diff options
Diffstat (limited to 'source/use_case/kws/src/UseCaseHandler.cc')
| -rw-r--r-- | source/use_case/kws/src/UseCaseHandler.cc | 124 |
1 files changed, 60 insertions, 64 deletions
diff --git a/source/use_case/kws/src/UseCaseHandler.cc b/source/use_case/kws/src/UseCaseHandler.cc index 8dd7724..e04cefc 100644 --- a/source/use_case/kws/src/UseCaseHandler.cc +++ b/source/use_case/kws/src/UseCaseHandler.cc @@ -35,16 +35,14 @@ using KwsClassifier = arm::app::Classifier; namespace arm { namespace app { - + /** * @brief Presents inference results using the data presentation * object. - * @param[in] platform Reference to the hal platform object. * @param[in] results Vector of classification results to be displayed. * @return true if successful, false otherwise. **/ - static bool PresentInferenceResult(hal_platform& platform, - const std::vector<arm::app::kws::KwsResult>& results); + static bool PresentInferenceResult(const std::vector<arm::app::kws::KwsResult>& results); /** * @brief Returns a function to perform feature calculation and populates input tensor data with @@ -68,7 +66,6 @@ namespace app { /* Audio inference handler. */ 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; @@ -137,7 +134,7 @@ namespace app { const float secondsPerSample = 1.0/audio::MicroNetKwsMFCC::ms_defaultSamplingFreq; do { - platform.data_psn->clear(COLOR_BLACK); + hal_lcd_clear(COLOR_BLACK); auto currentIndex = ctx.Get<uint32_t>("clipIndex"); @@ -171,7 +168,7 @@ namespace app { /* Display message on the LCD - inference running. */ std::string str_inf{"Running inference... "}; - platform.data_psn->present_data_text( + hal_lcd_display_text( str_inf.c_str(), str_inf.size(), dataPsnTxtInfStartX, dataPsnTxtInfStartY, 0); info("Running inference on audio clip %" PRIu32 " => %s\n", currentIndex, @@ -223,13 +220,13 @@ namespace app { /* Erase. */ str_inf = std::string(str_inf.size(), ' '); - platform.data_psn->present_data_text( + hal_lcd_display_text( str_inf.c_str(), str_inf.size(), dataPsnTxtInfStartX, dataPsnTxtInfStartY, false); ctx.Set<std::vector<arm::app::kws::KwsResult>>("results", results); - if (!PresentInferenceResult(platform, results)) { + if (!PresentInferenceResult(results)) { return false; } @@ -242,61 +239,6 @@ namespace app { return true; } - static bool PresentInferenceResult(hal_platform& platform, - const std::vector<arm::app::kws::KwsResult>& results) - { - constexpr uint32_t dataPsnTxtStartX1 = 20; - constexpr uint32_t dataPsnTxtStartY1 = 30; - 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; - - for (uint32_t i = 0; i < results.size(); ++i) { - - std::string topKeyword{"<none>"}; - float score = 0.f; - if (!results[i].m_resultVec.empty()) { - topKeyword = results[i].m_resultVec[0].m_label; - score = results[i].m_resultVec[0].m_normalisedVal; - } - - std::string resultStr = - std::string{"@"} + std::to_string(results[i].m_timeStamp) + - std::string{"s: "} + topKeyword + std::string{" ("} + - std::to_string(static_cast<int>(score * 100)) + std::string{"%)"}; - - platform.data_psn->present_data_text( - resultStr.c_str(), resultStr.size(), - dataPsnTxtStartX1, rowIdx1, false); - rowIdx1 += dataPsnTxtYIncr; - - if (results[i].m_resultVec.empty()) { - info("For timestamp: %f (inference #: %" PRIu32 - "); 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 #: %" PRIu32 - "); 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); - } - } - } - - return true; - } - /** * @brief Generic feature calculator factory. * @@ -344,6 +286,60 @@ namespace app { }; } + static bool PresentInferenceResult(const std::vector<arm::app::kws::KwsResult>& results) + { + constexpr uint32_t dataPsnTxtStartX1 = 20; + constexpr uint32_t dataPsnTxtStartY1 = 30; + constexpr uint32_t dataPsnTxtYIncr = 16; /* Row index increment. */ + + hal_lcd_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; + + for (uint32_t i = 0; i < results.size(); ++i) { + + std::string topKeyword{"<none>"}; + float score = 0.f; + if (!results[i].m_resultVec.empty()) { + topKeyword = results[i].m_resultVec[0].m_label; + score = results[i].m_resultVec[0].m_normalisedVal; + } + + std::string resultStr = + std::string{"@"} + std::to_string(results[i].m_timeStamp) + + std::string{"s: "} + topKeyword + std::string{" ("} + + std::to_string(static_cast<int>(score * 100)) + std::string{"%)"}; + + hal_lcd_display_text( + resultStr.c_str(), resultStr.size(), + dataPsnTxtStartX1, rowIdx1, false); + rowIdx1 += dataPsnTxtYIncr; + + if (results[i].m_resultVec.empty()) { + info("For timestamp: %f (inference #: %" PRIu32 + "); 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 #: %" PRIu32 + "); 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); + } + } + } + + return true; + } + template std::function<void (std::vector<int16_t>&, size_t , bool, size_t)> FeatureCalc<int8_t>(TfLiteTensor* inputTensor, size_t cacheSize, |