diff options
Diffstat (limited to 'samples/ObjectDetection/src')
| -rw-r--r-- | samples/ObjectDetection/src/Main.cpp | 15 | ||||
| -rw-r--r-- | samples/ObjectDetection/src/ObjectDetectionPipeline.cpp | 26 |
2 files changed, 26 insertions, 15 deletions
diff --git a/samples/ObjectDetection/src/Main.cpp b/samples/ObjectDetection/src/Main.cpp index e057981550..8bc2f0de38 100644 --- a/samples/ObjectDetection/src/Main.cpp +++ b/samples/ObjectDetection/src/Main.cpp @@ -20,6 +20,7 @@ const std::string MODEL_FILE_PATH = "--model-file-path"; const std::string OUTPUT_VIDEO_FILE_PATH = "--output-video-file-path"; const std::string LABEL_PATH = "--label-path"; const std::string PREFERRED_BACKENDS = "--preferred-backends"; +const std::string PROFILING_ENABLED = "--profiling_enabled"; const std::string HELP = "--help"; /* @@ -29,13 +30,16 @@ static std::map<std::string, std::string> CMD_OPTIONS = { {VIDEO_FILE_PATH, "[REQUIRED] Path to the video file to run object detection on"}, {MODEL_FILE_PATH, "[REQUIRED] Path to the Object Detection model to use"}, {LABEL_PATH, "[REQUIRED] Path to the label set for the provided model file. " - "Label file is should just be an ordered list, seperated by new line."}, + "Label file should be an ordered list, separated by a new line."}, {MODEL_NAME, "[REQUIRED] The name of the model being used. Accepted options: YOLO_V3_TINY, SSD_MOBILE"}, {OUTPUT_VIDEO_FILE_PATH, "[OPTIONAL] Path to the output video file with detections added in. " "If specified will save file to disk, else displays the output to screen"}, {PREFERRED_BACKENDS, "[OPTIONAL] Takes the preferred backends in preference order, separated by comma." " For example: CpuAcc,GpuAcc,CpuRef. Accepted options: [CpuAcc, CpuRef, GpuAcc]." - " Defaults to CpuAcc,CpuRef"} + " Defaults to CpuAcc,CpuRef"}, + {PROFILING_ENABLED, "[OPTIONAL] Enabling this option will print important ML related milestones timing" + "information in micro-seconds. By default, this option is disabled." + "Accepted options are true/false."} }; /* @@ -137,6 +141,10 @@ int main(int argc, char *argv[]) pipelineOptions.m_ModelFilePath = GetSpecifiedOption(options, MODEL_FILE_PATH); pipelineOptions.m_ModelName = GetSpecifiedOption(options, MODEL_NAME); + if (CheckOptionSpecified(options, PROFILING_ENABLED)) + { + pipelineOptions.m_ProfilingEnabled = GetSpecifiedOption(options, PROFILING_ENABLED) == "true"; + } if(CheckOptionSpecified(options, PREFERRED_BACKENDS)) { pipelineOptions.m_backends = GetPreferredBackendList((GetSpecifiedOption(options, PREFERRED_BACKENDS))); @@ -148,6 +156,8 @@ int main(int argc, char *argv[]) auto labels = AssignColourToLabel(GetSpecifiedOption(options, LABEL_PATH)); + common::Profiling profiling(pipelineOptions.m_ProfilingEnabled); + profiling.ProfilingStart(); od::IPipelinePtr objectDetectionPipeline = od::CreatePipeline(pipelineOptions); auto inputAndOutput = GetFrameSourceAndSink(options); @@ -180,5 +190,6 @@ int main(int argc, char *argv[]) frame = reader->ReadFrame(); } sink->Close(); + profiling.ProfilingStopAndPrintUs("Overall compute time"); return 0; } diff --git a/samples/ObjectDetection/src/ObjectDetectionPipeline.cpp b/samples/ObjectDetection/src/ObjectDetectionPipeline.cpp index 077caa40cb..2c4a76d35a 100644 --- a/samples/ObjectDetection/src/ObjectDetectionPipeline.cpp +++ b/samples/ObjectDetection/src/ObjectDetectionPipeline.cpp @@ -11,8 +11,8 @@ namespace od ObjDetectionPipeline::ObjDetectionPipeline(std::unique_ptr<common::ArmnnNetworkExecutor<float>> executor, std::unique_ptr<IDetectionResultDecoder> decoder) : - m_executor(std::move(executor)), - m_decoder(std::move(decoder)){} + m_executor(std::move(executor)), + m_decoder(std::move(decoder)){} void od::ObjDetectionPipeline::Inference(const cv::Mat& processed, common::InferenceResults<float>& result) { @@ -39,8 +39,8 @@ void ObjDetectionPipeline::PreProcessing(const cv::Mat& frame, cv::Mat& processe MobileNetSSDv1::MobileNetSSDv1(std::unique_ptr<common::ArmnnNetworkExecutor<float>> executor, float objectThreshold) : - ObjDetectionPipeline(std::move(executor), - std::make_unique<SSDResultDecoder>(objectThreshold)) + ObjDetectionPipeline(std::move(executor), + std::make_unique<SSDResultDecoder>(objectThreshold)) {} void MobileNetSSDv1::PreProcessing(const cv::Mat& frame, cv::Mat& processed) @@ -52,13 +52,12 @@ void MobileNetSSDv1::PreProcessing(const cv::Mat& frame, cv::Mat& processed) processed.convertTo(processed, CV_32FC3, 1 / 127.5, -1); } } - YoloV3Tiny::YoloV3Tiny(std::unique_ptr<common::ArmnnNetworkExecutor<float>> executor, float NMSThreshold, float ClsThreshold, float ObjectThreshold) : - ObjDetectionPipeline(std::move(executor), - std::move(std::make_unique<YoloResultDecoder>(NMSThreshold, - ClsThreshold, - ObjectThreshold))) + ObjDetectionPipeline(std::move(executor), + std::move(std::make_unique<YoloResultDecoder>(NMSThreshold, + ClsThreshold, + ObjectThreshold))) {} void YoloV3Tiny::PreProcessing(const cv::Mat& frame, cv::Mat& processed) @@ -72,11 +71,12 @@ void YoloV3Tiny::PreProcessing(const cv::Mat& frame, cv::Mat& processed) IPipelinePtr CreatePipeline(common::PipelineOptions& config) { - auto executor = std::make_unique<common::ArmnnNetworkExecutor<float>>(config.m_ModelFilePath, config.m_backends); - + auto executor = std::make_unique<common::ArmnnNetworkExecutor<float>>(config.m_ModelFilePath, + config.m_backends, + config.m_ProfilingEnabled); if (config.m_ModelName == "SSD_MOBILE") { - float detectionThreshold = 0.6; + float detectionThreshold = 0.5; return std::make_unique<od::MobileNetSSDv1>(std::move(executor), detectionThreshold @@ -99,4 +99,4 @@ IPipelinePtr CreatePipeline(common::PipelineOptions& config) } } -}// namespace od
\ No newline at end of file +}// namespace od |