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Open Source Computer Vision Library
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250 lines
6.9 KiB
250 lines
6.9 KiB
#ifndef OPENCV_GAPI_PIPELINE_MODELING_TOOL_PIPELINE_HPP |
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#define OPENCV_GAPI_PIPELINE_MODELING_TOOL_PIPELINE_HPP |
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#include <iomanip> |
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struct PerfReport { |
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std::string name; |
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double avg_latency = 0.0; |
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double min_latency = 0.0; |
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double max_latency = 0.0; |
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double first_latency = 0.0; |
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double throughput = 0.0; |
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double elapsed = 0.0; |
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double warmup_time = 0.0; |
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int64_t num_late_frames = 0; |
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std::vector<double> latencies; |
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std::vector<int64_t> seq_ids; |
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std::string toStr(bool expanded = false) const; |
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}; |
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std::string PerfReport::toStr(bool expand) const { |
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const auto to_double_str = [](double val) { |
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std::stringstream ss; |
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ss << std::fixed << std::setprecision(3) << val; |
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return ss.str(); |
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}; |
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std::stringstream ss; |
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ss << name << ": warm-up: " << to_double_str(warmup_time) |
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<< " ms, execution time: " << to_double_str(elapsed) |
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<< " ms, throughput: " << to_double_str(throughput) |
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<< " FPS, latency: first: " << to_double_str(first_latency) |
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<< " ms, min: " << to_double_str(min_latency) |
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<< " ms, avg: " << to_double_str(avg_latency) |
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<< " ms, max: " << to_double_str(max_latency) |
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<< " ms, frames: " << num_late_frames << "/" << seq_ids.back()+1 << " (dropped/all)"; |
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if (expand) { |
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for (size_t i = 0; i < latencies.size(); ++i) { |
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ss << "\nFrame:" << i << "\nLatency: " |
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<< to_double_str(latencies[i]) << " ms"; |
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} |
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} |
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return ss.str(); |
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} |
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class StopCriterion { |
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public: |
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using Ptr = std::unique_ptr<StopCriterion>; |
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virtual void start() = 0; |
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virtual void iter() = 0; |
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virtual bool done() = 0; |
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virtual ~StopCriterion() = default; |
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}; |
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class Pipeline { |
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public: |
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using Ptr = std::shared_ptr<Pipeline>; |
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Pipeline(std::string&& name, |
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cv::GComputation&& comp, |
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std::shared_ptr<DummySource>&& src, |
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StopCriterion::Ptr stop_criterion, |
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cv::GCompileArgs&& args, |
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const size_t num_outputs); |
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void compile(); |
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void run(); |
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const PerfReport& report() const; |
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const std::string& name() const { return m_name;} |
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virtual ~Pipeline() = default; |
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protected: |
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virtual void _compile() = 0; |
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virtual void run_iter() = 0; |
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virtual void init() {}; |
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virtual void deinit() {}; |
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void prepareOutputs(); |
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std::string m_name; |
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cv::GComputation m_comp; |
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std::shared_ptr<DummySource> m_src; |
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StopCriterion::Ptr m_stop_criterion; |
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cv::GCompileArgs m_args; |
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size_t m_num_outputs; |
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PerfReport m_perf; |
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cv::GRunArgsP m_pipeline_outputs; |
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std::vector<cv::Mat> m_out_mats; |
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int64_t m_start_ts; |
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int64_t m_seq_id; |
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}; |
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Pipeline::Pipeline(std::string&& name, |
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cv::GComputation&& comp, |
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std::shared_ptr<DummySource>&& src, |
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StopCriterion::Ptr stop_criterion, |
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cv::GCompileArgs&& args, |
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const size_t num_outputs) |
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: m_name(std::move(name)), |
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m_comp(std::move(comp)), |
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m_src(std::move(src)), |
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m_stop_criterion(std::move(stop_criterion)), |
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m_args(std::move(args)), |
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m_num_outputs(num_outputs) { |
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m_perf.name = m_name; |
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} |
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void Pipeline::compile() { |
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m_perf.warmup_time = |
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utils::measure<utils::double_ms_t>([this]() { |
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_compile(); |
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}); |
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} |
