->output_labels_) { 18 | // Reshape to loaded labels. 19 | top[1]->ReshapeLike(prefetch_current_->label_); 20 | top[1]->set_gpu_data(prefetch_current_->label_.mutable_gpu_data()); 21 | } 22 | } 23 | 24 | INSTANTIATE_LAYER_GPU_FORWARD(BasePrefetchingDataLayer); 25 | 26 | } // namespace caffe 27 | -------------------------------------------------------------------------------- /ros/sptam/src/standAlone/Test/ReadImagesFromDir/ReadImagesFromDir.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | #include 3 | #include 4 | #include 5 | #include 6 | #include 7 | 8 | using namespace std; 9 | using namespace cv; 10 | 11 | int main() 12 | { 13 | vector filenames; // notice here that we are using the Opencv's embedded "String" class 14 | String folder = "/home/taihu/datasets/KITTI/00/image_0/"; // again we are using the Opencv's embedded "String" class 15 | 16 | glob(folder, filenames); // new function that does the job ;-) 17 | 18 | for(size_t i = 0; i < filenames.size(); ++i) 19 | { 20 | Mat src = imread(filenames[i]); 21 | 22 | if(!src.data) 23 | cerr << "Problem loading image!!!" << endl; 24 | else { 25 | imshow("output",src); 26 | waitKey(0); 27 | } 28 | } 29 | } 30 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/src/caffe/solvers/adagrad_solver.cu: -------------------------------------------------------------------------------- 1 | #include "caffe/util/math_functions.hpp" 2 | 3 | 4 | namespace caffe { 5 | 6 | template 7 | __global__ void AdaGradUpdate(int N, Dtype* g, Dtype* h, Dtype delta, 8 | Dtype local_rate) { 9 | CUDA_KERNEL_LOOP(i, N) { 10 | float gi = g[i]; 11 | float hi = h[i] = h[i] + gi*gi; 12 | g[i] = local_rate * gi / (sqrt(hi) + delta); 13 | } 14 | } 15 | template 16 | void adagrad_update_gpu(int N, Dtype* g, Dtype* h, Dtype delta, 17 | Dtype local_rate) { 18 | AdaGradUpdate // NOLINT_NEXT_LINE(whitespace/operators) 19 | <<>>( 20 | N, g, h, delta, local_rate); 21 | CUDA_POST_KERNEL_CHECK; 22 | } 23 | template void adagrad_update_gpu(int, float*, float*, float, float); 24 | template void adagrad_update_gpu(int, double*, double*, double, double); 25 | 26 | } // namespace caffe 27 | -------------------------------------------------------------------------------- /ros/dl_node/src/_init_paths_softnms.py: -------------------------------------------------------------------------------- 1 | # -------------------------------------------------------- 2 | # Fast R-CNN 3 | # Copyright (c) 2015 Microsoft 4 | # Licensed under The MIT License [see LICENSE for details] 5 | # Written by Ross Girshick 6 | # -------------------------------------------------------- 7 | 8 | """Set up paths for Fast R-CNN.""" 9 | 10 | import os.path as osp 11 | import sys 12 | 13 | def add_path(path): 14 | if path not in sys.path: 15 | sys.path.insert(0, path) 16 | 17 | ##this_dir = osp.dirname(__file__) 18 | 19 | # Add caffe to PYTHONPATH 20 | ## Hardcoded 21 | caffe_path = osp.join('/','home','javier','rcnn','soft-nms' ,'caffe', 'python') 22 | add_path(caffe_path) 23 | 24 | # Add lib to PYTHONPATH 25 | ## Hardcoded 26 | lib_path = osp.join('/','home','javier','rcnn','soft-nms','lib') 27 | add_path(lib_path) 28 | 29 | #tools_path = osp.join('/','home','javier','rcnn','py-faster-rcnn' ,'tools') 30 | #add_path(tools_path) 31 | 32 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/kitti_gftt_brisk.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'GFTT' 4 | 5 | nfeatures: 2000 6 | minDistance: 15.0 7 | qualityLevel: 0.01 8 | useHarrisDetector: false 9 | 10 | DescriptorExtractor: 11 | Name: 'BRISK' 12 | # OpenCV2 13 | # orientationNormalized: 'true' 14 | # scaleNormalized: 'true' 15 | # patternScale: '22.0' 16 | 17 | # OpenCV3 18 | # thresh: '30' 19 | # octaves: '3' 20 | # patternScale: '1.0' 21 | 22 | 23 | DescriptorMatcher: 24 | # normType: use 25 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 26 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 27 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 28 | Name: 'BruteForce-Hamming' 29 | crossCheck: false 30 | 31 | MatchingCellSize: 15 32 | MatchingNeighborhood: 1 33 | MatchingDistance: 100 34 | EpipolarDistance: 0 35 | FrustumNearPlaneDist: 0.1 36 | FrustumFarPlaneDist: 10000.0 37 | BundleAdjustmentActiveKeyframes: 10 38 | 39 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/kitti_star_brisk.yaml: -------------------------------------------------------------------------------- 1 | %YAML:1.0 2 | 3 | FeatureDetector: 4 | 5 | Name: 'STAR' 6 | 7 | maxSize: 16 8 | responseThreshold: 20 9 | suppressNonmaxSize: 5 10 | 11 | DescriptorExtractor: 12 | Name: 'BRISK' 13 | 14 | # OpenCV2 15 | # orientationNormalized: 'true' 16 | # scaleNormalized: 'true' 17 | # patternScale: '22.0' 18 | 19 | # OpenCV3 20 | # thresh: '30' 21 | # octaves: '3' 22 | # patternScale: '1.0' 23 | 24 | 25 | DescriptorMatcher: 26 | # normType: use 27 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 28 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 29 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 30 | Name: 'BruteForce-Hamming' 31 | crossCheck: 'false' 32 | 33 | MatchingCellSize: 15 34 | MatchingNeighborhood: 1 35 | MatchingDistance: 100 36 | EpipolarDistance: 0 37 | FrustumNearPlaneDist: 0.1 38 | FrustumFarPlaneDist: 10000.0 39 | BundleAdjustmentActiveKeyframes: 10 40 | 41 | -------------------------------------------------------------------------------- /dependencies/meta/readme.md: -------------------------------------------------------------------------------- 1 | # Meta: A tiny metaprogramming library 2 | 3 | [![Build Status](https://travis-ci.org/ericniebler/meta.svg?branch=master)](https://travis-ci.org/ericniebler/meta) 4 | 5 | *Meta* is a tiny and header-only C++11 metaprogramming library released under the 6 | Boost Software License. Supported compilers are clang >= 3.4 and gcc >= 4.9. To compile with meta you just have to: 7 | 8 | ```.cpp 9 | #include 10 | ``` 11 | 12 | You can find documentation online [here](https://ericniebler.github.io/meta/index.html). 13 | 14 | For a quick start see Eric Niebler's blog post: 15 | [A tiny metaprogramming library](http://ericniebler.com/2014/11/13/tiny-metaprogramming-library/). (Note: the names in Meta are different from those describe in the blog post, but the overall design remains the same.) 16 | 17 | To generate the up-to-date tutorial and documentation run `make doc` in the 18 | build directory (requires Doxygen, LaTeX, dvips, ghostscript). 19 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/bnll.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: BNLL Layer 3 | --- 4 | 5 | # BNLL Layer 6 | 7 | * Layer type: `BNLL` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1BNLLLayer.html) 9 | * Header: [`./include/caffe/layers/bnll_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/bnll_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/bnll_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/bnll_layer.cpp) 11 | * CUDA GPU implementation: [`./src/caffe/layers/bnll_layer.cu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/bnll_layer.cu) 12 | 13 | The `BNLL` (binomial normal log likelihood) layer computes the output as log(1 + exp(x)) for each input element x. 14 | 15 | ## Parameters 16 | No parameters. 17 | 18 | ## Sample 19 | 20 | layer { 21 | name: "layer" 22 | bottom: "in" 23 | top: "out" 24 | type: BNLL 25 | } 26 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/examples/siamese/mnist_siamese_solver.prototxt: -------------------------------------------------------------------------------- 1 | # The train/test net protocol buffer definition 2 | net: "examples/siamese/mnist_siamese_train_test.prototxt" 3 | # test_iter specifies how many forward passes the test should carry out. 4 | # In the case of MNIST, we have test batch size 100 and 100 test iterations, 5 | # covering the full 10,000 testing images. 6 | test_iter: 100 7 | # Carry out testing every 500 training iterations. 8 | test_interval: 500 9 | # The base learning rate, momentum and the weight decay of the network. 