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Open Source Computer Vision Library
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465 lines
17 KiB
465 lines
17 KiB
#include <iostream> |
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#include <fstream> |
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#include <thread> |
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#include <exception> |
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#include <unordered_map> |
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#include <vector> |
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#include <opencv2/gapi.hpp> |
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#include <opencv2/highgui.hpp> // cv::CommandLineParser |
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#include <opencv2/core/utils/filesystem.hpp> |
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#if defined(_WIN32) |
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#define NOMINMAX |
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#include <windows.h> |
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#undef NOMINMAX |
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#endif |
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#include "pipeline_modeling_tool/dummy_source.hpp" |
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#include "pipeline_modeling_tool/utils.hpp" |
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#include "pipeline_modeling_tool/pipeline_builder.hpp" |
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enum class AppMode { |
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REALTIME, |
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BENCHMARK |
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}; |
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static AppMode strToAppMode(const std::string& mode_str) { |
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if (mode_str == "realtime") { |
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return AppMode::REALTIME; |
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} else if (mode_str == "benchmark") { |
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return AppMode::BENCHMARK; |
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} else { |
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throw std::logic_error("Unsupported AppMode: " + mode_str + |
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"\nPlease chose between: realtime and benchmark"); |
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} |
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} |
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template <typename T> |
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T read(const cv::FileNode& node) { |
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return static_cast<T>(node); |
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} |
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static cv::FileNode check_and_get_fn(const cv::FileNode& fn, |
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const std::string& field, |
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const std::string& uplvl) { |
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const bool is_map = fn.isMap(); |
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if (!is_map || fn[field].empty()) { |
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throw std::logic_error(uplvl + " must contain field: " + field); |
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} |
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return fn[field]; |
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} |
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static cv::FileNode check_and_get_fn(const cv::FileStorage& fs, |
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const std::string& field, |
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const std::string& uplvl) { |
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auto fn = fs[field]; |
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if (fn.empty()) { |
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throw std::logic_error(uplvl + " must contain field: " + field); |
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} |
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return fn; |
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} |
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template <typename T, typename FileT> |
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T check_and_read(const FileT& f, |
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const std::string& field, |
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const std::string& uplvl) { |
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auto fn = check_and_get_fn(f, field, uplvl); |
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return read<T>(fn); |
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} |
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template <typename T> |
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cv::optional<T> readOpt(const cv::FileNode& fn) { |
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return fn.empty() ? cv::optional<T>() : cv::optional<T>(read<T>(fn)); |
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} |
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template <typename T> |
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std::vector<T> readList(const cv::FileNode& fn, |
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const std::string& field, |
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const std::string& uplvl) { |
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auto fn_field = check_and_get_fn(fn, field, uplvl); |
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if (!fn_field.isSeq()) { |
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throw std::logic_error(field + " in " + uplvl + " must be a sequence"); |
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} |
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std::vector<T> vec; |
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for (auto iter : fn_field) { |
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vec.push_back(read<T>(iter)); |
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} |
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return vec; |
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} |
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template <typename T> |
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std::vector<T> readVec(const cv::FileNode& fn, |
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const std::string& field, |
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const std::string& uplvl) { |
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auto fn_field = check_and_get_fn(fn, field, uplvl); |
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std::vector<T> vec; |
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fn_field >> vec; |
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return vec; |
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} |
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static int strToPrecision(const std::string& precision) { |
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static std::unordered_map<std::string, int> str_to_precision = { |
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{"U8", CV_8U}, {"FP32", CV_32F}, {"FP16", CV_16F} |
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}; |
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auto it = str_to_precision.find(precision); |
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if (it == str_to_precision.end()) { |
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throw std::logic_error("Unsupported precision: " + precision); |
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} |
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return it->second; |
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} |
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template <> |
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OutputDescr read<OutputDescr>(const cv::FileNode& fn) { |
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auto dims = readVec<int>(fn, "dims", "output"); |
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auto str_prec = check_and_read<std::string>(fn, "precision", "output"); |
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return OutputDescr{dims, strToPrecision(str_prec)}; |
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} |
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template <> |
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Edge read<Edge>(const cv::FileNode& fn) { |
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auto from = check_and_read<std::string>(fn, "from", "edge"); |
