QtCreator下用openpose搭建自己的QT工程

最近做东西需要用到openpose，需要用到QT搭建自己的显示界面，而且用海康摄像机的SDK来获取图像

编译环境Ubuntu14.04 x64 QT5.8

1 首先按照openpose Git上的教程安装编译，编译过程不再赘述，

2 编译完成后 make distribute ,会生成distribute文件夹，将里面的/lib/文件夹下的库文件拷到工程目录，然后 将/3rdparty/caffe/distribute/lib/文件夹下的库文件拷到工程目录

3 修改工程的.pro文件，如下：红颜色的是要根据自己的实际情况修改的，这样可以利用openpose的代码来实现自己想实现的功能。

QT       += core gui

greaterThan(QT_MAJOR_VERSION, 4): QT += widgets

TARGET = pose_test
TEMPLATE = app

# The following define makes your compiler emit warnings if you use
# any feature of Qt which as been marked as deprecated (the exact warnings
# depend on your compiler). Please consult the documentation of the
# deprecated API in order to know how to port your code away from it.
DEFINES += QT_DEPRECATED_WARNINGS

# You can also make your code fail to compile if you use deprecated APIs.
# In order to do so, uncomment the following line.
# You can also select to disable deprecated APIs only up to a certain version of Qt.
#DEFINES += QT_DISABLE_DEPRECATED_BEFORE=0x060000    # disables all the APIs deprecated before Qt 6.0.0

SOURCES += main.cpp\
mainwindow.cpp

HEADERS  += mainwindow.h \
openpose_test.h

FORMS    += mainwindow.ui

#增加头文件包含路径

INCLUDEPATH += /home/xxx/opencv-2.4.13/include/opencv \
INCLUDEPATH += /home/xxx/opencv-2.4.13/include/opencv2 \
INCLUDEPATH += /home/xxx/dlib \
INCLUDEPATH += /usr/include \
INCLUDEPATH += /usr/local/include \
INCLUDEPATH += /usr/local/cuda-8.0/include \
INCLUDEPATH += /home/xxx/openpose/include \
INCLUDEPATH += /home/xxx/openpose/3rdparty/caffe/include \

##增加库文件包含路径

LIBS += -L/usr/lib/
LIBS += -L/usr/local/lib/
LIBS += -L/usr/lib/x86_64-linux-gnu
LIBS += -L/usr/local/cuda-8.0/lib64/
LIBS += -L/usr/local/cuda/lib/
LIBS += -L/usr/lib/nvidia-375/

LIBS += -lcurand -lcublas -lcublas_device -lcudnn -lcudart_static

LIBS += -L/home/neu-lu/opencv-2.4.13\build\lib\
-lopencv_core \
-lopencv_imgproc \
-lopencv_highgui \
-lopencv_ml \
-lopencv_video \
-lopencv_features2d \
-lopencv_calib3d \
-lopencv_objdetect \
-lopencv_contrib \
-lopencv_legacy \
-lopencv_flann \

LIBS += -lGLU -lGL -lglut
LIBS += -lcudnn -lglog -lgflags -lboost_system -lboost_filesystem -lm -lboost_thread
LIBS += -pthread -fPIC -std=c++11 -fopenmp

LIBS+=-L/home/neu-lu/qt_project/pose_test \
-lopenpose -lcaffe

4 程序示例：本程序是利用自己的方法读取图片转化成cv::Mat格式，然后利用openpose的模型获取人体姿态，并显示，比较简单，为了方便起见，直接用opencv读取视频，进行处理，不用openpose封装好的图片读取接口。程序如下：

