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opencv_contrib/modules/gapi/samples/pipeline_modeling_tool/utils.hpp
Alexander Smorkalov 2d69dd1215 Merge pull request #3827 from asmorkalov:as/gapi_migration
Migrate G-API module from main repo to opencv_contrib #3827

Related to https://github.com/opencv/opencv/pull/26469
Required https://github.com/opencv/opencv/pull/26527
CI: https://github.com/opencv/ci-gha-workflow/pull/201

TODO:
- [x]  Python types generator fix
- [x] CI update

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [ ] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-11-27 16:02:16 +03:00

145 lines
4.0 KiB
C++

#ifndef OPENCV_GAPI_PIPELINE_MODELING_TOOL_UTILS_HPP
#define OPENCV_GAPI_PIPELINE_MODELING_TOOL_UTILS_HPP
#include <map>
#include <opencv2/core.hpp>
#if defined(_WIN32)
#include <windows.h>
#endif
// FIXME: It's better to place it somewhere in common.hpp
struct OutputDescr {
std::vector<int> dims;
int precision;
};
namespace utils {
using double_ms_t = std::chrono::duration<double, std::milli>;
inline void createNDMat(cv::Mat& mat, const std::vector<int>& dims, int depth) {
GAPI_Assert(!dims.empty());
mat.create(dims, depth);
if (dims.size() == 1) {
//FIXME: Well-known 1D mat WA
mat.dims = 1;
}
}
inline void generateRandom(cv::Mat& out) {
switch (out.depth()) {
case CV_8U:
cv::randu(out, 0, 255);
break;
case CV_32F:
cv::randu(out, 0.f, 1.f);
break;
case CV_16F: {
std::vector<int> dims;
for (int i = 0; i < out.size.dims(); ++i) {
dims.push_back(out.size[i]);
}
cv::Mat fp32_mat;
createNDMat(fp32_mat, dims, CV_32F);
cv::randu(fp32_mat, 0.f, 1.f);
fp32_mat.convertTo(out, out.type());
break;
}
default:
throw std::logic_error("Unsupported preprocessing depth");
}
}
inline void sleep(std::chrono::microseconds delay) {
#if defined(_WIN32)
// FIXME: Wrap it to RAII and instance only once.
HANDLE timer = CreateWaitableTimer(NULL, true, NULL);
if (!timer) {
throw std::logic_error("Failed to create timer");
}
LARGE_INTEGER li;
using ns_t = std::chrono::nanoseconds;
using ns_100_t = std::chrono::duration<ns_t::rep,
std::ratio_multiply<std::ratio<100>, ns_t::period>>;
// NB: QuadPart takes portions of 100 nanoseconds.
li.QuadPart = -std::chrono::duration_cast<ns_100_t>(delay).count();
if(!SetWaitableTimer(timer, &li, 0, NULL, NULL, false)){
CloseHandle(timer);
throw std::logic_error("Failed to set timer");
}
if (WaitForSingleObject(timer, INFINITE) != WAIT_OBJECT_0) {
CloseHandle(timer);
throw std::logic_error("Failed to wait timer");
}
CloseHandle(timer);
#else
std::this_thread::sleep_for(delay);
#endif
}
template <typename duration_t>
typename duration_t::rep measure(std::function<void()> f) {
using namespace std::chrono;
auto start = high_resolution_clock::now();
f();
return duration_cast<duration_t>(
high_resolution_clock::now() - start).count();
}
template <typename duration_t>
typename duration_t::rep timestamp() {
using namespace std::chrono;
auto now = high_resolution_clock::now();
return duration_cast<duration_t>(now.time_since_epoch()).count();
}
inline void busyWait(std::chrono::microseconds delay) {
auto start_ts = timestamp<std::chrono::microseconds>();
auto end_ts = start_ts;
auto time_to_wait = delay.count();
while (end_ts - start_ts < time_to_wait) {
end_ts = timestamp<std::chrono::microseconds>();
}
}
template <typename K, typename V>
void mergeMapWith(std::map<K, V>& target, const std::map<K, V>& second) {
for (auto&& item : second) {
auto it = target.find(item.first);
if (it != target.end()) {
throw std::logic_error("Error: key: " + it->first + " is already in target map");
}
target.insert(item);
}
}
template <typename T>
double avg(const std::vector<T>& vec) {
return std::accumulate(vec.begin(), vec.end(), 0.0) / vec.size();
}
template <typename T>
T max(const std::vector<T>& vec) {
return *std::max_element(vec.begin(), vec.end());
}
template <typename T>
T min(const std::vector<T>& vec) {
return *std::min_element(vec.begin(), vec.end());
}
template <typename T>
int64_t ms_to_mcs(T ms) {
using namespace std::chrono;
return duration_cast<microseconds>(duration<T, std::milli>(ms)).count();
}
} // namespace utils
#endif // OPENCV_GAPI_PIPELINE_MODELING_TOOL_UTILS_HPP