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auto to = check_and_read<std::string>(fn, "to", "edge"); |
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auto splitNameAndPort = [](const std::string& str) { |
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auto pos = str.find(':'); |
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auto name = |
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pos == std::string::npos ? str : std::string(str.c_str(), pos); |
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size_t port = |
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pos == std::string::npos ? 0 : std::atoi(str.c_str() + pos + 1); |
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return std::make_pair(name, port); |
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}; |
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auto p1 = splitNameAndPort(from); |
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auto p2 = splitNameAndPort(to); |
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return Edge{Edge::P{p1.first, p1.second}, Edge::P{p2.first, p2.second}}; |
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} |
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static std::string getModelsPath() { |
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static char* models_path_c = std::getenv("PIPELINE_MODELS_PATH"); |
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static std::string models_path = models_path_c ? models_path_c : "."; |
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return models_path; |
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} |
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template <> |
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ModelPath read<ModelPath>(const cv::FileNode& fn) { |
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using cv::utils::fs::join; |
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if (!fn["xml"].empty() && !fn["bin"].empty()) { |
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return ModelPath{LoadPath{join(getModelsPath(), fn["xml"].string()), |
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join(getModelsPath(), fn["bin"].string())}}; |
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} else if (!fn["blob"].empty()){ |
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return ModelPath{ImportPath{join(getModelsPath(), fn["blob"].string())}}; |
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} else { |
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const std::string emsg = R""""( |
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Path to OpenVINO model must be specified in either of two formats: |
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1. |
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xml: path to *.xml |
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bin: path to *.bin |
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2. |
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blob: path to *.blob |
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)""""; |
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throw std::logic_error(emsg); |
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} |
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} |
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static PLMode strToPLMode(const std::string& mode_str) { |
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if (mode_str == "streaming") { |
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return PLMode::STREAMING; |
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} else if (mode_str == "regular") { |
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return PLMode::REGULAR; |
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} else { |
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throw std::logic_error("Unsupported PLMode: " + mode_str + |
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"\nPlease chose between: streaming and regular"); |
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} |
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} |
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template <> |
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CallParams read<CallParams>(const cv::FileNode& fn) { |
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auto name = |
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check_and_read<std::string>(fn, "name", "node"); |
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// FIXME: Impossible to read size_t due OpenCV limitations. |
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auto call_every_nth_opt = readOpt<int>(fn["call_every_nth"]); |
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auto call_every_nth = call_every_nth_opt.value_or(1); |
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if (call_every_nth <= 0) { |
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throw std::logic_error( |
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name + " call_every_nth must be greater than zero\n" |
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"Current call_every_nth: " + std::to_string(call_every_nth)); |
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} |
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return CallParams{std::move(name), static_cast<size_t>(call_every_nth)}; |
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} |
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template <> |
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InferParams read<InferParams>(const cv::FileNode& fn) { |
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auto name = |
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check_and_read<std::string>(fn, "name", "node"); |
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InferParams params; |
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params.path = read<ModelPath>(fn); |
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params.device = check_and_read<std::string>(fn, "device", name); |
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params.input_layers = readList<std::string>(fn, "input_layers", name); |
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params.output_layers = readList<std::string>(fn, "output_layers", name); |
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return params; |
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} |
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template <> |
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DummyParams read<DummyParams>(const cv::FileNode& fn) { |
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auto name = |
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check_and_read<std::string>(fn, "name", "node"); |
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DummyParams params; |
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params.time = check_and_read<double>(fn, "time", name); |
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if (params.time < 0) { |
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throw std::logic_error(name + " time must be positive"); |
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} |
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params.output = check_and_read<OutputDescr>(fn, "output", name); |
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return params; |
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} |
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static std::vector<std::string> parseExecList(const std::string& exec_list) { |
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std::vector<std::string> pl_types; |
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std::stringstream ss(exec_list); |
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std::string pl_type; |
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while (getline(ss, pl_type, ',')) { |
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pl_types.push_back(pl_type); |
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} |
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return pl_types; |
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} |
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static void loadConfig(const std::string& filename, |
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std::map<std::string, std::string>& config) { |
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cv::FileStorage fs(filename, cv::FileStorage::READ); |
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if (!fs.isOpened()) { |
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throw std::runtime_error("Failed to load config: " + filename); |
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} |
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cv::FileNode root = fs.root(); |
