Add MocapNET

This commit is contained in:
Justin John
2023-12-15 04:22:41 +05:30
parent 8434144ded
commit 65e8934d5e
336 changed files with 100584 additions and 0 deletions
+378
View File
@@ -0,0 +1,378 @@
project( MocapNETProject )
cmake_minimum_required( VERSION 2.8.13 )
#Make fast, lean and platform independent binaries..
#The -fuse-ld=gold flag solves issue https://github.com/FORTH-ModelBasedTracker/MocapNET/issues/34
#However it causes https://github.com/FORTH-ModelBasedTracker/MocapNET/issues/38
set(CMAKE_CXX_FLAGS "-s -O3 -fPIC -march=native -mtune=native") #-fuse-ld=gold
set(CMAKE_C_FLAGS "-s -O3 -fPIC -march=native -mtune=native") #-fuse-ld=gold
OPTION(ENABLE_OPENGL OFF)
OPTION(INTEL_OPTIMIZATIONS OFF)
SET (CMAKE_MODULE_PATH ${CMAKE_MODULE_PATH} "${CMAKE_CURRENT_SOURCE_DIR}/cmake")
INCLUDE(FindSSE)
FindSSE ()
IF(SSE2_FOUND)
SET(INTEL_OPTIMIZATIONS ON)
MESSAGE("SSE2 detected and will be used..")
ENDIF(SSE2_FOUND)
if (INTEL_OPTIMIZATIONS)
add_definitions(-DINTEL_OPTIMIZATIONS)
endif(INTEL_OPTIMIZATIONS)
set_property(GLOBAL PROPERTY USE_FOLDERS ON)
#JPEG/PNG libraries..
set(JPG_Libs jpeg)
set(PNG_Libs png)
#------------------------------------------------------------------------------------------------------------------------------------------------
#First search for Tensorflow 2.x
#------------------------------------------------------------------------------------------------------------------------------------------------
IF(EXISTS "${CMAKE_SOURCE_DIR}/dependencies/libtensorflow/lib/libtensorflow.so.2")
MESSAGE("Using locally found libtensorflow v2 C-API")
set(TENSORFLOW_ROOT "${CMAKE_SOURCE_DIR}/dependencies/libtensorflow/lib/" CACHE PATH "tensorflow root")
set(TENSORFLOW_INCLUDE_ROOT "${CMAKE_SOURCE_DIR}/dependencies/libtensorflow/include/" CACHE PATH "tensorflow include")
set(TENSORFLOW2_FOUND true CACHE BOOL "Tensorflow 2 available")
set(TENSORFLOW_SOURCE_FILES
${CMAKE_SOURCE_DIR}/src/NeuralNetworkAbstractionLayer/neuralNetworkAbstraction.cpp
${CMAKE_SOURCE_DIR}/src/Tensorflow/tensorflow.cpp
${CMAKE_SOURCE_DIR}/src/Tensorflow/tf_utils.cpp
)
ELSEIF(EXISTS "/usr/local/lib/libtensorflow.so.2")
MESSAGE("Using system-wide found libtensorflow v2 C-API")
set(TENSORFLOW_ROOT "/usr/local/lib/" CACHE PATH "tensorflow root")
set(TENSORFLOW_INCLUDE_ROOT "/usr/local/include/" CACHE PATH "tensorflow include")
set(TENSORFLOW2_FOUND true CACHE BOOL "Tensorflow 2 available")
set(TENSORFLOW_SOURCE_FILES
${CMAKE_SOURCE_DIR}/src/NeuralNetworkAbstractionLayer/neuralNetworkAbstraction.cpp
${CMAKE_SOURCE_DIR}/src/Tensorflow/tensorflow.cpp
${CMAKE_SOURCE_DIR}/src/Tensorflow/tf_utils.cpp
)
#------------------------------------------------------------------------------------------------------------------------------------------------
#If we can't find it then search for Tensorflow 1.x
#------------------------------------------------------------------------------------------------------------------------------------------------
ELSEIF(EXISTS "${CMAKE_SOURCE_DIR}/dependencies/libtensorflow/lib/libtensorflow.so")
MESSAGE("Using locally found libtensorflow v1 C-API")
set(TENSORFLOW_ROOT "${CMAKE_SOURCE_DIR}/dependencies/libtensorflow/lib/" CACHE PATH "tensorflow root")
set(TENSORFLOW_INCLUDE_ROOT "${CMAKE_SOURCE_DIR}/dependencies/libtensorflow/include/" CACHE PATH "tensorflow include")
set(TENSORFLOW_SOURCE_FILES
${CMAKE_SOURCE_DIR}/src/NeuralNetworkAbstractionLayer/neuralNetworkAbstraction.cpp
${CMAKE_SOURCE_DIR}/src/Tensorflow/tensorflow.cpp
${CMAKE_SOURCE_DIR}/src/Tensorflow/tf_utils.cpp
)
ELSEIF(EXISTS "/usr/local/lib/libtensorflow.so")
MESSAGE("Using system-wide found libtensorflow v1 C-API")
set(TENSORFLOW_ROOT "/usr/local/lib/" CACHE PATH "tensorflow root")
set(TENSORFLOW_INCLUDE_ROOT "/usr/local/include/" CACHE PATH "tensorflow include")
set(TENSORFLOW_SOURCE_FILES
${CMAKE_SOURCE_DIR}/src/NeuralNetworkAbstractionLayer/neuralNetworkAbstraction.cpp
${CMAKE_SOURCE_DIR}/src/Tensorflow/tensorflow.cpp
${CMAKE_SOURCE_DIR}/src/Tensorflow/tf_utils.cpp
)
#------------------------------------------------------------------------------------------------------------------------------------------------
#If we can't find any Tensorflow just point to the /usr/lib and hope for the best..
#------------------------------------------------------------------------------------------------------------------------------------------------
ELSE()
MESSAGE("Did not find a tensorflow version, please consider running the initialize.sh script or reading the README file")
#Set some default tensorflow paths to give some valid error afterwards..
set(TENSORFLOW_ROOT "/usr/local/lib/" CACHE PATH "tensorflow root")
set(TENSORFLOW_INCLUDE_ROOT "/usr/local/include/" CACHE PATH "tensorflow include")
ENDIF()
#------------------------------------------------------------------------------------------------------------------------------------------------
include_directories(${TENSORFLOW_INCLUDE_ROOT})
ADD_LIBRARY(TensorflowFramework SHARED IMPORTED)
IF (TENSORFLOW2_FOUND)
SET_TARGET_PROPERTIES(TensorflowFramework PROPERTIES IMPORTED_LOCATION ${TENSORFLOW_ROOT}/libtensorflow_framework.so.2)
ELSE(TENSORFLOW2_FOUND)
SET_TARGET_PROPERTIES(TensorflowFramework PROPERTIES IMPORTED_LOCATION ${TENSORFLOW_ROOT}/libtensorflow_framework.so)
ENDIF (TENSORFLOW2_FOUND)
ADD_LIBRARY(Tensorflow SHARED IMPORTED)
IF (TENSORFLOW2_FOUND)
SET_TARGET_PROPERTIES(Tensorflow PROPERTIES IMPORTED_LOCATION ${TENSORFLOW_ROOT}/libtensorflow.so.2)
ELSE(TENSORFLOW2_FOUND)
SET_TARGET_PROPERTIES(Tensorflow PROPERTIES IMPORTED_LOCATION ${TENSORFLOW_ROOT}/libtensorflow.so)
ENDIF (TENSORFLOW2_FOUND)
#If our development environment has RGBDAcquisition then we can use BVH capabilities..
#------------------------------------------------------------------------------------------------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------------------------------------
set(BVH_SOURCE "")
IF(EXISTS "${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader")
add_definitions(-DUSE_BVH)
set(BVH_SOURCE
#--------------------------------------------------------------------------------
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/tools/PThreadWorkerPool/pthreadWorkerPool.h
#--------------------------------------------------------------------------------
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/bvh_loader.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/calculate/bvh_to_tri_pose.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/calculate/bvh_transform.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/calculate/bvh_project.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/import/fromBVH.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/export/bvh_to_trajectoryParserTRI.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/export/bvh_to_trajectoryParserPrimitives.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/export/bvh_export.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/export/bvh_to_c.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/export/bvh_to_bvh.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/export/bvh_to_svg.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/export/bvh_to_csv.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/export/bvh_to_json.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/export/bvh_export.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/edit/bvh_randomize.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/edit/bvh_filter.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/edit/bvh_rename.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/edit/bvh_merge.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/edit/bvh_cut_paste.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/edit/bvh_interpolate.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/edit/bvh_remapangles.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/ik/bvh_inverseKinematics.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/ik/hardcodedProblems_inverseKinematics.c
#${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/ik/levmar.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/metrics/bvh_measure.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader/tests/test.c
#--------------------------------------------------------------------------------
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/tools/Calibration/calibration.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/tools/Calibration/calibration.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/tools/Calibration/transform.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/tools/Calibration/transform.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/tools/Calibration/undistort.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/tools/Calibration/undistort.h
#--------------------------------------------------------------------------------
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/tools/AmMatrix/matrixTools.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/tools/AmMatrix/matrix3x3Tools.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/tools/AmMatrix/matrix4x4Tools.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/tools/AmMatrix/matrixOpenGL.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/tools/AmMatrix/matrixCalculations.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/tools/AmMatrix/solveLinearSystemGJ.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/tools/AmMatrix/solveHomography.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/tools/AmMatrix/quaternions.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/tools/AmMatrix/simpleRenderer.c
)
MESSAGE("BVH Code found and will be used..")
add_subdirectory(src/GroundTruthGenerator/) #Ground Truth generator can only be compiled with BVH code..
add_subdirectory(src/MocapNET2/reshapeCSVFileToMakeClassification/) #Orientation classification needs this tool to be built before working..
#MESSAGE("${BVH_SOURCE}")
ENDIF()
#------------------------------------------------------------------------------------------------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------------------------------------
set(OPENGL_LIBS "")
set(OPENGL_SOURCE "")
if (ENABLE_OPENGL)
IF(EXISTS "${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library")
add_subdirectory(${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/tools/Codecs)
add_subdirectory(${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/tools/Calibration)
#add_subdirectory(${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library) #OpenGLAcquisition
add_definitions(-DUSE_OPENGL)
#add_definitions(-DUSE_GLEW)
set(OPENGL_LIBS rt m GL GLU GLEW X11 Codecs CalibrationLibrary)
set(OPENGL_SOURCE
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/OpenGLAcquisition.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/OpenGLAcquisition.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/System/glx.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/System/glx.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/System/glx2.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/System/glx2.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/System/glx3.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/System/glx3.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/main.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/OGLRendererSandbox.h
#3D Models and how to load them
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/ModelLoader/model_loader.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/ModelLoader/model_loader.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/ModelLoader/model_loader_obj.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/ModelLoader/model_loader_obj.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/ModelLoader/model_loader_tri.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/ModelLoader/model_loader_tri.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/ModelLoader/model_processor.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/ModelLoader/model_processor.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/ModelLoader/model_loader_hardcoded.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/ModelLoader/model_loader_hardcoded.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/ModelLoader/model_loader_transform_joints.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/ModelLoader/model_loader_transform_joints.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/ModelLoader/model_converter.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/ModelLoader/model_converter.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/ModelLoader/model_editor.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/ModelLoader/model_editor.h
#Textures and how to load them
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/TextureLoader/texture_loader.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/TextureLoader/texture_loader.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/TextureLoader/image_proc.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/TextureLoader/image_proc.h
#OpenGL Rendering stuff
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Rendering/FixedPipeline/ogl_fixed_pipeline_renderer.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Rendering/FixedPipeline/ogl_fixed_pipeline_renderer.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Rendering/ShaderPipeline/render_buffer.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Rendering/ShaderPipeline/render_buffer.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Rendering/ShaderPipeline/uploadGeometry.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Rendering/ShaderPipeline/uploadGeometry.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Rendering/ShaderPipeline/ogl_shader_pipeline_renderer.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Rendering/ShaderPipeline/ogl_shader_pipeline_renderer.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Rendering/ShaderPipeline/shader_loader.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Rendering/ShaderPipeline/shader_loader.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Rendering/ogl_rendering.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Rendering/ogl_rendering.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Rendering/tiledRenderer.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Rendering/tiledRenderer.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Rendering/downloadFromRenderer.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Rendering/downloadFromRenderer.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Tools/tools.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Tools/tools.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Tools/save_to_file.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Tools/save_to_file.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Scene/scene.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Scene/scene.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Scene/control.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Scene/control.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Scene/photoShootingScene.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Scene/photoShootingScene.c
#AmMatrix dependencies
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition//tools/AmMatrix/quaternions.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition//tools/AmMatrix/quaternions.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition//tools/AmMatrix/matrix3x3Tools.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition//tools/AmMatrix/matrix3x3Tools.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition//tools/AmMatrix/matrix4x4Tools.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition//tools/AmMatrix/matrix4x4Tools.h
#../tools/AmMatrix/matrixProject.c
#../tools/AmMatrix/matrixProject.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition//tools/AmMatrix/matrixCalculations.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition//tools/AmMatrix/matrixCalculations.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition//tools/AmMatrix/matrixOpenGL.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition//tools/AmMatrix/matrixOpenGL.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition//tools/AmMatrix/solveLinearSystemGJ.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition//tools/AmMatrix/solveLinearSystemGJ.h
#ImageOperations dependencies
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition//tools/ImageOperations/depthClassifier.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition//tools/ImageOperations/convolutionFilter.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition//tools/ImageOperations/imageFilters.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition//tools/ImageOperations/findSubImage.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition//tools/ImageOperations/imageOps.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition//tools/ImageOperations/patchComparison.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition//tools/ImageOperations/patchComparison.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition//tools/ImageOperations/resize.c
#Rest of the stuff
#${CMAKE_SOURCE_DIR}/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/TrajectoryParser/InputParser_C.c
#${CMAKE_SOURCE_DIR}/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/TrajectoryParser/InputParser_C.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/TrajectoryParser/TrajectoryParser.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/TrajectoryParser/TrajectoryParser.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/TrajectoryParser/TrajectoryParserDataStructures.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/TrajectoryParser/TrajectoryParserDataStructures.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/TrajectoryParser/TrajectoryCalculator.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/TrajectoryParser/TrajectoryCalculator.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/TrajectoryParser/TrajectoryPrimitives.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/TrajectoryParser/TrajectoryPrimitives.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/TrajectoryParser/hashmap.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/TrajectoryParser/hashmap.h
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Interfaces/webInterface.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/Interfaces/webInterface.h
)
MESSAGE("OpenGL code found and will be used..")
ELSE()
MESSAGE("OpenGL support enabled, but OpenGL code not found..")
ENDIF()
ELSE (ENABLE_OPENGL)
MESSAGE("OpenGL support will not be compiled in")
ENDIF(ENABLE_OPENGL)
#------------------------------------------------------------------------------------------------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------------------------------------
#Autosearch for the opencv maybe installed by the user..!
find_package(OpenCV PATHS dependencies/opencv-3.2.0/build NO_DEFAULT_PATH)
find_package (OpenCV)
if (OpenCV_FOUND)
add_definitions(-DUSE_OPENCV)
MESSAGE("OpenCV code found and will be used..")
MESSAGE(${OpenCV_DIR})
ENDIF(OpenCV_FOUND)
#If ammarserver is present then use it..
set(NETWORK_CLIENT_LIBRARIES "")
IF(EXISTS "${CMAKE_SOURCE_DIR}/dependencies/AmmarServer/src/AmmServerlib")
add_definitions(-DUSE_NETWORKING)
MESSAGE("AmmarServer support will be compiled in")
#add_subdirectory (dependencies/AmmarServer/) #You can force add everything but this adds too much to the build time
set(NETWORK_CLIENT_LIBRARIES "AmmClient")
add_subdirectory (dependencies/AmmarServer/src/AmmClient)
add_subdirectory (dependencies/AmmarServer/src/AmmServerlib)
add_subdirectory (dependencies/AmmarServer/src/Hashmap)
add_subdirectory (dependencies/AmmarServer/src/InputParser)
ENDIF()
#This needs Tensorflow C-API installed...
#https://www.tensorflow.org/install/lang_c
#wget https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-linux-x86_64-1.13.1.tar.gz
#pip3 show protobuf
#add_subdirectory (MocapNETStandalone/)
IF(EXISTS "${CMAKE_SOURCE_DIR}/dependencies/AmmarServer/src/AmmServerlib")
#add_subdirectory (src/MocapNET1/MocapNETServerHTTP/)
ENDIF()
if (OpenCV_FOUND)
add_subdirectory (src/Webcam/)
#Deactivated to keep build targets sane
add_subdirectory(src/MocapNET2/BVHGUI2)
add_subdirectory(src/MocapNET2/MocapNET2LiveWebcamDemo)
ENDIF(OpenCV_FOUND)
#add_subdirectory(src/MocapNET2/BVHTemplate/)
add_subdirectory(src/MocapNET2/MocapNETLib2/)
add_subdirectory(src/MocapNET2/MocapNETFromCSV/)
add_subdirectory(src/MocapNET2/Converters/Openpose)
add_subdirectory(src/MocapNET2/Converters/H36M)
add_subdirectory(src/MocapNET2/Converters/convertCSV3D)
add_subdirectory(src/MocapNET2/testCSV/)
add_subdirectory(src/MocapNET2/drawCSV/)
add_subdirectory(src/MocapNET2/CSVClusterPlot)
#------------------------------------------------------------------
add_subdirectory(src/JointEstimator2D)
# TODO FIX INSTALLATION DIRECTORIES
# install(TARGETS RGBDAcquisitionProject
# LIBRARY DESTINATION lib
# ARCHIVE DESTINATION lib
# RUNTIME DESTINATION bin)
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# MocapNET Project
![MocapNET](https://raw.githubusercontent.com/FORTH-ModelBasedTracker/MocapNET/mnet4/doc/method.png)
Finishing my PhD this will probably be the *final* version of MocapNET!
MocapNET 4 will deal with upperbody / lowerbody / hands / eye tracking and / facial capture
It has a written from scratch python interface, but maintain the same compatible BVH output format.
It will also be compatible with Raspberry Pi 4 and use Tensorflow /Tf-Lite / ONNX backends
This branch is still under construction, and has been ported to Python to boost usability
so if you want the older C/C++ version of MocapNET you ignore it for now..!
![MocapNET](https://raw.githubusercontent.com/FORTH-ModelBasedTracker/MocapNET/mnet4/doc/ICCV2023_Presentation_Slide18.png)
## Deploy it now on Google Colab with a single click!
------------------------------------------------------------------
Click here for one click setup : [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/FORTH-ModelBasedTracker/MocapNET/blob/mnet4/mocapnet4.ipynb)
## Relevant publications!
------------------------------------------------------------------
| Download Paper | Year | Conference | Title |
| ------------- | ------------- | ------------- | ------------- |
| [![A Unified Approach for Occlusion Tolerant 3D Facial Pose Capture and Gaze Estimation using MocapNETs](https://github.com/FORTH-ModelBasedTracker/MocapNET/blob/mnet4/doc/pdf.png?raw=true)](http://users.ics.forth.gr/~argyros/mypapers/2023_10_AMFG_Qammaz.pdf) | 2023 | AMFG@ICCV | A Unified Approach for Occlusion Tolerant 3D Facial Pose Capture and Gaze Estimation using MocapNETs |
| [![Compacting MocapNET-based 3D Human Pose Estimation via Dimensionality Reduction](https://github.com/FORTH-ModelBasedTracker/MocapNET/blob/mnet4/doc/pdf.png?raw=true)](http://users.ics.forth.gr/~argyros/mypapers/2023_07_PETRA_Qammaz.pdf) | 2023 | PeTRA | Compacting MocapNET-based 3D Human Pose Estimation via Dimensionality Reduction |
| [![Towards Holistic Real-time Human 3D Pose Estimation using MocapNETs](https://github.com/FORTH-ModelBasedTracker/MocapNET/blob/mnet4/doc/pdf.png?raw=true)](http://users.ics.forth.gr/~argyros/mypapers/2021_11_BMVC_Qammaz.pdf) | 2021 | BMVC | Towards Holistic Real-time Human 3D Pose Estimation using MocapNETs |
| [![Occlusion-tolerant and personalized 3D human pose estimation in RGB images](https://github.com/FORTH-ModelBasedTracker/MocapNET/blob/mnet4/doc/pdf.png?raw=true)](http://users.ics.forth.gr/~argyros/mypapers/2021_01_ICPR_Qammaz.pdf) | 2021 | ICPR | Occlusion-tolerant and personalized 3D human pose estimation in RGB images |
| [![MocapNET: Ensemble of SNN Encoders for 3D Human Pose Estimation in RGB Images](https://github.com/FORTH-ModelBasedTracker/MocapNET/blob/mnet4/doc/pdf.png?raw=true)](http://users.ics.forth.gr/~argyros/mypapers/2019_09_BMVC_mocapnet.pdf) | 2019 | BMVC | MocapNET: Ensemble of SNN Encoders for 3D Human Pose Estimation in RGB Images |
## AMFG@ICCV 2023 Poster
------------------------------------------------------------------
![Our Poster in the Analysis and Modeling of Faces and Gestures Workshop @ ICCV 2023 ](https://github.com/FORTH-ModelBasedTracker/MocapNET/blob/mnet4/doc/ICCV2023_MocapNET4_poster.png?raw=true)
## Citation
------------------------------------------------------------------
Please cite the following papers if this work helps your research :
```
@inproceedings{Qammaz2023b,
author = {Qammaz, Ammar and Argyros, Antonis},
title = {A Unified Approach for Occlusion Tolerant 3D Facial Pose Capture and Gaze Estimation using MocapNETs},
booktitle = {International Conference on Computer Vision Workshops (AMFG 2023 - ICCVW 2023), (to appear)},
publisher = {IEEE},
year = {2023},
month = {October},
address = {Paris, France},
projects = {VMWARE,I.C.HUMANS},
pdflink = {http://users.ics.forth.gr/ argyros/mypapers/2023_10_AMFG_Qammaz.pdf}
}
@inproceedings{Qammaz2021,
author = {Qammaz, Ammar and Argyros, Antonis A},
title = {Towards Holistic Real-time Human 3D Pose Estimation using MocapNETs},
booktitle = {British Machine Vision Conference (BMVC 2021)},
publisher = {BMVA},
year = {2021},
month = {November},
projects = {I.C.HUMANS},
videolink = {https://www.youtube.com/watch?v=aaLOSY_p6Zc}
}
```
## License
------------------------------------------------------------------
This library is provided under the [FORTH license](https://github.com/FORTH-ModelBasedTracker/MocapNET/blob/master/license.txt)
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@@ -0,0 +1,36 @@
@inproceedings{Qammaz2021,
author = {Qammaz, Ammar and Argyros, Antonis A},
title = {Towards Holistic Real-time Human 3D Pose Estimation using MocapNETs},
booktitle = {British Machine Vision Conference (BMVC 2021)},
publisher = {BMVA},
year = {2021},
month = {November},
projects = {I.C.HUMANS},
videolink = {https://www.youtube.com/watch?v=aaLOSY_p6Zc}
}
@inproceedings{Qammaz2020,
author = {Ammar Qammaz and Antonis A. Argyros},
title = {Occlusion-tolerant and personalized 3D human pose estimation in RGB images},
booktitle = {IEEE International Conference on Pattern Recognition (ICPR 2020), (to appear)},
year = {2021},
month = {January},
url = {http://users.ics.forth.gr/argyros/res_mocapnet_II.html},
projects = {Co4Robots},
pdflink = {http://users.ics.forth.gr/argyros/mypapers/2021_01_ICPR_Qammaz.pdf},
videolink = {https://youtu.be/Jgz1MRq-I-k}
}
@inproceedings{Qammaz2019,
author = {Qammaz, Ammar and Argyros, Antonis A},
title = {MocapNET: Ensemble of SNN Encoders for 3D Human Pose Estimation in RGB Images},
booktitle = {British Machine Vision Conference (BMVC 2019)},
publisher = {BMVA},
year = {2019},
month = {September},
address = {Cardiff, UK},
url = {http://users.ics.forth.gr/argyros/res_mocapnet.html},
projects = {CO4ROBOTS,MINGEI},
pdflink = {http://users.ics.forth.gr/argyros/mypapers/2019_09_BMVC_mocapnet.pdf},
videolink = {https://youtu.be/fH5e-KMBvM0}
}
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#https://github.com/hideo55/CMake-FindSSE/blob/master/FindSSE.cmake
# Check if SSE instructions are available on the machine where
# the project is compiled.
MACRO (FindSSE)
IF(CMAKE_SYSTEM_NAME MATCHES "Linux")
EXEC_PROGRAM(cat ARGS "/proc/cpuinfo" OUTPUT_VARIABLE CPUINFO)
STRING(REGEX REPLACE "^.*(sse2).*$" "\\1" SSE_THERE ${CPUINFO})
STRING(COMPARE EQUAL "sse2" "${SSE_THERE}" SSE2_TRUE)
IF (SSE2_TRUE)
set(SSE2_FOUND true CACHE BOOL "SSE2 available on host")
ELSE (SSE2_TRUE)
set(SSE2_FOUND false CACHE BOOL "SSE2 available on host")
ENDIF (SSE2_TRUE)
# /proc/cpuinfo apparently omits sse3 :(
STRING(REGEX REPLACE "^.*[^s](sse3).*$" "\\1" SSE_THERE ${CPUINFO})
STRING(COMPARE EQUAL "sse3" "${SSE_THERE}" SSE3_TRUE)
IF (NOT SSE3_TRUE)
STRING(REGEX REPLACE "^.*(T2300).*$" "\\1" SSE_THERE ${CPUINFO})
STRING(COMPARE EQUAL "T2300" "${SSE_THERE}" SSE3_TRUE)
ENDIF (NOT SSE3_TRUE)
STRING(REGEX REPLACE "^.*(ssse3).*$" "\\1" SSE_THERE ${CPUINFO})
STRING(COMPARE EQUAL "ssse3" "${SSE_THERE}" SSSE3_TRUE)
IF (SSE3_TRUE OR SSSE3_TRUE)
set(SSE3_FOUND true CACHE BOOL "SSE3 available on host")
ELSE (SSE3_TRUE OR SSSE3_TRUE)
set(SSE3_FOUND false CACHE BOOL "SSE3 available on host")
ENDIF (SSE3_TRUE OR SSSE3_TRUE)
IF (SSSE3_TRUE)
set(SSSE3_FOUND true CACHE BOOL "SSSE3 available on host")
ELSE (SSSE3_TRUE)
set(SSSE3_FOUND false CACHE BOOL "SSSE3 available on host")
ENDIF (SSSE3_TRUE)
STRING(REGEX REPLACE "^.*(sse4_1).*$" "\\1" SSE_THERE ${CPUINFO})
STRING(COMPARE EQUAL "sse4_1" "${SSE_THERE}" SSE41_TRUE)
IF (SSE41_TRUE)
set(SSE4_1_FOUND true CACHE BOOL "SSE4.1 available on host")
ELSE (SSE41_TRUE)
set(SSE4_1_FOUND false CACHE BOOL "SSE4.1 available on host")
ENDIF (SSE41_TRUE)
STRING(REGEX REPLACE "^.*(sse4_2).*$" "\\1" SSE_THERE ${CPUINFO})
STRING(COMPARE EQUAL "sse4_2" "${SSE_THERE}" SSE42_TRUE)
IF (SSE42_TRUE)
set(SSE4_2_FOUND true CACHE BOOL "SSE4.2 available on host")
ELSE (SSE42_TRUE)
set(SSE4_2_FOUND false CACHE BOOL "SSE4.2 available on host")
ENDIF (SSE42_TRUE)
ELSEIF(CMAKE_SYSTEM_NAME MATCHES "Darwin")
EXEC_PROGRAM("/usr/sbin/sysctl -n machdep.cpu.features" OUTPUT_VARIABLE
CPUINFO)
STRING(REGEX REPLACE "^.*[^S](SSE2).*$" "\\1" SSE_THERE ${CPUINFO})
STRING(COMPARE EQUAL "SSE2" "${SSE_THERE}" SSE2_TRUE)
IF (SSE2_TRUE)
set(SSE2_FOUND true CACHE BOOL "SSE2 available on host")
ELSE (SSE2_TRUE)
set(SSE2_FOUND false CACHE BOOL "SSE2 available on host")
ENDIF (SSE2_TRUE)
STRING(REGEX REPLACE "^.*[^S](SSE3).*$" "\\1" SSE_THERE ${CPUINFO})
STRING(COMPARE EQUAL "SSE3" "${SSE_THERE}" SSE3_TRUE)
IF (SSE3_TRUE)
set(SSE3_FOUND true CACHE BOOL "SSE3 available on host")
ELSE (SSE3_TRUE)
set(SSE3_FOUND false CACHE BOOL "SSE3 available on host")
ENDIF (SSE3_TRUE)
STRING(REGEX REPLACE "^.*(SSSE3).*$" "\\1" SSE_THERE ${CPUINFO})
STRING(COMPARE EQUAL "SSSE3" "${SSE_THERE}" SSSE3_TRUE)
IF (SSSE3_TRUE)
set(SSSE3_FOUND true CACHE BOOL "SSSE3 available on host")
ELSE (SSSE3_TRUE)
set(SSSE3_FOUND false CACHE BOOL "SSSE3 available on host")
ENDIF (SSSE3_TRUE)
STRING(REGEX REPLACE "^.*(SSE4.1).*$" "\\1" SSE_THERE ${CPUINFO})
STRING(COMPARE EQUAL "SSE4.1" "${SSE_THERE}" SSE41_TRUE)
IF (SSE41_TRUE)
set(SSE4_1_FOUND true CACHE BOOL "SSE4.1 available on host")
ELSE (SSE41_TRUE)
set(SSE4_1_FOUND false CACHE BOOL "SSE4.1 available on host")
ENDIF (SSE41_TRUE)
STRING(REGEX REPLACE "^.*(SSE4.2).*$" "\\1" SSE_THERE ${CPUINFO})
STRING(COMPARE EQUAL "SSE4.2" "${SSE_THERE}" SSE42_TRUE)
IF (SSE42_TRUE)
set(SSE4_2_FOUND true CACHE BOOL "SSE4.2 available on host")
ELSE (SSE42_TRUE)
set(SSE4_2_FOUND false CACHE BOOL "SSE4.2 available on host")
ENDIF (SSE42_TRUE)
ELSEIF(CMAKE_SYSTEM_NAME MATCHES "Windows")
# TODO
set(SSE2_FOUND true CACHE BOOL "SSE2 available on host")
set(SSE3_FOUND false CACHE BOOL "SSE3 available on host")
set(SSSE3_FOUND false CACHE BOOL "SSSE3 available on host")
set(SSE4_1_FOUND false CACHE BOOL "SSE4.1 available on host")
set(SSE4_2_FOUND false CACHE BOOL "SSE4.2 available on host")
ELSE(CMAKE_SYSTEM_NAME MATCHES "Linux")
set(SSE2_FOUND true CACHE BOOL "SSE2 available on host")
set(SSE3_FOUND false CACHE BOOL "SSE3 available on host")
set(SSSE3_FOUND false CACHE BOOL "SSSE3 available on host")
set(SSE4_1_FOUND false CACHE BOOL "SSE4.1 available on host")
set(SSE4_2_FOUND false CACHE BOOL "SSE4.2 available on host")
ENDIF(CMAKE_SYSTEM_NAME MATCHES "Linux")
IF(CMAKE_COMPILER_IS_GNUCXX)
EXECUTE_PROCESS(COMMAND ${CMAKE_CXX_COMPILER} -dumpversion OUTPUT_VARIABLE GCC_VERSION)
IF(GCC_VERSION VERSION_LESS 4.2)
set(SSE4_1_FOUND false CACHE BOOL "SSE4.1 available on host" FORCE)
set(SSE4_2_FOUND false CACHE BOOL "SSE4.2 available on host" FORCE)
ENDIF()
ENDIF(CMAKE_COMPILER_IS_GNUCXX)
if(NOT SSE2_FOUND)
MESSAGE(STATUS "Could not find support for SSE2 on this machine.")