10 | base_lr: 0.01 11 | momentum: 0.9 12 | weight_decay: 0.0000 13 | # The learning rate policy 14 | lr_policy: "inv" 15 | gamma: 0.0001 16 | power: 0.75 17 | # Display every 100 iterations 18 | display: 100 19 | # The maximum number of iterations 20 | max_iter: 50000 21 | # snapshot intermediate results 22 | snapshot: 5000 23 | snapshot_prefix: "examples/siamese/mnist_siamese" 24 | # solver mode: CPU or GPU 25 | solver_mode: GPU 26 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/kitti_akaze.yaml: -------------------------------------------------------------------------------- 1 | FeatureDetector: 2 | 3 | Name: 'AKAZE' 4 | 5 | descriptor_type: 5 6 | descriptor_size: 0 7 | descriptor_channels: 1 8 | threshold: 0.005 9 | nOctaves: 1 10 | nOctaveLayers: 1 11 | diffusivity: 1 12 | 13 | DescriptorExtractor: 14 | Name: 'AKAZE' 15 | 16 | descriptor_type: 5 17 | descriptor_size: 0 18 | descriptor_channels: 1 19 | threshold: 0.005 20 | nOctaves: 1 21 | nOctaveLayers: 1 22 | diffusivity: 1 23 | 24 | DescriptorMatcher: 25 | # normType: use 26 | # - NORM_L1 or NORM_L2 for SIFT and SURF descriptors 27 | # - NORM_HAMMING for ORB, BRISK, and BRIEF 28 | # - NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 29 | Name: 'BruteForce-Hamming' 30 | crossCheck: false 31 | 32 | MatchingCellSize: 15 33 | MatchingNeighborhood: 1 34 | MatchingDistance: 15 35 | EpipolarDistance: 1 36 | FrustumNearPlaneDist: 0.1 37 | FrustumFarPlaneDist: 10000.0 38 | BundleAdjustmentActiveKeyframes: 10 39 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/euclideanloss.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Euclidean Loss Layer 3 | --- 4 | # Sum-of-Squares / Euclidean Loss Layer 5 | 6 | * Layer type: `EuclideanLoss` 7 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1EuclideanLossLayer.html) 8 | * Header: [`./include/caffe/layers/euclidean_loss_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/euclidean_loss_layer.hpp) 9 | * CPU implementation: [`./src/caffe/layers/euclidean_loss_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/euclidean_loss_layer.cpp) 10 | * CUDA GPU implementation: [`./src/caffe/layers/euclidean_loss_layer.cu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/euclidean_loss_layer.cu) 11 | 12 | The Euclidean loss layer computes the sum of squares of differences of its two inputs, $$\frac 1 {2N} \sum_{i=1}^N \| x^1_i - x^2_i \|_2^2$$. 13 | 14 | ## Parameters 15 | 16 | Does not take any parameters. 17 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/flatten.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Flatten Layer 3 | --- 4 | 5 | # Flatten Layer 6 | 7 | * Layer type: `Flatten` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1FlattenLayer.html) 9 | * Header: [`./include/caffe/layers/flatten_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/flatten_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/flatten_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/flatten_layer.cpp) 11 | 12 | The `Flatten` layer is a utility layer that flattens an input of shape `n * c * h * w` to a simple vector output of shape `n * (c*h*w)`. 13 | 14 | ## Parameters 15 | 16 | * Parameters (`FlattenParameter flatten_param`) 17 | * From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto): 18 | 19 | {% highlight Protobuf %} 20 | {% include proto/FlattenParameter.txt %} 21 | {% endhighlight %} 22 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/multinomiallogisticloss.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Multinomial Logistic Loss Layer 3 | --- 4 | 5 | # Multinomial Logistic Loss Layer 6 | 7 | * Layer type: `MultinomialLogisticLoss` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1MultinomialLogisticLossLayer.html) 9 | * Header: [`./include/caffe/layers/multinomial_logistic_loss_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/multinomial_logistic_loss_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/multinomial_logistic_loss_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/multinomial_logistic_loss_layer.cpp) 11 | 12 | ## Parameters 13 | 14 | * Parameters (`LossParameter loss_param`) 15 | * From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto): 16 | 17 | {% highlight Protobuf %} 18 | {% include proto/LossParameter.txt %} 19 | {% endhighlight %} 20 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/sigmoid.