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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
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modules/gapi/samples/pipeline_modeling_tool/utils.hpp
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144
modules/gapi/samples/pipeline_modeling_tool/utils.hpp
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#ifndef OPENCV_GAPI_PIPELINE_MODELING_TOOL_UTILS_HPP
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#define OPENCV_GAPI_PIPELINE_MODELING_TOOL_UTILS_HPP
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#include <map>
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#include <opencv2/core.hpp>
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#if defined(_WIN32)
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#include <windows.h>
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#endif
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// FIXME: It's better to place it somewhere in common.hpp
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struct OutputDescr {
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std::vector<int> dims;
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int precision;
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};
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namespace utils {
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using double_ms_t = std::chrono::duration<double, std::milli>;
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inline void createNDMat(cv::Mat& mat, const std::vector<int>& dims, int depth) {
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GAPI_Assert(!dims.empty());
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mat.create(dims, depth);
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if (dims.size() == 1) {
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//FIXME: Well-known 1D mat WA
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mat.dims = 1;
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}
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}
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inline void generateRandom(cv::Mat& out) {
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switch (out.depth()) {
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case CV_8U:
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cv::randu(out, 0, 255);
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break;
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case CV_32F:
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cv::randu(out, 0.f, 1.f);
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break;
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case CV_16F: {
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std::vector<int> dims;
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for (int i = 0; i < out.size.dims(); ++i) {
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dims.push_back(out.size[i]);
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}
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cv::Mat fp32_mat;
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createNDMat(fp32_mat, dims, CV_32F);
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cv::randu(fp32_mat, 0.f, 1.f);
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fp32_mat.convertTo(out, out.type());
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break;
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}
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default:
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throw std::logic_error("Unsupported preprocessing depth");
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}
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}
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inline void sleep(std::chrono::microseconds delay) {
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#if defined(_WIN32)
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// FIXME: Wrap it to RAII and instance only once.
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HANDLE timer = CreateWaitableTimer(NULL, true, NULL);
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if (!timer) {
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throw std::logic_error("Failed to create timer");
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}
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LARGE_INTEGER li;
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using ns_t = std::chrono::nanoseconds;
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using ns_100_t = std::chrono::duration<ns_t::rep,
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std::ratio_multiply<std::ratio<100>, ns_t::period>>;
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// NB: QuadPart takes portions of 100 nanoseconds.
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li.QuadPart = -std::chrono::duration_cast<ns_100_t>(delay).count();
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if(!SetWaitableTimer(timer, &li, 0, NULL, NULL, false)){
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CloseHandle(timer);
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throw std::logic_error("Failed to set timer");
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}
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if (WaitForSingleObject(timer, INFINITE) != WAIT_OBJECT_0) {
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CloseHandle(timer);
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throw std::logic_error("Failed to wait timer");
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}
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CloseHandle(timer);
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#else
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std::this_thread::sleep_for(delay);
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#endif
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}
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template <typename duration_t>
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typename duration_t::rep measure(std::function<void()> f) {
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using namespace std::chrono;
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auto start = high_resolution_clock::now();
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f();
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return duration_cast<duration_t>(
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high_resolution_clock::now() - start).count();
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}
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template <typename duration_t>
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typename duration_t::rep timestamp() {
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using namespace std::chrono;
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auto now = high_resolution_clock::now();
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return duration_cast<duration_t>(now.time_since_epoch()).count();
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}
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inline void busyWait(std::chrono::microseconds delay) {
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auto start_ts = timestamp<std::chrono::microseconds>();
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auto end_ts = start_ts;
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auto time_to_wait = delay.count();
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while (end_ts - start_ts < time_to_wait) {
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end_ts = timestamp<std::chrono::microseconds>();
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}
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}
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template <typename K, typename V>
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void mergeMapWith(std::map<K, V>& target, const std::map<K, V>& second) {
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for (auto&& item : second) {
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auto it = target.find(item.first);
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if (it != target.end()) {
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throw std::logic_error("Error: key: " + it->first + " is already in target map");
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}
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target.insert(item);
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}
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}
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template <typename T>
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double avg(const std::vector<T>& vec) {
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return std::accumulate(vec.begin(), vec.end(), 0.0) / vec.size();
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}
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template <typename T>
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T max(const std::vector<T>& vec) {
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return *std::max_element(vec.begin(), vec.end());
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}
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template <typename T>
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T min(const std::vector<T>& vec) {
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return *std::min_element(vec.begin(), vec.end());
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}
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template <typename T>
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int64_t ms_to_mcs(T ms) {
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using namespace std::chrono;
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return duration_cast<microseconds>(duration<T, std::milli>(ms)).count();
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}
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} // namespace utils
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#endif // OPENCV_GAPI_PIPELINE_MODELING_TOOL_UTILS_HPP
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