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openpose/examples/tutorial_pose/1_extract_from_image.cpp
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// ------------------------- OpenPose Library Tutorial - Pose - Example 1 - Extract from Image -------------------------
// This first example shows the user how to:
// 1. Load an image (`filestream` module)
// 2. Extract the pose of that image (`pose` module)
// 3. Render the pose on a resized copy of the input image (`pose` module)
// 4. Display the rendered pose (`gui` module)
// 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
// 2. `utilities` module: for the error & logging functions, i.e. op::error & op::log respectively
// 3rdpary depencencies
#include <gflags/gflags.h> // DEFINE_bool, DEFINE_int32, DEFINE_int64, DEFINE_uint64, DEFINE_double, DEFINE_string
#include <glog/logging.h> // google::InitGoogleLogging, CHECK, CHECK_EQ, LOG, VLOG, ...
// OpenPose dependencies
#include <openpose/core/headers.hpp>
#include <openpose/filestream/headers.hpp>
#include <openpose/gui/headers.hpp>
#include <openpose/pose/headers.hpp>
#include <openpose/utilities/headers.hpp>
// Gflags in the command line terminal. Check all the options by adding the flag `--help`, e.g. `rtpose.bin --help`.
// Note: This command will show you flags for several files. Check only the flags for the file you are checking. E.g. for `rtpose`, look for `Flags from examples/openpose/rtpose.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_path, "examples/media/COCO_val2014_000000000192.jpg", "Process the desired image.");
// OpenPose
DEFINE_string(model_pose, "COCO", "Model to be used (e.g. COCO, MPI, MPI_4_layers).");
DEFINE_string(model_folder, "models/", "Folder where the pose models (COCO and MPI) are located.");
DEFINE_string(net_resolution, "656x368", "Multiples of 16.");
DEFINE_string(resolution, "1280x720", "The image resolution (display). Use \"-1x-1\" to force the program to use the default images resolution.");
DEFINE_int32(num_gpu_start, 0, "GPU device start number.");
DEFINE_double(scale_gap, 0.3, "Scale gap between scales. No effect unless num_scales>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_int32(num_scales, 1, "Number of scales to average.");
// OpenPose Rendering
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.");
op::PoseModel gflagToPoseModel(const std::string& poseModeString)
{
op::log("", op::Priority::Low, __LINE__, __FUNCTION__, __FILE__);
if (poseModeString == "COCO")
return op::PoseModel::COCO_18;
else if (poseModeString == "MPI")
return op::PoseModel::MPI_15;
else if (poseModeString == "MPI_4_layers")
return op::PoseModel::MPI_15_4;
else
{
op::error("String does not correspond to any model (COCO, MPI, MPI_4_layers)", __LINE__, __FUNCTION__, __FILE__);
return op::PoseModel::COCO_18;
}
}
// Google flags into program variables
std::tuple<cv::Size, cv::Size, cv::Size, op::PoseModel> gflagsToOpParameters()
{
op::log("", op::Priority::Low, __LINE__, __FUNCTION__, __FILE__);
// outputSize
cv::Size outputSize;
auto nRead = sscanf(FLAGS_resolution.c_str(), "%dx%d", &outputSize.width, &outputSize.height);
op::checkE(nRead, 2, "Error, resolution format (" + FLAGS_resolution + ") invalid, should be e.g., 960x540 ", __LINE__, __FUNCTION__, __FILE__);
// netInputSize
cv::Size netInputSize;
nRead = sscanf(FLAGS_net_resolution.c_str(), "%dx%d", &netInputSize.width, &netInputSize.height);
op::checkE(nRead, 2, "Error, net resolution format (" + FLAGS_net_resolution + ") invalid, should be e.g., 656x368 (multiples of 16)", __LINE__, __FUNCTION__, __FILE__);
// netOutputSize
const auto netOutputSize = netInputSize;
// poseModel
const auto poseModel = gflagToPoseModel(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_num_scales > 1)
op::error("Uncompatible flag configuration: scale_gap must be greater than 0 or num_scales = 1.", __LINE__, __FUNCTION__, __FILE__);
// Logging and return result
op::log("", op::Priority::Low, __LINE__, __FUNCTION__, __FILE__);
return std::make_tuple(outputSize, netInputSize, netOutputSize, poseModel);
}
int openPoseTutorialPose1()
{
op::log("OpenPose Library Tutorial - Example 1.", op::Priority::Max);
// ------------------------- 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);
// Step 2 - Read Google flags (user defined configuration)
cv::Size outputSize;
cv::Size netInputSize;
cv::Size netOutputSize;
op::PoseModel poseModel;
std::tie(outputSize, netInputSize, netOutputSize, poseModel) = gflagsToOpParameters();
// Step 3 - Initialize all required classes
op::CvMatToOpInput cvMatToOpInput{netInputSize, FLAGS_num_scales, (float)FLAGS_scale_gap};
op::CvMatToOpOutput cvMatToOpOutput{outputSize};
op::PoseExtractorCaffe poseExtractorCaffe{netInputSize, netOutputSize, outputSize, FLAGS_num_scales, (float)FLAGS_scale_gap, poseModel,
FLAGS_model_folder, FLAGS_num_gpu_start};
op::PoseRenderer poseRenderer{netOutputSize, outputSize, poseModel, nullptr, (float)FLAGS_alpha_pose};
op::OpOutputToCvMat opOutputToCvMat{outputSize};
const cv::Size windowedSize = outputSize;
op::FrameDisplayer frameDisplayer{windowedSize, "OpenPose Tutorial - Example 1"};
// Step 4 - Initialize resources on desired thread (in this case single thread, i.e. we init resources here)
poseExtractorCaffe.initializationOnThread();
poseRenderer.initializationOnThread();
// ------------------------- POSE ESTIMATION AND RENDERING -------------------------
// Step 1 - Read and load image, error if empty (possibly wrong path)
cv::Mat inputImage = op::loadImage(FLAGS_image_path, CV_LOAD_IMAGE_COLOR); // Alternative: cv::imread(FLAGS_image_path, CV_LOAD_IMAGE_COLOR);
if(inputImage.empty())
op::error("Could not open or find the image: " + FLAGS_image_path, __LINE__, __FUNCTION__, __FILE__);
// Step 2 - Format input image to OpenPose input and output formats
const auto netInputArray = cvMatToOpInput.format(inputImage);
double scaleInputToOutput;
op::Array<float> outputArray;
std::tie(scaleInputToOutput, outputArray) = cvMatToOpOutput.format(inputImage);
// Step 3 - Estimate poseKeyPoints
poseExtractorCaffe.forwardPass(netInputArray, inputImage.size());
const auto poseKeyPoints = poseExtractorCaffe.getPoseKeyPoints();
// Step 4 - Render poseKeyPoints
poseRenderer.renderPose(outputArray, poseKeyPoints);
// Step 5 - OpenPose output format to cv::Mat
auto outputImage = opOutputToCvMat.formatToCvMat(outputArray);
// ------------------------- SHOWING RESULT AND CLOSING -------------------------
// Step 1 - Show results
frameDisplayer.displayFrame(outputImage, 0); // Alternative: cv::imshow(outputImage) + cv::waitKey(0)
// Step 2 - Logging information message
op::log("Example 1 successfully finished.", op::Priority::Max);
// Return successful message
return 0;
}
int main(int argc, char *argv[])
{
// Initializing google logging (Caffe uses it for logging)
google::InitGoogleLogging("openPoseTutorialPose1");
// Parsing command line flags
gflags::ParseCommandLineFlags(&argc, &argv, true);
// Running openPoseTutorialPose1
return openPoseTutorialPose1();
}