diff options
Diffstat (limited to 'source/use_case/kws/src/UseCaseHandler.cc')
| -rw-r--r-- | source/use_case/kws/src/UseCaseHandler.cc | 30 |
1 files changed, 21 insertions, 9 deletions
diff --git a/source/use_case/kws/src/UseCaseHandler.cc b/source/use_case/kws/src/UseCaseHandler.cc index 872d323..d2cba55 100644 --- a/source/use_case/kws/src/UseCaseHandler.cc +++ b/source/use_case/kws/src/UseCaseHandler.cc @@ -82,6 +82,7 @@ namespace app { bool ClassifyAudioHandler(ApplicationContext& ctx, uint32_t clipIndex, bool runAll) { auto& platform = ctx.Get<hal_platform&>("platform"); + auto& profiler = ctx.Get<Profiler&>("profiler"); constexpr uint32_t dataPsnTxtInfStartX = 20; constexpr uint32_t dataPsnTxtInfStartY = 40; @@ -215,7 +216,7 @@ namespace app { audioDataSlider.TotalStrides() + 1); /* Run inference over this audio clip sliding window. */ - arm::app::RunInference(platform, model); + arm::app::RunInference(model, profiler); std::vector<ClassificationResult> classificationResult; auto& classifier = ctx.Get<KwsClassifier&>("classifier"); @@ -243,6 +244,8 @@ namespace app { return false; } + profiler.PrintProfilingResult(); + _IncrementAppCtxClipIdx(ctx); } while (runAll && ctx.Get<uint32_t>("clipIndex") != startClipIdx); @@ -281,6 +284,8 @@ namespace app { constexpr uint32_t dataPsnTxtYIncr = 16; /* Row index increment. */ platform.data_psn->set_text_color(COLOR_GREEN); + info("Final results:\n"); + info("Total number of inferences: %zu\n", results.size()); /* Display each result */ uint32_t rowIdx1 = dataPsnTxtStartY1 + 2 * dataPsnTxtYIncr; @@ -290,7 +295,7 @@ namespace app { std::string topKeyword{"<none>"}; float score = 0.f; - if (results[i].m_resultVec.size()) { + if (!results[i].m_resultVec.empty()) { topKeyword = results[i].m_resultVec[0].m_label; score = results[i].m_resultVec[0].m_normalisedVal; } @@ -305,13 +310,20 @@ namespace app { dataPsnTxtStartX1, rowIdx1, false); rowIdx1 += dataPsnTxtYIncr; - info("For timestamp: %f (inference #: %u); threshold: %f\n", - results[i].m_timeStamp, results[i].m_inferenceNumber, - results[i].m_threshold); - for (uint32_t j = 0; j < results[i].m_resultVec.size(); ++j) { - info("\t\tlabel @ %u: %s, score: %f\n", j, - results[i].m_resultVec[j].m_label.c_str(), - results[i].m_resultVec[j].m_normalisedVal); + if (results[i].m_resultVec.empty()) { + info("For timestamp: %f (inference #: %u); label: %s; threshold: %f\n", + results[i].m_timeStamp, results[i].m_inferenceNumber, + topKeyword.c_str(), + results[i].m_threshold); + } else { + for (uint32_t j = 0; j < results[i].m_resultVec.size(); ++j) { + info("For timestamp: %f (inference #: %u); label: %s, score: %f; threshold: %f\n", + results[i].m_timeStamp, + results[i].m_inferenceNumber, + results[i].m_resultVec[j].m_label.c_str(), + results[i].m_resultVec[j].m_normalisedVal, + results[i].m_threshold); + } } } |