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Sigmoid Layer 3 | --- 4 | 5 | # Sigmoid Layer 6 | 7 | * Layer type: `Sigmoid` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1SigmoidLayer.html) 9 | * Header: [`./include/caffe/layers/sigmoid_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/sigmoid_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/sigmoid_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/sigmoid_layer.cpp) 11 | * CUDA GPU implementation: [`./src/caffe/layers/sigmoid_layer.cu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/sigmoid_layer.cu) 12 | 13 | ## Parameters 14 | 15 | * Parameters (`SigmoidParameter sigmoid_param`) 16 | * From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto): 17 | 18 | {% highlight Protobuf %} 19 | {% include proto/SigmoidParameter.txt %} 20 | {% endhighlight %} 21 | -------------------------------------------------------------------------------- /ros/sptam/configurationFiles/calibrations/00b09d0100626e63_left.yaml: -------------------------------------------------------------------------------- 1 | camera_matrix: 2 | cols: 3 3 | data: [524.1301433371835, 0.0, 315.4348325473679, 0.0, 523.5072606249538, 245.2304775179637, 4 | 0.0, 0.0, 1.0] 5 | rows: 3 6 | camera_name: 00b09d0100626e63_left 7 | distortion_coefficients: 8 | cols: 5 9 | data: [-0.3396282468279343, 0.1228228088191552, 0.00043662096897748227, 0.00022545714383195398, 10 | 0.0] 11 | rows: 1 12 | distortion_model: plumb_bob 13 | image_height: 480 14 | image_width: 640 15 | projection_matrix: 16 | cols: 4 17 | data: [419.1912564118346, 0.0, 324.0353889465332, 0.0, 0.0, 419.1912564118346, 249.37464714050293, 18 | 0.0, 0.0, 0.0, 1.0, 0.0] 19 | rows: 3 20 | rectification_matrix: 21 | cols: 3 22 | data: [0.9999661557612708, -0.0010506708961703429, -0.008159866585558536, 0.001029522374188195, 23 | 0.9999961016173224, -0.0025955411456627534, 0.008162561834817544, 0.002587052536328365, 24 | 0.9999633391997264] 25 | rows: 3 26 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/dropout.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Dropout Layer 3 | --- 4 | 5 | # Dropout Layer 6 | 7 | * Layer type: `Dropout` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1DropoutLayer.html) 9 | * Header: [`./include/caffe/layers/dropout_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/dropout_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/dropout_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/dropout_layer.cpp) 11 | * CUDA GPU implementation: [`./src/caffe/layers/dropout_layer.cu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/dropout_layer.cu) 12 | 13 | ## Parameters 14 | 15 | * Parameters (`DropoutParameter dropout_param`) 16 | * From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto)): 17 | 18 | {% highlight Protobuf %} 19 | {% include proto/DropoutParameter.txt %} 20 | {% endhighlight %} 21 | -------------------------------------------------------------------------------- /py-faster-rcnn/caffe-fast-rcnn/docs/tutorial/layers/eltwise.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: Eltwise Layer 3 | --- 4 | 5 | # Eltwise Layer 6 | 7 | * Layer type: `Eltwise` 8 | * [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1EltwiseLayer.html) 9 | * Header: [`./include/caffe/layers/eltwise_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/eltwise_layer.hpp) 10 | * CPU implementation: [`./src/caffe/layers/eltwise_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/eltwise_layer.cpp) 11 | * CUDA GPU implementation: [`./src/caffe/layers/eltwise_layer.cu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/eltwise_layer.cu) 12 | 13 | ## Parameters 14 | 15 | * Parameters (`EltwiseParameter eltwise_param`) 16 | * From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto)): 17 | 18 | {% highlight Protobuf %} 19 | {% include proto/EltwiseParameter.txt %} 20 | {% endhighlight %} 21 | --------------------------------------------------------------------------------