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// ------------------------- OpenPose Library Tutorial - Wrapper - Example 2 - Synchronous -------------------------
// Synchronous mode: ideal for performance. The user can add his own frames producer / post-processor / consumer to the OpenPose wrapper or use the
// default ones.
// This example shows the user how to use the OpenPose wrapper class:
// 1. User reads images
// 2. Extract and render keypoint / heatmap / PAF of that image
// 3. Save the results on disk
// 4. User displays the rendered pose
// Everything in a multi-thread scenario
// In addition to the previous OpenPose modules, we also need to use:
// 1. `core` module:
// For the Array<float> class that the `pose` module needs
// For the Datum struct that the `thread` module sends between the queues
// 2. `utilities` module: for the error & logging functions, i.e. op::error & op::log respectively
// This file should only be used for the user to take specific examples.
// C++ std library dependencies
#include <chrono> // `std::chrono::` functions and classes, e.g. std::chrono::milliseconds
#include <thread> // std::this_thread
// Other 3rdparty dependencies
// GFlags: DEFINE_bool, _int32, _int64, _uint64, _double, _string
#include <gflags/gflags.h>
// Allow Google Flags in Ubuntu 14
#ifndef GFLAGS_GFLAGS_H_
namespace gflags = google;
#endif
// OpenPose dependencies
#include <openpose/headers.hpp>
// See all the available parameter options withe the `--help` flag. E.g. `build/examples/openpose/openpose.bin --help`
// Note: This command will show you flags for other unnecessary 3rdparty files. Check only the flags for the OpenPose
// executable. E.g. for `openpose.bin`, look for `Flags from examples/openpose/openpose.cpp:`.
// Debugging
DEFINE_int32(logging_level, 3, "The logging level. Integer in the range [0, 255]. 0 will output any log() message, while"
" 255 will not output any. Current OpenPose library messages are in the range 0-4: 1 for"
" low priority messages and 4 for important ones.");
// Producer
DEFINE_string(image_dir, "examples/media/", "Process a directory of images. Read all standard formats (jpg, png, bmp, etc.).");
// OpenPose
DEFINE_string(model_folder, "models/", "Folder path (absolute or relative) where the models (pose, face, ...) are located.");
DEFINE_string(output_resolution, "-1x-1", "The image resolution (display and output). Use \"-1x-1\" to force the program to use the"
" input image resolution.");
DEFINE_int32(num_gpu, -1, "The number of GPU devices to use. If negative, it will use all the available GPUs in your"
" machine.");
DEFINE_int32(num_gpu_start, 0, "GPU device start number.");
DEFINE_int32(keypoint_scale, 0, "Scaling of the (x,y) coordinates of the final pose data array, i.e. the scale of the (x,y)"
" coordinates that will be saved with the `write_keypoint` & `write_keypoint_json` flags."
" Select `0` to scale it to the original source resolution, `1`to scale it to the net output"
" size (set with `net_resolution`), `2` to scale it to the final output size (set with"
" `resolution`), `3` to scale it in the range [0,1], and 4 for range [-1,1]. Non related"
" with `scale_number` and `scale_gap`.");
// OpenPose Body Pose
DEFINE_bool(body_disable, false, "Disable body keypoint detection. Option only possible for faster (but less accurate) face"
" keypoint detection.");
DEFINE_string(model_pose, "COCO", "Model to be used. E.g. `COCO` (18 keypoints), `MPI` (15 keypoints, ~10% faster), "
"`MPI_4_layers` (15 keypoints, even faster but less accurate).");
DEFINE_string(net_resolution, "-1x368", "Multiples of 16. If it is increased, the accuracy potentially increases. If it is"
" decreased, the speed increases. For maximum speed-accuracy balance, it should keep the"
" closest aspect ratio possible to the images or videos to be processed. Using `-1` in"
" any of the dimensions, OP will choose the optimal aspect ratio depending on the user's"
" input value. E.g. the default `-1x368` is equivalent to `656x368` in 16:9 resolutions,"
" e.g. full HD (1980x1080) and HD (1280x720) resolutions.");
DEFINE_int32(scale_number, 1, "Number of scales to average.");
DEFINE_double(scale_gap, 0.3, "Scale gap between scales. No effect unless scale_number > 1. Initial scale is always 1."