endif(NOT SSE2_FOUND)
if(NOT SSE3_FOUND)
MESSAGE(STATUS "Could not find support for SSE3 on this machine.")
endif(NOT SSE3_FOUND)
if(NOT SSSE3_FOUND)
MESSAGE(STATUS "Could not find support for SSSE3 on this machine.")
endif(NOT SSSE3_FOUND)
if(NOT SSE4_1_FOUND)
MESSAGE(STATUS "Could not find support for SSE4.1 on this machine.")
endif(NOT SSE4_1_FOUND)
if(NOT SSE4_2_FOUND)
MESSAGE(STATUS "Could not find support for SSE4.2 on this machine.")
endif(NOT SSE4_2_FOUND)
mark_as_advanced(SSE2_FOUND SSE3_FOUND SSSE3_FOUND SSE4_1_FOUND SSE4_2_FOUND)
ENDMACRO(FindSSE)
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# MocapNET Project
## Dataset generation
------------------------------------------------------------------
If you are interested in generating the data to train a MocapNET please use the scripts [createRandomizedDataset.sh](https://github.com/FORTH-ModelBasedTracker/MocapNET/blob/master/createRandomizedDataset.sh) and [createTestDataset.sh](https://github.com/FORTH-ModelBasedTracker/MocapNET/blob/master/createTestDataset.sh) after building the GroundTruthDumper tool. (It will be automatically generated after running the initialization script)
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HIERARCHY
ROOT root
{
OFFSET 0 0 0
CHANNELS 6 Xposition Yposition Zposition Zrotation Yrotation Xrotation
JOINT X_Axis
{
OFFSET 10.0 0.0 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT X_Axis_Ornament
{
OFFSET 1.0 0.0 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT X_Ornament_A
{
OFFSET 0.0 0.0 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 0.0 -5.0 -5.0
}
}
JOINT X_Ornament_B
{
OFFSET 0.0 0.0 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 0.0 5.0 -5.0
}
}
JOINT X_Ornament_C
{
OFFSET 0.0 0.0 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 0.0 5.0 5.0
}
}
JOINT X_Ornament_D
{
OFFSET 0.0 0.0 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 0.0 -5.0 5.0
}
}
}
}
JOINT Y_Axis
{
OFFSET 0.0 10.0 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT Y_Axis_Ornament
{
OFFSET 0.0 1.0 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT Y_Ornament_A
{
OFFSET 0.0 0.0 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET -5.0 0.0 -5.0
}
}
JOINT Y_Ornament_B
{
OFFSET 0.0 0.0 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 5.0 0.0 -5.0
}
}
JOINT Y_Ornament_C
{
OFFSET 0.0 0.0 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 0.0 0.0 5.0
}
}
}
}
JOINT Z_Axis
{
OFFSET 0.0 0.0 10.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT Z_Axis_Ornament
{
OFFSET 0.0 0.0 1.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT Z_Ornament_A0
{
OFFSET -2.5 -2.5 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT Z_Ornament_A1
{
OFFSET -2.5 -2.5 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT Z_Ornament_A2
{
OFFSET 5.0 0.0 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 5.0 0.0 0.0
}
}
}
}
JOINT Z_Ornament_B0
{
OFFSET 2.5 2.5 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT Z_Ornament_B1
{
OFFSET 2.5 2.5 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT Z_Ornament_B2
{
OFFSET -5.0 0.0 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET -5.0 0.0 0.0
}
}
}
}
}
}
}
MOTION
Frames: 1
Frame Time: 0.040000
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
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@@ -0,0 +1,276 @@
HIERARCHY
ROOT hip
{
OFFSET 0 0 0
CHANNELS 6 Xposition Yposition Zposition Zrotation Yrotation Xrotation
JOINT abdomen
{
OFFSET 0 20.6881 -0.73152
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT chest
{
OFFSET 0 11.7043 -0.48768
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT neck
{
OFFSET 0 22.1894 -2.19456
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT head
{
OFFSET -0.24384 7.07133 1.2192
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT leftEye
{
OFFSET 4.14528 8.04674 8.04672
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 1 0 0
}
}
JOINT rightEye
{
OFFSET -3.6576 8.04674 8.04672
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 1 0 0
}
}
}
}
JOINT rCollar
{
OFFSET -2.68224 19.2634 -4.8768
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rShldr
{
OFFSET -8.77824 -1.95073 1.46304
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rForeArm
{
OFFSET -28.1742 -1.7115 0.48768
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rHand
{
OFFSET -22.5879 0.773209 7.07136
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rThumb1
{
OFFSET -1.2192 -0.487915 3.41376
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rThumb2
{
OFFSET -3.37035 -0.52449 3.41376
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET -1.78271 -1.18214 1.43049
}
}
}
JOINT rIndex1
{
OFFSET -7.75947 0.938293 5.60832
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rIndex2
{
OFFSET -2.54057 -0.884171 1.56538
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET -1.62519 -0.234802 1.16502
}
}
}
JOINT rMid1
{
OFFSET -8.24714 1.18213 3.41376
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rMid2
{
OFFSET -3.10165 -0.590103 1.0647
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET -2.48547 -0.328903 0.83742
}
}
}
JOINT rRing1
{
OFFSET -8.82822 0.546677 1.51678
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rRing2
{
OFFSET -2.60934 -0.819778 -0.0198488
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET -2.33842 -0.294052 0.168128
}
}
}
JOINT rPinky1
{
OFFSET -8.27202 -0.0477905 -0.4584
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rPinky2
{
OFFSET -1.82734 -0.647385 -0.700984
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET -1.69225 -0.51767 -0.607171
}
}
}
}
}
}
}
JOINT lCollar
{
OFFSET 2.68224 19.2634 -4.8768
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lShldr
{
OFFSET 8.77824 -1.95073 1.46304
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lForeArm
{
OFFSET 28.1742 -1.7115 0.48768
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lHand
{
OFFSET 22.5879 0.773209 7.07136
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lThumb1
{
OFFSET 1.2192 -0.487915 3.41376
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lThumb2
{
OFFSET 3.37035 -0.52449 3.41376
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 1.78271 -1.18214 1.43049
}
}
}
JOINT lIndex1
{
OFFSET 7.75947 0.938293 5.60832
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lIndex2
{
OFFSET 2.54057 -0.884171 1.56538
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 1.62519 -0.234802 1.16502
}
}
}
JOINT lMid1
{
OFFSET 8.24714 1.18213 3.41376
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lMid2
{
OFFSET 3.10165 -0.590103 1.0647
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 2.48547 -0.328903 0.83742
}
}
}
JOINT lRing1
{
OFFSET 8.82822 0.546677 1.51678
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lRing2
{
OFFSET 2.60934 -0.819778 -0.0198488
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 2.33842 -0.294052 0.168128
}
}
}
JOINT lPinky1
{
OFFSET 8.27202 -0.0477905 -0.4584
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lPinky2
{
OFFSET 1.82734 -0.647385 -0.700984
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 1.69225 -0.51767 -0.607171
}
}
}
}
}
}
}
}
}
JOINT rButtock
{
OFFSET -8.77824 4.35084 1.2192
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rThigh
{
OFFSET 0 -1.70687 -2.19456
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rShin
{
OFFSET 0 -36.8199 0.73152
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rFoot
{
OFFSET 0.73152 -45.1104 -5.12064
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET -1.1221 -3.69964 12.103
}
}
}
}
}
JOINT lButtock
{
OFFSET 8.77824 4.35084 1.2192
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lThigh
{
OFFSET 0 -1.70687 -2.19456
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lShin
{
OFFSET 0 -36.8199 0.73152
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lFoot
{
OFFSET -0.73152 -45.1104 -5.12064
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 1.1221 -3.69964 12.103
}
}
}
}
}
}
MOTION
Frames: 1
Frame Time: 0.04
-36.9591 -6.6997 -109.9615 1.6043 -4.3309 5.0092 0.5097 6.5673 1.3846 -0.0103 -0.0119 0.0508 -8.6191 3.2278 -3.0830 12.7205 0.1189 -1.1459 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 52.8597 33.4915 1.4029 -17.6149 -9.0171 30.5911 -2.2427 12.5892 2.8079 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0239 0.0136 0.0138 0.0000 0.0000 0.0000 0.0304 0.0086 0.0160 0.0000 0.0000 0.0000 0.0156 0.0211 0.0357 0.0000 0.0000 0.0000 0.0280 -0.0226 -0.0298 0.0000 0.0000 0.0000 -65.5102 14.9901 -0.2439 19.8193 -15.0257 -36.4212 0.3359 -3.4324 1.3281 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 -0.0134 0.0062 -0.0052 0.0000 0.0000 0.0000 -0.0334 0.0306 -0.0050 0.0000 0.0000 0.0000 -0.0305 0.0041 -0.0329 0.0000 0.0000 0.0000 -0.0039 -0.0187 0.0140 0.0000 0.0000 0.0000 -2.8009 -15.7151 -7.3415 -1.0408 24.0401 0.0885 -3.2956 -8.0185 -8.6331 0.0000 0.0000 0.0000 0.6124 -9.9020 -2.4375 0.6809 24.1049 -0.8555 0.7591 -9.1731 2.8152
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# This is a rendering configuration for ../dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/
#
# If you want to make a new 3D model to replace the default one install makehuman, install the CMU plus Face rig ( http://www.makehuman.org/content/cmu_plus_face.html )
# select it as the used rig and make the body pose at a t-pose, finally export it as Collada(dae) with Feet on ground , Y up, face Z , Bone orienation Local=Global and decimeters
#
# compile assimpTester in ../dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/submodules/Assimp
# ./assimpTester --convert makehumanexports/newmodel.dae makehuman.tri --paint 123 123 123
#
# copy the new makehuman.tri to your dataset/makehuman.tri
#
# You can verify that it is properly rendering without running the demo
# cd ../dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/
# mkdir build
# cd build && cmake .. && make
# cd ..
# ./Renderer --from path/to/this/human3D.conf
#
BACKGROUND(0,0,0)
#INCLUDE(Scenes/renderLikeMBVRH.conf)
#This is the way to render like the mbv renderer :)
AUTOREFRESH(1500)
NEAR_CLIP(0.1)
FAR_CLIP(1000)
#Bring our world to the MBV coordinate system
SCALE_WORLD(-0.01,-0.01,0.01)
MAP_ROTATIONS(-1,-1,1,zxy)
OFFSET_ROTATIONS(0,0,0)
#EMULATE_PROJECTION_MATRIX(535.423889 , 0.0 , 320.0 , 0.0 , 533.48468, 240.0 , 0 , 1)
EMULATE_PROJECTION_MATRIX(582.18394 , 0.0 , 960.0 , 0.0 , 582.52915, 540.0 , 0 , 1)
SILENT(1)
RATE(120)
INTERPOLATE_TIME(1)
MOVE_VIEW(1)
OBJECT_TYPE(floorType,grid)
#OBJECT(floor,floorType,0,235,255,0 ,0, 50.0,50.0,50.0)
OBJECT_TYPE(humanMesh,dataset/makehuman.tri,http://ammar.gr/mocapnet/makehuman.tri)
RIGID_OBJECT(human,humanMesh, 255,0,0,0,0 ,1.0,1.0,1.0)
LIGHT(0,0,-100)
#Note of all the bones in file..
Bone 0 : Scene
Bone 1 : CMU+Face_compliant_skeleton
Bone 2 : Hips
Bone 3 : LHipJoint
Bone 4 : LeftUpLeg
Bone 5 : LeftLeg
Bone 6 : LeftFoot
Bone 7 : LeftToeBase
Bone 8 : LowerBack
Bone 9 : Spine
Bone 10 : Spine1
Bone 11 : LeftShoulder
Bone 12 : LeftArm
Bone 13 : LeftForeArm
Bone 14 : LeftHand
Bone 15 : metacarpal1_L
Bone 16 : finger2-1_L
Bone 17 : finger2-2_L
Bone 18 : finger2-3_L
Bone 19 : metacarpal2_L
Bone 20 : finger3-1_L
Bone 21 : finger3-2_L
Bone 22 : finger3-3_L
Bone 23 : metacarpal3_L
Bone 24 : finger4-1_L
Bone 25 : finger4-2_L
Bone 26 : finger4-3_L
Bone 27 : metacarpal4_L
Bone 28 : finger5-1_L
Bone 29 : finger5-2_L
Bone 30 : finger5-3_L
Bone 31 : LThumb
Bone 32 : finger1-2_L
Bone 33 : finger1-3_L
Bone 34 : Neck
Bone 35 : Neck1
Bone 36 : Head
Bone 37 : jaw
Bone 38 : special04
Bone 39 : oris02
Bone 40 : oris01
Bone 41 : oris06_L
Bone 42 : oris07_L
Bone 43 : oris06_R
Bone 44 : oris07_R
Bone 45 : tongue00
Bone 46 : tongue01
Bone 47 : tongue02
Bone 48 : tongue03
Bone 49 : tongue04
Bone 50 : tongue07_L
Bone 51 : tongue07_R
Bone 52 : tongue06_L
Bone 53 : tongue06_R
Bone 54 : tongue05_L
Bone 55 : tongue05_R
Bone 56 : levator02_L
Bone 57 : levator03_L
Bone 58 : levator04_L
Bone 59 : levator05_L
Bone 60 : levator02_R
Bone 61 : levator03_R
Bone 62 : levator04_R
Bone 63 : levator05_R
Bone 64 : special01
Bone 65 : oris04_L
Bone 66 : oris03_L
Bone 67 : oris04_R
Bone 68 : oris03_R
Bone 69 : oris06
Bone 70 : oris05
Bone 71 : special03
Bone 72 : levator06_L
Bone 73 : levator06_R
Bone 74 : special06_L
Bone 75 : special05_L
Bone 76 : eye_L
Bone 77 : orbicularis03_L
Bone 78 : orbicularis04_L
Bone 79 : special06_R
Bone 80 : special05_R
Bone 81 : eye_R
Bone 82 : orbicularis03_R
Bone 83 : orbicularis04_R
Bone 84 : temporalis01_L
Bone 85 : oculi02_L
Bone 86 : oculi01_L
Bone 87 : temporalis01_R
Bone 88 : oculi02_R
Bone 89 : oculi01_R
Bone 90 : temporalis02_L
Bone 91 : risorius02_L
Bone 92 : risorius03_L
Bone 93 : temporalis02_R
Bone 94 : risorius02_R
Bone 95 : risorius03_R
Bone 96 : RightShoulder
Bone 97 : RightArm
Bone 98 : RightForeArm
Bone 99 : RightHand
Bone 100 : metacarpal1_R
Bone 101 : finger2-1_R
Bone 102 : finger2-2_R
Bone 103 : finger2-3_R
Bone 104 : metacarpal2_R
Bone 105 : finger3-1_R
Bone 106 : finger3-2_R
Bone 107 : finger3-3_R
Bone 108 : metacarpal3_R
Bone 109 : finger4-1_R
Bone 110 : finger4-2_R
Bone 111 : finger4-3_R
Bone 112 : metacarpal4_R
Bone 113 : finger5-1_R
Bone 114 : finger5-2_R
Bone 115 : finger5-3_R
Bone 116 : RThumb
Bone 117 : finger1-2_R
Bone 118 : finger1-3_R
Bone 119 : RHipJoint
Bone 120 : RightUpLeg
Bone 121 : RightLeg
Bone 122 : RightFoot
Bone 123 : RightToeBase
Bone 124 : newmodel-baseObject
Bone 125 : newmodel-highpolyeyesObject
#cat human3D.conf | grep Bone | cut -d':' -f2 | tr '\n' '~' | tr -d '[:blank:]' | sed -e 's/\~/,ZXY)\nPOSE_ROTATION_ORDER\(human,/g'
OBJECT_ROTATION_ORDER(human,ZYX)
POSE_ROTATION_ORDER(human,Hips,ZYX)
POSE_ROTATION_ORDER(human,LHipJoint,ZXY)
POSE_ROTATION_ORDER(human,LeftUpLeg,ZXY)
POSE_ROTATION_ORDER(human,LeftLeg,ZXY)
POSE_ROTATION_ORDER(human,LeftFoot,ZXY)
POSE_ROTATION_ORDER(human,LeftToeBase,ZXY)
POSE_ROTATION_ORDER(human,LowerBack,ZXY)
POSE_ROTATION_ORDER(human,Spine,ZXY)
POSE_ROTATION_ORDER(human,Spine1,ZXY)
POSE_ROTATION_ORDER(human,LeftShoulder,ZXY)
POSE_ROTATION_ORDER(human,LeftArm,ZXY)
POSE_ROTATION_ORDER(human,LeftForeArm,ZXY)
POSE_ROTATION_ORDER(human,LeftHand,ZXY)
POSE_ROTATION_ORDER(human,metacarpal1_L,ZXY)
POSE_ROTATION_ORDER(human,finger2-1_L,ZXY)
POSE_ROTATION_ORDER(human,finger2-2_L,ZXY)
POSE_ROTATION_ORDER(human,finger2-3_L,ZXY)
POSE_ROTATION_ORDER(human,metacarpal2_L,ZXY)
POSE_ROTATION_ORDER(human,finger3-1_L,ZXY)
POSE_ROTATION_ORDER(human,finger3-2_L,ZXY)
POSE_ROTATION_ORDER(human,finger3-3_L,ZXY)
POSE_ROTATION_ORDER(human,metacarpal3_L,ZXY)
POSE_ROTATION_ORDER(human,finger4-1_L,ZXY)
POSE_ROTATION_ORDER(human,finger4-2_L,ZXY)
POSE_ROTATION_ORDER(human,finger4-3_L,ZXY)
POSE_ROTATION_ORDER(human,metacarpal4_L,ZXY)
POSE_ROTATION_ORDER(human,finger5-1_L,ZXY)
POSE_ROTATION_ORDER(human,finger5-2_L,ZXY)
POSE_ROTATION_ORDER(human,finger5-3_L,ZXY)
POSE_ROTATION_ORDER(human,LThumb,ZXY)
POSE_ROTATION_ORDER(human,finger1-2_L,ZXY)
POSE_ROTATION_ORDER(human,finger1-3_L,ZXY)
POSE_ROTATION_ORDER(human,Neck,ZXY)
POSE_ROTATION_ORDER(human,Neck1,ZXY)
POSE_ROTATION_ORDER(human,Head,ZXY)
POSE_ROTATION_ORDER(human,jaw,ZXY)
POSE_ROTATION_ORDER(human,special04,ZXY)
POSE_ROTATION_ORDER(human,oris02,ZXY)
POSE_ROTATION_ORDER(human,oris01,ZXY)
POSE_ROTATION_ORDER(human,oris06_L,ZXY)
POSE_ROTATION_ORDER(human,oris07_L,ZXY)
POSE_ROTATION_ORDER(human,oris06_R,ZXY)
POSE_ROTATION_ORDER(human,oris07_R,ZXY)
POSE_ROTATION_ORDER(human,tongue00,ZXY)
POSE_ROTATION_ORDER(human,tongue01,ZXY)
POSE_ROTATION_ORDER(human,tongue02,ZXY)
POSE_ROTATION_ORDER(human,tongue03,ZXY)
POSE_ROTATION_ORDER(human,tongue04,ZXY)
POSE_ROTATION_ORDER(human,tongue07_L,ZXY)
POSE_ROTATION_ORDER(human,tongue07_R,ZXY)
POSE_ROTATION_ORDER(human,tongue06_L,ZXY)
POSE_ROTATION_ORDER(human,tongue06_R,ZXY)
POSE_ROTATION_ORDER(human,tongue05_L,ZXY)
POSE_ROTATION_ORDER(human,tongue05_R,ZXY)
POSE_ROTATION_ORDER(human,levator02_L,ZXY)
POSE_ROTATION_ORDER(human,levator03_L,ZXY)
POSE_ROTATION_ORDER(human,levator04_L,ZXY)
POSE_ROTATION_ORDER(human,levator05_L,ZXY)
POSE_ROTATION_ORDER(human,levator02_R,ZXY)
POSE_ROTATION_ORDER(human,levator03_R,ZXY)
POSE_ROTATION_ORDER(human,levator04_R,ZXY)
POSE_ROTATION_ORDER(human,levator05_R,ZXY)
POSE_ROTATION_ORDER(human,special01,ZXY)
POSE_ROTATION_ORDER(human,oris04_L,ZXY)
POSE_ROTATION_ORDER(human,oris03_L,ZXY)
POSE_ROTATION_ORDER(human,oris04_R,ZXY)
POSE_ROTATION_ORDER(human,oris03_R,ZXY)
POSE_ROTATION_ORDER(human,oris06,ZXY)
POSE_ROTATION_ORDER(human,oris05,ZXY)
POSE_ROTATION_ORDER(human,special03,ZXY)
POSE_ROTATION_ORDER(human,levator06_L,ZXY)
POSE_ROTATION_ORDER(human,levator06_R,ZXY)
POSE_ROTATION_ORDER(human,special06_L,ZXY)
POSE_ROTATION_ORDER(human,special05_L,ZXY)
POSE_ROTATION_ORDER(human,eye_L,ZXY)
POSE_ROTATION_ORDER(human,orbicularis03_L,ZXY)
POSE_ROTATION_ORDER(human,orbicularis04_L,ZXY)
POSE_ROTATION_ORDER(human,special06_R,ZXY)
POSE_ROTATION_ORDER(human,special05_R,ZXY)
POSE_ROTATION_ORDER(human,eye_R,ZXY)
POSE_ROTATION_ORDER(human,orbicularis03_R,ZXY)
POSE_ROTATION_ORDER(human,orbicularis04_R,ZXY)
POSE_ROTATION_ORDER(human,temporalis01_L,ZXY)
POSE_ROTATION_ORDER(human,oculi02_L,ZXY)
POSE_ROTATION_ORDER(human,oculi01_L,ZXY)
POSE_ROTATION_ORDER(human,temporalis01_R,ZXY)
POSE_ROTATION_ORDER(human,oculi02_R,ZXY)
POSE_ROTATION_ORDER(human,oculi01_R,ZXY)
POSE_ROTATION_ORDER(human,temporalis02_L,ZXY)
POSE_ROTATION_ORDER(human,risorius02_L,ZXY)
POSE_ROTATION_ORDER(human,risorius03_L,ZXY)
POSE_ROTATION_ORDER(human,temporalis02_R,ZXY)
POSE_ROTATION_ORDER(human,risorius02_R,ZXY)
POSE_ROTATION_ORDER(human,risorius03_R,ZXY)
POSE_ROTATION_ORDER(human,RightShoulder,ZXY)
POSE_ROTATION_ORDER(human,RightArm,ZXY)
POSE_ROTATION_ORDER(human,RightForeArm,ZXY)
POSE_ROTATION_ORDER(human,RightHand,ZXY)
POSE_ROTATION_ORDER(human,metacarpal1_R,ZXY)
POSE_ROTATION_ORDER(human,finger2-1_R,ZXY)
POSE_ROTATION_ORDER(human,finger2-2_R,ZXY)
POSE_ROTATION_ORDER(human,finger2-3_R,ZXY)
POSE_ROTATION_ORDER(human,metacarpal2_R,ZXY)
POSE_ROTATION_ORDER(human,finger3-1_R,ZXY)
POSE_ROTATION_ORDER(human,finger3-2_R,ZXY)
POSE_ROTATION_ORDER(human,finger3-3_R,ZXY)
POSE_ROTATION_ORDER(human,metacarpal3_R,ZXY)
POSE_ROTATION_ORDER(human,finger4-1_R,ZXY)
POSE_ROTATION_ORDER(human,finger4-2_R,ZXY)
POSE_ROTATION_ORDER(human,finger4-3_R,ZXY)
POSE_ROTATION_ORDER(human,metacarpal4_R,ZXY)
POSE_ROTATION_ORDER(human,finger5-1_R,ZXY)
POSE_ROTATION_ORDER(human,finger5-2_R,ZXY)
POSE_ROTATION_ORDER(human,finger5-3_R,ZXY)
POSE_ROTATION_ORDER(human,RThumb,ZXY)
POSE_ROTATION_ORDER(human,finger1-2_R,ZXY)
POSE_ROTATION_ORDER(human,finger1-3_R,ZXY)
POSE_ROTATION_ORDER(human,RHipJoint,ZXY)
POSE_ROTATION_ORDER(human,RightUpLeg,ZXY)
POSE_ROTATION_ORDER(human,RightLeg,ZXY)
POSE_ROTATION_ORDER(human,RightFoot,ZXY)
POSE_ROTATION_ORDER(human,RightToeBase,ZXY)
#MOVE(floor,0,0.0,2784.976,3699.735,0.0,0.0,0.0,0.0)
#Root joint euler angle order ZYX
MOVE(human,0,0.0,900.0,2000,0.0,180.0,0.0)
#cat human3D.conf | grep Bone | cut -d':' -f2 | tr '\n' '~' | tr -d '[:blank:]' | sed -e 's/\~/,0,0,0)\nPOSE(human,0,/g'
POSE(human,0,Hips,0,0,0)
POSE(human,0,LHipJoint,0,0,0)
POSE(human,0,LeftUpLeg,0,0,0)
POSE(human,0,LeftLeg,0,0,0)
POSE(human,0,LeftFoot,0,0,0)
POSE(human,0,LeftToeBase,0,0,0)
POSE(human,0,LowerBack,0,0,0)
POSE(human,0,Spine,0,0,0)
POSE(human,0,Spine1,0,0,0)
POSE(human,0,LeftShoulder,0,0,0)
POSE(human,0,LeftArm,0,0,0)
POSE(human,0,LeftForeArm,0,0,0)
POSE(human,0,LeftHand,0,0,0)
POSE(human,0,metacarpal1_L,0,0,0)
POSE(human,0,finger2-1_L,0,0,0)
POSE(human,0,finger2-2_L,0,0,0)
POSE(human,0,finger2-3_L,0,0,0)
POSE(human,0,metacarpal2_L,0,0,0)
POSE(human,0,finger3-1_L,0,0,0)
POSE(human,0,finger3-2_L,0,0,0)
POSE(human,0,finger3-3_L,0,0,0)
POSE(human,0,metacarpal3_L,0,0,0)
POSE(human,0,finger4-1_L,0,0,0)
POSE(human,0,finger4-2_L,0,0,0)
POSE(human,0,finger4-3_L,0,0,0)
POSE(human,0,metacarpal4_L,0,0,0)
POSE(human,0,finger5-1_L,0,0,0)
POSE(human,0,finger5-2_L,0,0,0)
POSE(human,0,finger5-3_L,0,0,0)
POSE(human,0,LThumb,0,0,0)
POSE(human,0,finger1-2_L,0,0,0)
POSE(human,0,finger1-3_L,0,0,0)
POSE(human,0,Neck,0,0,0)
POSE(human,0,Neck1,0,0,0)
POSE(human,0,Head,0,0,0)
POSE(human,0,jaw,0,0,0)
POSE(human,0,special04,0,0,0)
POSE(human,0,oris02,0,0,0)
POSE(human,0,oris01,0,0,0)
POSE(human,0,oris06_L,0,0,0)
POSE(human,0,oris07_L,0,0,0)
POSE(human,0,oris06_R,0,0,0)
POSE(human,0,oris07_R,0,0,0)
POSE(human,0,tongue00,0,0,0)
POSE(human,0,tongue01,0,0,0)
POSE(human,0,tongue02,0,0,0)
POSE(human,0,tongue03,0,0,0)
POSE(human,0,tongue04,0,0,0)
POSE(human,0,tongue07_L,0,0,0)
POSE(human,0,tongue07_R,0,0,0)
POSE(human,0,tongue06_L,0,0,0)
POSE(human,0,tongue06_R,0,0,0)
POSE(human,0,tongue05_L,0,0,0)
POSE(human,0,tongue05_R,0,0,0)
POSE(human,0,levator02_L,0,0,0)
POSE(human,0,levator03_L,0,0,0)
POSE(human,0,levator04_L,0,0,0)
POSE(human,0,levator05_L,0,0,0)
POSE(human,0,levator02_R,0,0,0)
POSE(human,0,levator03_R,0,0,0)
POSE(human,0,levator04_R,0,0,0)
POSE(human,0,levator05_R,0,0,0)
POSE(human,0,special01,0,0,0)
POSE(human,0,oris04_L,0,0,0)
POSE(human,0,oris03_L,0,0,0)
POSE(human,0,oris04_R,0,0,0)
POSE(human,0,oris03_R,0,0,0)
POSE(human,0,oris06,0,0,0)
POSE(human,0,oris05,0,0,0)
POSE(human,0,special03,0,0,0)
POSE(human,0,levator06_L,0,0,0)
POSE(human,0,levator06_R,0,0,0)
POSE(human,0,special06_L,0,0,0)
POSE(human,0,special05_L,0,0,0)
POSE(human,0,eye_L,0,0,0)
POSE(human,0,orbicularis03_L,0,0,0)
POSE(human,0,orbicularis04_L,0,0,0)
POSE(human,0,special06_R,0,0,0)
POSE(human,0,special05_R,0,0,0)
POSE(human,0,eye_R,0,0,0)
POSE(human,0,orbicularis03_R,0,0,0)
POSE(human,0,orbicularis04_R,0,0,0)
POSE(human,0,temporalis01_L,0,0,0)
POSE(human,0,oculi02_L,0,0,0)
POSE(human,0,oculi01_L,0,0,0)
POSE(human,0,temporalis01_R,0,0,0)
POSE(human,0,oculi02_R,0,0,0)
POSE(human,0,oculi01_R,0,0,0)
POSE(human,0,temporalis02_L,0,0,0)
POSE(human,0,risorius02_L,0,0,0)
POSE(human,0,risorius03_L,0,0,0)
POSE(human,0,temporalis02_R,0,0,0)
POSE(human,0,risorius02_R,0,0,0)
POSE(human,0,risorius03_R,0,0,0)
POSE(human,0,RightShoulder,0,0,0)
POSE(human,0,RightArm,0,0,0)
POSE(human,0,RightForeArm,0,0,0)
POSE(human,0,RightHand,0,0,0)
POSE(human,0,metacarpal1_R,0,0,0)
POSE(human,0,finger2-1_R,0,0,0)
POSE(human,0,finger2-2_R,0,0,0)
POSE(human,0,finger2-3_R,0,0,0)
POSE(human,0,metacarpal2_R,0,0,0)
POSE(human,0,finger3-1_R,0,0,0)
POSE(human,0,finger3-2_R,0,0,0)
POSE(human,0,finger3-3_R,0,0,0)
POSE(human,0,metacarpal3_R,0,0,0)
POSE(human,0,finger4-1_R,0,0,0)
POSE(human,0,finger4-2_R,0,0,0)
POSE(human,0,finger4-3_R,0,0,0)
POSE(human,0,metacarpal4_R,0,0,0)
POSE(human,0,finger5-1_R,0,0,0)
POSE(human,0,finger5-2_R,0,0,0)
POSE(human,0,finger5-3_R,0,0,0)
POSE(human,0,RThumb,0,0,0)
POSE(human,0,finger1-2_R,0,0,0)
POSE(human,0,finger1-3_R,0,0,0)
POSE(human,0,RHipJoint,0,0,0)
POSE(human,0,RightUpLeg,0,0,0)
POSE(human,0,RightLeg,0,0,0)
POSE(human,0,RightFoot,0,0,0)
POSE(human,0,RightToeBase,0,0,0)
#MOVE(floor,1,-19.231,2784.976,3699.735,0.0,0.0,0.0,0.0)
#Root joint euler angle order ZYX
MOVE(human,1,0.0,900.0,2000,0.0,180.0,0.0)
#cat human3D.conf | grep Bone | cut -d':' -f2 | tr '\n' '~' | tr -d '[:blank:]' | sed -e 's/\~/,0,0,0)\nPOSE(human,1,/g'
POSE(human,1,Hips,0,0,0)
POSE(human,1,LHipJoint,0,0,0)
POSE(human,1,LeftUpLeg,0,0,0)
POSE(human,1,LeftLeg,0,0,0)
POSE(human,1,LeftFoot,0,0,0)
POSE(human,1,LeftToeBase,0,0,0)
POSE(human,1,LowerBack,0,0,0)
POSE(human,1,Spine,0,0,0)
POSE(human,1,Spine1,0,0,0)
POSE(human,1,LeftShoulder,0,0,0)
POSE(human,1,LeftArm,0,0,0)
POSE(human,1,LeftForeArm,0,0,0)
POSE(human,1,LeftHand,0,0,0)
POSE(human,1,metacarpal1_L,0,0,0)
POSE(human,1,finger2-1_L,0,0,0)
POSE(human,1,finger2-2_L,0,0,0)
POSE(human,1,finger2-3_L,0,0,0)
POSE(human,1,metacarpal2_L,0,0,0)
