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//
// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include <catch.hpp>
#include <opencv2/opencv.hpp>
#include "ArmnnNetworkExecutor.hpp"
#include "Types.hpp"
#include "ImageUtils.hpp"
#include "SSDResultDecoder.hpp"
#include "YoloResultDecoder.hpp"
using namespace std;
static string GetResourceFilePath(const string& filename)
{
string testResources = TEST_RESOURCE_DIR;
if(testResources.back() != '/')
{
return testResources + "/" + filename;
}
else
{
return testResources + filename;
}
}
TEST_CASE("Test Delegate Execution SSD_MOBILE")
{
string testResources = TEST_RESOURCE_DIR;
REQUIRE(testResources != "");
vector<armnn::BackendId> m_backends = {"CpuRef"};
string file_path = GetResourceFilePath("ssd_mobilenet_v1.tflite");
common::InferenceResults<float> results;
cv::Mat processed;
cv::Mat cache;
float detectionThreshold = 0.6;
common::Profiling profiling(true);
profiling.ProfilingStart();
auto executor = make_unique<common::ArmnnNetworkExecutor<float>>(file_path, m_backends, true);
int width = executor->GetImageAspectRatio().m_Width;
int height = executor->GetImageAspectRatio().m_Height;
od::SSDResultDecoder ssdResult(detectionThreshold);
/* check GetInputDataType */
CHECK(executor->GetInputDataType() == armnn::DataType::QAsymmU8);
/* check GetImageAspectRatio */
CHECK(width == 300);
CHECK(height == 300);
cv::Mat inputFrame = cv::imread(GetResourceFilePath("basketball1.png"), cv::IMREAD_COLOR);
cv::cvtColor(inputFrame, inputFrame, cv::COLOR_BGR2RGB);
ResizeWithPad(inputFrame, processed, cache, common::Size(width,height));
CHECK(executor->Run(processed.data, processed.total() * processed.elemSize(), results) == true);
od::DetectedObjects detections = ssdResult.Decode(results,
common::Size(inputFrame.size().width, inputFrame.size().height),
common::Size(width, height), {});
/* Make sure we've found 2 persons in the image */
CHECK(detections.size() == 2 );
CHECK(detections[0].GetLabel() == "0");
CHECK(detections[1].GetLabel() == "0");
/* check GetQuantizationScale */
CHECK(to_string(executor->GetQuantizationScale()) == string("0.007812"));
/* check GetQuantizationOffset */
CHECK(executor->GetQuantizationOffset() == 128);
/* check GetQuantizationScale */
CHECK(executor->GetOutputQuantizationScale(0) == 0.0f);
/* check GetOutputQuantizationOffset */
CHECK(executor->GetOutputQuantizationOffset(0) == 0);
profiling.ProfilingStopAndPrintUs("Overall test");
}
TEST_CASE("Test Delegate Execution YOLO_V3")
{
string testResources = TEST_RESOURCE_DIR;
REQUIRE(testResources != "");
vector<armnn::BackendId> m_backends = {"CpuRef"};
string file_path = GetResourceFilePath("yolo_v3_tiny_darknet_fp32.tflite");
common::InferenceResults<float> results;
cv::Mat processed;
cv::Mat cache;
float NMSThreshold = 0.3f;
float ClsThreshold = 0.3f;
float ObjectThreshold = 0.3f;
auto executor = make_unique<common::ArmnnNetworkExecutor<float>>(file_path, m_backends);
int width = executor->GetImageAspectRatio().m_Width;
int height = executor->GetImageAspectRatio().m_Height;
od::YoloResultDecoder yoloResult(NMSThreshold, ClsThreshold, ObjectThreshold);
/* check GetInputDataType */
CHECK(executor->GetInputDataType() == armnn::DataType::Float32);
/* check GetImageAspectRatio */
CHECK(width == 416);
CHECK(height == 416);
/* read the image */
cv::Mat inputFrame = cv::imread(GetResourceFilePath("basketball1.png"), cv::IMREAD_COLOR);
/* resize it according to the the input tensor requirments */
ResizeWithPad(inputFrame, processed, cache, common::Size(width,height));
/* converting to 3 channel matrix of 32 bits floats */
processed.convertTo(processed, CV_32FC3);
/* run the inference */
CHECK(executor->Run(processed.data, processed.total() * processed.elemSize(), results) == true);
/* decode the results */
od::DetectedObjects detections = yoloResult.Decode(results,
common::Size(inputFrame.size().width, inputFrame.size().height),
common::Size(width, height), {});
/* Make sure we've found 2 persons in the image */
CHECK(detections.size() == 2 );
CHECK(detections[0].GetLabel() == "0");
CHECK(detections[1].GetLabel() == "0");
/* check GetQuantizationScale */
CHECK(to_string(executor->GetQuantizationScale()) == string("0.000000"));
/* check GetQuantizationOffset */
CHECK(executor->GetQuantizationOffset() == 0);
/* check GetQuantizationScale */
CHECK(executor->GetOutputQuantizationScale(0) == 0.0f);
/* check GetOutputQuantizationOffset */
CHECK(executor->GetOutputQuantizationOffset(0) == 0);
}
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