" If you want to change the initial scale, you actually want to multiply the"
" `net_resolution` by your desired initial scale.");
DEFINE_bool(heatmaps_add_parts, false, "If true, it will add the body part heatmaps to the final op::Datum::poseHeatMaps array,"
" and analogously face & hand heatmaps to op::Datum::faceHeatMaps & op::Datum::handHeatMaps"
" (program speed will decrease). Not required for our library, enable it only if you intend"
" to process this information later. If more than one `add_heatmaps_X` flag is enabled, it"
" will place then in sequential memory order: body parts + bkg + PAFs. It will follow the"
" order on POSE_BODY_PART_MAPPING in `include/openpose/pose/poseParameters.hpp`.");
DEFINE_bool(heatmaps_add_bkg, false, "Same functionality as `add_heatmaps_parts`, but adding the heatmap corresponding to"
" background.");
DEFINE_bool(heatmaps_add_PAFs, false, "Same functionality as `add_heatmaps_parts`, but adding the PAFs.");
DEFINE_int32(heatmaps_scale, 2, "Set 0 to scale op::Datum::poseHeatMaps in the range [0,1], 1 for [-1,1]; and 2 for integer"
" rounded [0,255].");
// OpenPose Face
DEFINE_bool(face, false, "Enables face keypoint detection. It will share some parameters from the body pose, e.g."
" `model_folder`. Note that this will considerable slow down the performance and increse"
" the required GPU memory. In addition, the greater number of people on the image, the"
" slower OpenPose will be.");
DEFINE_string(face_net_resolution, "368x368", "Multiples of 16 and squared. Analogous to `net_resolution` but applied to the face keypoint"
" detector. 320x320 usually works fine while giving a substantial speed up when multiple"
" faces on the image.");
// OpenPose Hand
DEFINE_bool(hand, false, "Enables hand keypoint detection. It will share some parameters from the body pose, e.g."
" `model_folder`. Analogously to `--face`, it will also slow down the performance, increase"
" the required GPU memory and its speed depends on the number of people.");
DEFINE_string(hand_net_resolution, "368x368", "Multiples of 16 and squared. Analogous to `net_resolution` but applied to the hand keypoint"
" detector.");
DEFINE_int32(hand_scale_number, 1, "Analogous to `scale_number` but applied to the hand keypoint detector. Our best results"
" were found with `hand_scale_number` = 6 and `hand_scale_range` = 0.4");
DEFINE_double(hand_scale_range, 0.4, "Analogous purpose than `scale_gap` but applied to the hand keypoint detector. Total range"
" between smallest and biggest scale. The scales will be centered in ratio 1. E.g. if"
" scaleRange = 0.4 and scalesNumber = 2, then there will be 2 scales, 0.8 and 1.2.");
DEFINE_bool(hand_tracking, false, "Adding hand tracking might improve hand keypoints detection for webcam (if the frame rate"
" is high enough, i.e. >7 FPS per GPU) and video. This is not person ID tracking, it"
" simply looks for hands in positions at which hands were located in previous frames, but"
" it does not guarantee the same person ID among frames");
// OpenPose Rendering
DEFINE_int32(part_to_show, 0, "Prediction channel to visualize (default: 0). 0 for all the body parts, 1-18 for each body"
" part heat map, 19 for the background heat map, 20 for all the body part heat maps"
" together, 21 for all the PAFs, 22-40 for each body part pair PAF");
DEFINE_bool(disable_blending, false, "If enabled, it will render the results (keypoint skeletons or heatmaps) on a black"
" background, instead of being rendered into the original image. Related: `part_to_show`,"
" `alpha_pose`, and `alpha_pose`.");
// OpenPose Rendering Pose
DEFINE_double(render_threshold, 0.05, "Only estimated keypoints whose score confidences are higher than this threshold will be"