void MainWindow::on_pushButton_clicked()
{
//openPoseDemo();
//openPoseTutorialPose1();
op::log("OpenPose Library Tutorial - Example 1.", op::Priority::High);
// ------------------------- INITIALIZATION -------------------------
// Step 1 - Set logging level
// - 0 will output all the logging messages
// - 255 will output nothing
op::check(0 <= FLAGS_logging_level && FLAGS_logging_level <= 255, "Wrong logging_level value.",
__LINE__, __FUNCTION__, __FILE__);
op::ConfigureLog::setPriorityThreshold((op::Priority)FLAGS_logging_level);
op::log("", op::Priority::Low, __LINE__, __FUNCTION__, __FILE__);
// Step 2 - Read Google flags (user defined configuration)
// outputSize
const auto outputSize = op::flagsToPoint(FLAGS_output_resolution, "-1x-1");
// netInputSize
const auto netInputSize = op::flagsToPoint(FLAGS_net_resolution, "-1x368");
// poseModel
const auto poseModel = op::flagsToPoseModel(FLAGS_model_pose);
// Check no contradictory flags enabled
if (FLAGS_alpha_pose < 0. || FLAGS_alpha_pose > 1.)
op::error("Alpha value for blending must be in the range [0,1].", __LINE__, __FUNCTION__, __FILE__);
if (FLAGS_scale_gap <= 0. && FLAGS_scale_number > 1)
op::error("Incompatible flag configuration: scale_gap must be greater than 0 or scale_number = 1.",
__LINE__, __FUNCTION__, __FILE__);
// Enabling Google Logging
const bool enableGoogleLogging = true;
// Logging
op::log("", op::Priority::Low, __LINE__, __FUNCTION__, __FILE__);
// Step 3 - Initialize all required classes
op::ScaleAndSizeExtractor scaleAndSizeExtractor(netInputSize, outputSize, FLAGS_scale_number, FLAGS_scale_gap);
op::CvMatToOpInput cvMatToOpInput;
op::CvMatToOpOutput cvMatToOpOutput;
op::PoseExtractorCaffe poseExtractorCaffe{poseModel, FLAGS_model_folder,
FLAGS_num_gpu_start, {}, op::ScaleMode::ZeroToOne, enableGoogleLogging};
op::PoseCpuRenderer poseRenderer{poseModel, (float)FLAGS_render_threshold, !FLAGS_disable_blending,
(float)FLAGS_alpha_pose};
op::OpOutputToCvMat opOutputToCvMat;
op::FrameDisplayer frameDisplayer{"OpenPose Tutorial - Example 1", outputSize};
// Step 4 - Initialize resources on desired thread (in this case single thread, i.e. we init resources here)
poseExtractorCaffe.initializationOnThread();
poseRenderer.initializationOnThread();
//cv::Mat inputImage = cv::imread("/home/neu-lu/openpose/examples/media/COCO_val2014_000000000257.jpg");
//cv::imshow("test",inputImage);
cv::VideoCapture cap;
cap.open("video.avi");
cv::Mat frame;
while(cap.isOpened())
{
cap>>frame;
cv::Mat inputImage = frame;
if(inputImage.empty())
op::error("Could not open or find the image: ");
//op::error("Could not open or find the image: " + FLAGS_image_path, __LINE__, __FUNCTION__, __FILE__);
const op::Point<int> imageSize{inputImage.cols, inputImage.rows};
// Step 2 - Get desired scale sizes
std::vector<double> scaleInputToNetInputs;
std::vector<op::Point<int>> netInputSizes;
double scaleInputToOutput;
op::Point<int> outputResolution;
std::tie(scaleInputToNetInputs, netInputSizes, scaleInputToOutput, outputResolution)
= scaleAndSizeExtractor.extract(imageSize);
// Step 3 - Format input image to OpenPose input and output formats
const auto netInputArray = cvMatToOpInput.createArray(inputImage, scaleInputToNetInputs, netInputSizes);
auto outputArray = cvMatToOpOutput.createArray(inputImage, scaleInputToOutput, outputResolution);
// Step 4 - Estimate poseKeypoints
poseExtractorCaffe.forwardPass(netInputArray, imageSize, scaleInputToNetInputs);
const auto poseKeypoints = poseExtractorCaffe.getPoseKeypoints();
// Step 5 - Render poseKeypoints
poseRenderer.renderPose(outputArray, poseKeypoints, scaleInputToOutput);
// Step 6 - OpenPose output format to cv::Mat
auto outputImage = opOutputToCvMat.formatToCvMat(outputArray);

// ------------------------- SHOWING RESULT AND CLOSING -------------------------
// Step 1 - Show results
//frameDisplayer.displayFrame(outputImage, 0);
cv::imshow("test",outputImage);// + cv::waitKey(0)
// Step 2 - Logging information message

//cv::imshow("test",frame);
cv::waitKey(1);
}

}