POSE(human,1,finger3-1_L,0,0,0)
POSE(human,1,finger3-2_L,0,0,0)
POSE(human,1,finger3-3_L,0,0,0)
POSE(human,1,metacarpal3_L,0,0,0)
POSE(human,1,finger4-1_L,0,0,0)
POSE(human,1,finger4-2_L,0,0,0)
POSE(human,1,finger4-3_L,0,0,0)
POSE(human,1,metacarpal4_L,0,0,0)
POSE(human,1,finger5-1_L,0,0,0)
POSE(human,1,finger5-2_L,0,0,0)
POSE(human,1,finger5-3_L,0,0,0)
POSE(human,1,LThumb,0,0,0)
POSE(human,1,finger1-2_L,0,0,0)
POSE(human,1,finger1-3_L,0,0,0)
POSE(human,1,Neck,0,0,0)
POSE(human,1,Neck1,0,0,0)
POSE(human,1,Head,0,0,0)
POSE(human,1,jaw,0,0,0)
POSE(human,1,special04,0,0,0)
POSE(human,1,oris02,0,0,0)
POSE(human,1,oris01,0,0,0)
POSE(human,1,oris06_L,0,0,0)
POSE(human,1,oris07_L,0,0,0)
POSE(human,1,oris06_R,0,0,0)
POSE(human,1,oris07_R,0,0,0)
POSE(human,1,tongue00,0,0,0)
POSE(human,1,tongue01,0,0,0)
POSE(human,1,tongue02,0,0,0)
POSE(human,1,tongue03,0,0,0)
POSE(human,1,tongue04,0,0,0)
POSE(human,1,tongue07_L,0,0,0)
POSE(human,1,tongue07_R,0,0,0)
POSE(human,1,tongue06_L,0,0,0)
POSE(human,1,tongue06_R,0,0,0)
POSE(human,1,tongue05_L,0,0,0)
POSE(human,1,tongue05_R,0,0,0)
POSE(human,1,levator02_L,0,0,0)
POSE(human,1,levator03_L,0,0,0)
POSE(human,1,levator04_L,0,0,0)
POSE(human,1,levator05_L,0,0,0)
POSE(human,1,levator02_R,0,0,0)
POSE(human,1,levator03_R,0,0,0)
POSE(human,1,levator04_R,0,0,0)
POSE(human,1,levator05_R,0,0,0)
POSE(human,1,special01,0,0,0)
POSE(human,1,oris04_L,0,0,0)
POSE(human,1,oris03_L,0,0,0)
POSE(human,1,oris04_R,0,0,0)
POSE(human,1,oris03_R,0,0,0)
POSE(human,1,oris06,0,0,0)
POSE(human,1,oris05,0,0,0)
POSE(human,1,special03,0,0,0)
POSE(human,1,levator06_L,0,0,0)
POSE(human,1,levator06_R,0,0,0)
POSE(human,1,special06_L,0,0,0)
POSE(human,1,special05_L,0,0,0)
POSE(human,1,eye_L,0,0,0)
POSE(human,1,orbicularis03_L,0,0,0)
POSE(human,1,orbicularis04_L,0,0,0)
POSE(human,1,special06_R,0,0,0)
POSE(human,1,special05_R,0,0,0)
POSE(human,1,eye_R,0,0,0)
POSE(human,1,orbicularis03_R,0,0,0)
POSE(human,1,orbicularis04_R,0,0,0)
POSE(human,1,temporalis01_L,0,0,0)
POSE(human,1,oculi02_L,0,0,0)
POSE(human,1,oculi01_L,0,0,0)
POSE(human,1,temporalis01_R,0,0,0)
POSE(human,1,oculi02_R,0,0,0)
POSE(human,1,oculi01_R,0,0,0)
POSE(human,1,temporalis02_L,0,0,0)
POSE(human,1,risorius02_L,0,0,0)
POSE(human,1,risorius03_L,0,0,0)
POSE(human,1,temporalis02_R,0,0,0)
POSE(human,1,risorius02_R,0,0,0)
POSE(human,1,risorius03_R,0,0,0)
POSE(human,1,RightShoulder,0,0,0)
POSE(human,1,RightArm,0,0,0)
POSE(human,1,RightForeArm,0,0,0)
POSE(human,1,RightHand,0,0,0)
POSE(human,1,metacarpal1_R,0,0,0)
POSE(human,1,finger2-1_R,0,0,0)
POSE(human,1,finger2-2_R,0,0,0)
POSE(human,1,finger2-3_R,0,0,0)
POSE(human,1,metacarpal2_R,0,0,0)
POSE(human,1,finger3-1_R,0,0,0)
POSE(human,1,finger3-2_R,0,0,0)
POSE(human,1,finger3-3_R,0,0,0)
POSE(human,1,metacarpal3_R,0,0,0)
POSE(human,1,finger4-1_R,0,0,0)
POSE(human,1,finger4-2_R,0,0,0)
POSE(human,1,finger4-3_R,0,0,0)
POSE(human,1,metacarpal4_R,0,0,0)
POSE(human,1,finger5-1_R,0,0,0)
POSE(human,1,finger5-2_R,0,0,0)
POSE(human,1,finger5-3_R,0,0,0)
POSE(human,1,RThumb,0,0,0)
POSE(human,1,finger1-2_R,0,0,0)
POSE(human,1,finger1-3_R,0,0,0)
POSE(human,1,RHipJoint,0,0,0)
POSE(human,1,RightUpLeg,0,0,0)
POSE(human,1,RightLeg,0,0,0)
POSE(human,1,RightFoot,0,0,0)
POSE(human,1,RightToeBase,0,0,0)
POSE(human,1,newmodel-baseObject,0,0,0)
POSE(human,1,newmodel-highpolyeyesObject,0,0,0)
+140
View File
@@ -0,0 +1,140 @@
HIERARCHY
ROOT lHand
{
OFFSET 0 0 0
CHANNELS 6 Xposition Yposition Zposition Zrotation Yrotation Xrotation
JOINT metacarpal1.l
{
OFFSET 4.0 -0.27 2.00
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger2-1.l
{
OFFSET 4.5 0.27 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger2-2.l
{
OFFSET 3.5 -0.32 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger2-3.l
{
OFFSET 2.1 -0.29 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 1.98 -0.68 0.0
}
}
}
}
}
JOINT metacarpal2.l
{
OFFSET 4.0 -0.27 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger3-1.l
{
OFFSET 4.50 0.62 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger3-2.l
{
OFFSET 3.97 -0.58 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger3-3.l
{
OFFSET 2.5 -0.42 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 1.964 -0.73 0.00
}
}
}
}
}
JOINT __metacarpal3.l
{
OFFSET 2.5 -0.27 -2.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT metacarpal3.l
{
OFFSET 1.5 -0.16 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger4-1.l
{
OFFSET 4.5 0.70 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger4-2.l
{
OFFSET 3.67 -0.48 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger4-3.l
{
OFFSET 2.27 -0.35 -0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 1.904 -0.62 0.0
}
}
}
}
}
}
JOINT __metacarpal4.l
{
OFFSET 2.0 -0.27 -3.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT metacarpal4.l
{
OFFSET 2.0 -0.16 -1.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger5-1.l
{
OFFSET 4.0 0.17 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger5-2.l
{
OFFSET 3.2 -0.17 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger5-3.l
{
OFFSET 1.495 -0.10 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 1.9 -0.10 0.0
}
}
}
}
}
}
JOINT lthumbBase
{
OFFSET 2.0 -0.279 4.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lthumb
{
OFFSET 2.0 -0.142 1.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger1-2.l
{
OFFSET 1.9598 -2.10 1.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger1-3.l
{
OFFSET 2.76 -0.46 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 2.595 -0.16 0.0
}
}
}
}
}
}
MOTION
Frames: 1
Frame Time: 0.040000
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
+140
View File
@@ -0,0 +1,140 @@
HIERARCHY
ROOT lHand
{
OFFSET 0 0 0
CHANNELS 7 Xposition Yposition Zposition Wrotation Xrotation Yrotation Zrotation
JOINT metacarpal1.l
{
OFFSET 4.0 -0.27 2.00
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger2-1.l
{
OFFSET 4.5 0.27 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger2-2.l
{
OFFSET 3.5 -0.32 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger2-3.l
{
OFFSET 2.1 -0.29 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 1.98 -0.68 0.0
}
}
}
}
}
JOINT metacarpal2.l
{
OFFSET 4.0 -0.27 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger3-1.l
{
OFFSET 4.50 0.62 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger3-2.l
{
OFFSET 3.97 -0.58 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger3-3.l
{
OFFSET 2.5 -0.42 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 1.964 -0.73 0.00
}
}
}
}
}
JOINT __metacarpal3.l
{
OFFSET 2.5 -0.27 -2.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT metacarpal3.l
{
OFFSET 1.5 -0.16 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger4-1.l
{
OFFSET 4.5 0.70 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger4-2.l
{
OFFSET 3.67 -0.48 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger4-3.l
{
OFFSET 2.27 -0.35 -0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 1.904 -0.62 0.0
}
}
}
}
}
}
JOINT __metacarpal4.l
{
OFFSET 2.0 -0.27 -3.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT metacarpal4.l
{
OFFSET 2.0 -0.16 -1.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger5-1.l
{
OFFSET 4.0 0.17 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger5-2.l
{
OFFSET 3.2 -0.17 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger5-3.l
{
OFFSET 1.495 -0.10 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 1.9 -0.10 0.0
}
}
}
}
}
}
JOINT lthumbBase
{
OFFSET 0.0 -0.279 2.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lthumb
{
OFFSET 2.0 -0.142 1.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger1-2.l
{
OFFSET 1.9598 -2.10 1.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger1-3.l
{
OFFSET 2.76 -0.46 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 2.595 -0.16 0.0
}
}
}
}
}
}
MOTION
Frames: 1
Frame Time: 0.040000
0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
+140
View File
@@ -0,0 +1,140 @@
HIERARCHY
ROOT rHand
{
OFFSET 0 0 0
CHANNELS 6 Xposition Yposition Zposition Zrotation Yrotation Xrotation
JOINT metacarpal1.r
{
OFFSET -4.0 -0.27 2.00
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger2-1.r
{
OFFSET -4.5 0.27 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger2-2.r
{
OFFSET -3.5 -0.32 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger2-3.r
{
OFFSET -2.1 -0.29 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET -1.98 -0.68 0.0
}
}
}
}
}
JOINT metacarpal2.r
{
OFFSET -4.0 -0.27 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger3-1.r
{
OFFSET -4.50 0.62 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger3-2.r
{
OFFSET -3.97 -0.58 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger3-3.r
{
OFFSET -2.5 -0.42 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET -1.964 -0.73 0.00
}
}
}
}
}
JOINT __metacarpal3.r
{
OFFSET -2.5 -0.27 -2.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT metacarpal3.r
{
OFFSET -1.5 -0.16 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger4-1.r
{
OFFSET -4.5 0.70 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger4-2.r
{
OFFSET -3.67 -0.48 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger4-3.r
{
OFFSET -2.27 -0.35 -0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET -1.904 -0.62 0.0
}
}
}
}
}
}
JOINT __metacarpal4.r
{
OFFSET -2.0 -0.27 -3.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT metacarpal4.r
{
OFFSET -2.0 -0.16 -1.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger5-1.r
{
OFFSET -4.0 0.17 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger5-2.r
{
OFFSET -3.2 -0.17 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger5-3.r
{
OFFSET -1.495 -0.10 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET -1.9 -0.10 0.0
}
}
}
}
}
}
JOINT rthumbBase
{
OFFSET -2.0 -0.279 4.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rthumb
{
OFFSET -2.0 -0.142 1.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger1-2.r
{
OFFSET -1.9598 -2.10 1.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger1-3.r
{
OFFSET -2.76 -0.46 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET -2.595 -0.16 0.0
}
}
}
}
}
}
MOTION
Frames: 1
Frame Time: 0.040000
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
+140
View File
@@ -0,0 +1,140 @@
HIERARCHY
ROOT rHand
{
OFFSET 0 0 0
CHANNELS 7 Xposition Yposition Zposition Wrotation Xrotation Yrotation Zrotation
JOINT metacarpal1.r
{
OFFSET -4.0 -0.27 2.00
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger2-1.r
{
OFFSET -4.5 0.27 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger2-2.r
{
OFFSET -3.5 -0.32 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger2-3.r
{
OFFSET -2.1 -0.29 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET -1.98 -0.68 0.0
}
}
}
}
}
JOINT metacarpal2.r
{
OFFSET -4.0 -0.27 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger3-1.r
{
OFFSET -4.50 0.62 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger3-2.r
{
OFFSET -3.97 -0.58 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger3-3.r
{
OFFSET -2.5 -0.42 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET -1.964 -0.73 0.00
}
}
}
}
}
JOINT __metacarpal3.r
{
OFFSET -2.5 -0.27 -2.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT metacarpal3.r
{
OFFSET -1.5 -0.16 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger4-1.r
{
OFFSET -4.5 0.70 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger4-2.r
{
OFFSET -3.67 -0.48 0.0
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger4-3.r
{
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CHANNELS 3 Zrotation Xrotation Yrotation
End Site
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}
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JOINT __metacarpal4.r
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CHANNELS 3 Zrotation Xrotation Yrotation
JOINT metacarpal4.r
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CHANNELS 3 Zrotation Xrotation Yrotation
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CHANNELS 3 Zrotation Xrotation Yrotation
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CHANNELS 3 Zrotation Xrotation Yrotation
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CHANNELS 3 Zrotation Xrotation Yrotation
End Site
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JOINT rthumbBase
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CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rthumb
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CHANNELS 3 Zrotation Xrotation Yrotation
JOINT finger1-2.r
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CHANNELS 3 Zrotation Xrotation Yrotation
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MOTION
Frames: 1
Frame Time: 0.040000
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#include "InputParser_C.h"
#include <math.h>
/* InputParser..
A small generic library for parsing a string and tokenizing it!
GITHUB Repo : http://github.com/AmmarkoV/InputParser
my URLs: http://ammar.gr
Written by Ammar Qammaz a.k.a. AmmarkoV 2006-2010
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#define WARN_ABOUT_INCORRECTLY_ALLOCATED_STACK_STRINGS 1
int warningsAboutIncorrectlyAllocatedStackIssued = 0;
char _ipc_ver[]=" 0.362\0"; //17/7/2023
/*
TODO
void stringToFloatArray(char * str , char delimiter , float * floatArr , int elements)
{
unsigned int strLength = strlen(str);
char * strPtr=str;
char * strStart=str;
char * strEnd=str+strLength;
int curElement = 0;
while ( (curElement<elements) && (strPtr<strEnd) )
{
while ( (strPtr<strEnd) && (*strPtr!=delimiter) )
{
++strPtr; //Seeking next delimiter
}
if (*strPtr==delimiter)
{
*strPtr=0; //Null terminate
floatArr[curElement]=atof(strStart);
++curElement;
*strPtr=delimiter;
strStart=strPtr+1;
}
}
}
*/
char * InputParserC_Version()
{
return (char *) _ipc_ver;
}
int InputParser_ClearNonCharacters(char * inpt , unsigned int length)
{
unsigned int skip_chars=0;
unsigned int i=0;
while (i<length)
{
if (inpt[i]<' ') /*The characters before space should be filtered*/
{
++skip_chars;
}
if (skip_chars>0)
{
if (i+skip_chars>=length)
{
inpt[i]=0;
}
else
{
inpt[i]=inpt[i+skip_chars];
}
}
++i;
}
return 1;
}
int InputParser_TrimCharactersStart(char * inpt , unsigned int length,char what2trim)
{
if ( ( inpt==0 ) || (length==0) )
{
return 0;
}
unsigned int skip_chars=0;
unsigned int i=0;
while ((skip_chars<length)&&(inpt[skip_chars]==what2trim))
{
++skip_chars;
}
while (i<length)
{
if (skip_chars>0)
{
if (i+skip_chars>=length)
{
inpt[i]=0;
}
else
{
inpt[i]=inpt[i+skip_chars];
}
}
++i;
}
return 1;
}
int InputParser_TrimCharactersEnd(char * inpt , unsigned int length,char what2trim)
{
if ( strlen(inpt)!=length )
{
length=strlen(inpt);
}
if ( length==0 )
{
return 1;
}
if ( (length==1) && (inpt[0]==what2trim) )
{
inpt[0]=0;
return 1;
}
else if ( length==1 )
{
return 1;
}
unsigned int i;
i=length-1;
while ((inpt[i]==what2trim)&&(i>0))
{
--i;
}
if ( i==length-1 )
{
/*No chars found*/ return 1;
}
if ((i==0) && (inpt[0]==what2trim) )
{
inpt[0]=0;
}
else
{
inpt[i+1]=0;
}
return 1;
}
int InputParser_TrimCharacters(char * inpt , unsigned int length,char what2trim)
{
int i=0;
i=InputParser_TrimCharactersStart(inpt,length,what2trim);
if (i==0)
{
return 0;
}
return InputParser_TrimCharactersEnd(inpt,length,what2trim);
}
static inline signed int Str2Int_internal(char * inpt,unsigned int start_from,unsigned int length)
{
if ( inpt == 0 )
{
fprintf(stderr,"Null string to Str2IntInternal!\n");
return 0;
}
int intresult;
int multiplier;
int curnum;
unsigned char trailing_sign_seek;
unsigned char positive_number;
signed int i;
intresult=0,multiplier=1,curnum=0;
trailing_sign_seek=1 , positive_number=1;
/*fprintf(stderr,"Converting to int string (%p) begining from %u and ending at %u ",inpt,start_from,start_from+length);*/
for (i=(signed int) start_from+length-1; i>=(signed int) start_from; i--)
{
if ( i < 0 )
{
/*fprintf("Gone negative! %u \n",i);*/ break;
}
curnum=(char) (inpt[i])-'0';
if ((curnum>=0)&(curnum<=9))
{
intresult=intresult+(multiplier*curnum);
multiplier=multiplier*10;
}
if (trailing_sign_seek)
{
/*fprintf(stderr,"Run to %c while searching for sign \n",inpt[i]);*/
if (inpt[i]=='+')
{
trailing_sign_seek=0;
}
else if (inpt[i]=='-')
{
trailing_sign_seek=0;
positive_number=0;
}
}
}
if (!positive_number)
{
intresult = intresult * (-1);
}
return intresult;
}
static inline unsigned char CheckIPCOk(struct InputParserC * ipc)
{
if ( ipc->guardbyte1.checksum != ipc->guardbyte2.checksum )
{
fprintf(stderr,"Input Parser - Wrong GuardChecksums #1\n");
return 0;
}
if ( ipc->guardbyte3.checksum != ipc->guardbyte4.checksum )
{
fprintf(stderr,"Input Parser - Wrong GuardChecksums #2\n");
return 0;
}
if ( ipc->guardbyte1.checksum != ipc->guardbyte4.checksum )
{
fprintf(stderr,"Input Parser - Wrong GuardChecksums #3\n");
return 0;
}
if ( (ipc->tokenlist==0) || (ipc->tokens_max<ipc->tokens_count) )
{
fprintf(stderr,"Input Parser - Tokenlist error\n");
return 0;
}
if ( (ipc->delimeters==0) || (ipc->max_delimeter_count<ipc->cur_delimeter_count) )
{
fprintf(stderr,"Input Parser - Delimeter error\n");
return 0;
}
return 1;
}
void InputParser_DefaultDelimeters(struct InputParserC * ipc)
{
if ( CheckIPCOk(ipc) == 0 )
{
return;
}
if ( ipc->delimeters == 0 )
{
return;
}
int i;
/*fprintf(stderr,"Default Delimters ( %u ) ",ipc->max_delimeter_count);*/
for ( i=0; i<ipc->max_delimeter_count; i++)
{
switch (i)
{
case 0 :
ipc->delimeters[0]='\n';
break;
case 1 :
ipc->delimeters[1]=',';
break;
case 2 :
ipc->delimeters[2]='=';
break;
case 3 :
ipc->delimeters[3]='(';
break;
case 4 :
ipc->delimeters[4]=')';
break;
default :
ipc->delimeters[i]='\n';
break;
};
/*fprintf(stderr," %u - %c ",i,ipc->delimeters[i]);*/
}
ipc->cur_delimeter_count = ipc->max_delimeter_count;
/*fprintf(stderr,"\n");*/
return;
}
/*
InitInputParser..
Allocates an ipc structure and with memory to it according to options for future use!
for example InitInputParser( 256 , 5 ) will allocate an InputParser Instance capeable of tokenizing up to 256 different words
from 5 delimeters
*/
struct InputParserC * InputParser_Create(unsigned int max_string_count,unsigned int max_delimiter_count)
{
struct InputParserC * ipc=0;
ipc = ( struct InputParserC * ) malloc ( sizeof ( struct InputParserC ) );
if ( ipc == 0 )
{
fprintf(stderr,"InputParserC unable to commit memory for a new instance\n");
return 0;
}
ipc->tokenlist = (struct tokens *) malloc( sizeof(struct tokens) * (max_string_count+1) );
if ( ipc->tokenlist == 0 )
{
fprintf(stderr,"InputParserC unable to commit memory for a new Token List\n");
free(ipc);
return 0;
}
ipc->tokens_count=0;
ipc->tokens_max = max_string_count;
ipc->delimeters = (char *) malloc( sizeof(char) * (max_delimiter_count+1) );
if ( ipc->delimeters == 0 )
{
fprintf(stderr,"InputParserC unable to commit memory for a new Delimeter List\n");
free(ipc->tokenlist);
free(ipc);
return 0;
}
ipc->max_delimeter_count=max_delimiter_count;
ipc->cur_delimeter_count=max_delimiter_count;
ipc->container_start=0;
ipc->container_end=0;
ipc->guardbyte1.checksum=66666;
ipc->guardbyte2.checksum=66666;
ipc->guardbyte3.checksum=66666;
ipc->guardbyte4.checksum=66666;
ipc->local_allocation = 0; /* No allocation by default! :)*/
ipc->str_length=0;
ipc->str=0;
InputParser_DefaultDelimeters(ipc);
return ipc;
}
/*
InputParser_Destroy..
Safely destroys a non null ipc structure and deallocates all commited memory
*/
void InputParser_Destroy(struct InputParserC * ipc)
{
if ( ipc == 0 )
{
return;
}
/*fprintf(stderr,"InputParserC freeing delimeters\n");*/
if ( ipc->delimeters != 0 )
{
free(ipc->delimeters);
ipc->delimeters=0;
}
ipc->cur_delimeter_count=0;
ipc->max_delimeter_count=0;
/*
if ( ipc->container_start != 0 )
{
free(ipc->container_start);
ipc->container_start=0;
}
if ( ipc->container_end != 0 )
{
free(ipc->container_end);
ipc->container_end=0;
}
*/
ipc->cur_container_count = 0;
ipc->max_container_count = 0;
/*fprintf(stderr,"InputParserC freeing tokenlist\n");*/
if ( ipc->tokenlist != 0 )
{
free(ipc->tokenlist);
ipc->tokenlist=0;
}
ipc->tokens_max=0;
ipc->tokens_count=0;
/*fprintf(stderr,"InputParserC freeing local allocation\n");*/
if ( ipc->local_allocation == 1 )
{
if ( ipc->str!=0 ) free(ipc->str);
}
/*ipc->local_allocation=0;*/
ipc->str_length=0;
/* RESULT */
ipc->guardbyte1.checksum = 0;
ipc->guardbyte2.checksum = 0;
ipc->guardbyte3.checksum = 0;
ipc->guardbyte4.checksum = 0;
/*fprintf(stderr,"InputParserC freeing ipc\n");*/
free(ipc);
}
/* ........................................................
Delimeters ........................................................
........................................................*/
/*
CheckDelimeterNumOk..
Checks if delimeter with number num has allocated space in memory
*/
static inline unsigned char CheckDelimeterNumOk(struct InputParserC * ipc,int num)
{
if ( ipc->max_delimeter_count <= num ) return 0;
return 1;
}
/*
SetDelimeter..
Sets Delimeter number num with value tmp
*/
void InputParser_SetDelimeter(struct InputParserC * ipc,int num,char tmp)
{
if (CheckDelimeterNumOk(ipc,num)==0)
{
return;
}
ipc->delimeters[num]=tmp;
}
/*
GetDelimeter..
Returns value of Delimeter with number num
*/
char InputParser_GetDelimeter(struct InputParserC * ipc,int num)
{
if (CheckDelimeterNumOk(ipc,num)==0)
{
return 0;
}
return ipc->delimeters[num];
}
/* .......................................................................
.......................................................................
.......................................................................*/
/*
Selfchecks IPC instance and returns 1 if everything is ok , 0 if error..
*/
unsigned char InputParser_SelfCheck(struct InputParserC * ipc)
{
if (CheckIPCOk(ipc)==0)
{
fprintf(stderr,"\n\n!!!!\nThis instance of InputParser is broken\n!!!!\n\n");
return 0;
}
return 1;
}
/*
CheckWordNumOk..
Checks if word with number num has allocated space in memory
*/
unsigned char CheckWordNumOk(struct InputParserC * ipc,unsigned int num)
{
if ( CheckIPCOk(ipc)==0)
{
return 0;
}
if ( (ipc->tokenlist==0) || ( ipc->tokens_count <= num ) )
{
return 0;
}
return 1;
}
unsigned int InputParser_GetNumberOfArguments(struct InputParserC * ipc)
{
if ( CheckIPCOk(ipc)==0)
{
return 0;
}
return ipc->tokens_count;
}
/*
InputParser_GetWord..
Copies token with number (num) to c string (wheretostore) , variable storagesize contains the total size of wheretostore..!
*/
unsigned int InputParser_IsEmptyWord(struct InputParserC * ipc,unsigned int num)
{
if ( CheckWordNumOk(ipc,num) == 0 )
{
return 1;
}
if ( ipc->tokenlist[num].length == 0 )
{
return 1;
}
unsigned int i=0;
for ( i = ipc->tokenlist[num].token_start; i<ipc->tokenlist[num].token_start+ipc->tokenlist[num].length; i++ )
{
switch (ipc->str[i])
{
case 10 :
break;
case 13 :
break;
case ' ' :
break;
default :
return 0;
};
}
return 1;
}
/*
InputParser_GetWord..
Copies token with number (num) to c string (wheretostore) , variable storagesize contains the total size of wheretostore..!
*/
unsigned int InputParser_GetWord(struct InputParserC * ipc,unsigned int num,char * wheretostore,unsigned int storagesize)
{
if ( CheckWordNumOk(ipc,num) == 0 )
{
return 0;
}
if ( storagesize < ipc->tokenlist[num].length+1 ) /* +1 gia to \0 */ return 0;
unsigned int i=0;
for ( i = ipc->tokenlist[num].token_start; i<ipc->tokenlist[num].token_start+ipc->tokenlist[num].length; i++ )
wheretostore[i-ipc->tokenlist[num].token_start] = ipc->str[i];
wheretostore[ipc->tokenlist[num].length] = 0;
return ipc->tokenlist[num].length;
}
/*
InputParser_WordCompareNoCase..
Compares word (word) with token with number (num) , null terminating character is not required , NO CASE SENSITIVITY..!
