MLECO-1252 ASR sample application using the public ArmNN C++ API.
Change-Id: I98cd505b8772a8c8fa88308121bc94135bb45068
Signed-off-by: Éanna Ó Catháin <eanna.ocathain@arm.com>
diff --git a/samples/ObjectDetection/src/Main.cpp b/samples/ObjectDetection/src/Main.cpp
index 10abb65..e057981 100644
--- a/samples/ObjectDetection/src/Main.cpp
+++ b/samples/ObjectDetection/src/Main.cpp
@@ -6,7 +6,7 @@
#include "CvVideoFrameReader.hpp"
#include "CvWindowOutput.hpp"
#include "CvVideoFileWriter.hpp"
-#include "NetworkPipeline.hpp"
+#include "ObjectDetectionPipeline.hpp"
#include "CmdArgsParser.hpp"
#include <fstream>
@@ -14,6 +14,30 @@
#include <map>
#include <random>
+const std::string MODEL_NAME = "--model-name";
+const std::string VIDEO_FILE_PATH = "--video-file-path";
+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 HELP = "--help";
+
+/*
+ * The accepted options for this Object detection executable
+ */
+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."},
+ {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"}
+};
+
/*
* Reads the user supplied backend preference, splits it by comma, and returns an ordered vector
*/
@@ -34,10 +58,10 @@
/*
* Assigns a color to each label in the label set
*/
-std::vector<std::tuple<std::string, od::BBoxColor>> AssignColourToLabel(const std::string& pathToLabelFile)
+std::vector<std::tuple<std::string, common::BBoxColor>> AssignColourToLabel(const std::string& pathToLabelFile)
{
std::ifstream in(pathToLabelFile);
- std::vector<std::tuple<std::string, od::BBoxColor>> labels;
+ std::vector<std::tuple<std::string, common::BBoxColor>> labels;
std::string str;
std::default_random_engine generator;
@@ -47,7 +71,7 @@
{
if(!str.empty())
{
- od::BBoxColor c{
+ common::BBoxColor c{
.colorCode = std::make_tuple(distribution(generator),
distribution(generator),
distribution(generator))
@@ -60,13 +84,13 @@
return labels;
}
-std::tuple<std::unique_ptr<od::IFrameReader<cv::Mat>>,
- std::unique_ptr<od::IFrameOutput<cv::Mat>>>
+std::tuple<std::unique_ptr<common::IFrameReader<cv::Mat>>,
+ std::unique_ptr<common::IFrameOutput<cv::Mat>>>
GetFrameSourceAndSink(const std::map<std::string, std::string>& options) {
- std::unique_ptr<od::IFrameReader<cv::Mat>> readerPtr;
+ std::unique_ptr<common::IFrameReader<cv::Mat>> readerPtr;
- std::unique_ptr<od::CvVideoFrameReader> reader = std::make_unique<od::CvVideoFrameReader>();
+ std::unique_ptr<common::CvVideoFrameReader> reader = std::make_unique<common::CvVideoFrameReader>();
reader->Init(GetSpecifiedOption(options, VIDEO_FILE_PATH));
auto enc = reader->GetSourceEncodingInt();
@@ -75,7 +99,7 @@
auto h = reader->GetSourceHeight();
if (!reader->ConvertToRGB())
{
- readerPtr = std::move(std::make_unique<od::CvVideoFrameReaderRgbWrapper>(std::move(reader)));
+ readerPtr = std::move(std::make_unique<common::CvVideoFrameReaderRgbWrapper>(std::move(reader)));
}
else
{
@@ -85,14 +109,14 @@
if(CheckOptionSpecified(options, OUTPUT_VIDEO_FILE_PATH))
{
std::string outputVideo = GetSpecifiedOption(options, OUTPUT_VIDEO_FILE_PATH);
- auto writer = std::make_unique<od::CvVideoFileWriter>();
+ auto writer = std::make_unique<common::CvVideoFileWriter>();
writer->Init(outputVideo, enc, fps, w, h);
return std::make_tuple<>(std::move(readerPtr), std::move(writer));
}
else
{
- auto writer = std::make_unique<od::CvWindowOutput>();
+ auto writer = std::make_unique<common::CvWindowOutput>();
writer->Init("Processed Video");
return std::make_tuple<>(std::move(readerPtr), std::move(writer));
}
@@ -109,7 +133,7 @@
}
// Create the network options
- od::ODPipelineOptions pipelineOptions;
+ common::PipelineOptions pipelineOptions;
pipelineOptions.m_ModelFilePath = GetSpecifiedOption(options, MODEL_FILE_PATH);
pipelineOptions.m_ModelName = GetSpecifiedOption(options, MODEL_NAME);
@@ -127,8 +151,8 @@
od::IPipelinePtr objectDetectionPipeline = od::CreatePipeline(pipelineOptions);
auto inputAndOutput = GetFrameSourceAndSink(options);
- std::unique_ptr<od::IFrameReader<cv::Mat>> reader = std::move(std::get<0>(inputAndOutput));
- std::unique_ptr<od::IFrameOutput<cv::Mat>> sink = std::move(std::get<1>(inputAndOutput));
+ std::unique_ptr<common::IFrameReader<cv::Mat>> reader = std::move(std::get<0>(inputAndOutput));
+ std::unique_ptr<common::IFrameOutput<cv::Mat>> sink = std::move(std::get<1>(inputAndOutput));
if (!sink->IsReady())
{
@@ -136,7 +160,7 @@
return 1;
}
- od::InferenceResults results;
+ common::InferenceResults<float> results;
std::shared_ptr<cv::Mat> frame = reader->ReadFrame();