" rendered. Generally, a high threshold (> 0.5) will only render very clear body parts;"
" while small thresholds (~0.1) will also output guessed and occluded keypoints, but also"
" more false positives (i.e. wrong detections).");
DEFINE_int32(render_pose, 2, "Set to 0 for no rendering, 1 for CPU rendering (slightly faster), and 2 for GPU rendering"
" (slower but greater functionality, e.g. `alpha_X` flags). If rendering is enabled, it will"
" render both `outputData` and `cvOutputData` with the original image and desired body part"
" to be shown (i.e. keypoints, heat maps or PAFs).");
DEFINE_double(alpha_pose, 0.6, "Blending factor (range 0-1) for the body part rendering. 1 will show it completely, 0 will"
" hide it. Only valid for GPU rendering.");
DEFINE_double(alpha_heatmap, 0.7, "Blending factor (range 0-1) between heatmap and original frame. 1 will only show the"
" heatmap, 0 will only show the frame. Only valid for GPU rendering.");
// OpenPose Rendering Face
DEFINE_double(face_render_threshold, 0.4, "Analogous to `render_threshold`, but applied to the face keypoints.");
DEFINE_int32(face_render, -1, "Analogous to `render_pose` but applied to the face. Extra option: -1 to use the same"
" configuration that `render_pose` is using.");
DEFINE_double(face_alpha_pose, 0.6, "Analogous to `alpha_pose` but applied to face.");
DEFINE_double(face_alpha_heatmap, 0.7, "Analogous to `alpha_heatmap` but applied to face.");
// OpenPose Rendering Hand
DEFINE_double(hand_render_threshold, 0.2, "Analogous to `render_threshold`, but applied to the hand keypoints.");
DEFINE_int32(hand_render, -1, "Analogous to `render_pose` but applied to the hand. Extra option: -1 to use the same"
" configuration that `render_pose` is using.");
DEFINE_double(hand_alpha_pose, 0.6, "Analogous to `alpha_pose` but applied to hand.");
DEFINE_double(hand_alpha_heatmap, 0.7, "Analogous to `alpha_heatmap` but applied to hand.");
// Result Saving
DEFINE_string(write_images, "", "Directory to write rendered frames in `write_images_format` image format.");
DEFINE_string(write_images_format, "png", "File extension and format for `write_images`, e.g. png, jpg or bmp. Check the OpenCV"
" function cv::imwrite for all compatible extensions.");
DEFINE_string(write_video, "", "Full file path to write rendered frames in motion JPEG video format. It might fail if the"
" final path does not finish in `.avi`. It internally uses cv::VideoWriter.");
DEFINE_string(write_keypoint, "", "Directory to write the people body pose keypoint data. Set format with `write_keypoint_format`.");
DEFINE_string(write_keypoint_format, "yml", "File extension and format for `write_keypoint`: json, xml, yaml & yml. Json not available"
" for OpenCV < 3.0, use `write_keypoint_json` instead.");
DEFINE_string(write_keypoint_json, "", "Directory to write people pose data in *.json format, compatible with any OpenCV version.");
DEFINE_string(write_coco_json, "", "Full file path to write people pose data with *.json COCO validation format.");
DEFINE_string(write_heatmaps, "", "Directory to write body pose heatmaps in *.png format. At least 1 `add_heatmaps_X` flag"
" must be enabled.");
DEFINE_string(write_heatmaps_format, "png", "File extension and format for `write_heatmaps`, analogous to `write_images_format`."
" Recommended `png` or any compressed and lossless format.");
// If the user needs his own variables, he can inherit the op::Datum struct and add them
// UserDatum can be directly used by the OpenPose wrapper because it inherits from op::Datum, just define
// Wrapper<UserDatum> instead of Wrapper<op::Datum>
struct UserDatum : public op::Datum
{
bool boolThatUserNeedsForSomeReason;
UserDatum(const bool boolThatUserNeedsForSomeReason_ = false) :