*/
unsigned char InputParser_WordCompareNoCase(struct InputParserC * ipc,unsigned int num,const char * word,unsigned int wordsize)
{
/*fprintf(stderr,"InputParser_WordCompareNoCase( %u , %s , %u )",num,word,wordsize);*/
if ( wordsize != InputParser_GetWordLength(ipc,num) )
{
return 0;
}
/*if ( ipc->str_length <= ipc->tokenlist[num].token_start+wordsize ) { fprintf(stderr,"Erroneous input on InputParser_WordCompareNoCase leads out of array \n"); return 0; }*/
unsigned int i=0;
for ( i=0; i<wordsize; i++ )
{
if (toupper(ipc->str[ipc->tokenlist[num].token_start+i])!=toupper(word[i]))
{
/*fprintf(stderr," returning fail ");*/ return 0;
}
}
/*fprintf(stderr," returning success ");*/
return 1;
}
/*
InputParser_WordCompareNoCase..
Compares word (word) with token with number (num) , null terminating character is required , NO CASE SENSITIVITY..!
*/
unsigned char InputParser_WordCompareNoCaseAuto(struct InputParserC * ipc,unsigned int num,const char * word)
{
if (word==0)
{
return 0;
}
unsigned int wordsize=strlen(word);
return InputParser_WordCompareNoCase(ipc,num,word,wordsize);
}
/*
InputParser_WordCompare..
Compares word (word) with token with number (num) , null terminating character is not required..!
*/
unsigned char InputParser_WordCompare(struct InputParserC * ipc,unsigned int num,const char * word,unsigned int wordsize)
{
if ( wordsize != InputParser_GetWordLength(ipc,num) )
{
return 0;
}
/*if ( ipc->str_length <= ipc->tokenlist[num].token_start+wordsize ) { fprintf(stderr,"Erroneous input on InputParser_WordCompareNoCase leads out of array \n"); return 0; }*/
unsigned int i=0;
for ( i=0; i<wordsize; i++ )
{
if (ipc->str[ipc->tokenlist[num].token_start+i]!=word[i])
{
return 0;
}
}
return 1;
}
/*
InputParser_WordCompareNoCase..
Compares word (word) with token with number (num) , null terminating character is required , NO CASE SENSITIVITY..!
*/
unsigned char InputParser_WordCompareAuto(struct InputParserC * ipc,unsigned int num,const char * word)
{
if (word==0)
{
return 0;
}
unsigned int wordsize=strlen(word);
return InputParser_WordCompare(ipc,num,word,wordsize);
}
/*
InputParser_GetUpcaseWord..
Same with InputParser_GetWord , the result is converted to upcase..!
*/
unsigned int InputParser_GetUpcaseWord(struct InputParserC * ipc,unsigned int num,char * wheretostore,unsigned int storagesize)
{
if ( CheckWordNumOk(ipc,num) == 0 )
{
return 0;
}
if ( storagesize < ipc->tokenlist[num].length+1 ) /* +1 gia to \0 */ return 0;
unsigned int i=0;
for ( i = ipc->tokenlist[num].token_start; i<ipc->tokenlist[num].token_start+ipc->tokenlist[num].length; i++ )
wheretostore[i-ipc->tokenlist[num].token_start] = toupper(ipc->str[i]);
wheretostore[ipc->tokenlist[num].length] = 0;
return ipc->tokenlist[num].length;
}
/*
InputParser_GetUpcaseWord..
Same with InputParser_GetWord , the result is converted to lowercase..!
*/
unsigned int InputParser_GetLowercaseWord(struct InputParserC * ipc,unsigned int num,char * wheretostore,unsigned int storagesize)
{
if ( CheckWordNumOk(ipc,num) == 0 )
{
return 0;
}
if ( storagesize < ipc->tokenlist[num].length+1 ) /* +1 gia to \0 */ return 0;
unsigned int i=0;
for ( i = ipc->tokenlist[num].token_start; i<ipc->tokenlist[num].token_start+ipc->tokenlist[num].length; i++ )
wheretostore[i-ipc->tokenlist[num].token_start] = tolower(ipc->str[i]);
wheretostore[ipc->tokenlist[num].length] = 0;
return ipc->tokenlist[num].length;
}
/*
InputParser_GetChar..
Returns character (pos) from token (num)..!
*/
char InputParser_GetWordChar(struct InputParserC * ipc,unsigned int num,unsigned int pos)
{
if ( CheckWordNumOk(ipc,num) == 0 )
{
return 0;
}
if ( pos>=ipc->tokenlist[num].token_start+ipc->tokenlist[num].length )
{
return 0;
}
return ipc->str[ipc->tokenlist[num].token_start + pos ];
}
/*
InputParser_GetWordInt..
Same with InputParser_GetWord , if the result can be converted to a number , it returns this number
else 0 is returned
*/
signed int InputParser_GetWordInt(struct InputParserC * ipc,unsigned int num)
{
if ( CheckWordNumOk(ipc,num) == 0 )
{
return 0;
}
return Str2Int_internal(ipc->str,ipc->tokenlist[num].token_start,ipc->tokenlist[num].length);
}
/*
InputParser_GetWordFloat..
Same with InputParser_GetWord , if the result can be converted to a float number , it returns this number
else 0.0 is returned
*/
float InputParser_GetWordFloat(struct InputParserC * ipc,unsigned int num)
{
if ( CheckWordNumOk(ipc,num) == 0 )
{
return 0.0;
}
if (ipc->tokenlist[num].length == 0 )
{
return 0.0;
}
char remember = 0;
char * string_segment = 0;
char * last_char_of_string_segment = 0;
unsigned char isLocallyAllocated = ipc->local_allocation;
unsigned int tokenStart = ipc->tokenlist[num].token_start;
unsigned int tokenLength = ipc->tokenlist[num].length;
unsigned int stringLength = ipc->str_length;
float return_value=0.0;
//Our string is a "string_segment" , and its last character ( which will be temporary become null ) is last_char_of_string_segment
if (!isLocallyAllocated)
{
string_segment = (char*) malloc( (tokenLength+1) * sizeof(char) );
//memset(string_segment,0,(tokenLength+1) * sizeof(char));
if (string_segment==0)
{
fprintf(stderr,"InputParser_GetWordFloat could not allocate memory to return float value , returning NaN \n");
return NAN;
}
strncpy(string_segment,ipc->str+tokenStart,tokenLength);
last_char_of_string_segment = string_segment + ipc->tokenlist[num].length;
}
else
{
string_segment = ipc->str+tokenStart;
last_char_of_string_segment = string_segment + ipc->tokenlist[num].length;
}
if (tokenStart + tokenLength < stringLength)
{
remember = *last_char_of_string_segment;
*last_char_of_string_segment = (char) 0; //Temporarily convert the string segment to a null terminated string
}
//else we are on the last part of the string so no reason to do the whole 0 remember thing..
#if USE_SCANF
//fprintf(stderr,"Using sscanf to parse %s \n",string_segment);
#warning "scanf without field width limits can crash with huge input data on libc versions older than 2.13-25. Add a field width specifier to fix this problem"
/*
Sample program that can crash:
#include <stdio.h>
int main()
{ int a; scanf("%i", &a); return 0; }
To make it crash:
perl -e 'print "5"x2100000' | ./a.out|
*/
sscanf(string_segment,"%f",&return_value);
#else
//fprintf(stderr,"Using atof to parse `%s` \n",string_segment);
return_value=atof(string_segment);
//fprintf(stderr,"Returns `%0.6f` \n",return_value);
#endif // USE_SCANF
if ( tokenStart + tokenLength < stringLength)
{
*last_char_of_string_segment = remember; //Restore string..
}
if (!isLocallyAllocated)
{
free(string_segment);
}
return return_value;
}
/*
InputParser_GetChar..
Returns total length of token (num)..!
*/
unsigned int InputParser_GetWordLength(struct InputParserC * ipc,unsigned int num)
{
if ( CheckWordNumOk(ipc,num) == 0 )
{
return 0;
}
return ipc->tokenlist[num].length;
}
/*
InputParser_SeperateWords..
Seperates words in c string (inpt) to tokens using delimiters set-up at structure ipc and keeps result at structure ipc
if the c string will be erased before getting back the tokens you can set the keepcopy byte to 1 , this will allocate memory to
keep a copy of the string..!
the number returned is the total of tokens extracted!
*/
int InputParser_SeperateWords(struct InputParserC * ipc,char * inpt,char keepcopy)
{
if (keepcopy==0)
{
#if WARN_ABOUT_INCORRECTLY_ALLOCATED_STACK_STRINGS
if (warningsAboutIncorrectlyAllocatedStackIssued==0)
{
fprintf(stderr,"Please note that feeding input parser with strings allocated on the stack it is generally a good idea to enable keepcopy\n");
fprintf(stderr,"For example passing here a string allocated as char* hello = \"hello!\"; might lead to a segFault ( i.e. when calling InputParser_GetWordFloat ) \n");
fprintf(stderr,"The correct way for allocating a string with in place processing is char hello[] = \"hello!\"; \n");
fprintf(stderr,"Valgrind classifies these errors as \"Bad permissions for mapped region at address\" \n");
++warningsAboutIncorrectlyAllocatedStackIssued ;
}
#endif
}
if (CheckIPCOk(ipc)==0)
{
return 0;
}
if ( inpt == 0 ) return 0; /* NULL INPUT -> NULL OUTPUT*/
unsigned int STRING_END = strlen(inpt) ;
int WORDS_SEPERATED = 0 , NEXT_SHOULD_NOT_BE_A_DELIMITER=1 , FOUND_DELIMETER ; /* Ignores starting ,,,,,string,etc*/
if ( STRING_END == 0 )
{
return 0; /* NULL INPUT -> NULL OUTPUT pt 2*/
}
/* >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
COPY STRING ( OR POINTER ) TO IPC STRUCTURE*/
if ( keepcopy == 1 ) /* IF WE HAVE ALREADY ALLOCATED A STRING TO ipc->str , we should free it to prevent memory leaks!*/
{
if (ipc->local_allocation == 1)
{
if (ipc->str!=0)
{
/* ipc->str contains a previous value!*/
free(ipc->str);
ipc->local_allocation = 0;
}
}
ipc->str = (char * ) malloc( sizeof(char) * (STRING_END+1) );
memset(ipc->str,0,sizeof(char) * (STRING_END+1));
ipc->local_allocation = 1;
strncpy( ipc->str , inpt , STRING_END ) ;
}
else
{
ipc->str = inpt;
}
ipc->str_length = STRING_END;
/* COPY STRING ( OR POINTER ) TO IPC STRUCTURE
>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>*/
unsigned int i,z;
ipc->tokens_count = 0 , ipc->tokenlist[0].token_start=0;
for (i=0; i<STRING_END; i++)
{
FOUND_DELIMETER = 0;
for (z=0; z<ipc->cur_delimeter_count; z++)
{
if ( inpt[i] == ipc->delimeters[z] )
{
FOUND_DELIMETER = 1;
if (NEXT_SHOULD_NOT_BE_A_DELIMITER==0)
{
ipc->tokenlist[ipc->tokens_count].length = i - ipc->tokenlist[ipc->tokens_count].token_start;
ipc->tokens_count+=1;
ipc->tokenlist[ipc->tokens_count].token_start = i+1;
WORDS_SEPERATED+=1;
break;
}
else
{
ipc->tokenlist[ipc->tokens_count].token_start=i+1;
}
}
}
if (FOUND_DELIMETER == 0 ) NEXT_SHOULD_NOT_BE_A_DELIMITER=0;
else if (FOUND_DELIMETER == 1 ) NEXT_SHOULD_NOT_BE_A_DELIMITER=1;
}
if (NEXT_SHOULD_NOT_BE_A_DELIMITER==0)
{
ipc->tokenlist[ipc->tokens_count].length = i - ipc->tokenlist[ipc->tokens_count].token_start;
ipc->tokens_count+=1;
ipc->tokenlist[ipc->tokens_count].token_start = i+1;
WORDS_SEPERATED+=1;
}
else
ipc->tokenlist[ipc->tokens_count].length = i - ipc->tokenlist[ipc->tokens_count].token_start;
return WORDS_SEPERATED;
}
/*
Same with InputParser_SeperateWords it does the (char *) type cast
*/
int InputParser_SeperateWordsCC(struct InputParserC * ipc,const char * inpt,char keepcopy)
{
return InputParser_SeperateWords(ipc,(char * )inpt,keepcopy);
}
/*
Same with InputParser_SeperateWords it does the (char *) type cast
*/
int InputParser_SeperateWordsUC(struct InputParserC * ipc,unsigned char * inpt,char keepcopy)
{
return InputParser_SeperateWords(ipc,(char * )inpt,keepcopy);
}
@@ -0,0 +1,392 @@
/** @file InputParser_C.h
* @brief A very handy string tokenizer for C this basically a swiss army knife kind code segment that can be used wherever we get strings
* and we want to seperate them. This code is used in many of my projects including and not limited to
* https://github.com/AmmarkoV/RoboVision
* https://github.com/AmmarkoV/FlashySlideshows
* https://github.com/AmmarkoV/RGBDAcquisition
* https://github.com/AmmarkoV/AmmarServer
* Basic usage is the following
*
* struct InputParserC * ipc=0;
* ipc = InputParser_Create(512,5); //We want to separte lines of Max 512 different strings seperated using 5 delimiters
* InputParser_SetDelimeter(ipc,0,' '); //We want to seperate spaces
*
* char word[512];
* int numberOfWords = InputParser_SeperateWords(ipc,"zero,one,2,three(four)",1);
* for (int i=0; i<numberOfWords; i++)
* {
* InputParser_GetWord(ipc,i,word,512);
* }
* InputParser_Destroy(ipc);
*
* @author Ammar Qammaz (AmmarkoV)
*/
#ifndef _INPUTPARSER_C_H_
#define _INPUTPARSER_C_H_
#ifdef __cplusplus
extern "C" {
#endif
#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <ctype.h>
/** @brief Controls the use of scanf for getting back floats ,
scanf without field width limits can crash with huge input data on libc versions older than 2.13-25.
so this is better turned of and atof is used to do the float conversion*/
#define USE_SCANF 0
/**
* @brief A struct that contains the token list
*/
struct tokens
{
/* START MEANS THE FIRST CHARACTER TO READ..!
LENGTH MEANS total characters to be read
i.e. a _ S _ A _ M _ P _ L _ E
0 1 2 3 4 5 6
this token starts from 0 and has 7 characters length*/
unsigned int token_start;
unsigned int length;
};
/**
* @brief Guard Byte to make sure that there is no overflow
*/
struct guard_byte
{
unsigned int checksum;
};
/**
* @brief The structure that holds all of the Input Parsing Context
*/
struct InputParserC
{
/* >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> */
struct guard_byte guardbyte1;
/* >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> */
unsigned int str_length;
unsigned char local_allocation;
char * str; /* String to process */
/* >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> */
struct guard_byte guardbyte2;
/* >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> */
unsigned short cur_container_count;
unsigned short max_container_count;
char *container_start;
char *container_end;
unsigned short cur_delimeter_count;
unsigned short max_delimeter_count;
char *delimeters;
/* >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> */
struct guard_byte guardbyte3;
/* >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> */
/* RESULT */
unsigned int tokens_max;
unsigned int tokens_count;
struct tokens* tokenlist;
/* >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> */
struct guard_byte guardbyte4;
/* >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> */
};
/**
* @brief Get Back a String containing the version of the InputParser
* @retval Pointer to a C String that contains the version of InputParser
*/
char * InputParserC_Version();
/**
* @brief Clear any non-character characters from string
* @ingroup InputParser
* @param String Input/Output
* @param Length of String
* @retval 1 if success , 0 if not
*/
int InputParser_ClearNonCharacters(char * inpt , unsigned int length);
/**
* @brief Trim Starting Characters preceeding string
* @ingroup InputParser
* @param String Input/Output
* @param Length of String
* @param Character to Trim
* @retval 1 if success , 0 if not
*/
int InputParser_TrimCharactersStart(char * inpt , unsigned int length,char what2trim);
/**
* @brief Trim Starting Characters after string
* @ingroup InputParser
* @param String Input/Output
* @param Length of String
* @param Character to Trim
* @retval 1 if success , 0 if not
*/
int InputParser_TrimCharactersEnd(char * inpt , unsigned int length,char what2trim);
/**
* @brief This call will remove all characters specified from the string
* @ingroup InputParser
* @param String Input/Output
* @param Length of String
* @param Character to Trim
* @retval 1 if success , 0 if not
*/
int InputParser_TrimCharacters(char * inpt , unsigned int length,char what2trim);
/**
* @brief This call will setup the default delimiters that are typically used , these are '\n' ',' '=' '(' and ')'
* these can be also read by InputParser_GetDelimeter or changed at any time using InputParser_SetDelimeter
* @ingroup InputParser
* @param InputParser Context ( needs to be created using InputParser_Create )
*/
void InputParser_DefaultDelimeters(struct InputParserC * ipc);
/**
* @brief This call will change the value of a delimiter so that it will also act as a tokenization split character
* @ingroup InputParser
* @param InputParser Context ( needs to be created using InputParser_Create )
* @param Number of delimiter we want to set ( has to be less than the max_delimiter_count value we gave in InputParser_Create )
* @param New Value for the delimiter we want to set
*/
void InputParser_SetDelimeter(struct InputParserC * ipc,int num,char tmp);
/**
* @brief Get Back the characters that are used as delimiters
* @ingroup InputParser
* @param InputParser Context ( needs to be created using InputParser_Create )
* @param Number of delimiter we want to set ( has to be less than the max_delimiter_count value we gave in InputParser_Create )
* @retval Character used as delimiter , or Null if incorrect delimter number requested
*/
char InputParser_GetDelimeter(struct InputParserC * ipc,int num);
/**
* @brief Create an InputParser Structure and Context that can be used to tokenize strings
* @ingroup InputParser
* @param The maximum number of strings/tokens to be returned as output from a SeperateWords command
* @param The maximum number of delimters used typically 5 for the defaults '\n' ',' '=' '(' and ')'
* @retval InputParser Context , or Null if there is an error
*/
struct InputParserC * InputParser_Create(unsigned int max_string_count,unsigned int max_delimiter_count);
/**
* @brief Destroy an InputParser Structure and Context and safely free all of the memory it might have allocated
* @ingroup InputParser
* @param InputParser Context ( needs to be created using InputParser_Create )
*/
void InputParser_Destroy(struct InputParserC * ipc);
/**
* @brief Perform an internal integrity check
* @ingroup InputParser
* @param InputParser Context to be checked ( needs to be created using InputParser_Create )
* @retval 1=Success,0=Error
*/
unsigned char InputParser_SelfCheck(struct InputParserC * ipc);
/**
* @brief Retrieve the number of arguments seperated from the last InputParser_SeperateWords call
* @ingroup InputParser
* @param InputParser Context to be used ( needs to be created using InputParser_Create )
* @retval Number of arguments tokenized , 0=No arguments/Error
*/
unsigned int InputParser_GetNumberOfArguments(struct InputParserC * ipc);
/**
* @brief Check if a word ( InputParser_GetWord ) is empty after issuing a InputParser_SeperateWords call
* @ingroup InputParser
* @param InputParser Context to be used ( needs to be created using InputParser_Create )
* @param Word that we want to check
* @retval 1=Success,0=Error
*/
unsigned int InputParser_IsEmptyWord(struct InputParserC * ipc,unsigned int num);
/**
* @brief Checks if word with number num has allocated space in memory ( see InputParser_GetWord )
* @ingroup InputParser
* @param InputParser Context to be used ( needs to be created using InputParser_Create )
* @param Word that we want to check
* @retval 1=Success,0=Error
*/
unsigned char CheckWordNumOk(struct InputParserC * ipc,unsigned int num);
/**
* @brief Get a specific character of a Word ( instead of the whole string that would be returned with InputParser_GetWord )
* @ingroup InputParser
* @param InputParser Context to be used ( needs to be created using InputParser_Create )
* @param Word that we want to check
* @param Character of word we want to get back
* @retval Character we requested or null if there is an error
*/
char InputParser_GetWordChar(struct InputParserC * ipc,unsigned int num,unsigned int pos);
/**
* @brief Compare two words without case sensitivity and return wether they match or not..!
* @ingroup InputParser
* @param InputParser Context to be used ( needs to be created using InputParser_Create )
* @param Word that we want to check
* @param String that we want to compare against
* @param Length of String that we want to compare against
* @retval 1=Match,0=Strings are different
*/
unsigned char InputParser_WordCompareNoCase(struct InputParserC * ipc,unsigned int num,const char * word,unsigned int wordsize);
/**
* @brief Same as InputParser_WordCompareNoCase but supposes word is null terminated and auto-counts its length
* @ingroup InputParser
* @param InputParser Context to be used ( needs to be created using InputParser_Create )
* @param Word that we want to check
* @param String that we want to compare against ( that should be null terminated )
* @retval 1=Match,0=Strings are different
*/
unsigned char InputParser_WordCompareNoCaseAuto(struct InputParserC * ipc,unsigned int num,const char * word);
/**
* @brief Compare two words with case sensitivity and return wether they match or not..!
* @ingroup InputParser
* @param InputParser Context to be used ( needs to be created using InputParser_Create )
* @param Word that we want to check
* @param String that we want to compare against ( that should be null terminated )
* @retval 1=Match,0=Strings are different
*/
unsigned char InputParser_WordCompare(struct InputParserC * ipc,unsigned int num,const char * word,unsigned int wordsize);
/**
* @brief Same as InputParser_WordCompare but supposes word is null terminated and auto-counts its length
* @ingroup InputParser
* @param InputParser Context to be used ( needs to be created using InputParser_Create )
* @param Word that we want to check
* @param String that we want to compare against ( that should be null terminated )
* @retval 1=Match,0=Strings are different
*/
unsigned char InputParser_WordCompareAuto(struct InputParserC * ipc,unsigned int num,const char * word);
/**
* @brief Get back a string ( token ) after performing InputParser_SeperateWords
* @ingroup InputParser
* @param InputParser Context to be used ( needs to be created using InputParser_Create )
* @param Word that we want to get
* @param Pointer to a C String that will accomodate the output
* @param Size of Pointer provided , should be big enough for the whole string plus its null terminator
* @retval 1=Sucess,0=Failure
*/
unsigned int InputParser_GetWord(struct InputParserC * ipc,unsigned int num,char * wheretostore,unsigned int storagesize);
/**
* @brief Get back an uppercase string ( token ) after performing InputParser_SeperateWords
* @ingroup InputParser
* @param InputParser Context to be used ( needs to be created using InputParser_Create )
* @param Word that we want to get
* @param Pointer to a C String that will accomodate the output
* @param Size of Pointer provided , should be big enough for the whole string plus its null terminator
* @retval 1=Sucess,0=Failure
*/
unsigned int InputParser_GetUpcaseWord(struct InputParserC * ipc,unsigned int num,char * wheretostore,unsigned int storagesize);
/**
* @brief Get back a lowercase string ( token ) after performing InputParser_SeperateWords
* @ingroup InputParser
* @param InputParser Context to be used ( needs to be created using InputParser_Create )
* @param Word that we want to get
* @param Pointer to a C String that will accomodate the output
* @param Size of Pointer provided , should be big enough for the whole string plus its null terminator
* @retval 1=Sucess,0=Failure
*/
unsigned int InputParser_GetLowercaseWord(struct InputParserC * ipc,unsigned int num,char * wheretostore,unsigned int storagesize);
/**
* @brief Get back a signed integer ( token ) after performing InputParser_SeperateWords
* @ingroup InputParser
* @param InputParser Context to be used ( needs to be created using InputParser_Create )
* @param Word that we want to get
* @retval The value in the form of a number of token with number num , if the token is not a number returns null
*/
signed int InputParser_GetWordInt(struct InputParserC * ipc,unsigned int num);
/**
* @brief Get back a float ( token ) after performing InputParser_SeperateWords
* @ingroup InputParser
* @param InputParser Context to be used ( needs to be created using InputParser_Create )
* @param Word that we want to get
* @retval The value in the form of a floating precision number of token , if the token is not a number returns NaN
*/
float InputParser_GetWordFloat(struct InputParserC * ipc,unsigned int num);
/**
* @brief Get back The Length of a token so that we can allocate a proper buffer and then call InputParser_GetWord
* @ingroup InputParser
* @param InputParser Context to be used ( needs to be created using InputParser_Create )
* @param Word that we want to get
* @retval The length of the token string size , 0=Failure to access token num
*/
unsigned int InputParser_GetWordLength(struct InputParserC * ipc,unsigned int num);
/**
* @brief Split input string in tokens, this is the main functionality of this library..!
* @ingroup InputParser
* @param InputParser Context to be used ( needs to be created using InputParser_Create )
* @param Word that we want to split to tokens
* @param 1=Keep a copy of the input string, this is safer in case the input string changes from another thread etc. , 0=Zero copy splitting that has more chances of going wrong
* @retval The number of tokens split,0=Failure
*/
int InputParser_SeperateWords(struct InputParserC * ipc,char * inpt,char keepcopy);
/**
* @brief Same as InputParser_SeperateWords but accepts const char strings as input
* @ingroup InputParser
* @param InputParser Context to be used ( needs to be created using InputParser_Create )
* @param Word that we want to split to tokens
* @param 1=Keep a copy of the input string, this is safer in case the input string changes from another thread etc. , 0=Zero copy splitting that has more chances of going wrong
* @retval The number of tokens split,0=Failure
*/
int InputParser_SeperateWordsCC(struct InputParserC * ipc,const char * inpt,char keepcopy);
/**
* @brief Same as InputParser_SeperateWords but accepts unsigned char strings as input
* @ingroup InputParser
* @param InputParser Context to be used ( needs to be created using InputParser_Create )
* @param Word that we want to split to tokens
* @param 1=Keep a copy of the input string, this is safer in case the input string changes from another thread etc. , 0=Zero copy splitting that has more chances of going wrong
* @retval The number of tokens split,0=Failure
*/
int InputParser_SeperateWordsUC(struct InputParserC * ipc,unsigned char * inpt,char keepcopy);
#ifdef __cplusplus
}
#endif
#endif
@@ -0,0 +1,2 @@
This code actually has it's own repository ( https://github.com/AmmarkoV/InputParser ) and also included in the AmmarServer dependency ( https://github.com/AmmarkoV/AmmarServer/tree/master/src/InputParser )
However to simplify build process it is also included as standalone here.
@@ -0,0 +1,3 @@
This is the dependencies subdirectory
At minimum here there should be a libtensorflow , RGBDAcquisition and maybe an opencv-3.2.0
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/**
@mainpage MocapNET
@author Ammar Qammaz a.k.a. AmmarkoV - http://ammar.gr
Ensemble of SNN Encoders for 3D Human Pose Estimation in RGB Images
Website: https://github.com/AmmarkoV/RGBDAcquisition
@section libIntro Introduction
We present MocapNET, an ensemble of SNN encoders that estimates the 3D human body pose based on 2D joint estimations extracted from monocular RGB images. MocapNET provides an efficient divide and conquer strategy for supervised learning. It outputs skeletal information directly into the BVH format which can be rendered in real-time or imported without any additional processing in most popular 3D animation software. The proposed architecture achieves 3D human pose estimations at state of the art rates of 400Hz in high-end systems using only CPU processing.
Please cite the following paper if this work helps your research :
@inproceedings{Qammaz2019,
author = {Qammaz, Ammar and Argyros, Antonis A},
title = {MocapNET: Ensemble of SNN Encoders for 3D Human Pose Estimation in RGB Images},
booktitle = {British Machine Vision Conference (BMVC 2019)},
publisher = {BMVA},
year = {2019},
month = {September},
address = {Cardiff, UK},
url = {http://users.ics.forth.gr/argyros/res_mocapnet.html},
projects = {CO4ROBOTS,MINGEI},
pdflink = {http://users.ics.forth.gr/ argyros/mypapers/2019_09_BMVC_mocapnet.pdf},
videolink = {https://youtu.be/fH5e-KMBvM0}
}
@section libDesignOverview Overview, System Requirements and Dependencies
MocapNET is a high performance 2D to 3D single person pose estimator. This code base targets recent Linux (Ubuntu 18.04 - 20.04 +) machines, and relies on the Tensorflow C-API and OpenCV. Windows 10 users can try the linux subsystem that has been also reported to work.
Tensorflow is used as the Neural Network framework for our work and OpenCV is used to enable the acquisition of images from webcams or video files as well as to provide an easy visualization method.
We have provided an initialization script that automatically handles most dependencies, as well as download all needed pretrained models. After running it the application should be ready for use.
Any issues not automatically resolved by the script can be reported on the issues section of this repository.
In order to enable a series of easy to use mini-demos with as few dependencies as possible. We have included a MocapNETBenchmark utility which has hardcoded input and output that can run even in a system without OpenCV to give you a performance estimation of our method. If you have OpenCV available you can use our live demo ( MocapNETLiveWebcamDemo binary ) that also contains the 2D joint detector. By giving it the correct parameters you can switch between a cut-down version of OpenPose (--openpose), VNect (--vnect) or our own MobileNet (default) based 2D joint estimator. All of these are automatically downloaded using the initialize.sh script. However in order to achieve higher accuracy estimations you are advised to set up a full OpenPose instance and use it to acquire JSON files with 2D detections that can be subsequently converted to 3D BVH files using the MocapNETJSON binary. They will provide superior accuracy compared to the bundled 2D joint detectors which are provided for faster performance in the live demo, since 2D estimation is the bottleneck of the application. The lowest end machine where this codebase is currently deployed is an Intel Core 2 6600 PC with 4GB of RAM and an NVIDIA GeForce GT740 GPU where MocapNET achieves 50fps and the bundled 2D Joint Detector 10fps for an aggregate 7fps of 3D pose estimation from RGB. Our live demo will try to run the 2D Joint estimation on your GPU and MocapNET 3D estimation on the system CPU to achieve a combined framerate of over 30 fps which in most cases matches or surpasses the acquisition rate of web cameras. Unfortunately there are many GPU compatibility issues with Tensorflow C-API builds since recent versions have dropped CUDA 9.0 support as well as compute capabilities that might be required by your system, you can edit the initialize.sh script and change the variable TENSORFLOW_VERSION according to your needs. If you want CUDA 9.0 you should se it to 1.12.0. If you want CUDA 9.0 and have a card with older compute capabilities (5.2) then choose version 1.11.0. If all else fails you can always recompile the tensorflow C-API to match your specific hardware configuration. You can also use this script that automates building tensorflow r1.15 that might help you, dealing with the Bazel build system and all of its weirdness. Release 1.15 is the final of the 1.x tensorflow tree and is compatible with MocapNET, Tensorflow 2.0 does not yet have C bindings and is thus not yet supported, according to the Tensorflow site, version 2.3 will be the first to re-include C bindings.