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for (auto it = root.begin(); it != root.end(); ++it) { |
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auto device = *it; |
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if (!device.isMap()) { |
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throw std::runtime_error("Failed to parse config: " + filename); |
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} |
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for (auto item : device) { |
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config.emplace(item.name(), item.string()); |
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} |
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} |
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} |
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int main(int argc, char* argv[]) { |
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#if defined(_WIN32) |
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timeBeginPeriod(1); |
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#endif |
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try { |
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const std::string keys = |
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"{ h help | | Print this help message. }" |
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"{ cfg | | Path to the config which is either" |
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" YAML file or string. }" |
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"{ load_config | | Optional. Path to XML/YAML/JSON file" |
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" to load custom IE parameters. }" |
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"{ cache_dir | | Optional. Enables caching of loaded models" |
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" to specified directory. }" |
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"{ log_file | | Optional. If file is specified, app will" |
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" dump expanded execution information. }" |
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"{ pl_mode | streaming | Optional. Pipeline mode: streaming/regular" |
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" if it's specified will be applied for" |
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" every pipeline. }" |
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"{ qc | 1 | Optional. Calculated automatically by G-API" |
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" if set to 0. If it's specified will be" |
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" applied for every pipeline. }" |
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"{ app_mode | realtime | Application mode (realtime/benchmark). }" |
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"{ drop_frames | false | Drop frames if they come earlier than pipeline is completed. }" |
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"{ exec_list | | A comma-separated list of pipelines that" |
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" will be executed. Spaces around commas" |
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" are prohibited. }"; |
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cv::CommandLineParser cmd(argc, argv, keys); |
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if (cmd.has("help")) { |
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cmd.printMessage(); |
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return 0; |
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} |
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const auto cfg = cmd.get<std::string>("cfg"); |
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const auto load_config = cmd.get<std::string>("load_config"); |
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const auto cached_dir = cmd.get<std::string>("cache_dir"); |
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const auto log_file = cmd.get<std::string>("log_file"); |
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const auto cmd_pl_mode = strToPLMode(cmd.get<std::string>("pl_mode")); |
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const auto qc = cmd.get<int>("qc"); |
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const auto app_mode = strToAppMode(cmd.get<std::string>("app_mode")); |
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const auto exec_str = cmd.get<std::string>("exec_list"); |
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const auto drop_frames = cmd.get<bool>("drop_frames"); |
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cv::FileStorage fs; |
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if (cfg.empty()) { |
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throw std::logic_error("Config must be specified via --cfg option"); |
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} |
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// NB: *.yml |
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if (cfg.size() < 5) { |
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throw std::logic_error("--cfg string must contain at least 5 symbols" |
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" to determine if it's a file (*.yml) a or string"); |
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} |
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if (cfg.substr(cfg.size() - 4, cfg.size()) == ".yml") { |
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if (!fs.open(cfg, cv::FileStorage::READ)) { |
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throw std::logic_error("Failed to open config file: " + cfg); |
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} |
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} else { |
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fs = cv::FileStorage(cfg, cv::FileStorage::FORMAT_YAML | |
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cv::FileStorage::MEMORY); |
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} |
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std::map<std::string, std::string> config; |
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if (!load_config.empty()) { |
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loadConfig(load_config, config); |
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} |
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// NB: Takes priority over config from file |
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if (!cached_dir.empty()) { |
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config = |
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std::map<std::string, std::string>{{"CACHE_DIR", cached_dir}}; |
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} |
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const double work_time_ms = |
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check_and_read<double>(fs, "work_time", "Config"); |
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if (work_time_ms < 0) { |
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throw std::logic_error("work_time must be positive"); |
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} |
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auto pipelines_fn = check_and_get_fn(fs, "Pipelines", "Config"); |
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if (!pipelines_fn.isMap()) { |
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throw std::logic_error("Pipelines field must be a map"); |
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} |
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auto exec_list = !exec_str.empty() ? parseExecList(exec_str) |
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: pipelines_fn.keys(); |
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std::vector<Pipeline::Ptr> pipelines; |
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pipelines.reserve(exec_list.size()); |
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// NB: Build pipelines based on config information |
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PipelineBuilder builder; |
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for (const auto& name : exec_list) { |
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const auto& pl_fn = check_and_get_fn(pipelines_fn, name, "Pipelines"); |
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builder.setName(name); |
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// NB: Set source |
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{ |
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const auto& src_fn = check_and_get_fn(pl_fn, "source", name); |
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auto src_name = |
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check_and_read<std::string>(src_fn, "name", "source"); |