boolThatUserNeedsForSomeReason{boolThatUserNeedsForSomeReason_}
{}
};
// The W-classes can be implemented either as a template or as simple classes given
// that the user usually knows which kind of data he will move between the queues,
// in this case we assume a std::shared_ptr of a std::vector of UserDatum
// This worker will just read and return all the jpg files in a directory
class WUserInput : public op::WorkerProducer<std::shared_ptr<std::vector<UserDatum>>>
{
public:
WUserInput(const std::string& directoryPath) :
mImageFiles{op::getFilesOnDirectory(directoryPath, "jpg")},
// If we want "jpg" + "png" images
// mImageFiles{op::getFilesOnDirectory(directoryPath, std::vector<std::string>{"jpg", "png"})},
mCounter{0}
{
if (mImageFiles.empty())
op::error("No images found on: " + directoryPath, __LINE__, __FUNCTION__, __FILE__);
}
void initializationOnThread() {}
std::shared_ptr<std::vector<UserDatum>> workProducer()
{
try
{
// Close program when empty frame
if (mImageFiles.size() <= mCounter)
{
op::log("Last frame read and added to queue. Closing program after it is processed.",
op::Priority::High);
// This funtion stops this worker, which will eventually stop the whole thread system once all the
// frames have been processed
this->stop();
return nullptr;
}
else
{
// Create new datum
auto datumsPtr = std::make_shared<std::vector<UserDatum>>();
datumsPtr->emplace_back();
auto& datum = datumsPtr->at(0);
// Fill datum
datum.cvInputData = cv::imread(mImageFiles.at(mCounter++));
// If empty frame -> return nullptr
if (datum.cvInputData.empty())
{
op::log("Empty frame detected on path: " + mImageFiles.at(mCounter-1) + ". Closing program.",
op::Priority::High);
this->stop();
datumsPtr = nullptr;
}
return datumsPtr;
}
}
catch (const std::exception& e)
{
op::log("Some kind of unexpected error happened.");
this->stop();
op::error(e.what(), __LINE__, __FUNCTION__, __FILE__);
return nullptr;
}
}
private:
const std::vector<std::string> mImageFiles;
unsigned long long mCounter;
};
// This worker will just invert the image
class WUserPostProcessing : public op::Worker<std::shared_ptr<std::vector<UserDatum>>>
{
public:
WUserPostProcessing()
{
// User's constructor here
}
void initializationOnThread() {}
void work(std::shared_ptr<std::vector<UserDatum>>& datumsPtr)
{
// User's post-processing (after OpenPose processing & before OpenPose outputs) here
// datum.cvOutputData: rendered frame with pose or heatmaps
// datum.poseKeypoints: Array<float> with the estimated pose
try
{
if (datumsPtr != nullptr && !datumsPtr->empty())
for (auto& datum : *datumsPtr)
cv::bitwise_not(datum.cvOutputData, datum.cvOutputData);
}
catch (const std::exception& e)
{
op::log("Some kind of unexpected error happened.");
this->stop();
op::error(e.what(), __LINE__, __FUNCTION__, __FILE__);
}
}
};
// This worker will just read and return all the jpg files in a directory
class WUserOutput : public op::WorkerConsumer<std::shared_ptr<std::vector<UserDatum>>>
{
public:
void initializationOnThread() {}
void workConsumer(const std::shared_ptr<std::vector<UserDatum>>& datumsPtr)
{
try
{
// User's displaying/saving/other processing here
// datum.cvOutputData: rendered frame with pose or heatmaps
// datum.poseKeypoints: Array<float> with the estimated pose
if (datumsPtr != nullptr && !datumsPtr->empty())
{
// Show in command line the resulting pose keypoints for body, face and hands
op::log("\nKeypoints:");
// Accesing each element of the keypoints
const auto& poseKeypoints = datumsPtr->at(0).poseKeypoints;
op::log("Person pose keypoints:");
for (auto person = 0 ; person < poseKeypoints.getSize(0) ; person++)
{
op::log("Person " + std::to_string(person) + " (x, y, score):");
for (auto bodyPart = 0 ; bodyPart < poseKeypoints.getSize(1) ; bodyPart++)