If you are interested in generating BVH training data for your research, we have also provided the code that handles randomization and pose perturbation from the CMU dataset. After a successful compilation, dataset generation is accessible using the scripts scripts/createRandomizedDataset.sh and scripts/createTestDataset.sh. All BVH manipulation code is imported from a secondary github project that is automatically downloaded, included and built using the initialize.sh script. These scripts/createRandomizedDataset.sh and scripts/createTestDataset.sh scripts will populate the dataset/ directory with CSV files that contain valid training samples based on the CMU dataset. It is trivial to load these files using python. After loading them using them as training samples in conjunction with a deep learning framework like Keras you can facilitate learning of 2D to 3D BVH.
@section libBuilding Building the library
To compile the library issue :
sudo apt-get install build-essential cmake libopencv-dev libjpeg-dev libpng-dev libglew-dev libpthread-stubs0-dev
./initialize.sh
After performing changes to the source code, you do not need to rerun the initialization script. You can recompile the code by using :
cd build
cmake ..
make
cd ..
@section libUpdating Updating the library
The MocapNET library is under active development, the same thing is true for its dependencies.
In order to update all the relevant parts of the code you can use the update.sh script provided.
./update.sh
If you made changes to the source code that you want to discard and want to revert to the master you can also use the revert.sh script provided
./revert.sh
*/
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Workflow for 2-D Video Conversion to a .bvh File on Windows and Linux
For highest speed and accuracy install OpenPose, in a Linux, Windows or Mac system, using the faster GPU version if a capable GPU is available. Probably a graphics card with 8GB of VRAM is the minimum needed. As described later, a Linux system will be needed to run the MocapNET utilities for making conversions to a .bvh file.
After installing OpenPose, navigate in a terminal to wherever the openpose directory is located. For example in Windows PowerShell:
cd D:\openpose-1.7.0-binaries-win64-gpu-python3.7-flir-3d_recommended\openpose
Run OpenPose as shown here for Windows PowerShell:
bin\OpenPoseDemo.exe --video D:\Test4.mp4 --hand --scale_number 8 --scale_gap 0.125 --net_resolution "320x176" --write_json output_jsons/ --model_pose BODY_25B -number_people_max 1
The above command specifies slower, higher accuracy scale flags with body bones and additional hand bones. Add --face to generate face bones if there is enough graphics memory. A rather low net resolution is needed to prevent Cuda out of video memory errors. 320x176 resolution works on an 8GB VRAM RTX 2070. If you have more video memory you might be able to set the resolution with --net_resolution -1x368 or higher. OpenPose can process a crowd but the programs to convert its output to a .bvh file handle one person only. The --model_pose BODY_25B flag specifies a high resolution body model that can be added as follows:
Download the Caffe model (100 MB) from:
http://posefs1.perception.cs.cmu.edu/OpenPose/models/pose/1_25BBkg/body_25b/pose_iter_XXXXXX.caffemodel
Then go to:
https://github.com/CMU-Perceptual-Computing-Lab/openpose_train/blob/master/experimental_models/1_25BBkg/body_25b
Right-click on the pose_deploy.prototxt file and Save link as..., which will name it as pose_deploy.prototxt. Save it into an openpose/models/pose/body_25b folder you create. Also put the Caffe model you downloaded in this folder. You can now run OpenPose with this higher accuracy model.
The output of the OpenPose run will be in the folder openpose/output_jsons containing .json files that specify the joints’ x and y positions for each frame. For the next operation change all the .json file names using, for example, Bulk Rename Utility in Windows and rename the resulting folder with a convenient name such as BRUout. Change sections Name (2) Fixed, and Numbering (10) Mode, Insert at 13, Start 0 and Pad 5. The exact new names of the .json files should be:
colorFrame_0_00000_keypoints.json, colorFrame_0_00001_keypoints.json, etc.
Install MocapNET
Run the MocapNET installer in an Ubuntu-like Linux system after installing the dependencies. MocapNET has utilities to convert the OpenPose .json files into a comma-separated-values (CSV) file, which in turn will be converted into a .bvh file. If your computer has Windows only, you can try the command-line Windows Subsystem for Linux (WSL) in newer versions of Win 10, though it won’t provide a graphical output. Otherwise install Ubuntu as a virtual machine in VirtualBox on Windows. Another solution is to add Ubuntu as a dual-boot option on a Windows computer.
After installation of MocapNET copy the BRUout folder created above into the MocapNET folder. Then in a terminal navigate to the MocapNET folder and run:
./convertOpenPoseJSONToCSV --from BRUout --size 640 480
The program will run, showing the progress of processing the data and will output a file stored at BRUout/2dJoints_v1.4.csv. This CSV file can then be further processed with the following command:
./MocapNET2CSV --from BRUout/2dJoints_v1.4.csv --size 640 480
After completion the output will be an out.bvh file in the MocapNET folder. This file can be loaded into Blender, etc. using an import mocap bvh option, and re-targeted to any desired armature for animation. One good option is to use the MakeHuman program to generate a model with a matching CMU body, hands and face rig. The MakehHuman MHX2 option provides another way to retarget the .bvh to an armature.
Note that presently the public version of MocapNET supports conversion of body bones only, but hand and face bone support is well underway.
- end -
@@ -0,0 +1,99 @@
## Towards Holistic Real-time Human 3D Pose Estimation using MocapNETs
### Ablation study experimental results
_Ammar Qammaz_
<br/>
<br/>
This is a summary of the ablation experiments that accompanies the following paper:
A. Qammaz and A.A. Argyros, "Towards Holistic Real-time Human 3D Pose Estimation using MocapNETs", In British Machine Vision Conference (BMVC 2021), (to appear), BMVA, UK, November 2021.
We conducted all the experiments listed here by acquiring the STB and RHD datasets from the [VAE 3D hands repository](https://github.com/spurra/vae-hands-3d). We used the [HandOnlyTest utility](https://github.com/FORTH-ModelBasedTracker/MocapNET/blob/master/src/MocapNET2/HandOnlyTest/handTest.cpp) to compute standalone 3D hand poses and this [Python utility](https://github.com/FORTH-ModelBasedTracker/MocapNET/blob/master/src/python/compareUtility/compareUtility.py) to compare the 3D output of the proposed method to ground truth and extract results.
Due to RAM constraints, the largest generated data samples consisted of 7.276.716 M samples. A fully trained ensemble for the left hand took approximately 6 days to train for 7M samples. Using a tenth of the sample size (727K) we where able to conduct faster experiments to cover a larger variety of combinations, but we also used an intermediate 1/2 sample ratio with 3,638,568 samples also comparing the possible variance that sample size introduces to the training procedure. It should be noted that we generate each of the [3 differently sized datasets *once* using this tool](https://github.com/FORTH-ModelBasedTracker/MocapNET/blob/master/scripts/createRandomHandDataset.sh#L58) in order for all the experiments across a sample size to be directly compareable. The tensorflow [randomized seed](https://www.tensorflow.org/api_docs/python/tf/random/set_seed) is also fixed to 0 for each training to be deterministic and reproducible.
The tables below are all variations on the final proposed setup of the MocapNET3 ensemble that uses *Hierarchical Coordinate Descent (HCD)* optimization as a fine tuning step, *eNSRM* descriptors to encode 2D input data, *SWISH* activations, a dropout of *0.3* or 30% and where each of the encoders regresses *1 degree of freedom(d.o.f.)* . Starting from this configuration we alternate settings to inspect how they affect 3D pose estimation training accuracy on the STB and RHD datasets.
The first set of "small" sample size experiments using 1/10 of the final sample size for different combinations of a 2D Descriptor, comparing the proposed eNSRM with the rich diagonal with the [MocapNET2 NSRM](http://users.ics.forth.gr/~argyros/mypapers/2021_01_ICPR_Qammaz.pdf) and the [Self-normalizing (SELU)](https://arxiv.org/abs/1706.02515) activations of [MocapNET 1](http://users.ics.forth.gr/~argyros/mypapers/2019_09_BMVC_mocapnet.pdf) and [MocapNET 2](http://users.ics.forth.gr/~argyros/mypapers/2021_01_ICPR_Qammaz.pdf). Finally, all runs are tested with and without the Hierarchical Coordinate Descent fine-tuning step introduced in [MocapNET 2](http://users.ics.forth.gr/~argyros/mypapers/2021_01_ICPR_Qammaz.pdf).
<br/>
| Sample Size | Dropout | D.o.f. | HCD | Descriptor | Activation | STB avg. acc. | RHD avg. acc. |
| :-: | :-: | :-: | :-: | :-: | :-: | :-: | :-: |
| 727.591 | 0.3 | 1 | &#10003; | NSRM | SWISH | 10.2 mm | 24.9 mm |
| 727.591 | 0.3 | 1 | &#10003; | eNSRM | SWISH | 11.8 mm | 25.0 mm |
| 727.591 | 0.3 | 1 | &#10003; | eNSRM | SELU | 10.1 mm | 25.2 mm |
| 727.591 | 0.3 | 1 | &#10003; | NSRM | SELU | 10.6 mm | 25.1 mm |
| 727.591 | 0.3 | 1 | &#10007; | NSRM | SWISH | 15.6 mm | 26.1 mm |
| 727.591 | 0.3 | 1 | &#10007; | eNSRM | SWISH | 18.2 mm | 26.4 mm |
| 727.591 | 0.3 | 1 | &#10007; | eNSRM | SELU | 18.0 mm | 27.1 mm |
| 727.591 | 0.3 | 1 | &#10007; | NSRM | SELU | 15.9 mm | 26.5 mm |
One of the first observations is that the HCD step plays an important role in improving accuracy, especially on temporarilly cohesive input data such as the STB data. The results also show that since the HCD improvements improve the results of the neural network, in order to properly compare neural network configurations this is best done when HCD is turned off. We also observe that for this small sample size although the proposed SWISH activation performs better than the [MNET2](http://users.ics.forth.gr/~argyros/mypapers/2021_01_ICPR_Qammaz.pdf) [SELU]((https://arxiv.org/abs/1706.02515) the richer diagonal actually makes the task more difficult for the neural network although the slightly increased error is still recoverable via the HCD step.
Another idea we tested is grouping together encoder outputs. Since the internal state of each of the encoders could theoretically be reused across more than one degrees of freedom, especially since many joints feature more than one degrees of freedoms, we attempted to regress 2,3 and 5 degrees of freedom using the same encoder. Testing these configurations without the HCD step reveals a gradually worse accuracy. This is to be expected since this was one of the reasons for the ensemble architecture of encoders with 1 d.o.f. . Our explanation for this behavior is that sharing the capacity of the network between more than one degrees of freedom means less network computations resources dedicated to each of the outputs. It also means that during training the loss function becomes less indicative of each of the outputs making the training procedure gradually harder.
<br/>
| Sample Size | Dropout | D.o.f. | HCD | Descriptor | Activation | STB avg. acc. | RHD avg. acc. |
| :-: | :-: | :-: | :-: | :-: | :-: | :-: | :-: |
| 727.591 | 0.3 | 2 | &#10007; | eNSRM | SWISH | 19.8 mm | 25.0 mm |
| 727.591 | 0.3 | 3 | &#10007; | eNSRM | SWISH | 25.5 mm | 24.2 mm |
| 727.591 | 0.3 | 5 | &#10007; | eNSRM | SWISH | 27.0 mm | 27.3 mm |
In order to successfully deepen a densely connected network we have employed residual connections and relatively intense dropout rates. Concerned about wether the high drop-out rate could cause the network encoders (seen in Figure 2 of the paper) to over-rely on the skip connections and thus effectively really utilize only a lower total number of layers, we performed experiments varying the dropout rate to study the effects. We observe that increased dropout improves results especially in the RHD dataset, however the accuracy variance is not indicative of such a side-effect.
<br/>
| Sample Size | Dropout | D.o.f. | HCD | Descriptor | Activation | STB avg. acc. | RHD avg. acc. |
| :-: | :-: | :-: | :-: | :-: | :-: | :-: | :-: |
| 727.591 | 0.1 | 1 | &#10003; | eNSRM | SWISH | 10.1 mm | 25.3 mm |
| 727.591 | 0.1 | 1 | &#10007; | eNSRM | SWISH | 19.1 mm | 27.2 mm |
| 727.591 | 0.2 | 1 | &#10003; | eNSRM | SWISH | 10.9 mm | 24.9 mm |
| 727.591 | 0.2 | 1 | &#10007; | eNSRM | SWISH | 18.2 mm | 26.7 mm |
| 727.591 | 0.25 | 1 | &#10003; | eNSRM | SWISH | 10.4 mm | 25.0 mm |
| 727.591 | 0.25 | 1 | &#10007; | eNSRM | SWISH | 19.3 mm | 26.8 mm |
We also performed some ablation experiments using the full sample size proposed in the paper. The following experiments that took approximately 3 weeks to complete, show less variance between the different combinations of design characteristics when HCD is enabled.
<br/>
| Sample Size | Dropout | D.o.f. | HCD | Descriptor | Activation | STB avg. acc. | RHD avg. acc. |
| :-: | :-: | :-: | :-: | :-: | :-: | :-: | :-: |
| 7.276.716 | 0.3 | 1 | &#10003; | eNSRM | SWISH | 9.9 mm | 25.3 mm |
| 7.276.716 | 0.3 | 1 | &#10007; | eNSRM | SWISH | 20.5 mm | 26.8 mm |
| 7.276.716 | 0.3 | 1 | &#10003; | NSRM | SWISH | 9.8 mm | 25.0 mm |
| 7.276.716 | 0.3 | 1 | &#10007; | NSRM | SELU | 19.5 mm | 26.3 mm |
| 7.276.716 | 0.3 | 1 | &#10003; | NSRM | SELU | 9.9 mm | 25.2 mm |
| 7.276.716 | 0.3 | 1 | &#10007; | NSRM | SELU | 17.6 mm | 27.5 mm |
Finally, using a dataset 1/2 the size of our final size we once again perform variations on the proposed configuration and we manage to slightly improve the best results of our method achieving 9.7 mm for the STB and 25.0 mm for the RHD. However, since the BMVC publication policies prohibit updating experimental results during the rebuttal period we did not include these slightly improved figures on the paper.
<br/>
| Sample Size | Dropout | D.o.f. | HCD | Descriptor | Activation | STB avg. acc. | RHD avg. acc. |
| :-: | :-: | :-: | :-: | :-: | :-: | :-: | :-: |
| 3.638.568 | 0.3 | 1 | &#10003; | eNSRM | SWISH | 9.7 mm | 25.0 mm |
| 3.638.568 | 0.3 | 1 | &#10007; | eNSRM | SWISH | 18.6 mm | 26.7 mm |
| 3.638.568 | 0.3 | 1 | &#10003; | NSRM | SWISH | 10.0 mm | 24.9 mm |
| 3.638.568 | 0.3 | 1 | &#10007; | NSRM | SWISH | 17.6 mm | 26.1 mm |
| 3.638.568 | 0.3 | 1 | &#10003; | NSRM | SELU | 11.5 mm | 25.1 mm |
| 3.638.568 | 0.3 | 1 | &#10007; | NSRM | SELU | 18.9 mm | 26.3 mm |
| 3.638.568 | 0.3 | 1 | &#10003; | eNSRM | SELU | 9.9 mm | 25.2 mm |
| 3.638.568 | 0.3 | 1 | &#10007; | eNSRM | SELU | 17.6 mm | 27.5 mm |
| 3.638.568 | 0.1 | 1 | &#10003; | eNSRM | SWISH | 10.2 mm | 25.2 mm |
| 3.638.568 | 0.1 | 1 | &#10007; | eNSRM | SWISH | 17.2 mm | 26.9 mm |
| 3.638.568 | 0.1 | 1 | &#10003; | eNSRM | SELU | 10.0 mm | 25.4 mm |
| 3.638.568 | 0.1 | 1 | &#10007; | eNSRM | SELU | 16.3 mm | 27.2 mm |
| 3.638.568 | 0.1 | 1 | &#10003; | NSRM | SELU | 10.8 mm | 25.2 mm |
| 3.638.568 | 0.1 | 1 | &#10007; | NSRM | SELU | 19.8 mm | 26.6 mm |
To summarize our ablation study results, the hierarchical coordinate descent (HCD) algorithm provides significant pose estimation improvements regardless of the configuration and training of the neural network providing the initial 3D pose estimation. That being said, a network that can arrive closer to the correct solution makes HCD perform even better. A second conclusion from our experimental observations is that a reduced dropout rate does not seem to have a dramatic effect on error thus suggesting that the utilized capacity of the network remains similar under all tested dropout ratios. We observe that a larger number of samples improves network accuracy especially in the case of eNSRM descriptors that feature more complex features and also perform 2D alignment of 2D shapes that are more difficult to "learn". Finally, SELU and SWISH activation functions seem to perform similarly, however due to the slight edge of SWISH experiments and their improved computational performance they seem to be a good choice for the MNET3 ensemble.
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#!/bin/bash
#Switch to this directory
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
cd "$DIR"
export MOCAPNET_DOXYGEN_INPUT="$DIR/.."
export MOCAPNET_DOXYGEN_OUTPUT="$DIR/../doc"
echo "Doxygen Input file will be $MOCAPNET_DOXYGEN_INPUT"
echo "Doxygen Output file will be $MOCAPNET_DOXYGEN_OUTPUT"
cd ..
doxygen doc/doxyfile
cd doc/latex
make
cd ..
cd ..
ln -s doc/latex/refman.pdf MocapNETManual.pdf
cd "$DIR"
exit 0
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FROM tensorflow/tensorflow:latest-gpu
ARG user_id
ARG root_psw="12345678"
ARG user_psw="ok"
ARG user_name=user
# Installs the necessary pkgs.
RUN \
echo "**** packages installation ****" \
&& apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/3bf863cc.pub \
&& apt-get update && apt-get install -y \
vim \
build-essential \
cmake \
libopencv-dev \
libjpeg-dev \
libpng-dev \
libglew-dev \
libpthread-stubs0-dev \
git \
virtualenv \
time \
sudo \
wget \
nano \
python3.10-venv \
&& echo "**** python pip update ****" \
&& /usr/bin/python3 -m pip install --upgrade pip \
&& echo "**** aliases for l and ll commands creation ****" \
&& echo -e 'ls --color=auto "$@"' > /usr/bin/l \
&& echo -e 'ls -lah --color=auto "$@"' > /usr/bin/ll \
&& chmod +x /usr/bin/ll /usr/bin/l \
&& echo "**** history-search-backward by pressing F8 ****" \
&& sed -i 's/# "\\e\[5~": history-search-backward/"\\e\[19~": history-search-backward/' /etc/inputrc \
&& echo "**** root password creation ****" \
&& echo "root:${root_psw}" | chpasswd \
&& echo "**** user creation ****" \
&& useradd -m -s /usr/bin/bash -u ${user_id} -G sudo ${user_name} \
&& echo "${user_name}:${user_psw}" | chpasswd \
&& chown -R ${user_name}:${user_name} /home/${user_name}/ \
&& mkdir /home/${user_name}/workspace/ \
&& chown -R user:user /home/${user_name}/workspace
USER ${user_name}
WORKDIR /home/${user_name}/
RUN cd /home/${user_name}/workspace && git clone -b mnet4 https://github.com/FORTH-ModelBasedTracker/MocapNET && cd MocapNET/src/python/mnet4/ && ./setup.sh --collab
@@ -0,0 +1,44 @@
#!/usr/bin/env bash
# This script builds and runs a docker image for local use.
#Although I dislike the use of docker for a myriad of reasons, due needing it to deploy on a particular machine
#I am adding a docker container builder for the repository to automate the process
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
cd "$DIR"
cd ..
REPOSITORY=`pwd`
cd "$DIR"
NAME="mocapnet"
dockerfile_pth="$DIR"
mount_pth="$REPOSITORY"
# update tensorflow image
docker pull tensorflow/tensorflow:latest-gpu
# build and run tensorflow
docker build \
-t $NAME \
$dockerfile_pth \
--build-arg user_id=$UID
docker run -d \
--gpus all \
--shm-size 8G \
-it \
--name $NAME-container \
-v $mount_pth:/home/user/workspace \
$NAME
docker ps -a
OUR_DOCKER_ID=`docker ps -a | grep mocapnet | cut -f1 -d' '`
echo "Our docker ID is : $OUR_DOCKER_ID"
echo "Attaching it using : docker attach $OUD_DOCKER_ID"
docker attach $OUR_DOCKER_ID
exit 0
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#!/bin/bash
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
cd "$DIR"
ORIG_DIR=`pwd`
ASK_QUESTIONS=1
if [[ $* == *--collab* ]]
then
echo "Using non-blocking collab mode"
ASK_QUESTIONS=0
fi
if [ "$ASK_QUESTIONS" -eq "0" ]; then
echo "We assume collab machines have everything we need.."
else
#Simple dependency checker that will apt-get stuff if something is missing
# sudo apt-get install build-essential cmake libopencv-dev libjpeg-dev libpng-dev libglew-dev libpthread-stubs0-dev
SYSTEM_DEPENDENCIES="wget git build-essential cmake libopencv-dev libjpeg-dev libpng-dev libglew-dev libpthread-stubs0-dev"
#------------------------------------------------------------------------------
for REQUIRED_PKG in $SYSTEM_DEPENDENCIES
do
PKG_OK=$(dpkg-query -W --showformat='${Status}\n' $REQUIRED_PKG|grep "install ok installed")
echo "Checking for $REQUIRED_PKG: $PKG_OK"
if [ "" = "$PKG_OK" ]; then
echo "No $REQUIRED_PKG. Setting up $REQUIRED_PKG."
#If this is uncommented then only packages that are missing will get prompted..
#sudo apt-get --yes install $REQUIRED_PKG
#if this is uncommented then if one package is missing then all missing packages are immediately installed..
sudo apt-get install $SYSTEM_DEPENDENCIES
break
fi
done
#------------------------------------------------------------------------------
fi
cd "$DIR"
if [ -f dependencies/RGBDAcquisition/README.md ]; then
echo "RGBDAcquisition appears to already exist .."
#cd "$DIR/dependencies/RGBAcquisition"
#echo "We can make sure that it is up to date to avoid issues like https://github.com/FORTH-ModelBasedTracker/MocapNET/issues/48.."
#echo "However someone might not want to update the code.. what to do.."
#git pull
#cd "$DIR"
else
cd "$DIR/dependencies"
git clone https://github.com/AmmarkoV/RGBDAcquisition
cd RGBDAcquisition
mkdir build
cd build
cmake ..
#We dont need to make it
#make
cd ../opengl_acquisition_shared_library/opengl_depth_and_color_renderer
mkdir build
cd build
cmake ..
#We dont need to make it
#make
cd "$DIR"
#Also retrieve Renderer
#ln -s dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/Renderer
fi
cd "$DIR"
cd src/python/mnet4
rm -rf BVH/
ln -s ../../../dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_re
nderer/src/Applications/BVHTester/ BVH
cd BVH
./makeLibrary.sh
cd ..
#Install rest of python stuff..
./setup.sh
#Now that we have everything lets build..
echo "Now to try and build MocapNET.."
cd "$DIR"
#if there is an already existing build directory and you called initialize.sh
#it will get initialized as well.. (https://github.com/FORTH-ModelBasedTracker/MocapNET/issues/19)
if [ -d "build" ]; then
echo "Build directory already exists, but since the initialize.sh script was called "
echo "this means the user wants to also initialize the build directory, so doing this"
echo "to prevent problems like https://github.com/FORTH-ModelBasedTracker/MocapNET/issues/19"
rm -rf build/
fi
mkdir build
cd build
cmake ..
make
cd "$DIR"
exit 0
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FORTH & END-USER LICENSE AGREEMENT
for the
FORTH-ICS MOCAPNET LIBRARY
PLEASE READ THE FOLLOWING CAREFULLY BEFORE USING:
By using this hereby licensed to You product you expressly acknowledge and agree, on your own behalf as an individual, and on behalf of your employer or another entity which has not yet done so (collectively "You" or "Your"), that You are entering into a legal binding license agreement with FORTH ("FORTH"), have full authority to bind such employer or other entity with this License Agreement, and have understood and agree to comply with the terms & conditions of this License Agreement below (hereafter "Terms", "License Agreement"). You hereby waive any applicable rights to requirements for an original (non-electronic) signature or delivery or retention of non-electronic records, to the extent permitted under applicable law, customs & codes of practice.
1. Scope of this License Agreement
Subject to these Terms, FORTH hereby grants to You a limited, worldwide (subject to applicable export restrictions), non-exclusive, personal, non-transferable, revocable, license to use the FORTH proprietary MOCAPNET LIBRARY that was developed at and by FORTH (under the supervision of Prof. A. Argyros, at FORTH-ICS, Computational Vision and Robotics Lab) and is solely owned by FORTH and known as FORTH-ICS MOCAPNET LIBRARY" (referred to hereafter as "LIBRARY") only for "personal" research and/or academic, non-profit, non-commercial use, pursuant to this License Agreement with FORTH.
2. Restrictions
a. You agree to use this Licensed LIBRARY only as permitted herein;
b. You are not allowed utilizing this Licensed LIBRARY with content/products/services that is not appropriate for viewing by a general audience or that directs users to such content/actions, which include, without limitation to, that which: (a) promote offensive, criminal, illegal content or activities; (b) violate any law, statute, order, or regulation, or; (c) violate intellectual property rights; (d) result in legal liability for FORTH; and/or (e) is considered by FORTH as unfair competition and/or prejudice to FORTH" s legitimate rights and interests ;
c. You shall not and shall not permit third parties to: (a) integrate the Licensed LIBRARY with any products and/or services, (b) distribute the Licensed LIBRARY in any manner, (c) use or make available the Licensed LIBRARY to any person other than You, notwithstanding any applicable open source license terms or otherwise, (d) modify the Licensed LIBRARY,; or (e) change, obscure or delete any proprietary notices or legends which appear in the Licensed LIBRARY, for purposes other than as explicitly permitted herein;
d. You agree that You will not, directly or indirectly, and You shall not permit third parties to (a) decompile, disassemble or reverse engineer the LIBRARY, in whole or in part, or use, copy, reproduce, write or develop any derivative software or any other software program based upon all or any part of the LIBRARY or any confidential information of FORTH, without FORTH's express prior written consent and/or for purposes other than "personal use" as herein permitted; (b) not compete directly or indirectly with FORTH in exploitation or otherwise of the LIBRARY and/or of any accompanying Hardware; and (c) not provide software maintenance, training or consulting or other expertise services in respect of the LIBRARY. In the event applicable law grants You the right to reverse engineer, You shall provide FORTH with prior written notice including information sufficient regarding Your intended method of reverse engineering, its purpose and the legal authority for such activity and shall afford FORTH a reasonable period before initiating such activity in order to evaluate and/or legally challenge the activity. You shall refrain from such activity until such time as any legal challenge is resolved in Your favor. Reverse engineering includes, without limitation, sniffing, decompiling, or otherwise deriving source code.
3. Intellectual Property Ownership
FORTH and/or its rightholders shall respect and retain at all times all rights, title and interests, including all intellectual property rights, in and to the FORTH Logos, copyright notices and Terms and conditions of permitted use, and/or (if any) other applicable open source copyright notices and license terms, as well as with respect to any and all improvements, modifications, enhancements, and derivative works (if any) thereof and/or feedback associated therewith while using this Licensed LIBRARY, that You shall refer to always and provide to FORTH. All rights not specifically granted in these Terms shall be retained by FORTH.
4. Warranties
You represent and warrant that: (a) You have the full right, power and authority to enter into these Terms and carry out Your obligations hereunder; (b) the consent to and performance of these Terms will not result in the breach or violation of any law or regulation applicable to it or any contract or commitment by which You are bound; and (c) You do not infringe any rights of a third party.
5. User Support
FORTH shall not be required to provide support of any kind with respect to the Licensed LIBRARY.
6. Disclaimer of Warranties
THE LICENSED LIBRARY, IS DEEMED ACCEPTED BY YOU. TO THE MAXIMUM EXTENT PERMITTED BY APPLICABLE LAW, FORTH, ITS LICENSORS AND SUPPLIERS (if any) PROVIDE THE LICENSED SOFTWARE AND ANY (IF ANY) SUPPORT SERVICES "AS IS" AND WITHOUT LIABILITY; TO THE MAXIMUM EXTENT PERMITTED BY APPLICABLE LAW, FORTH EXPRESSLY DISCLAIMS ANY IMPLIED WARRANTIES AND CONDITIONS, INCLUDING WITHOUT LIMITATION IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, TITLE OR NON-INFRINGEMENT AS WELL AS ANY WARRANTIES THAT THE OPERATION OF THE SOFTWARE OR DRIVERS WILL BE UNINTERRUPTED OR ERROR FREE.
7. Indemnity
You agree to indemnify and hold FORTH, concerned personnel/developers and its licensors harmless against any cost, loss, liability or expense (including attorneys' fees) arising out of any third party claims against FORTH, its personnel/developers and/or its licensors (i) relating to Your utilization of the Licensed LIBRARY and/or (ii) arising from Your actions or omissions.
8. Term
These Terms shall become effective upon Your acceptance, use of the hereby Licensed software and shall remain in effect until these terms, use of the Licensed software are terminated by FORTH. Upon termination (a) the rights and license(s) granted to You pursuant to these Terms shall automatically terminate; (b) You shall certify to FORTH that the Licensed product subject to these Terms has been removed from any equipment, network, premises, product, services or any other location or space, (c) You shall cease to use all FORTH proprietary content, product, services.
9. Survival
The provisions of Sections 2-12 shall survive the expiration or termination of these Terms for any reason whatsoever.
10. Exclusion of Incidental, Consequential and certain other Damages
To the maximum extent permitted by applicable laws, in no event shall FORTH, its personnel, directors, licensors or its suppliers be liable for any special, incidental, indirect, or consequential damages whatsoever (including, but not limited to, damages for loss of profits or confidential or other information, for business interruption, for personal injury, for loss of privacy, for failure to meet any duty including of good faith or of reasonable care, for negligence, and for any other pecuniary or other loss whatsoever) arising out of or in any way related to the use of or inability to use the Licensed product, or otherwise under or in connection with any provision of these Terms, even in the event of the fault, tort (including negligence), strict liability, breach of contract or breach of warranty of FORTH, its personnel, directors, affiliates, licensors or any supplier, and even if they or any one of them has been advised of the possibility of such damages.
11. Limitation of Liability and Remedies
Notwithstanding anything to the contrary contained herein or any damages that You might incur for any reason whatsoever, the entire and maximum liability of FORTH, its personnel, directors, affiliates, licensors and any suppliers, in aggregate for all claims made in contract, tort or otherwise in connection with the subject matter hereof, and Your exclusive remedy for all of the foregoing shall be limited to the fees actually paid by You, if any. The foregoing limitations, exclusions and disclaimers shall apply to the maximum extent permitted by applicable laws, even if any remedy fails its essential purpose.
