Giter VIP home page Giter VIP logo

apriltag-gpu's People

Contributors

wykvictor avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar  avatar

apriltag-gpu's Issues

GPU not used

Hello,

After using the original AprilTag library I tried switching to this one, as the computation time was to big.
I installed OpenCV 3.1 with Cuda support, as well as Cuda 8.0. I am running Ubuntu 16.04 and this seems to be the only version available. The Cuda installation seems to work, according to the Cuda samples device query, see below.
The Issue is, that the GPU doesn't seem to be used. Wenn running it, it detects the AprilTag, but only one CPU core is utilized and the GPU is pretty much idle.
The computation per image takes around 350ms, which is similar to the original AprilTag library.
I implemented it in ROS and have therefore added a few things to the CMakeList.txt file. My usage of it is based on the demo code provided in the package.
I also included the modified CMakeList file, if there is an error there.
Is there maybe an option I did not consider or something else I might have gotten wrong?

Thank you for the help and if any further information is needed please let me know.

deviceQuery output:

/bin/x86_64/linux/release/deviceQuery Starting...

 CUDA Device Query (Runtime API) version (CUDART static linking)

Detected 1 CUDA Capable device(s)

Device 0: "GeForce GTX 770"
  CUDA Driver Version / Runtime Version          8.0 / 8.0
  CUDA Capability Major/Minor version number:    3.0
  Total amount of global memory:                 1999 MBytes (2095906816 bytes)
  ( 8) Multiprocessors, (192) CUDA Cores/MP:     1536 CUDA Cores
  GPU Max Clock rate:                            1202 MHz (1.20 GHz)
  Memory Clock rate:                             3505 Mhz
  Memory Bus Width:                              256-bit
  L2 Cache Size:                                 524288 bytes
  Maximum Texture Dimension Size (x,y,z)         1D=(65536), 2D=(65536, 65536), 3D=(4096, 4096, 4096)
  Maximum Layered 1D Texture Size, (num) layers  1D=(16384), 2048 layers
  Maximum Layered 2D Texture Size, (num) layers  2D=(16384, 16384), 2048 layers
  Total amount of constant memory:               65536 bytes
  Total amount of shared memory per block:       49152 bytes
  Total number of registers available per block: 65536
  Warp size:                                     32
  Maximum number of threads per multiprocessor:  2048
  Maximum number of threads per block:           1024
  Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
  Max dimension size of a grid size    (x,y,z): (2147483647, 65535, 65535)
  Maximum memory pitch:                          2147483647 bytes
  Texture alignment:                             512 bytes
  Concurrent copy and kernel execution:          Yes with 1 copy engine(s)
  Run time limit on kernels:                     Yes
  Integrated GPU sharing Host Memory:            No
  Support host page-locked memory mapping:       Yes
  Alignment requirement for Surfaces:            Yes
  Device has ECC support:                        Disabled
  Device supports Unified Addressing (UVA):      Yes
  Device PCI Domain ID / Bus ID / location ID:   0 / 1 / 0
  Compute Mode:
     < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >

deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 8.0, CUDA Runtime Version = 8.0, NumDevs = 1, Device0 = GeForce GTX 770
Result = PASS

CMakeList.txt file:

cmake_minimum_required(VERSION 2.8.3)
project(apriltag_gpu)

add_definitions(-std=c++14 -I /usr/include/eigen3/ -I /usr/local/cuda-8.0/include/)
find_package(catkin REQUIRED)

option(USE_PROFILE "Enable Profile codes, default to true" 1)
option(USE_CUDA "Use CUDA, default to true" 1)
option(USE_OPENMP "Use OpenMP, default to true" 1)

if (USE_PROFILE)
  add_definitions(-DPROFILE)
endif()

set(CUDA_TOOLKIT_ROOT_DIR /usr/local/cuda-8.0/)
find_package(CUDA REQUIRED)
set(CUDA_NVCC_FLAGS "${CUDA_NVCC_FLAGS} -Xcompiler=\"/FS\" --gpu-architecture=compute_30 --gpu-code=compute_30,sm_30")
set(CUDA_NVCC_FLAGS_RELEASE "${CUDA_NVCC_FLAGS_RELEASE} -O3")
add_definitions(-DHAVE_CUDA)  # used in src code to control workflow
set(CUDA_ATTACH_VS_BUILD_RULE_TO_CUDA_FILE OFF)

set(OpenCV_DIR /usr/local/share/OpenCV/)
find_package(OpenCV REQUIRED)
include_directories(${OpenCV_INCLUDE_DIRS})
set(DEPENDENCIES ${OpenCV_LIBS})
link_directories(${OpenCV_LIB_DIR})  # we can put some libs in it for linking

find_package(OpenMP REQUIRED)
include(ProcessorCount)
ProcessorCount(N)
if(NOT N EQUAL 0)
	MATH(EXPR N "${N}/2")
else()
	set(N 2)
endif()
MESSAGE(STATUS "Using OpenMP with ${N} threads")
add_definitions(-DHAVE_OPENMP=${N})
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${OpenMP_CXX_FLAGS}")
message("CMAKE_CXX_FLAGS in OpenMP: ${CMAKE_CXX_FLAGS}")

if (APPLE OR UNIX)
  add_compile_options(-std=c++14)
  set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wall -g -Wsign-compare -frounding-math -fPIC")
else ()
  set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /EHsc /Zi")
  set(CMAKE_CXX_FLAGS_RELEASE "/Gs ${CMAKE_CXX_FLAGS_RELEASE}")
  set(CMAKE_EXE_LINKER_FLAGS_RELEASE "${CMAKE_EXE_LINKER_FLAGS_RELEASE} /DEBUG")
  set(CMAKE_SHARED_LINKER_FLAGS_RELEASE "${CMAKE_SHARED_LINKER_FLAGS_RELEASE} /DEBUG")
endif()

if (MSVC)
  add_subdirectory(windows)
  include_directories(windows)
  set(DEPENDENCIES ${DEPENDENCIES} windows_port)
  set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /wd4819")  # skip the unicode warnings
endif()

catkin_package(
  INCLUDE_DIRS include
  # LIBRARIES 
  CATKIN_DEPENDS
	DEPENDS
	)

include_directories(
	SYSTEM
  include
  ${catkin_INCLUDE_DIRS}
	${OpenCV_INCLUDE_DIRS}
	${Eigen_INCLUDE_DIRS}
)

add_subdirectory(src)

set(${PROJECT_NAME}_SOURCES
	src/Edge.cc
	src/FloatImage.cc
	src/Gaussian.cc
	src/GLine2D.cc
	src/GLineSegment2D.cc
	src/GrayModel.cc
	src/Homography33.cc
	src/MathUtil.cc
	src/Quad.cc
	src/Segment.cc
	src/TagDetection.cc
	src/TagDetector.cc
	src/TagFamily.cc
	src/UnionFindSimple.cc
)

add_library(${PROJECT_NAME}_lib
  ${${PROJECT_NAME}_SOURCES}
)

target_link_libraries(
	${PROJECT_NAME}_lib 
	${catkin_LIBRARIES} 
	${OpenCV_LIBRARIES} 
	)

add_executable(demo src/main/apriltags_demo.cpp)
target_link_libraries(demo ${catkin_LIBRARIES} ${PROJECT_NAME}_lib)
add_dependencies(demo ${${PROJECT_NAME}_EXPORTED_TARGETS} ${catkin_EXPORTED_TARGETS})

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.