crosstyan/RapidPoseTriangulation
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Reimplemented wrapper in cpp.

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This commit is contained in:
Daniel
2025-01-17 16:42:05 +01:00
parent 8a249a2f16
commit 99368e5216
21 changed files with 26448 additions and 10 deletions
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ros/rpt2D_wrapper_cpp/tests/.gitignore vendored Normal file
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my_app

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ros/rpt2D_wrapper_cpp/tests/my_app.cpp Normal file
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#include <filesystem>
#include <vector>
#include <string>
#include <memory>
#include <opencv2/opencv.hpp>
#include "../src/utils_2d_pose.hpp"
// =================================================================================================
// =================================================================================================
int main(int argc, char **argv)
{
using namespace utils_2d_pose;
std::string base_path = "/RapidPoseTriangulation/extras/mmdeploy/exports/";
std::string model_path1 = base_path + "rtmdet-nano_1x320x320x3_fp16_extra-steps.onnx";
std::string model_path2 = base_path + "rtmpose-m_1x384x288x3_fp16_extra-steps.onnx";
std::vector<std::string> img_paths = {
"/RapidPoseTriangulation/data/h1/54138969-img_003201.jpg",
"/RapidPoseTriangulation/data/h1/55011271-img_003201.jpg",
"/RapidPoseTriangulation/data/h1/58860488-img_003201.jpg",
"/RapidPoseTriangulation/data/h1/60457274-img_003201.jpg",
};
// RTMDet model1(model_path1, 0.3, 0.1 * 0.1, 30);
// RTMPose model2(model_path2, 30);
// for (size_t i = 0; i < img_paths.size(); i++)
// {
// cv::Mat img = cv::imread(img_paths[i]);
// cv::cvtColor(img, img, cv::COLOR_BGR2RGB);
// auto outputs1 = model1.call(img);
// std::cout << "Model1 outputs: " << outputs1[0][0] << " " << outputs1[0][1] << " "
// << outputs1[0][2] << " " << outputs1[0][3] << " " << outputs1[0][4] << " "
// << std::endl;
// for (size_t j = 0; j < outputs1.size(); j++)
// {
// std::vector<std::array<float, 5>> bboxes = {outputs1[j]};
// auto outputs2 = model2.call(img, bboxes);
// std::cout << "Model2 outputs: " << outputs2[0][0] << " " << outputs2[0][1] << " "
// << outputs2[0][2] << " " << std::endl;
// }
// }
// TopDown model3(model_path1, model_path2, 0.3, 0.1 * 0.1, 30);
// for (size_t i = 0; i < img_paths.size(); i++)
// {
// cv::Mat img = cv::imread(img_paths[i]);
// cv::cvtColor(img, img, cv::COLOR_BGR2RGB);
// auto outputs3 = model3.predict(img);
// std::cout << "Model3 outputs: " << outputs3[0][0][0] << " " << outputs3[0][0][1] << " "
// << outputs3[0][0][2] << " " << std::endl;
// }
PosePredictor model4(false, 0.3, 0.1 * 0.1, false);
std::vector<cv::Mat> images;
for (size_t i = 0; i < img_paths.size(); i++)
{
cv::Mat img = cv::imread(img_paths[i]);
cv::cvtColor(img, img, cv::COLOR_BGR2RGB);
images.push_back(img);
}
auto outputs4 = model4.predict(images);
std::cout << "Model4 outputs: " << outputs4[0][0][0][0] << " " << outputs4[0][0][0][1] << " "
<< outputs4[0][0][0][2] << " " << std::endl;
return 0;
}