12. Miscellaneous
a. Governing Law; Attorneys Fees. These Terms shall be construed and controlled by the Greek Law, and You consent to the non-exclusive jurisdiction and venue of the Greek courts of Athens, provided that FORTH may seek immediate injunctive or other relief with respect to a violation of intellectual property rights or confidentiality obligations in any appropriate jurisdiction, and You waive all defenses of lack of personal jurisdiction and forum non conveniens. EACH OF THE PARTIES HERETO HEREBY IRREVOCABLY WAIVES ALL RIGHT TO TRIAL BY JURY.
b. Assignment. You may not assign these Terms or any portion thereof to any third party unless FORTH expressly consents in writing.
c. No Partnership. Nothing in these Terms shall be construed to create a partnership or agency between the parties, and neither shall have authority to bind or represent itself as the agent or partner of the other.
d. Severability. If any provision of these Terms shall be held to be invalid, illegal or unenforceable, such holding shall in no way affect or impair the remaining provisions, and the parties shall use their reasonable efforts to substitute valid and enforceable provisions which have the closest meaning and purpose as those so held.
e. Entire Agreement; Variation; Waiver; Counterparts. These Terms set forth the entire understanding of the parties, which supersedes and merges all prior proposals, understandings and all other agreements oral and written between the parties relating to the subject matter herein and may not be modified except in a writing executed by both parties or in new terms posted here or notified to You. Failure of a party to enforce any of the provisions of these Terms will not be construed to be a waiver of the provision, and no waiver of any rights hereunder shall be deemed to be a waiver of the same or other right on any other occasion.
" Copyright FORTH 2019. All rights reserved.
+316
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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#<----- Click this play button to setup MocapNET v4!\n",
"\n",
"#This is the Total Capture version that handles body, hands, gaze, face!\n",
"#It also has been rewritten from scratch in Python for your convenience.\n",
"#If you deploy this on your PC, run : jupyter notebook mocapnet4.ipynb\n",
"# and remove --collab from the setup.sh invocation 2 lines below..!\n",
"import os\n",
"if (os.path.isfile(\"MocapNET.py\")):\n",
" !git pull\n",
" exit\n",
"!git clone -b mnet4 https://github.com/FORTH-ModelBasedTracker/MocapNET.git\n",
"!MocapNET/src/python/mnet4/setup.sh --collab\n",
"os.chdir(\"MocapNET/src/python/mnet4\")\n",
"print(\"MocapNET setup is finished, you can run the next cell now..\")\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#<----- Click to get a video from the internet and then track it ( e.g. shuffle.webm )\n",
"\n",
"#You can also upload your own by clicking the Files icon and using the menu on the left\n",
"#You need to put files in the /content/MocapNET/src/python/mnet4/ directory\n",
"\n",
"#Make sure we are at the correct directory\n",
"import os\n",
"if (not os.path.isfile(\"mediapipeHolisticWebcamMocapNET.py\")):\n",
" os.chdir(\"MocapNET/src/python/mnet4\")\n",
"\n",
"!wget http://ammar.gr/mocapnet/shuffle.webm -O shuffle.webm\n",
"\n",
"#Analyze the file shuffle.web through MediaPipe 2D + MocapNET 3D Pose Estimation!\n",
"!(python3 -m mediapipeHolisticWebcamMocapNET --from shuffle.webm --ik 0.001 99 99 --smooth 60 10 --all --save --plot --headless 2> /dev/null)\n",
"print(\"MocapNET video input processing finished, you can run the next cells now to see the results..\")\n",
"\n",
"#Outputs are :\n",
"#livelastRun3DHiRes.mp4 | A video showing the regressed output overlayed on RGB\n",
"#livelastPlot3DHiRes.mp4| A video plot of the retrieved BVH degrees of freedom\n",
"#out.bvh | the extracted BVH file \n",
"#2d_out.csv | Input 2D joints used by MocapNET as a CSV file\n",
"#3d_out.csv | Output 3D joints produced by MocapNET as a CSV file\n",
"#bvh_out.csv | Output BVH angles produced by MocapNET as a CSV file\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#<----- Click to run a sign-language dataset without mediapipe from a dumped Openpose/JSON/CSV source\n",
"\n",
"#Make sure we are at the correct directory\n",
"import os\n",
"if (not os.path.isfile(\"csvNET.py\")):\n",
" os.chdir(\"MocapNET/src/python/mnet4\")\n",
"\n",
"#Download a single sign (con0014) from SIGNUM\n",
"!wget http://ammar.gr/datasets/signumtest.zip -O signumtest.zip\n",
"!unzip -o signumtest.zip\n",
"\n",
"#Analyze the file con0014/2dJoints_v1.4.csv through MediaPipe 2D + MocapNET 3D Pose Estimation!\n",
"!(python3 -m csvNET --from con0014/2dJoints_v1.4.csv --ik 0.001 99 99 --upperbody --reye --mouth --hands --save --plot --headless 2> /dev/null)\n",
"print(\"MocapNET video input processing finished, you can run the next cells now to see the results..\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#<----- Click to see the generated BVH angle plot of the last MocapNET run!\n",
"from IPython.display import Video\n",
"import os\n",
"if (not os.path.isfile(\"livelastPlot3DHiRes.mp4\")):\n",
" print(\"Please execute the previous cells and wait for them to complete before seeing this visualization!\")\n",
" exit\n",
"\n",
"Video(\"livelastPlot3DHiRes.mp4\",embed=True)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#<----- Click to see the generated visualization of the last MocapNET run!\n",
"from IPython.display import Video\n",
"import os\n",
"if (not os.path.isfile(\"livelastRun3DHiRes.mp4\")):\n",
" print(\"Please execute the previous cells and wait for them to complete before seeing this visualization!\")\n",
" exit\n",
"\n",
"Video(\"livelastRun3DHiRes.mp4\",embed=True)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#<----- Click to download the generated BVH/3D files of the last MocapNET run!\n",
"import os \n",
"from google.colab import files\n",
"if (not os.path.isfile(\"out.bvh\")) or (not os.path.isfile(\"2d_out.csv\")) or (not os.path.isfile(\"bvh_out.csv\")) or (not os.path.isfile(\"3d_out.csv\")):\n",
" print(\"Please execute the previous cells and wait for them to complete before downloading output!\")\n",
"else:\n",
" print(\"Download Output Files!\")\n",
" files.download(\"out.bvh\")\n",
" files.download(\"2d_out.csv\")\n",
" files.download(\"3d_out.csv\")\n",
" files.download(\"bvh_out.csv\")\n",
"#To render the 3D face get Blender from https://www.blender.org/\n",
"#Download http://ammar.gr/mocapnet/mnet4/face.blend and open it using Blender\n",
"#Download http://ammar.gr/mocapnet/mnet4/headerWithHeadAndOneMotion.bvh and open it using Blender at a 0.01 scale\n",
"#Run The Loaded Python Script\n",
"#Click on the armature and on the menu right click the orange rectangle\n",
"#Select headerWithHeadAndOneMotion as Source BVH\n",
"#Select newgirl as Target Obj\n",
"#Select a directory as a target for generated dataset\n",
"#Select the path to the regressed bvh_out.csv to load pre-generated dataset\n",
"#Click Just Render CSV Dataset\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#<----- Click to attempt MocapNET live demo by streaming your camera to Google Colab\n",
"#EXPERIMENTAL, performance is impacted because of low image throughput!\n",
"\n",
"import cv2\n",
"import os\n",
"from colabStream import init_camera,take_frame,show_frame\n",
"\n",
" \n",
"from mediapipeHolisticWebcamMocapNET import MediaPipeHolistic\n",
"from MocapNET import easyMocapNETConstructor\n",
"from folderStream import resize_with_padding\n",
"\n",
"# Create instances of MediaPipeHolistic and MocapNET\n",
"mp_holistic = MediaPipeHolistic(doMediapipeVisualization=False)\n",
"mnet = easyMocapNETConstructor(\n",
" engine = \"onnx\",\n",
" doProfiling = False,\n",
" multiThreaded = False,\n",
" doHCDPostProcessing = True,\n",
" hcdLearningRate = 0.001,\n",
" hcdEpochs = 99,\n",
" hcdIterations = 99,\n",
" bvhScale = 1.0,\n",
" doBody = True,\n",
" doFace = False,\n",
" doREye = True,\n",
" doMouth = True,\n",
" doHands = True,\n",
" addNoise = 0.0\n",
")\n",
"\n",
"\n",
"# init JavaScript code\n",
"init_camera()\n",
"\n",
"while True:\n",
" try:\n",
" image = take_frame()\n",
" \n",
" image = resize_with_padding(image,1280,720)\n",
"\n",
" # Perform image processing with MediaPipeHolistic\n",
" mocapNETInput, annotated_image = mp_holistic.convertImageToMocapNETInput(image)\n",
"\n",
" # Perform 3D joint prediction with MocapNET\n",
" mocapNET3DOutput = mnet.predict3DJoints(mocapNETInput)\n",
"\n",
" # Visualize the results on the image\n",
" #image_with_results = Image.fromarray(cv2.cvtColor(annotated_image, cv2.COLOR_BGR2RGB))\n",
" \n",
" from MocapNETVisualization import visualizeMocapNETEnsemble\n",
" image,plotImage = visualizeMocapNETEnsemble(mnet,annotated_image,plotBVHChannels=False)\n",
" \n",
" show_frame(annotated_image) # it replace previous image\n",
" \n",
" except Exception as err:\n",
" print('Exception:', err)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#D/L and compile a different version of MocapNET and evaluate it against CMUBVH test dataset\n",
"#Running this will take a while, but it is usefult to compare different trained MocapNET Models!\n",
"import os\n",
"\n",
"#Download Test Set!\n",
"if (not os.path.isfile(\"dataset/generated/bvh_body_all_test.csv\")):\n",
" print(\"Downloading test set!\")\n",
" os.system(\"wget http://ammar.gr/datasets/testBody.zip && unzip testBody.zip\")\n",
"\n",
"#Download a different MocapNET build\n",
"!python3 -m getModelFromDatabase --get 319 #<- change number to try a different version\n",
"\n",
"#Do Evaluation\n",
"!python3 -m evaluateMocapNET --config dataset/body_configuration.json --all body --skip 5 --engine onnx > lastEvaluationLog.txt\n",
"!tail -n 30 lastEvaluationLog.txt "
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<iframe width=\"560\" height=\"315\" src=\"https://youtube.com/embed/ooLRUS5j4AI\"\n",
"</iframe>\n"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%%HTML\n",
"<!-- Activate this block to see a youtube video about rendering MocapNET results with Blender -->\n",
"<iframe width=\"560\" height=\"315\" src=\"https://youtube.com/embed/ooLRUS5j4AI\"></iframe>"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"\"\"\"\n",
"\n",
"This library is provided under the FORTH license\n",
"https://github.com/FORTH-ModelBasedTracker/MocapNET/blob/master/license.txt\n",
"\n",
"If you use this version of MocapNET for your research please consider citing : \n",
"\n",
"@inproceedings{Qammaz2023b,\n",
" author = {Qammaz, Ammar and Argyros, Antonis},\n",
" title = {A Unified Approach for Occlusion Tolerant 3D Facial Pose Capture and Gaze Estimation using MocapNETs},\n",
" booktitle = {International Conference on Computer Vision Workshops (AMFG 2023 - ICCVW 2023), (to appear)},\n",
" publisher = {IEEE},\n",
" year = {2023},\n",
" month = {October},\n",
" address = {Paris, France},\n",
" projects = {VMWARE,I.C.HUMANS},\n",
" pdflink = {http://users.ics.forth.gr/ argyros/mypapers/2023_10_AMFG_Qammaz.pdf}\n",
"}\n",
"\n",
"@inproceedings{Qammaz2021,\n",
" author = {Qammaz, Ammar and Argyros, Antonis A},\n",
" title = {Towards Holistic Real-time Human 3D Pose Estimation using MocapNETs},\n",
" booktitle = {British Machine Vision Conference (BMVC 2021)},\n",
" publisher = {BMVA},\n",
" year = {2021},\n",
" month = {November},\n",
" projects = {I.C.HUMANS},\n",
" videolink = {https://www.youtube.com/watch?v=aaLOSY_p6Zc}\n",
"}\n",
"\"\"\" "
]
}
],
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.12"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
+37
View File
@@ -0,0 +1,37 @@
#!/bin/bash
#Reminder , to get a single file out of the repo use "git checkout -- path/to/file.c"
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
cd "$DIR"
#All OpenGL/BVH code relies on RGBDAcquisition code so we need to sync this as well
if [ -f dependencies/RGBDAcquisition/README.md ]; then
echo "RGBDAcquisition appears to exist, reverting it .."
cd dependencies/RGBDAcquisition
git reset --hard HEAD
git pull origin master
cd "$DIR"
else
echo "Could not find RGBDAcquisition, please rerun the initialize.sh script .."
fi
if [ -f dependencies/AmmarServer/README.md ]; then
echo "AmmarServer appears to exist, reverting it .."
cd dependencies/AmmarServer
git reset --hard HEAD
git pull origin master
cd "$DIR"
fi
#Now sync rest of code
cd "$DIR"
git reset --hard HEAD
git pull origin master
exit 0
@@ -0,0 +1,410 @@
#!/bin/bash
# Ansi color code variables
red="\e[0;91m"
blue="\e[0;94m"
expand_bg="\e[K"
blue_bg="\e[0;104m${expand_bg}"
red_bg="\e[0;101m${expand_bg}"
green_bg="\e[0;102m${expand_bg}"
green="\e[0;92m"
white="\e[0;97m"
bold="\e[1m"
uline="\e[4m"
reset="\e[0m"
function checkForError
{
RESULT=$?
if [ $RESULT -eq 0 ]; then
echo "Successfully ran the hand pose estimation"
else
echo -e "${red_bg}TERMINATING SCRIPT${reset}"
echo -e "${red}Failed running $1${reset}"
exit 1
fi
}
#We move to the correct directory..
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
cd "$DIR"
cd ..
if [ $# -eq 0 ]
then
echo "No arguments supplied, please run with --quaternions or --euler"
exit 0
fi
#Setting this to qbvh will activate
#quaternion code..!
BVH_TYPE="bvh"
if [ "$1" == "--quaternions" ]; then
BVH_TYPE="qbvh"
elif [ "$1" == "--euler" ]; then
BVH_TYPE="bvh"
else
echo "You gave arguments but where not what we expected.."
exit 0
fi
#FULL SIZE EXPERIMENT
echo "Doing full size experiment"
FULL_RANDOM_POSES="1999999"
ZERO_POSES="199999"
BASE_POSES="599999"
FINGER_POSES="399999"
#SMALL SIZE (1/2) EXPERIMENT
#echo "Doing small (1/2) size experiment"
#FULL_RANDOM_POSES="1000000"
#ZERO_POSES="100000"
#BASE_POSES="300000"
#FINGER_POSES="200000"
#SMALL SIZE (1/10) EXPERIMENT
#echo "Doing small (1/10) size experiment"
#FULL_RANDOM_POSES="199999"
#ZERO_POSES="19999"
#BASE_POSES="59999"
#FINGER_POSES="39999"
#BASE_POSES="99999"
#FINGER_POSES="19999"
USE_OCCLUSIONS="" # Set to "--occlusions" for occlusions #deactivated @ 2021-03-05
USE_END_JOINTS="1" # We need end joints since they are our fingertips..
#Where is our output located
outputDir="dataset/"
# Use --printparams in view commands to view the commands that are given to the utility at stderr
VIEW_COMMANDS=" --printparams "
HIDEBODY=" $DONT_USE_END_JOINTS 8 abdomen chest eye.r eye.l toe1-2.r toe5-3.r toe1-2.l toe5-3.l"
SELECT_RHAND="--selectJoints $USE_END_JOINTS 17 rHand finger5-1.r finger5-2.r finger5-3.r finger4-1.r finger4-2.r finger4-3.r finger3-1.r finger3-2.r finger3-3.r finger2-1.r finger2-2.r finger2-3.r rthumbBase rthumb finger1-2.r finger1-3.r --hide2DLocationOfJoints 0 1 rthumbBase"
#Note on --hide2DLocationOfJoints: We want to contain these joints in the BVH file and solve them, but they do not correspond to the BODY25 format so we hide them as 2D points..
SELECT_LHAND="--selectJoints $USE_END_JOINTS 17 lHand finger5-1.l finger5-2.l finger5-3.l finger4-1.l finger4-2.l finger4-3.l finger3-1.l finger3-2.l finger3-3.l finger2-1.l finger2-2.l finger2-3.l lthumbBase lthumb finger1-2.l finger1-3.l --hide2DLocationOfJoints 0 1 lthumbBase"
#Note on --hide2DLocationOfJoints: We want to contain these joints in the BVH file and solve them, but they do not correspond to the BODY25 format so we hide them as 2D points..
# LEFT RIGHT
MID_THUMBBASE_Y="63" #Thumb Left/Right -56->48 -48->56
MID_FINGER5_1_Y="54" #Pinky Left/Right -10->22 -22->10
MID_FINGER4_1_Y="39" #Ring Left/Right -12->12 -12->12
MID_FINGER3_1_Y="24" #Mid Left/Right -12->12 -12->12
MID_FINGER2_1_Y="24" #Pointer Left/Right -12->12 -12->12
NATURAL_LHAND="--set 12 -5.0 --set 39 5.0 --set 54 10.5 --set 63 -18"
NATURAL_RHAND="--set 12 5.0 --set 39 -5.0 --set 54 -10.5 --set 63 18"
#----------------------------------------------------------------------------------------------------------------------------------------------------
#----------------------------------------------------------------------------------------------------------------------------------------------------
#----------------------------------------------------------------------------------------------------------------------------------------------------
#----------------------------------------------------------------------------------------------------------------------------------------------------
function generateRightHandDataset
{
OUTBASE="$1"
#Make sure file is wiped before
#adding new poses..
#-------------------------
rm $outputDir/2d_$OUTBASE
rm $outputDir/bvh_$OUTBASE
#-------------------------
MIN_HAND_DEPTH="$2"
MAX_HAND_DEPTH="$3" #1500
MIN_RHAND_RZ="$4"
MAX_RHAND_RZ="$7"
MIN_RHAND_RY="$5"
MAX_RHAND_RY="$8"
MIN_RHAND_RX="$6"
MAX_RHAND_RX="$9"
FROM="--haltonerror $VIEW_COMMANDS --from dataset/rhand.$BVH_TYPE"
RANDOM_POSITION_ROTATION="--randomize2D $MIN_HAND_DEPTH $MAX_HAND_DEPTH $MIN_RHAND_RZ $MIN_RHAND_RY $MIN_RHAND_RX $MAX_RHAND_RZ $MAX_RHAND_RY $MAX_RHAND_RX $USE_OCCLUSIONS"
OUT="--csv $outputDir $OUTBASE 2d+bvh "
#RHAND
#./BVHGUI2 --from dataset/rhand.qbvh --set 2 -25 --set 3 0.5 --set 4 -0.5 --set 5 0.5 --set 6 -0.5 --set 12 5.0 --set 39 -5.0 --set 54 -10.5 --set 63 18
echo "TEST?"
#New automatic pose generation based on IK Problem..
./GroundTruthDumper $FROM $NATURAL_RHAND --repeat $FULL_RANDOM_POSES $SELECT_RHAND --randomizeBasedOnIKConstrains rhand $RANDOM_POSITION_ROTATION $OUT
checkForError "rhand full random"
#Default BVH poses with everything at zero but hand is naturally open
./GroundTruthDumper $FROM $NATURAL_RHAND --repeat $BASE_POSES $SELECT_RHAND $RANDOM_POSITION_ROTATION $OUT
checkForError "rhand naturally open"
#Default BVH poses with everything at zero but hand is not naturally open, it is has fingers touching
./GroundTruthDumper $FROM --repeat $ZERO_POSES $SELECT_RHAND $RANDOM_POSITION_ROTATION $OUT
checkForError "rhand to zero"
#Default BVH poses with hand naturally open but thumb in the middle
./GroundTruthDumper $FROM $NATURAL_RHAND --set 63 -6.5 --set 64 28.7 --set 65 -8.5 --set 66 -37 --set 67 13 --set 68 -7.6 --set 69 22 --set 70 5 --set 71 -43 --set 72 0 --repeat $ZERO_POSES $SELECT_RHAND $RANDOM_POSITION_ROTATION $OUT
checkForError "rhand naturally open thumb in the middle"
#Right hand Thumb Movement on default pose
./GroundTruthDumper $FROM $NATURAL_RHAND --repeat $FINGER_POSES $SELECT_RHAND $RANDOM_POSITION_ROTATION --randomizeMID $MID_THUMBBASE_Y -48.0 56.0 $OUT
checkForError "Right hand Thumb Movement on default pose"
#All hand open naturally, only finger 5 (pinky) moving
RANDOMIZE_RIGHT_HAND="--/randomizeJointAngles 3 0 65 1 finger5-1.r finger5-2.r finger5-3.r"
./GroundTruthDumper $FROM $NATURAL_RHAND --repeat $FINGER_POSES $SELECT_RHAND $RANDOM_POSITION_ROTATION $RANDOMIZE_RIGHT_HAND $OUT
checkForError "All hand open naturally, only finger 5 (pinky) moving"
#All hand open naturally, only finger 4 (ring) moving
RANDOMIZE_RIGHT_HAND="--randomizeJointAngles 3 0 65 1 finger4-1.r finger4-2.r finger4-3.r"
./GroundTruthDumper $FROM $NATURAL_RHAND --repeat $FINGER_POSES $SELECT_RHAND $RANDOM_POSITION_ROTATION $RANDOMIZE_RIGHT_HAND $OUT
checkForError "All hand open naturally, only finger 4 (ring) moving"
#All hand open naturally, only finger 3 (middle) moving
RANDOMIZE_RIGHT_HAND="--randomizeJointAngles 3 0 65 1 finger3-1.r finger3-2.r finger3-3.r"
./GroundTruthDumper $FROM $NATURAL_RHAND --repeat $FINGER_POSES $SELECT_RHAND $RANDOM_POSITION_ROTATION $RANDOMIZE_RIGHT_HAND $OUT
checkForError "All hand open naturally, only finger 3 (middle) moving"
#All hand open naturally, only finger 2 (pointer) moving
RANDOMIZE_RIGHT_HAND="--randomizeJointAngles 3 0 65 1 finger2-1.r finger2-2.r finger2-3.r"
./GroundTruthDumper $FROM $NATURAL_RHAND --repeat $FINGER_POSES $SELECT_RHAND $RANDOM_POSITION_ROTATION $RANDOMIZE_RIGHT_HAND $OUT
checkForError "All hand open naturally, only finger 2 (pointer) moving"
#All hand open naturally, only finger 1 (thumb) moving
RANDOMIZE_RIGHT_HAND="--randomizeJointAngles 2 -75 75 2 rthumb finger1-2.r --randomizeJointAngles 1 0 45 3 rthumb"
./GroundTruthDumper $FROM $NATURAL_RHAND --repeat $FINGER_POSES $SELECT_RHAND $RANDOM_POSITION_ROTATION $RANDOMIZE_RIGHT_HAND $OUT
checkForError "All hand open naturally, only finger 1 (thumb) moving"
#All fingers closed only thumb moving!
RANDOMIZE_RIGHT_HAND="--randomizeJointAngles 15 65 65 1 finger5-1.r finger5-2.r finger5-3.r finger4-1.r finger4-2.r finger4-3.r finger3-1.r finger3-2.r finger3-3.r finger2-1.r finger2-2.r finger2-3.r rthumb finger1-2.r finger1-3.r --randomizeJointAngles 5 90 90 1 finger5-1.r finger4-1.r finger3-1.r finger2-1.r rthumb --randomizeJointAngles 2 -75 75 2 rthumb finger1-2.r --randomizeJointAngles 1 0 45 3 rthumb"
./GroundTruthDumper $FROM $NATURAL_RHAND --repeat $FINGER_POSES $SELECT_RHAND $RANDOM_POSITION_ROTATION $RANDOMIZE_RIGHT_HAND $OUT
checkForError "RHand - All fingers closed only thumb moving!"
#All fingers closed except Finger 5 ( pinky )
RANDOMIZE_RIGHT_HAND="--randomizeJointAngles 15 65 65 1 finger5-1.r finger5-2.r finger5-3.r finger4-1.r finger4-2.r finger4-3.r finger3-1.r finger3-2.r finger3-3.r finger2-1.r finger2-2.r finger2-3.r rthumb finger1-2.r finger1-3.r --randomizeJointAngles 5 90 90 1 finger5-1.r finger4-1.r finger3-1.r finger2-1.r rthumb --randomizeJointAngles 2 75 75 2 rthumb finger1-2.r --randomizeJointAngles 1 45 45 3 rthumb --randomizeJointAngles 3 0 65 1 finger5-1.r finger5-2.r finger5-3.r"
./GroundTruthDumper $FROM $NATURAL_RHAND --repeat $FINGER_POSES $SELECT_RHAND $RANDOM_POSITION_ROTATION $RANDOMIZE_RIGHT_HAND $OUT
checkForError "RHand - All fingers closed except Finger 5 ( pinky )"
#All fingers closed except Finger 4 ( ring )
RANDOMIZE_RIGHT_HAND="--randomizeJointAngles 15 65 65 1 finger5-1.r finger5-2.r finger5-3.r finger4-1.r finger4-2.r finger4-3.r finger3-1.r finger3-2.r finger3-3.r finger2-1.r finger2-2.r finger2-3.r rthumb finger1-2.r finger1-3.r --randomizeJointAngles 5 90 90 1 finger5-1.r finger4-1.r finger3-1.r finger2-1.r rthumb --randomizeJointAngles 2 75 75 2 rthumb finger1-2.r --randomizeJointAngles 1 45 45 3 rthumb --randomizeJointAngles 3 0 65 1 finger4-1.r finger4-2.r finger4-3.r"
./GroundTruthDumper $FROM $NATURAL_RHAND --repeat $FINGER_POSES $SELECT_RHAND $RANDOM_POSITION_ROTATION $RANDOMIZE_RIGHT_HAND $OUT
checkForError "RHand - All fingers closed except Finger 4 ( ring )"
#All fingers closed except Finger 3 ( middle )
RANDOMIZE_RIGHT_HAND="--randomizeJointAngles 15 65 65 1 finger5-1.r finger5-2.r finger5-3.r finger4-1.r finger4-2.r finger4-3.r finger3-1.r finger3-2.r finger3-3.r finger2-1.r finger2-2.r finger2-3.r rthumb finger1-2.r finger1-3.r --randomizeJointAngles 5 90 90 1 finger5-1.r finger4-1.r finger3-1.r finger2-1.r rthumb --randomizeJointAngles 2 75 75 2 rthumb finger1-2.r --randomizeJointAngles 1 45 45 3 rthumb --randomizeJointAngles 3 0 65 1 finger3-1.r finger3-2.r finger3-3.r"
./GroundTruthDumper $FROM $NATURAL_RHAND --repeat $FINGER_POSES $SELECT_RHAND $RANDOM_POSITION_ROTATION $RANDOMIZE_RIGHT_HAND $OUT
checkForError "RHand - All fingers closed except Finger 3 ( middle )"
#All fingers closed except Finger 2 ( pointer )
RANDOMIZE_RIGHT_HAND="--randomizeJointAngles 15 65 65 1 finger5-1.r finger5-2.r finger5-3.r finger4-1.r finger4-2.r finger4-3.r finger3-1.r finger3-2.r finger3-3.r finger2-1.r finger2-2.r finger2-3.r rthumb finger1-2.r finger1-3.r --randomizeJointAngles 5 90 90 1 finger5-1.r finger4-1.r finger3-1.r finger2-1.r rthumb --randomizeJointAngles 2 75 75 2 rthumb finger1-2.r --randomizeJointAngles 1 45 45 3 rthumb --randomizeJointAngles 3 0 65 1 finger2-1.r finger2-2.r finger2-3.r"
./GroundTruthDumper $FROM $NATURAL_RHAND --repeat $FINGER_POSES $SELECT_RHAND $RANDOM_POSITION_ROTATION $RANDOMIZE_RIGHT_HAND $OUT
checkForError "RHand - All fingers closed except Finger 2 ( pointer )"
#Done
}
#----------------------------------------------------------------------------------------------------------------------------------------------------
#----------------------------------------------------------------------------------------------------------------------------------------------------
#----------------------------------------------------------------------------------------------------------------------------------------------------
#----------------------------------------------------------------------------------------------------------------------------------------------------
function generateLeftHandDataset
{
OUTBASE="$1"
#Make sure file is wiped before
#adding new poses..
#-------------------------
rm $outputDir/2d_$OUTBASE
rm $outputDir/bvh_$OUTBASE
#-------------------------
MIN_HAND_DEPTH="$2"
MAX_HAND_DEPTH="$3" #1500
MIN_LHAND_RZ="$4"
MAX_LHAND_RZ="$7"
MIN_LHAND_RY="$5"
MAX_LHAND_RY="$8"
MIN_LHAND_RX="$6"
MAX_LHAND_RX="$9"
FROM="--haltonerror $VIEW_COMMANDS --from dataset/lhand.$BVH_TYPE"
RANDOM_POSITION_ROTATION="--randomize2D $MIN_HAND_DEPTH $MAX_HAND_DEPTH $MIN_LHAND_RZ $MIN_LHAND_RY $MIN_LHAND_RX $MAX_LHAND_RZ $MAX_LHAND_RY $MAX_LHAND_RX $USE_OCCLUSIONS"
OUT="--csv $outputDir $OUTBASE 2d+bvh "
# ./BVHGUI2 --from dataset/lhand.qbvh --set 2 -25 --set 3 0.5 --set 4 -0.5 --set 5 -0.5 --set 6 0.5 --set 12 -5.0 --set 39 5.0 --set 54 10.5 --set 63 -18
#New automatic pose generation based on IK Problem..