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void Pipeline::prepareOutputs() { |
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// NB: N-2 buffers + timestamp + seq_id. |
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m_out_mats.resize(m_num_outputs - 2); |
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for (auto& m : m_out_mats) { |
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m_pipeline_outputs += cv::gout(m); |
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} |
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m_pipeline_outputs += cv::gout(m_start_ts); |
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m_pipeline_outputs += cv::gout(m_seq_id); |
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} |
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void Pipeline::run() { |
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using namespace std::chrono; |
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// NB: Allocate outputs for execution |
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prepareOutputs(); |
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// NB: Warm-up iteration invalidates source state |
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// so need to copy it |
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auto orig_src = m_src; |
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auto copy_src = std::make_shared<DummySource>(*m_src); |
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// NB: Use copy for warm-up iteration |
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m_src = copy_src; |
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// NB: Warm-up iteration |
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init(); |
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run_iter(); |
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deinit(); |
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// NB: Calculate first latency |
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m_perf.first_latency = utils::double_ms_t{ |
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microseconds{utils::timestamp<microseconds>() - m_start_ts}}.count(); |
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// NB: Now use original source |
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m_src = orig_src; |
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// NB: Start measuring execution |
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init(); |
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auto start = high_resolution_clock::now(); |
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m_stop_criterion->start(); |
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while (true) { |
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run_iter(); |
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const auto latency = utils::double_ms_t{ |
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microseconds{utils::timestamp<microseconds>() - m_start_ts}}.count(); |
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m_perf.latencies.push_back(latency); |
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m_perf.seq_ids.push_back(m_seq_id); |
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m_stop_criterion->iter(); |
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if (m_stop_criterion->done()) { |
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m_perf.elapsed = duration_cast<utils::double_ms_t>( |
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high_resolution_clock::now() - start).count(); |
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deinit(); |
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break; |
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} |
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} |
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m_perf.avg_latency = utils::avg(m_perf.latencies); |
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m_perf.min_latency = utils::min(m_perf.latencies); |
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m_perf.max_latency = utils::max(m_perf.latencies); |
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// NB: Count the number of dropped frames |
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int64_t prev_seq_id = m_perf.seq_ids[0]; |
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for (size_t i = 1; i < m_perf.seq_ids.size(); ++i) { |
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m_perf.num_late_frames += m_perf.seq_ids[i] - prev_seq_id - 1; |
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prev_seq_id = m_perf.seq_ids[i]; |
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} |
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m_perf.throughput = (m_perf.latencies.size() / m_perf.elapsed) * 1000; |
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} |
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const PerfReport& Pipeline::report() const { |
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return m_perf; |
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} |
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class StreamingPipeline : public Pipeline { |
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public: |
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using Pipeline::Pipeline; |
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private: |
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void _compile() override { |
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m_compiled = |
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m_comp.compileStreaming({m_src->descr_of()}, |
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cv::GCompileArgs(m_args)); |
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} |
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virtual void init() override { |
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m_compiled.setSource(m_src); |
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m_compiled.start(); |
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} |
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virtual void deinit() override { |
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m_compiled.stop(); |
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} |
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virtual void run_iter() override { |
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m_compiled.pull(cv::GRunArgsP{m_pipeline_outputs}); |
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} |
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cv::GStreamingCompiled m_compiled; |
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}; |
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class RegularPipeline : public Pipeline { |
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public: |
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using Pipeline::Pipeline; |
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private: |
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void _compile() override { |
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m_compiled = |
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m_comp.compile({m_src->descr_of()}, |
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cv::GCompileArgs(m_args)); |
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} |
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virtual void run_iter() override { |
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cv::gapi::wip::Data data; |
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m_src->pull(data); |
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m_compiled({data}, cv::GRunArgsP{m_pipeline_outputs}); |
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} |
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cv::GCompiled m_compiled; |
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}; |
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enum class PLMode { |
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REGULAR, |
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STREAMING |
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}; |
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#endif // OPENCV_GAPI_PIPELINE_MODELING_TOOL_PIPELINE_HPP
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