{
std::string valueToPrint;
for (auto xyscore = 0 ; xyscore < poseKeypoints.getSize(2) ; xyscore++)
{
valueToPrint += std::to_string( poseKeypoints[{person, bodyPart, xyscore}] ) + " ";
}
op::log(valueToPrint);
}
}
op::log(" ");
// Alternative: just getting std::string equivalent
op::log("Face keypoints: " + datumsPtr->at(0).faceKeypoints.toString());
op::log("Left hand keypoints: " + datumsPtr->at(0).handKeypoints[0].toString());
op::log("Right hand keypoints: " + datumsPtr->at(0).handKeypoints[1].toString());
// Heatmaps
const auto& poseHeatMaps = datumsPtr->at(0).poseHeatMaps;
if (!poseHeatMaps.empty())
{
op::log("Pose heatmaps size: [" + std::to_string(poseHeatMaps.getSize(0)) + ", "
+ std::to_string(poseHeatMaps.getSize(1)) + ", "
+ std::to_string(poseHeatMaps.getSize(2)) + "]");
const auto& faceHeatMaps = datumsPtr->at(0).faceHeatMaps;
op::log("Face heatmaps size: [" + std::to_string(faceHeatMaps.getSize(0)) + ", "
+ std::to_string(faceHeatMaps.getSize(1)) + ", "
+ std::to_string(faceHeatMaps.getSize(2)) + ", "
+ std::to_string(faceHeatMaps.getSize(3)) + "]");
const auto& handHeatMaps = datumsPtr->at(0).handHeatMaps;
op::log("Left hand heatmaps size: [" + std::to_string(handHeatMaps[0].getSize(0)) + ", "
+ std::to_string(handHeatMaps[0].getSize(1)) + ", "
+ std::to_string(handHeatMaps[0].getSize(2)) + ", "
+ std::to_string(handHeatMaps[0].getSize(3)) + "]");
op::log("Right hand heatmaps size: [" + std::to_string(handHeatMaps[1].getSize(0)) + ", "
+ std::to_string(handHeatMaps[1].getSize(1)) + ", "
+ std::to_string(handHeatMaps[1].getSize(2)) + ", "
+ std::to_string(handHeatMaps[1].getSize(3)) + "]");
}
// Display rendered output image
cv::imshow("User worker GUI", datumsPtr->at(0).cvOutputData);
// Display image and sleeps at least 1 ms (it usually sleeps ~5-10 msec to display the image)
const char key = (char)cv::waitKey(1);
if (key == 27)
this->stop();
}
}
catch (const std::exception& e)
{
op::log("Some kind of unexpected error happened.");
this->stop();
op::error(e.what(), __LINE__, __FUNCTION__, __FILE__);
}
}
};
int openPoseTutorialWrapper2()
{
// logging_level
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::ConfigureLog::setPriorityThreshold(op::Priority::None); // To print all logging messages
op::log("Starting pose estimation demo.", op::Priority::High);
const auto timerBegin = std::chrono::high_resolution_clock::now();
// Applying user defined configuration - Google flags to program variables
// outputSize
const auto outputSize = op::flagsToPoint(FLAGS_output_resolution, "-1x-1");
// netInputSize
const auto netInputSize = op::flagsToPoint(FLAGS_net_resolution, "-1x368");
// faceNetInputSize
const auto faceNetInputSize = op::flagsToPoint(FLAGS_face_net_resolution, "368x368 (multiples of 16)");
// handNetInputSize
const auto handNetInputSize = op::flagsToPoint(FLAGS_hand_net_resolution, "368x368 (multiples of 16)");
// poseModel
const auto poseModel = op::flagsToPoseModel(FLAGS_model_pose);
// keypointScale
const auto keypointScale = op::flagsToScaleMode(FLAGS_keypoint_scale);
// heatmaps to add
const auto heatMapTypes = op::flagsToHeatMaps(FLAGS_heatmaps_add_parts, FLAGS_heatmaps_add_bkg,
FLAGS_heatmaps_add_PAFs);
op::check(FLAGS_heatmaps_scale >= 0 && FLAGS_heatmaps_scale <= 2, "Non valid `heatmaps_scale`.",
__LINE__, __FUNCTION__, __FILE__);
const auto heatMapScale = (FLAGS_heatmaps_scale == 0 ? op::ScaleMode::PlusMinusOne
: (FLAGS_heatmaps_scale == 1 ? op::ScaleMode::ZeroToOne : op::ScaleMode::UnsignedChar ));
// Enabling Google Logging
const bool enableGoogleLogging = true;
// Logging
op::log("", op::Priority::Low, __LINE__, __FUNCTION__, __FILE__);
// Initializing the user custom classes
// Frames producer (e.g. video, webcam, ...)