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auto latency = |
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check_and_read<double>(src_fn, "latency", "source"); |
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auto output = |
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check_and_read<OutputDescr>(src_fn, "output", "source"); |
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// NB: In case BENCHMARK mode sources work with zero latency. |
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if (app_mode == AppMode::BENCHMARK) { |
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latency = 0.0; |
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} |
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auto src = std::make_shared<DummySource>(latency, output, drop_frames); |
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builder.setSource(src_name, src); |
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} |
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const auto& nodes_fn = check_and_get_fn(pl_fn, "nodes", name); |
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if (!nodes_fn.isSeq()) { |
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throw std::logic_error("nodes in " + name + " must be a sequence"); |
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} |
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for (auto node_fn : nodes_fn) { |
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auto call_params = read<CallParams>(node_fn); |
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auto node_type = |
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check_and_read<std::string>(node_fn, "type", "node"); |
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if (node_type == "Dummy") { |
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builder.addDummy(call_params, read<DummyParams>(node_fn)); |
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} else if (node_type == "Infer") { |
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auto infer_params = read<InferParams>(node_fn); |
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infer_params.config = config; |
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builder.addInfer(call_params, infer_params); |
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} else { |
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throw std::logic_error("Unsupported node type: " + node_type); |
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} |
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} |
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const auto edges_fn = check_and_get_fn(pl_fn, "edges", name); |
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if (!edges_fn.isSeq()) { |
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throw std::logic_error("edges in " + name + " must be a sequence"); |
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} |
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for (auto edge_fn : edges_fn) { |
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auto edge = read<Edge>(edge_fn); |
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builder.addEdge(edge); |
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} |
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auto cfg_pl_mode = readOpt<std::string>(pl_fn["mode"]); |
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// NB: Pipeline mode from config takes priority over cmd. |
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auto pl_mode = cfg_pl_mode.has_value() |
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? strToPLMode(cfg_pl_mode.value()) : cmd_pl_mode; |
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// NB: Using drop_frames with streaming pipelines will follow to |
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// incorrect performance results. |
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if (drop_frames && pl_mode == PLMode::STREAMING) { |
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throw std::logic_error( |
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"--drop_frames option is supported only for pipelines in \"regular\" mode"); |
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} |
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builder.setMode(pl_mode); |
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// NB: Queue capacity from config takes priority over cmd. |
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auto config_qc = readOpt<int>(pl_fn["queue_capacity"]); |
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auto queue_capacity = config_qc.has_value() ? config_qc.value() : qc; |
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// NB: 0 is special constant that means |
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// queue capacity should be calculated automatically. |
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if (queue_capacity != 0) { |
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builder.setQueueCapacity(queue_capacity); |
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} |
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auto dump = readOpt<std::string>(pl_fn["dump"]); |
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if (dump) { |
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builder.setDumpFilePath(dump.value()); |
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} |
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pipelines.emplace_back(builder.build()); |
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} |
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// NB: Compille pipelines |
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for (size_t i = 0; i < pipelines.size(); ++i) { |
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pipelines[i]->compile(); |
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} |
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// NB: Execute pipelines |
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std::vector<std::exception_ptr> eptrs(pipelines.size(), nullptr); |
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std::vector<std::thread> threads(pipelines.size()); |
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for (size_t i = 0; i < pipelines.size(); ++i) { |
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threads[i] = std::thread([&, i]() { |
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try { |
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pipelines[i]->run(work_time_ms); |
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} catch (...) { |
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eptrs[i] = std::current_exception(); |
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} |
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}); |
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} |
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std::ofstream file; |
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if (!log_file.empty()) { |
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file.open(log_file); |
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} |
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for (size_t i = 0; i < threads.size(); ++i) { |
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threads[i].join(); |
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} |
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for (size_t i = 0; i < threads.size(); ++i) { |
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if (eptrs[i] != nullptr) { |
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try { |
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std::rethrow_exception(eptrs[i]); |
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} catch (std::exception& e) { |
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throw std::logic_error(pipelines[i]->name() + " failed: " + e.what()); |
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} |
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} |
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if (file.is_open()) { |
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file << pipelines[i]->report().toStr(true) << std::endl; |
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} |
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std::cout << pipelines[i]->report().toStr() << std::endl; |
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} |
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} catch (const std::exception& e) { |
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std::cout << e.what() << std::endl; |
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throw; |
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} |
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return 0; |
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}
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