./GroundTruthDumper $FROM --repeat $FULL_RANDOM_POSES $SELECT_LHAND --randomizeBasedOnIKConstrains lhand $RANDOM_POSITION_ROTATION $OUT
checkForError "lhand full random"
#Default BVH poses with everything at zero but hand is naturally open
./GroundTruthDumper $FROM $NATURAL_LHAND --repeat $BASE_POSES $SELECT_LHAND $RANDOM_POSITION_ROTATION $OUT
checkForError "lhand naturally open"
#Default BVH poses with everything at zero but hand is not naturally open, it is has fingers touching
./GroundTruthDumper $FROM --repeat $ZERO_POSES $SELECT_LHAND $RANDOM_POSITION_ROTATION $OUT
checkForError "lhand to zero"
#Default BVH poses with hand naturally open but thumb in the middle
./GroundTruthDumper $FROM $NATURAL_LHAND --set 63 6.5 --set 64 -28.7 --set 65 8.5 --set 66 37 --set 67 -13 --set 68 7.6 --set 69 -22 --set 70 -5 --set 71 43 --set 72 0 --repeat $ZERO_POSES $SELECT_LHAND $RANDOM_POSITION_ROTATION $OUT
checkForError "lhand naturally open thumb in the middle"
#Left hand Thumb Movement on default pose
./GroundTruthDumper $FROM $NATURAL_LHAND --repeat $FINGER_POSES $SELECT_LHAND $RANDOM_POSITION_ROTATION --randomizeMID $MID_THUMBBASE_Y -56.0 48.0 $OUT
checkForError "LHand - Left hand Thumb Movement on default pose"
#All hand open naturally, only finger 5 (pinky) moving
RANDOMIZE_LEFT_HAND="--randomizeJointAngles 3 0 65 1 finger5-1.l finger5-2.l finger5-3.l"
./GroundTruthDumper $FROM $NATURAL_LHAND --repeat $FINGER_POSES $SELECT_LHAND $RANDOM_POSITION_ROTATION $RANDOMIZE_LEFT_HAND $OUT
checkForError "LHand - All hand open naturally, only finger 5 (pinky) moving"
#All hand open naturally, only finger 4 (ring) moving
RANDOMIZE_LEFT_HAND="--randomizeJointAngles 3 0 65 1 finger4-1.l finger4-2.l finger4-3.l"
./GroundTruthDumper $FROM $NATURAL_LHAND --repeat $FINGER_POSES $SELECT_LHAND $RANDOM_POSITION_ROTATION $RANDOMIZE_LEFT_HAND $OUT
checkForError "LHand - All hand open naturally, only finger 4 (ring) moving"
#All hand open naturally, only finger 3 (middle) moving
RANDOMIZE_LEFT_HAND="--randomizeJointAngles 3 0 65 1 finger3-1.l finger3-2.l finger3-3.l"
./GroundTruthDumper $FROM $NATURAL_LHAND --repeat $FINGER_POSES $SELECT_LHAND $RANDOM_POSITION_ROTATION $RANDOMIZE_LEFT_HAND $OUT
checkForError "LHand - All hand open naturally, only finger 3 (middle) moving"
#All hand open naturally, only finger 2 (pointer) moving
RANDOMIZE_LEFT_HAND="--randomizeJointAngles 3 0 65 1 finger2-1.l finger2-2.l finger2-3.l"
./GroundTruthDumper $FROM $NATURAL_LHAND --repeat $FINGER_POSES $SELECT_LHAND $RANDOM_POSITION_ROTATION $RANDOMIZE_LEFT_HAND $OUT
checkForError "LHand - All hand open naturally, only finger 2 (pointer) moving"
#All hand open naturally, only finger 1 (thumb) moving
RANDOMIZE_LEFT_HAND="--randomizeJointAngles 2 -75 75 2 lthumb finger1-2.l --randomizeJointAngles 1 0 45 3 lthumb"
./GroundTruthDumper $FROM $NATURAL_LHAND --repeat $FINGER_POSES $SELECT_LHAND $RANDOM_POSITION_ROTATION $RANDOMIZE_LEFT_HAND $OUT
checkForError "LHand - All hand open naturally, only finger 1 (thumb) moving"
#All fingers closed only thumb Open!
RANDOMIZE_LEFT_HAND="--randomizeJointAngles 15 65 65 1 finger5-1.l finger5-2.l finger5-3.l finger4-1.l finger4-2.l finger4-3.l finger3-1.l finger3-2.l finger3-3.l finger2-1.l finger2-2.l finger2-3.l lthumb finger1-2.l finger1-3.l --randomizeJointAngles 5 90 90 1 finger5-1.l finger4-1.l finger3-1.l finger2-1.l lthumb --randomizeJointAngles 2 -75 75 2 lthumb finger1-2.l --randomizeJointAngles 1 0 45 3 lthumb"
./GroundTruthDumper $FROM $NATURAL_LHAND --repeat $FINGER_POSES $SELECT_LHAND $RANDOM_POSITION_ROTATION $RANDOMIZE_LEFT_HAND $OUT
checkForError "LHand - All fingers closed only thumb Open!"
#All fingers closed except Finger 5 ( pinky )
RANDOMIZE_LEFT_HAND="--randomizeJointAngles 15 65 65 1 finger5-1.l finger5-2.l finger5-3.l finger4-1.l finger4-2.l finger4-3.l finger3-1.l finger3-2.l finger3-3.l finger2-1.l finger2-2.l finger2-3.l lthumb finger1-2.l finger1-3.l --randomizeJointAngles 5 90 90 1 finger5-1.l finger4-1.l finger3-1.l finger2-1.l lthumb --randomizeJointAngles 2 75 75 2 lthumb finger1-2.l --randomizeJointAngles 1 45 45 3 lthumb --randomizeJointAngles 3 0 65 1 finger5-1.l finger5-2.l finger5-3.l"
./GroundTruthDumper $FROM $NATURAL_LHAND --repeat $FINGER_POSES $SELECT_LHAND $RANDOM_POSITION_ROTATION $RANDOMIZE_LEFT_HAND $OUT
checkForError "LHand - All fingers closed except Finger 5 ( pinky )"
#All fingers closed except Finger 4 ( ring )
RANDOMIZE_LEFT_HAND="--randomizeJointAngles 15 65 65 1 finger5-1.l finger5-2.l finger5-3.l finger4-1.l finger4-2.l finger4-3.l finger3-1.l finger3-2.l finger3-3.l finger2-1.l finger2-2.l finger2-3.l lthumb finger1-2.l finger1-3.l --randomizeJointAngles 5 90 90 1 finger5-1.l finger4-1.l finger3-1.l finger2-1.l lthumb --randomizeJointAngles 2 75 75 2 lthumb finger1-2.l --randomizeJointAngles 1 45 45 3 lthumb --randomizeJointAngles 3 0 65 1 finger4-1.l finger4-2.l finger4-3.l"
./GroundTruthDumper $FROM $NATURAL_LHAND --repeat $FINGER_POSES $SELECT_LHAND $RANDOM_POSITION_ROTATION $RANDOMIZE_LEFT_HAND $OUT
checkForError "LHand - All fingers closed except Finger 4 ( ring )"
#All fingers closed except Finger 3 ( middle )
RANDOMIZE_LEFT_HAND="--randomizeJointAngles 15 65 65 1 finger5-1.l finger5-2.l finger5-3.l finger4-1.l finger4-2.l finger4-3.l finger3-1.l finger3-2.l finger3-3.l finger2-1.l finger2-2.l finger2-3.l lthumb finger1-2.l finger1-3.l --randomizeJointAngles 5 90 90 1 finger5-1.l finger4-1.l finger3-1.l finger2-1.l lthumb --randomizeJointAngles 2 75 75 2 lthumb finger1-2.l --randomizeJointAngles 1 45 45 3 lthumb --randomizeJointAngles 3 0 65 1 finger3-1.l finger3-2.l finger3-3.l"
./GroundTruthDumper $FROM $NATURAL_LHAND --repeat $FINGER_POSES $SELECT_LHAND $RANDOM_POSITION_ROTATION $RANDOMIZE_LEFT_HAND $OUT
checkForError "LHand - All fingers closed except Finger 3 ( middle )"
#All fingers closed except Finger 2 ( pointer )
RANDOMIZE_LEFT_HAND="--randomizeJointAngles 15 65 65 1 finger5-1.l finger5-2.l finger5-3.l finger4-1.l finger4-2.l finger4-3.l finger3-1.l finger3-2.l finger3-3.l finger2-1.l finger2-2.l finger2-3.l lthumb finger1-2.l finger1-3.l --randomizeJointAngles 5 90 90 1 finger5-1.l finger4-1.l finger3-1.l finger2-1.l lthumb --randomizeJointAngles 2 75 75 2 lthumb finger1-2.l --randomizeJointAngles 1 45 45 3 lthumb --randomizeJointAngles 3 0 65 1 finger2-1.l finger2-2.l finger2-3.l"
./GroundTruthDumper $FROM $NATURAL_LHAND --repeat $FINGER_POSES $SELECT_LHAND $RANDOM_POSITION_ROTATION $RANDOMIZE_LEFT_HAND $OUT
checkForError "LHand - All fingers closed except Finger 2 ( pointer )"
#Done
#Let's count it and store the numbers so we don't have to spam disk reads on every training..
wc -l $outputDir/2d_$1 > $outputDir/count_$1
#wc -l $outputDir/3d_$1 > $outputDir/count_$1
wc -l $outputDir/bvh_$1 > $outputDir/count_$1
}
#----------------------------------------------------------------------------------------------------------------------------------------------------
#----------------------------------------------------------------------------------------------------------------------------------------------------
#----------------------------------------------------------------------------------------------------------------------------------------------------
#----------------------------------------------------------------------------------------------------------------------------------------------------
# ./BVHGUI2 --from dataset/lhand.$BVH_TYPE --set 3 -90 --set 4 0 --set 5 -135
MIN_HAND_DEPTH="200"
MAX_HAND_DEPTH="2000" #1500
MIN_HAND_RZ="-90"
MAX_HAND_RZ="-90"
MIN_HAND_RY="-50"
MAX_HAND_RY="50"
#If we have a quaternion we can handle all orientations!
if [ "$1" == "--quaternions" ]; then
MIN_HAND_RZ="-179.9"
MAX_HAND_RZ="179.9"
MIN_HAND_RY="-179.9"
MAX_HAND_RY="179.9"
fi
MIN_HAND_RX="-179.9"
MAX_HAND_RX="179.9"
generateLeftHandDataset lhand_all.csv $MIN_HAND_DEPTH $MAX_HAND_DEPTH $MIN_HAND_RZ $MIN_HAND_RY $MIN_HAND_RX $MAX_HAND_RZ $MAX_HAND_RY $MAX_HAND_RX
#./ReshapeCSV --from dataset/bvh_lhand_all.csv --faces 20 > dataset/category_lhand_all.csv
generateRightHandDataset rhand_all.csv $MIN_HAND_DEPTH $MAX_HAND_DEPTH $MIN_HAND_RZ $MIN_HAND_RY $MIN_HAND_RX $MAX_HAND_RZ $MAX_HAND_RY $MAX_HAND_RX
#./ReshapeCSV --from dataset/bvh_rhand_all.csv --faces 20 > dataset/category_rhand_all.csv
echo "Done Generating Hands.."
exit 0
MIN_HAND_RX="-135"
MAX_HAND_RX="-45"
generateRightHandDataset rhand_front.csv $MIN_HAND_DEPTH $MAX_HAND_DEPTH $MIN_HAND_RZ $MIN_HAND_RY $MIN_HAND_RX $MAX_HAND_RZ $MAX_HAND_RY $MAX_HAND_RX
generateLeftHandDataset lhand_front.csv $MIN_HAND_DEPTH $MAX_HAND_DEPTH $MIN_HAND_RZ $MIN_HAND_RY $MIN_HAND_RX $MAX_HAND_RZ $MAX_HAND_RY $MAX_HAND_RX
MIN_HAND_RX="45"
MAX_HAND_RX="135"
generateRightHandDataset rhand_back.csv $MIN_HAND_DEPTH $MAX_HAND_DEPTH $MIN_HAND_RZ $MIN_HAND_RY $MIN_HAND_RX $MAX_HAND_RZ $MAX_HAND_RY $MAX_HAND_RX
generateLeftHandDataset lhand_back.csv $MIN_HAND_DEPTH $MAX_HAND_DEPTH $MIN_HAND_RZ $MIN_HAND_RY $MIN_HAND_RX $MAX_HAND_RZ $MAX_HAND_RY $MAX_HAND_RX
MIN_HAND_RX="-45"
MAX_HAND_RX="45"
generateRightHandDataset rhand_left.csv $MIN_HAND_DEPTH $MAX_HAND_DEPTH $MIN_HAND_RZ $MIN_HAND_RY $MIN_HAND_RX $MAX_HAND_RZ $MAX_HAND_RY $MAX_HAND_RX
generateLeftHandDataset lhand_left.csv $MIN_HAND_DEPTH $MAX_HAND_DEPTH $MIN_HAND_RZ $MIN_HAND_RY $MIN_HAND_RX $MAX_HAND_RZ $MAX_HAND_RY $MAX_HAND_RX
MIN_HAND_RX="135"
MAX_HAND_RX="225"
generateRightHandDataset rhand_right.csv $MIN_HAND_DEPTH $MAX_HAND_DEPTH $MIN_HAND_RZ $MIN_HAND_RY $MIN_HAND_RX $MAX_HAND_RZ $MAX_HAND_RY $MAX_HAND_RX
generateLeftHandDataset lhand_right.csv $MIN_HAND_DEPTH $MAX_HAND_DEPTH $MIN_HAND_RZ $MIN_HAND_RY $MIN_HAND_RX $MAX_HAND_RZ $MAX_HAND_RY $MAX_HAND_RX
#--svg tmp/ --bvh randomRHand.$BVH_TYPE
#----------------------------------------------------------------------------------------------------------------------------------------------------
#----------------------------------------------------------------------------------------------------------------------------------------------------
#----------------------------------------------------------------------------------------------------------------------------------------------------
#----------------------------------------------------------------------------------------------------------------------------------------------------
exit 0
@@ -0,0 +1,320 @@
#!/bin/bash
#Colors for easier output
red=$(printf "\033[31m")
green=$(printf "\033[32m")
yellow=$(printf "\033[33m")
blue=$(printf "\033[34m")
magenta=$(printf "\033[35m")
cyan=$(printf "\033[36m")
white=$(printf "\033[37m")
normal=$(printf "\033[m")
#We can use R to gather statistics about the generated ground truth..
if ! [ -x "$(command -v R)" ]; then
echo 'Warning: R is not installed.' >&2
sudo apt-get install r-base
fi
function getStatistics
{
#use R to generate statistics
#sudo apt-get install r-base
R -q -e "x <- read.csv('$1', header = T); summary(x); sd(x[ , 1])" > $2
cat $1 | wc -l >> $2
}
#We move to the correct directory..
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
cd "$DIR"
cd ..
#Where is our datasets located, compared to the current directory..
datasetDir="dataset/MotionCapture"
#MocapNET1 -> datasetSubDir="01 02 03 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19"
datasetSubDir="h36 01 02 03 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 45 46 47 49 54 55 56 60 61 62 63 64 69 70 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 93 94 102 103 104 105 106 107 108 111 113 114 115 117 118 120 121 122 123 124 125 126 127 128 131 132 133 134 135 136 137 138 139 140 141 142 143 144"
#datasetSubDir="h36"
#Where is our output located
outputDir="dataset/"
# Use --printparams in view commands to view the commands that are given to the utility at stderr
VIEW_COMMANDS=" "
RAND_UPPER_BODY="--perturbJointAngles 2 30.0 rshoulder lshoulder --perturbJointAngles 2 16.0 relbow lelbow --perturbJointAngles 2 10.0 abdomen chest"
RAND_LOWER_BODY="--perturbJointAngles 2 30.0 rhip lhip --perturbJointAngles 4 10.0 lknee rknee lfoot rfoot --perturbJointAngles 2 10.0 abdomen chest"
RANDOMIZE_LEFT_HAND="--randomizeJointAngles 15 -65 0 1 finger5-1.l finger5-2.l finger5-3.l finger4-1.l finger4-2.l finger4-3.l finger3-1.l finger3-2.l finger3-3.l finger2-1.l finger2-2.l finger2-3.l lthumb finger1-2.l finger1-3.l --randomizeJointAngles 5 -90 0 1 finger5-1.l finger4-1.l finger3-1.l finger2-1.l lthumb --randomizeJointAngles 2 -75 75 2 lthumb finger1-2.l --randomizeJointAngles 1 -45 0 3 lthumb"
RANDOMIZE_RIGHT_HAND="--randomizeJointAngles 15 0 65 1 finger5-1.r finger5-2.r finger5-3.r finger4-1.r finger4-2.r finger4-3.r finger3-1.r finger3-2.r finger3-3.r finger2-1.r finger2-2.r finger2-3.r rthumb finger1-2.r finger1-3.r --randomizeJointAngles 5 0 90 1 finger5-1.r finger4-1.r finger3-1.r finger2-1.r rthumb --randomizeJointAngles 2 -75 75 2 rthumb finger1-2.r --randomizeJointAngles 1 0 45 3 rthumb"
FILTER_OUT_POSES_WITH_HANDS_IN_SIDE="--filterout 0 0 -130.0 0 90 0 1920 1080 570.7 570.3 6 rhand lhip 0 120 rhand rhip 0 120 rhand lhand 0 150 lhand rhip 0 120 lhand lhip 0 120 lhand rhand 0 150"
#FILTER_OUT_POSES_WITH_HANDS_IN_SIDE=" "
DONT_USE_END_JOINTS="0"
USE_END_JOINTS="1"
HIDEBODY="--hide2DLocationOfJoints $DONT_USE_END_JOINTS 8 abdomen chest eye.r eye.l toe1-2.r toe5-3.r toe1-2.l toe5-3.l" #We want to contain these joints in the BVH file and solve them, but they do not correspond to the BODY25 format so we hide them as 2D points..
SELECTBODY="--selectJoints $USE_END_JOINTS 23 hip eye.r eye.l abdomen chest neck head rshoulder relbow rhand lshoulder lelbow lhand rhip rknee rfoot lhip lknee lfoot toe1-2.r toe5-3.r toe1-2.l toe5-3.l $HIDEBODY"
HIDEUPPERBODY="--hide2DLocationOfJoints $DONT_USE_END_JOINTS 4 abdomen chest eye.r eye.l" #We want to contain these joints in the BVH file and solve them, but they do not correspond to the BODY25 format so we hide them as 2D points..
SELECTUPPERBODY="--selectJoints $USE_END_JOINTS 13 hip eye.r eye.l abdomen chest neck head rshoulder relbow rhand lshoulder lelbow lhand $HIDEUPPERBODY"
HIDELOWERBODY="--hide2DLocationOfJoints $DONT_USE_END_JOINTS 6 abdomen chest toe1-2.r toe5-3.r toe1-2.l toe5-3.l"
SELECTLOWERBODY="--selectJoints $USE_END_JOINTS 14 hip abdomen chest neck rhip rknee rfoot lhip lknee lfoot toe1-2.r toe5-3.r toe1-2.l toe5-3.l $HIDELOWERBODY"
SELECT_RHAND="--selectJoints $USE_END_JOINTS 16 rhand finger5-1.r finger5-2.r finger5-3.r finger4-1.r finger4-2.r finger4-3.r finger3-1.r finger3-2.r finger3-3.r finger2-1.r finger2-2.r finger2-3.r rthumb finger1-2.r finger1-3.r"
SELECT_LHAND="--selectJoints $USE_END_JOINTS 16 lhand finger5-1.l finger5-2.l finger5-3.l finger4-1.l finger4-2.l finger4-3.l finger3-1.l finger3-2.l finger3-3.l finger2-1.l finger2-2.l finger2-3.l lthumb finger1-2.l finger1-3.l"
#FAR
MIN_DEPTH="900" #1000 original
MAX_DEPTH="4500" #3000 is too small
ITERATIONS="1" #Smallest size..
#ITERATIONS="2" #float32 targeting 16GB RAM
#ITERATIONS="8" #float16 targeting 16GB RAM
#Get number of bytes in RAM
RAM=`free | grep Mem | tr -s ' '| cut -f2 -d ' '`
if [ "$RAM" -gt "11286464" ]; then
echo "More than 12GB";
ITERATIONS="0"
fi
if [ "$RAM" -gt "15297500" ]; then
echo "More than 16GB";
ITERATIONS="1"
fi
if [ "$RAM" -gt "31861780" ]; then
echo "More than 32GB";
ITERATIONS="2"
fi
#Uncomment next line to override settings and make the
#minimum training set for development
#ITERATIONS="0"
totaldatasetsToGo=`echo "$datasetSubDir" | awk '{print NF}'`
function generateDataset
{
datasetsProcessed=0
rm $outputDir/$1
rm $outputDir/count_$1
rm $outputDir/2d_$1
#rm $outputDir/3d_$1
rm $outputDir/bvh_$1
for d in $datasetSubDir
do
if [ -d $datasetDir/$d ]
then
echo "Generating $1 - $green Found $d directory $normal"
datasetFile=`ls $datasetDir/$d | grep bvh`
((datasetsProcessed++))
#-------------------------------------------------------
for f in $datasetFile
do
echo "$green Generating $1 - $datasetsProcessed/$totaldatasetsToGo - $datasetDir/$d/$f file $normal"
#||||||||||||||||||||||||||||||||||||||||||||||||||||||||
BVHFILE="$datasetDir/$d/$f" # --svg $outputDir
./GroundTruthDumper $VIEW_COMMANDS --haltonerror --from $BVHFILE --filtergimballocks 4 $3 --repeat $ITERATIONS $2 --occlusions --csv $outputDir $1 2d+bvh # --bvh $outputDir/$f-random.bvh
#||||||||||||||||||||||||||||||||||||||||||||||||||||||||
done
#-------------------------------------------------------
else
echo "$red Could not find $d directory $normal"
fi
done
#Let's count it and store the numbers so we don't have to spam disk reads on every training..
wc -l $outputDir/2d_$1 > $outputDir/count_$1
#wc -l $outputDir/3d_$1 >> $outputDir/count_$1
wc -l $outputDir/bvh_$1 >> $outputDir/count_$1
}
#------------------------------------------------------------------------------------------------------------
# MocapNET 1
# \ /
# \ BACK /
# \ /
# BACK \ / BACK
# \/
#-----------/\-------------
# / \
# FRONT / \ FRONT
# / FRONT \
# / \
#Old way to do that ( works if you don't go very far in depth )
#------------------------------------------------------------------------------------------------------------
#MINIMUM_POSITION="-1400 -300 $MIN_DEPTH"
#MINIMUM_ROTATION="-25 -178 -35"
#MAXIMUM_POSITION="1400 300 $MAX_DEPTH"
#MAXIMUM_ROTATION="25 178 35"
#generateDataset dataBack.csv "--flipRandomizationOrientation --randomizeranges $MINIMUM_POSITION -35 -179.999999 -35 $MAXIMUM_POSITION 35 -90 35 $MINIMUM_POSITION -35 90 -35 $MAXIMUM_POSITION 35 180 35"
#generateDataset dataAll.csv "--randomize $MINIMUM_POSITION -35 -179.999999 -35 $MAXIMUM_POSITION 35 180 35"
#generateDataset dataFront.csv "--randomize $MINIMUM_POSITION -35 -90 -35 $MAXIMUM_POSITION 35 90 35"
#------------------------------------------------------------------------------------------------------------
#New extra extra fine detail rotated by 45 degrees
# \ /
# \ BACK /
# \ /
# \ /
# \/
# LEFT /\ RIGHT
# / \
# / \
# / FRONT \
# / \
#------------------------------------------------------------------------------------------------------------
MIN_LIM="-45"
MAX_LIM="45"
#I have added 20 degrees on every limit more than the default
#to have some overlap and redundancy when switching between datasets
#---------------------------
FRONT_MIN_ORIENTATION="-55" #-45 default , -55 with 10 deg safety
FRONT_MAX_ORIENTATION="55" # 45 default , 55 with 10 deg safety
#---------------------------
BACK_MIN_ORIENTATION="125" # 135 default , 125 with 10 deg safety
BACK_MAX_ORIENTATION="235" # 225 default , 235 with 10 deg safety
#---------------------------
LEFT_MIN_ORIENTATION="-145" #-135 default
LEFT_MAX_ORIENTATION="-35" #-45 default
#---------------------------
RIGHT_MIN_ORIENTATION="35" # 45 default
RIGHT_MAX_ORIENTATION="145" # 135 default
# $FILTER_OUT_POSES_WITH_HANDS_IN_SIDE
#rm $outputDir/2d_filteredPosesRHand.csv
#rm $outputDir/bvh_filteredPosesRHand.csv
#./GroundTruthDumper --haltonerror --filtergimballocks --from filteredPosesRHand.bvh $SELECTUPPERBODY $RAND_UPPER_BODY --csvOrientation front --randomize2D $MIN_DEPTH $MAX_DEPTH -10 -45 -0 10 45 10 $SELECTUPPERBODY --occlusions --csv $outputDir #filteredPosesRHand.csv 2d+bvh
#exit 0
FILTER_OUT="$FILTER_OUT_POSES_WITH_HANDS_IN_SIDE"
#UPPER BODY
generateDataset upperbody_all.csv "$FILTER_OUT --randomize2D $MIN_DEPTH $MAX_DEPTH $MIN_LIM -179.999999 $MIN_LIM $MAX_LIM 180 $MAX_LIM" "$SELECTUPPERBODY"
./ReshapeCSV dataset/bvh_upperbody_all.csv > dataset/category_upperbody_all.csv
echo "Category size = "#cat dataset/category_upperbody_all.csv | wc -c
#-----------------------------------------------
generateDataset upperbody_front.csv "$FILTER_OUT --csvOrientation front --randomize2D $MIN_DEPTH $MAX_DEPTH $MIN_LIM $FRONT_MIN_ORIENTATION $MIN_LIM $MAX_LIM $FRONT_MAX_ORIENTATION $MAX_LIM" "$SELECTUPPERBODY $RAND_UPPER_BODY"
generateDataset upperbody_back.csv "$FILTER_OUT --csvOrientation back --randomize2D $MIN_DEPTH $MAX_DEPTH $MIN_LIM $BACK_MIN_ORIENTATION $MIN_LIM $MAX_LIM $BACK_MAX_ORIENTATION $MAX_LIM" "$SELECTUPPERBODY $RAND_UPPER_BODY"
generateDataset upperbody_left.csv "$FILTER_OUT --csvOrientation left --randomize2D $MIN_DEPTH $MAX_DEPTH $MIN_LIM $LEFT_MIN_ORIENTATION $MIN_LIM $MAX_LIM $LEFT_MAX_ORIENTATION $MAX_LIM" "$SELECTUPPERBODY $RAND_UPPER_BODY"
generateDataset upperbody_right.csv "$FILTER_OUT --csvOrientation right --randomize2D $MIN_DEPTH $MAX_DEPTH $MIN_LIM $RIGHT_MIN_ORIENTATION $MIN_LIM $MAX_LIM $RIGHT_MAX_ORIENTATION $MAX_LIM" "$SELECTUPPERBODY $RAND_UPPER_BODY"
#LOWER BODY
generateDataset lowerbody_all.csv "--randomize2D $MIN_DEPTH $MAX_DEPTH $MIN_LIM -179.999999 $MIN_LIM $MAX_LIM 180 $MAX_LIM" "$SELECTLOWERBODY"
./ReshapeCSV dataset/bvh_lowerbody_all.csv > dataset/category_lowerbody_all.csv
echo "Category size = "
cat dataset/category_lowerbody_all.csv | wc -c
#-----------------------------------------------
generateDataset lowerbody_front.csv "--csvOrientation front --randomize2D $MIN_DEPTH $MAX_DEPTH $MIN_LIM $FRONT_MIN_ORIENTATION $MIN_LIM $MAX_LIM $FRONT_MAX_ORIENTATION $MAX_LIM" "$SELECTLOWERBODY $RAND_LOWER_BODY"
generateDataset lowerbody_back.csv "--csvOrientation back --randomize2D $MIN_DEPTH $MAX_DEPTH $MIN_LIM $BACK_MIN_ORIENTATION $MIN_LIM $MAX_LIM $BACK_MAX_ORIENTATION $MAX_LIM" "$SELECTLOWERBODY $RAND_LOWER_BODY"
generateDataset lowerbody_left.csv "--csvOrientation left --randomize2D $MIN_DEPTH $MAX_DEPTH $MIN_LIM $LEFT_MIN_ORIENTATION $MIN_LIM $MAX_LIM $LEFT_MAX_ORIENTATION $MAX_LIM" "$SELECTLOWERBODY $RAND_LOWER_BODY"
generateDataset lowerbody_right.csv "--csvOrientation right --randomize2D $MIN_DEPTH $MAX_DEPTH $MIN_LIM $RIGHT_MIN_ORIENTATION $MIN_LIM $MAX_LIM $RIGHT_MAX_ORIENTATION $MAX_LIM" "$SELECTLOWERBODY $RAND_LOWER_BODY"
exit 0 # <> <> <> <> <> <> <> <> <> <> <> <> <> <> <> <> <> <> <>
#This is a better hand dataset generator that ignores poses
./createRandomHandDataset.sh
exit 0 # <> <> <> <> <> <> <> <> <> <> <> <> <> <> <> <> <> <> <>
#This hand is just based on CMU poses
#LEFT HAND
generateDataset lhand_front.csv "--csvOrientation front --randomize2D $MIN_DEPTH $MAX_DEPTH $MIN_LIM $FRONT_MIN_ORIENTATION $MIN_LIM $MAX_LIM $FRONT_MAX_ORIENTATION $MAX_LIM" "$SELECT_LHAND $RANDOMIZE_LEFT_HAND"
generateDataset lhand_back.csv "--csvOrientation back --randomize2D $MIN_DEPTH $MAX_DEPTH $MIN_LIM $BACK_MIN_ORIENTATION $MIN_LIM $MAX_LIM $BACK_MAX_ORIENTATION $MAX_LIM" "$SELECT_LHAND $RANDOMIZE_LEFT_HAND"
generateDataset lhand_left.csv "--csvOrientation left --randomize2D $MIN_DEPTH $MAX_DEPTH $MIN_LIM $LEFT_MIN_ORIENTATION $MIN_LIM $MAX_LIM $LEFT_MAX_ORIENTATION $MAX_LIM" "$SELECT_LHAND $RANDOMIZE_LEFT_HAND"
generateDataset lhand_right.csv "--csvOrientation right --randomize2D $MIN_DEPTH $MAX_DEPTH $MIN_LIM $RIGHT_MIN_ORIENTATION $MIN_LIM $MAX_LIM $RIGHT_MAX_ORIENTATION $MAX_LIM" "$SELECT_LHAND $RANDOMIZE_LEFT_HAND"
#RIGHT HAND
generateDataset rhand_front.csv "--csvOrientation front --randomize2D $MIN_DEPTH $MAX_DEPTH $MIN_LIM $FRONT_MIN_ORIENTATION $MIN_LIM $MAX_LIM $FRONT_MAX_ORIENTATION $MAX_LIM" "$SELECT_RHAND $RANDOMIZE_RIGHT_HAND"
generateDataset rhand_back.csv "--csvOrientation back --randomize2D $MIN_DEPTH $MAX_DEPTH $MIN_LIM $BACK_MIN_ORIENTATION $MIN_LIM $MAX_LIM $BACK_MAX_ORIENTATION $MAX_LIM" "$SELECT_RHAND $RANDOMIZE_RIGHT_HAND"
generateDataset rhand_left.csv "--csvOrientation left --randomize2D $MIN_DEPTH $MAX_DEPTH $MIN_LIM $LEFT_MIN_ORIENTATION $MIN_LIM $MAX_LIM $LEFT_MAX_ORIENTATION $MAX_LIM" "$SELECT_RHAND $RANDOMIZE_RIGHT_HAND"
generateDataset rhand_right.csv "--csvOrientation right --randomize2D $MIN_DEPTH $MAX_DEPTH $MIN_LIM $RIGHT_MIN_ORIENTATION $MIN_LIM $MAX_LIM $RIGHT_MAX_ORIENTATION $MAX_LIM" "$SELECT_RHAND $RANDOMIZE_RIGHT_HAND"
exit 0 # <> <> <> <> <> <> <> <> <> <> <> <> <> <> <> <> <> <> <>
#WHOLE BODY AT ONCE
generateDataset body_all.csv "$FILTER_OUT --randomize2D $MIN_DEPTH $MAX_DEPTH $MIN_LIM -179.999999 $MIN_LIM $MAX_LIM 180 $MAX_LIM" "$SELECTBODY"
./ReshapeCSV dataset/bvh_body_all.csv > dataset/category_body_all.csv
echo "Category size = "
cat dataset/category_body_all.csv | wc -c
#-----------------------------------------------
generateDataset body_front.csv "$FILTER_OUT --csvOrientation front --randomize2D $MIN_DEPTH $MAX_DEPTH $MIN_LIM $FRONT_MIN_ORIENTATION $MIN_LIM $MAX_LIM $FRONT_MAX_ORIENTATION $MAX_LIM" "$SELECTBODY"
generateDataset body_back.csv "$FILTER_OUT --csvOrientation back --randomize2D $MIN_DEPTH $MAX_DEPTH $MIN_LIM $BACK_MIN_ORIENTATION $MIN_LIM $MAX_LIM $BACK_MAX_ORIENTATION $MAX_LIM" "$SELECTBODY"
generateDataset body_left.csv "$FILTER_OUT --csvOrientation left --randomize2D $MIN_DEPTH $MAX_DEPTH $MIN_LIM $LEFT_MIN_ORIENTATION $MIN_LIM $MAX_LIM $LEFT_MAX_ORIENTATION $MAX_LIM" "$SELECTBODY"
generateDataset body_right.csv "$FILTER_OUT --csvOrientation right --randomize2D $MIN_DEPTH $MAX_DEPTH $MIN_LIM $RIGHT_MIN_ORIENTATION $MIN_LIM $MAX_LIM $RIGHT_MAX_ORIENTATION $MAX_LIM" "$SELECTBODY"
exit 0 # <> <> <> <> <> <> <> <> <> <> <> <> <> <> <> <> <> <> <>
echo "Getting statistics for front view.."