auto wUserInput = std::make_shared<WUserInput>(FLAGS_image_dir);
// Processing
auto wUserPostProcessing = std::make_shared<WUserPostProcessing>();
// GUI (Display)
auto wUserOutput = std::make_shared<WUserOutput>();
op::Wrapper<std::vector<UserDatum>> opWrapper;
// Add custom input
const auto workerInputOnNewThread = false;
opWrapper.setWorkerInput(wUserInput, workerInputOnNewThread);
// Add custom processing
const auto workerProcessingOnNewThread = false;
opWrapper.setWorkerPostProcessing(wUserPostProcessing, workerProcessingOnNewThread);
// Add custom output
const auto workerOutputOnNewThread = true;
opWrapper.setWorkerOutput(wUserOutput, workerOutputOnNewThread);
// Configure OpenPose
op::log("Configuring OpenPose wrapper.", op::Priority::Low, __LINE__, __FUNCTION__, __FILE__);
const op::WrapperStructPose wrapperStructPose{!FLAGS_body_disable, netInputSize, outputSize, keypointScale,
FLAGS_num_gpu, FLAGS_num_gpu_start, FLAGS_scale_number,
(float)FLAGS_scale_gap, op::flagsToRenderMode(FLAGS_render_pose),
poseModel, !FLAGS_disable_blending, (float)FLAGS_alpha_pose,
(float)FLAGS_alpha_heatmap, FLAGS_part_to_show, FLAGS_model_folder,
heatMapTypes, heatMapScale, (float)FLAGS_render_threshold,
enableGoogleLogging};
// Face configuration (use op::WrapperStructFace{} to disable it)
const op::WrapperStructFace wrapperStructFace{FLAGS_face, faceNetInputSize,
op::flagsToRenderMode(FLAGS_face_render, FLAGS_render_pose),
(float)FLAGS_face_alpha_pose, (float)FLAGS_face_alpha_heatmap,
(float)FLAGS_face_render_threshold};
// Hand configuration (use op::WrapperStructHand{} to disable it)
const op::WrapperStructHand wrapperStructHand{FLAGS_hand, handNetInputSize, FLAGS_hand_scale_number,
(float)FLAGS_hand_scale_range, FLAGS_hand_tracking,
op::flagsToRenderMode(FLAGS_hand_render, FLAGS_render_pose),
(float)FLAGS_hand_alpha_pose, (float)FLAGS_hand_alpha_heatmap,
(float)FLAGS_hand_render_threshold};
// Consumer (comment or use default argument to disable any output)
const bool displayGui = false;
const bool guiVerbose = false;
const bool fullScreen = false;
const op::WrapperStructOutput wrapperStructOutput{displayGui, guiVerbose, fullScreen, FLAGS_write_keypoint,
op::stringToDataFormat(FLAGS_write_keypoint_format), FLAGS_write_keypoint_json,
FLAGS_write_coco_json, FLAGS_write_images, FLAGS_write_images_format, FLAGS_write_video,
FLAGS_write_heatmaps, FLAGS_write_heatmaps_format};
// Configure wrapper
opWrapper.configure(wrapperStructPose, wrapperStructFace, wrapperStructHand, op::WrapperStructInput{},
wrapperStructOutput);
// Set to single-thread running (e.g. for debugging purposes)
// opWrapper.disableMultiThreading();
op::log("Starting thread(s)", op::Priority::High);
// Two different ways of running the program on multithread environment
// // Option a) Recommended - Also using the main thread (this thread) for processing (it saves 1 thread)
// // Start, run & stop threads
opWrapper.exec(); // It blocks this thread until all threads have finished
// Option b) Keeping this thread free in case you want to do something else meanwhile, e.g. profiling the GPU memory
// // VERY IMPORTANT NOTE: if OpenCV is compiled with Qt support, this option will not work. Qt needs the main
// // thread to plot visual results, so the final GUI (which uses OpenCV) would return an exception similar to:
// // `QMetaMethod::invoke: Unable to invoke methods with return values in queued connections`
// // Start threads
// opWrapper.start();
// // Profile used GPU memory
// // 1: wait ~10sec so the memory has been totally loaded on GPU
// // 2: profile the GPU memory
// std::this_thread::sleep_for(std::chrono::milliseconds{1000});
// op::log("Random task here...", op::Priority::High);
// // Keep program alive while running threads
// while (opWrapper.isRunning())
// std::this_thread::sleep_for(std::chrono::milliseconds{33});
// // Stop and join threads
// op::log("Stopping thread(s)", op::Priority::High);
// opWrapper.stop();
// Measuring total time
const auto now = std::chrono::high_resolution_clock::now();
const auto totalTimeSec = (double)std::chrono::duration_cast<std::chrono::nanoseconds>(now-timerBegin).count()
* 1e-9;
const auto message = "Real-time pose estimation demo successfully finished. Total time: "
+ std::to_string(totalTimeSec) + " seconds.";
op::log(message, op::Priority::High);
return 0;
}
int main(int argc, char *argv[])
{
// Parsing command line flags
gflags::ParseCommandLineFlags(&argc, &argv, true);
// Running openPoseTutorialWrapper2
return openPoseTutorialWrapper2();
}
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