cat dataset/bvh_body_front.csv | cut -d',' -f 5 > frontOrientations
getStatistics frontOrientations dataset/bvh_body_front_statistics.txt
cat dataset/bvh_body_front_statistics.txt
rm frontOrientations
echo "Getting statistics for back view.."
cat dataset/bvh_body_back.csv | cut -d',' -f 5 > backOrientations
getStatistics backOrientations dataset/bvh_body_back_statistics.txt
cat dataset/bvh_body_back_statistics.txt
rm backOrientations
echo "Getting statistics for left view.."
cat dataset/bvh_body_left.csv | cut -d',' -f 5 > leftOrientations
getStatistics leftOrientations dataset/bvh_body_left_statistics.txt
cat dataset/bvh_body_left_statistics.txt
rm leftOrientations
echo "Getting statistics for right view.."
cat dataset/bvh_body_right.csv | cut -d',' -f 5 > rightOrientations
getStatistics rightOrientations dataset/bvh_body_right_statistics.txt
cat dataset/bvh_body_right_statistics.txt
rm rightOrientations
echo "Getting statistics for all view.."
cat dataset/bvh_body_all.csv | cut -d',' -f 5 > allOrientations
getStatistics allOrientations dataset/bvh_body_all_statistics.txt
cat dataset/bvh_body_all_statistics.txt
rm allOrientations
echo "Done.."
exit 0
@@ -0,0 +1,67 @@
#!/bin/bash
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
cd "$DIR"
cd ..
red=$(printf "\033[31m")
green=$(printf "\033[32m")
yellow=$(printf "\033[33m")
blue=$(printf "\033[34m")
magenta=$(printf "\033[35m")
cyan=$(printf "\033[36m")
white=$(printf "\033[37m")
normal=$(printf "\033[m")
SELECTBODY="--selectJoints 21 hip abdomen chest neck head rcollar rshoulder relbow rhand lcollar lshoulder lelbow lhand rhip rknee rfoot lhip lknee lfoot toe3-2.r toe3-2.l"
SELECTRHAND="--selectJoints 11 rhand rthumb1 rthumb2 rindex1 rindex2 rmid1 rmid2 rring1 rring2 rpinky1 rpinky2"
SELECTLHAND="--selectJoints 11 lhand lthumb1 lthumb2 lindex1 lindex2 lmid1 lmid2 lring1 lring2 lpinky1 lpinky2"
datasetDir="dataset/MotionCapture"
datasetSubDir="01 02 03 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19"
outputDir="dataset/"
rm $outputDir/2d_body_test.csv
rm $outputDir/3d_body_test.csv
rm $outputDir/bvh_body_test.csv
#create a small test file with one example
#rm $outputDir/testSMALL.csv
# ./GroundTruthDumper --from MotionCapture/01/01_01.bvh --offsetPositionRotation 0 750 2500 0 0 0 --maxFrames 1 --csv $outputDir testSMALL.csv
#PRODUCESVG="--svg $outputDir/svg"
PRODUCESVG=" "
datasetsProcessed=0
totaldatasetsToGo=`echo "$datasetSubDir" | awk '{print NF}'`
rm $outputDir/test.csv
for d in $datasetSubDir
do
if [ -d $datasetDir/$d ]
then
echo "$green Found $d directory $normal"
datasetFile=`ls $datasetDir/$d | grep bvh`
((datasetsProcessed++))
#-------------------------------------------------------
for f in $datasetFile
do
echo "$green Generating Test - $datasetsProcessed/$totaldatasetsToGo - $datasetDir/$d/$f file $normal"
#||||||||||||||||||||||||||||||||||||||||||||||||||||||||
BVHFILE="$datasetDir/$d/$f" # --svg $outputDir
#./GroundTruthDumper --from $BVHFILE --csv $outputDir test.csv# --bvh $outputDir/$f-random.bvh
./GroundTruthDumper --from $BVHFILE $SELECTBODY --offsetPositionRotation 0 750 2000 0 0 0 --occlusions --csv $outputDir body_test.csv 2d+bvh $PRODUCESVG #--to ~/Documents/Programming/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/Scenes/testBVH.conf --bvh $outputDir/$f-random.bvh --svg $outputDir/svg
#exit 0
#./GroundTruthDumper --from $BVHFILE --setPositionRotation 0 400 0 0 0 0 --csv $outputDir test.csv# --bvh $outputDir/$f-random.bvh
#||||||||||||||||||||||||||||||||||||||||||||||||||||||||
done
#-------------------------------------------------------
else
echo "$red Could not find $d directory $normal"
fi
done
exit 0
+37
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@@ -0,0 +1,37 @@
#!/bin/bash
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
cd "$DIR"
cd ..
#Valgrind can also be downloaded..
#https://www.valgrind.org/downloads/current.html
#Simple dependency checker that will apt-get stuff if something is missing
SYSTEM_DEPENDENCIES="valgrind"
for REQUIRED_PKG in $SYSTEM_DEPENDENCIES
do
PKG_OK=$(dpkg-query -W --showformat='${Status}\n' $REQUIRED_PKG|grep "install ok installed")
echo "Checking for $REQUIRED_PKG: $PKG_OK"
if [ "" = "$PKG_OK" ]; then
echo "No $REQUIRED_PKG. Setting up $REQUIRED_PKG."
#If this is uncommented then only packages that are missing will get prompted..
#sudo apt-get --yes install $REQUIRED_PKG
#if this is uncommented then if one package is missing then all missing packages are immediately installed..
sudo apt-get install $SYSTEM_DEPENDENCIES
break
fi
done
#------------------------------------------------------------------------------
valgrind --tool=memcheck --leak-check=yes --show-reachable=yes --track-origins=yes --num-callers=20 --track-fds=yes ./MocapNETLiveWebcamDemo --from shuffle $@ 2>error.txt
exit 0
@@ -0,0 +1,93 @@
#!/bin/bash
DATASET=""
if (( $#<1 ))
then
echo "Please provide arguments first argument is dataset "
exit 1
else
DATASET=$1-data
fi
# $1 holds the video file we want to process ( it should be something like path/to/videofile.mp4 )
#DATASET now holds the output directory we will create ( it should be something like path/to/videofile.mp4-data/ )
#Remember the directory where user started
STARTDIR=`pwd`
#Remember the directory where the script is ( and where MocapNET is :) )
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
#Please give the path to openpose here..
OPENPOSE_DIR="/home/ammar/Documents/3dParty/openpose/"
OPENPOSE_BINARY_DIR="/home/ammar/Documents/3dParty/openpose/build/examples/openpose/"
#Dataset dumping using ffmpeg
#-----------------------------------------------------------------------------
#-----------------------------------------------------------------------------
#-----------------------------------------------------------------------------
#Create the new dataset directory
mkdir $DATASET
#Dump the video files using our naming scheme
ffmpeg -i $1 -r 30 -q:v 1 $DATASET/colorFrame_0_%05d.jpg
#Make sure we start at frame 0
cp $DATASET/colorFrame_0_00001.jpg $DATASET/colorFrame_0_00000.jpg
#We now want to grab an absolute path to our dataset
cd $DATASET
FULL_PATH_TO_DATASET=`pwd`
#-----------------------------------------------------------------------------
#-----------------------------------------------------------------------------
#-----------------------------------------------------------------------------
#2D pose estimation using OpenPose
#-----------------------------------------------------------------------------
#-----------------------------------------------------------------------------
#-----------------------------------------------------------------------------
cd $OPENPOSE_DIR
LD_LIBRARY_PATH=/usr/local/cuda-9.0/lib64 $OPENPOSE_BINARY_DIR/openpose.bin -number_people_max 1 --hand --face --write_json $FULL_PATH_TO_DATASET -image_dir $FULL_PATH_TO_DATASET $@
#-----------------------------------------------------------------------------
#-----------------------------------------------------------------------------
#-----------------------------------------------------------------------------
#2D pose conversion to CSV using our tool
#-----------------------------------------------------------------------------
#-----------------------------------------------------------------------------
#-----------------------------------------------------------------------------
cd "$DIR"
cd ..
./convertOpenPoseJSONToCSV --from $DATASET
#-----------------------------------------------------------------------------
#-----------------------------------------------------------------------------
#-----------------------------------------------------------------------------
#3D pose estimation using MocapNET2
#-----------------------------------------------------------------------------
#-----------------------------------------------------------------------------
#-----------------------------------------------------------------------------
cd "$DIR"
cd ..
./MocapNET2CSV --from $FULL_PATH_TO_DATASET/2dJoints_v1.4.csv --mt --show 3 --save
cp out.bvh $FULL_PATH_TO_DATASET/predicted.bvh
#-----------------------------------------------------------------------------
#-----------------------------------------------------------------------------
#-----------------------------------------------------------------------------
cd $STARTDIR
exit 0
+37
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@@ -0,0 +1,37 @@
#!/bin/bash
#This is a script to dump a video file to JPG files
#it uses ffmpeg so make sure you have sudo apt-get install ffmpeg
#If you do ./dump_video.sh yourvideo.mp4
#There should be an output folder yourvideo.mp4-data that has all the frames of the video
#you can then point OpenPose to this directory to convert them to JSON 2D detections
STARTDIR=`pwd`
#Switch to this directory
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
cd "$DIR"
DATASET=""
if (( $#<1 ))
then
echo "Please provide arguments first argument is dataset "
exit 1
else
DATASET=$1-data
fi
THEDATETAG=`date +"%y-%m-%d_%H-%M-%S"`
mkdir $DATASET
ffmpeg -i $1 -r 30 -q:v 1 $DATASET/colorFrame_0_%05d.jpg
cp $DATASET/colorFrame_0_00001.jpg $DATASET/colorFrame_0_00000.jpg
cd $DATASET
cd ..
cd $STARTDIR
exit 0
@@ -0,0 +1,48 @@
#!/bin/bash
#Simple dependency checker that will apt-get stuff if something is missing
# sudo apt-get install gnuplot
SYSTEM_DEPENDENCIES="gnuplot"
for REQUIRED_PKG in $SYSTEM_DEPENDENCIES
do
PKG_OK=$(dpkg-query -W --showformat='${Status}\n' $REQUIRED_PKG|grep "install ok installed")
echo "Checking for $REQUIRED_PKG: $PKG_OK"
if [ "" = "$PKG_OK" ]; then
echo "No $REQUIRED_PKG. Setting up $REQUIRED_PKG."
#If this is uncommented then only packages that are missing will get prompted..
#sudo apt-get --yes install $REQUIRED_PKG
#if this is uncommented then if one package is missing then all missing packages are immediately installed..
sudo apt-get install $SYSTEM_DEPENDENCIES
break
fi
done
#------------------------------------------------------------------------------
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
cd "$DIR"
cd ..
./GroundTruthDumper --from dataset/CMU_Sample_05_01.bvh --selectJoints 0 23 hip eye.r eye.l abdomen chest neck head rshoulder relbow rhand lshoulder lelbow lhand rhip rknee rfoot lhip lknee lfoot toe1-2.r toe5-3.r toe1-2.l toe5-3.l --tuneIterations 130 100 130 0.01 5 30 20 > tuneIterations.dat
#set view 45,45; set view map; set yrange [9:90]; set zrange [30:90];
# set dgrid3d 25,25 qnorm 4;
#splot \"tuneIterations.dat\" using 1:3:2 with points pointsize 3 pointtype 7;
#HCD tuning iteration hyperparameter
GNUPLOT_CMD="set terminal png size 1000,800 font \"Helvetica,34\"; set output \"tuneIterations.png\"; set isosample 160; set pm3d at b; set palette defined (65 \"black\", 70 \"red\", 80 \"yellow\", 90 \"yellow\", 100 \"white\"); set view 30,45; set hidden3d; set xrange [1:25]; set yrange [9:90]; set zrange [30:90]; set style fill solid; set xlabel \"HCD Iterations\" rotate parallel; set ylabel \"Frames per second\" rotate parallel; set zlabel \"Mean average error in mm\" rotate parallel; set ztics 30; set title \"Mean average error in mm\"; set ytics 30; set multiplot; splot \"tuneIterations.dat\" using 1:3:2 with lines palette lw 2 title \" \"; splot \"tuneIterations.dat\" using 1:3:2 with points palette pointsize 1 pointtype 7 title \" \"; "
gnuplot -e "$GNUPLOT_CMD"
echo "Result of experiment is now ready @ tuneIterations.png"
timeout 10 gpicview tuneIterations.png
exit 0
+54
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@@ -0,0 +1,54 @@
#/bin/bash
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
cd "$DIR/../dependencies"
DEPENDENCIES_PATH=`pwd`
sudo apt-get install build-essential cmake git libgtk2.0-dev pkg-config ffmpeg libavcodec-dev libavformat-dev libavcodec-dev libavformat-dev libswscale-dev libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff5-dev libdc1394-22-dev libeigen3-dev libtheora-dev libvorbis-dev libxvidcore-dev libx264-dev sphinx-common libtbb-dev yasm libfaac-dev libopencore-amrnb-dev libopencore-amrwb-dev libopenexr-dev libgstreamer-plugins-base1.0-dev libavutil-dev libavfilter-dev libavresample-dev libpython3-all-dev python3-numpy python3-dev
#cd "$1"
echo "Will Install @ `pwd`"
#Want a different version?
#Check https://opencv.org/releases/ for versions and
#change the OPENCV_VERSION in the next line..
OPENCV_VERSION="3.2.0"
echo "Downloading"
wget http://ammar.gr/programs/opencv-$OPENCV_VERSION.zip
wget http://ammar.gr/programs/opencv_contrib-$OPENCV_VERSION.tar.gz
#wget https://codeload.github.com/opencv/opencv/zip/$OPENCV_VERSION -O opencv-$OPENCV_VERSION.zip
#wget https://codeload.github.com/opencv/opencv_contrib/zip/$OPENCV_VERSION -O opencv_contrib-$OPENCV_VERSION.tar.gz
echo "Extracting"
#tar xvzf opencv_contrib-$OPENCV_VERSION.tar.gz
unzip opencv_contrib-$OPENCV_VERSION.zip
unzip opencv-$OPENCV_VERSION.zip
echo "Building"
cd opencv-$OPENCV_VERSION
mkdir build
cd build
cmake -DOPENCV_ENABLE_NONFREE=ON -DOPENCV_EXTRA_MODULES_PATH=$DEPENDENCIES_PATH/opencv_contrib-$OPENCV_VERSION/modules ..
make -j5
echo "Do you want to install OpenCV to your system ? "
echo
echo -n " (Y/N)?"
read answer
if test "$answer" != "N" -a "$answer" != "n";
then
sudo make install
fi
cd "$DIR"
echo "Done"
exit 0
@@ -0,0 +1,32 @@
#!/bin/bash
#This script should be run after you have dumped a video to a directory using the dump_video.sh utility
#You should give a full path to this utility i.e. ./processDatasetWithOpenpose.sh "~/myDatasets/yourvideo.mp4-data/"
#and also dont forget to change the PATH_TO_OPENPOSE to the directory that has your openpose.bin!
PATH_TO_OPENPOSE="PLEASE/CHANGE/THIS/"
STARTDIR=`pwd`
#Switch to this directory
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
DATASET=""
if (( $#<1 ))
then
echo "Please provide arguments first argument is dataset "
exit 1
else
DATASET=$1
$PATH_TO_OPENPOSE/openpose.bin -number_people_max 1 --hand --face --write_json $DATASET -image_dir $DATASET $@
cd "$DIR"
echo "Went back to $DIR"
echo "Hopefully the path you have given is an absolute path.."
./convertBody25JSONToCSV -i $DATASET
exit 0
+47
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@@ -0,0 +1,47 @@
#!/bin/bash
FROMDATASET="$1"
X=0
# sudo apt-get install imagemagick
if (( $# != 1 )); then
echo "Please run giving the path to download and build"
echo "$0 \"DatasetNameSource\" "
exit 0
fi
TOTAL_FRAMES=100000
cd $FROMDATASET
echo "Spliting Dataset $FROMDATASET "
echo "Please wait .. "
for (( i=$X; i<=$TOTAL_FRAMES; i++ ))
do
XNUM=`printf %05u $i`
if [ -f "colorFrame_0_$XNUM.jpg" ]
then
width=$(identify -format "%w" "colorFrame_0_$XNUM.jpg")> /dev/null
height=$(identify -format "%h" "colorFrame_0_$XNUM.jpg")> /dev/null
halfWidth=$((width / 2))
echo "$width x $height -> 2x $halfWidth x $height"
#First crop second half ( before source file gets rewritten )
convert colorFrame_0_$XNUM.jpg -crop "$halfWidth"x$height+$halfWidth+0 colorFrame_1_$XNUM.jpg
convert colorFrame_0_$XNUM.jpg -crop "$halfWidth"x$height+0+0 colorFrame_0_$XNUM.jpg
else
break
fi
echo -n "."
done
echo "Passed TOTAL_FRAMES (!) this is a bug! :S"
cd ..
exit 0
@@ -0,0 +1,135 @@
#!/bin/bash
#Script last updated 25-03-2022
#Script that seems to be able to build bazel/tf2 on Ubuntu 20.04
#I really deeply dislike the bazel build system which is bloated and obfuscated for no reason, just Google "NIH syndrome"
#However Tensorflow2 is a great NN framework
# See this video "How To Make Package Managers Cry" -> https://www.youtube.com/watch?v=NSemlYagjIU#t=19m0s
echo "Check CUDA"
ls /usr/local/cuda/extras/CUPTI/lib64
ls /usr/local/cuda
ls /usr/local/cuda/lib64/ | grep libcudnn.so
nvcc -V
VERSION="2.8"
#Get number of bytes in RAM
RAM=`free | grep Mem | tr -s ' '| cut -f2 -d ' '`
BazelPleaseSlowDown="--local_resources 2048,.5,1.0"
if [ "$RAM" -gt "11286464" ]; then
echo "More than 12GB";
BazelPleaseSlowDown=" "
fi
if [ "$RAM" -gt "15297500" ]; then
echo "More than 16GB";
BazelPleaseSlowDown=" "
fi
if [ "$RAM" -gt "31861780" ]; then
echo "More than 32GB";
BazelPleaseSlowDown=" "
fi
#Tensorflow is a great Neural network library that unfortunately is coupled to the terrible Bazel build system
#This is a download and build script for Ubuntu 20.04, that should work building release 2.8
sudo apt-get install python3-dev python3-pip python3-venv python3-tk
pip3 install -U --user pip numpy wheel packaging
pip3 install -U --user keras_preprocessing --no-deps
cd ~/Documents
mkdir 3dParty
cd 3dParty
#wget https://github.com/bazelbuild/bazel/releases/download/4.2.1/bazel-4.2.1-installer-linux-x86_64.sh
#chmod +x bazel-4.2.1-installer-linux-x86_64.sh
#./bazel-4.2.1-installer-linux-x86_64.sh --user
#r2.8
mkdir -p "$HOME/.bazel/bin" && cd "$HOME/.bazel/bin" && curl -fLO https://releases.bazel.build/4.2.1/release/bazel-4.2.1-linux-x86_64 && chmod +x bazel-4.2.1-linux-x86_64
#Create shared directory
if [ -f ~/.bashrc ]
then
if cat ~/.bashrc | grep -q "BAZEL_CANCER"
then
echo "Bazel includes seem to be set-up.."
else
USER=`whoami`
echo "#BAZEL_CANCER" >> ~/.bashrc
echo "source $HOME/.bazel/bin/bazel-complete.bash" >> ~/.bashrc
echo "export PATH=\"\$PATH:\$HOME/bin\"" >> ~/.bashrc
source ~/.bashrc
fi
fi
if [ ! -d tensorflow ]
then
git clone https://github.com/tensorflow/tensorflow.git
fi
cd tensorflow
git pull
git checkout r$VERSION
#Make sure to check your target CPU and when asked used the correct -march= / -mtune=
# for example for an old intel i7 -march=nehalem is used..
#https://gcc.gnu.org/onlinedocs/gcc/x86-Options.html
echo "Answers to configure questions :"
echo "/usr/bin/python3"
echo "/usr/lib/python3/dist-packages"
echo "cuda Y"
echo "tensorrt Y"
echo "CUDA 11.2"
echo "CuDNN 8"
echo "TensorRT 8"
echo "/usr/local/cuda/,/usr/local/cuda/include/,/usr/local/cuda/bin/,/usr/local/cuda/lib64/,/usr/local/cuda/lib64/,/usr/local/tensorrt-8.2.3/,/usr/local/tensorrt-8.2.3/include/,/usr/local/tensorrt-8.2.3/lib/,"
echo "Compute capability 6.1 ( for GTX 1050 + cards )"
#Attempt to inform the configure script on how to find the CUDA stuff..
export CUDNN_INSTALL_PATH=/usr/local/cuda/,/usr/local/cuda/include/,/usr/local/cuda/bin/,/usr/local/cuda/lib64/,/usr/local/cuda/lib64/,/usr/local/tensorrt-8.2.3/,/usr/local/tensorrt-8.2.3/include/,/usr/local/tensorrt-8.2.3/lib/
./configure
bazel clean --expunge
#You should use CUDA 11.2 and cudnn-11.2-linux-x64-v8.1.1.33 and TensorRT 8.2.3
bazel build --config=opt --config=cuda --config=mkl --config=monolithic $BazelPleaseSlowDown //tensorflow/tools/pip_package:build_pip_package
./bazel-bin/tensorflow/tools/pip_package/build_pip_package ~/Documents/3dParty/
#To install
#pip3 --user install ~/Documents/3dParty/tensorflow-2.4.0-cp36-cp36m-linux_x86_64.whl
bazel build --config opt --config=cuda --config=monolithic //tensorflow/tools/lib_package:libtensorflow
cp bazel-bin/tensorflow/tools/lib_package/libtensorflow.tar.gz ~/Documents/3dParty/libtensorflow-r$VERSION.tar.gz
#Build tensorflow lite
#https://www.tensorflow.org/lite/guide/build_cmake
mkdir tflite_buld
cd tflite_buld/
cmake ../tensorflow/lite
cmake --build . -j
echo "Please visit ~/Documents/3dParty/ to collect your tensorflow python3 wheel, and C Library.."
echo "Will now use : python -c 'import tensorflow as tf;' to test your tensorflow"
python -c 'import tensorflow as tf;'
exit 0
@@ -0,0 +1,93 @@
#!/bin/bash
#Script source repository https://github.com/AmmarkoV/MyScripts/blob/master/Tensorflow/tensorflowBuild.sh
#Script last updated 23-06-2020
#Script that seems to be able to build bazel/tf2 on Ubuntu 20.04
#I really deeply dislike the bazel build system which is bloated and obfuscated for no reason, just Google "NIH syndrome"
#However Tensorflow2 is a great NN framework
# See this video "How To Make Package Managers Cry" -> https://www.youtube.com/watch?v=NSemlYagjIU#t=19m0s
#Get number of bytes in RAM
RAM=`free | grep Mem | tr -s ' '| cut -f2 -d ' '`
BazelPleaseSlowDown="--local_resources 2048,.5,1.0"
if [ "$RAM" -gt "11286464" ]; then
echo "More than 12GB";
BazelPleaseSlowDown=" "
fi
if [ "$RAM" -gt "15297500" ]; then
echo "More than 16GB";
BazelPleaseSlowDown=" "
fi
if [ "$RAM" -gt "31861780" ]; then
echo "More than 32GB";
BazelPleaseSlowDown=" "
fi
#Tensorflow is a great Neural network library that unfortunately is coupled to the terrible Bazel build system
#This is a download and build script for Ubuntu 18.04, that should work building release 1.15
sudo apt-get install python3-dev python3-pip python3-venv python3-tk
pip install -U --user pip six numpy wheel setuptools mock 'future>=0.17.1'
pip install -U --user keras_applications --no-deps
pip install -U --user keras_preprocessing --no-deps
cd ~/Documents
mkdir 3dParty
cd 3dParty
wget http://ammar.gr/mocapnet/bazel-0.24.1-installer-linux-x86_64-for-tensorflow-r1.15.sh
chmod +x bazel-0.24.1-installer-linux-x86_64-for-tensorflow-r1.15.sh
./bazel-0.24.1-installer-linux-x86_64-for-tensorflow-r1.15.sh --user
#Create shared directory
if [ -f ~/.bashrc ]
then
if cat ~/.bashrc | grep -q "BAZEL_CANCER"
then
echo "Bazel includes seem to be set-up.."
else
USER=`whoami`
echo "#BAZEL_CANCER" >> ~/.bashrc
echo "source ~/.bazel/bin/bazel-complete.bash" >> ~/.bashrc
echo "export PATH=\"\$PATH:\$HOME/bin\"" >> ~/.bashrc
source ~/.bashrc
fi
fi
if [ ! -d tensorflow ]
then
git clone https://github.com/tensorflow/tensorflow.git
fi
cd tensorflow
git pull
git checkout r1.15
./configure
bazel clean --expunge
#Flags for bazel if you have gcc<5.0
#--cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0"
#--noincompatible_do_not_split_linking_cmdline
bazel build --config=opt --config=cuda --config=mkl --config=monolithic $BazelPleaseSlowDown //tensorflow/tools/pip_package:build_pip_package
./bazel-bin/tensorflow/tools/pip_package/build_pip_package ~/Documents/3dParty/
bazel build --config opt --config=cuda --config=monolithic //tensorflow/tools/lib_package:libtensorflow
cp bazel-bin/tensorflow/tools/lib_package/libtensorflow.tar.gz ~/Documents/3dParty/libtensorflow-r1.15.tar.gz
echo "Please visit ~/Documents/3dParty/ to collect your tensorflow python3 wheel, and C Library.."
exit 0
@@ -0,0 +1,21 @@
project( GroundTruthDumper )
cmake_minimum_required( VERSION 2.8.13 )
set(CMAKE_MODULE_PATH ${CMAKE_CURRENT_SOURCE_DIR}/../cmake/modules ${CMAKE_MODULE_PATH})
add_executable(
GroundTruthDumper
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Applications/BVHTester/main.c
${CMAKE_SOURCE_DIR}/dependencies/RGBDAcquisition/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/TrajectoryParser/InputParser_C.c
${BVH_SOURCE}
)
target_link_libraries(GroundTruthDumper rt m pthread )
#add_dependencies(GroundTruthDumper OGLRendererSandbox)
set_target_properties(GroundTruthDumper PROPERTIES
ARCHIVE_OUTPUT_DIRECTORY "${CMAKE_SOURCE_DIR}"
LIBRARY_OUTPUT_DIRECTORY "${CMAKE_SOURCE_DIR}"
RUNTIME_OUTPUT_DIRECTORY "${CMAKE_SOURCE_DIR}"
)
@@ -0,0 +1,6 @@
To simplify package maintenance the GroundTruthGenerator uses the code from the BVHTester of RGBDAcquisition
If you want to browse the code, i.e. to find about different command line options this is the [main.c](https://github.com/AmmarkoV/RGBDAcquisition/blob/master/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Applications/BVHTester/main.c)
All the implementation files to parse BVH files are part of the MotionCaptureLoader module of the RGDAcquisition OGL Renderer Sandbox. You can [find the bvh code here](https://github.com/AmmarkoV/RGBDAcquisition/tree/master/opengl_acquisition_shared_library/opengl_depth_and_color_renderer/src/Library/MotionCaptureLoader)
Sorry for having different stuff in different places but it really minimizes the effort needed to relase the code and it also reduces the number of possible bugs from keeping the same code in sync in different machines etc.
@@ -0,0 +1,19 @@
project( helloWorld )
cmake_minimum_required(VERSION 3.5)
#-----------------------------------------------
# This is the converter utilities..
#-----------------------------------------------
project( helloWorld )
add_executable(helloWorld main.cpp)
target_link_libraries(helloWorld rt dl m )
set_target_properties(helloWorld PROPERTIES DEBUG_POSTFIX "D")
set_target_properties(helloWorld PROPERTIES
ARCHIVE_OUTPUT_DIRECTORY "${CMAKE_SOURCE_DIR}"
LIBRARY_OUTPUT_DIRECTORY "${CMAKE_SOURCE_DIR}"
RUNTIME_OUTPUT_DIRECTORY "${CMAKE_SOURCE_DIR}"
)

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