blob: 763578be3c8a5da3f283697eb711c3b1fab16d7b [file] [log] [blame]
//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include <reference/workloads/DetectionPostProcess.hpp>
#include <armnn/Descriptors.hpp>
#include <armnn/Types.hpp>
#include <doctest/doctest.h>
TEST_SUITE("RefDetectionPostProcess")
{
TEST_CASE("TopKSortTest")
{
unsigned int k = 3;
unsigned int indices[8] = { 0, 1, 2, 3, 4, 5, 6, 7 };
float values[8] = { 0, 7, 6, 5, 4, 3, 2, 500 };
armnn::TopKSort(k, indices, values, 8);
CHECK(indices[0] == 7);
CHECK(indices[1] == 1);
CHECK(indices[2] == 2);
}
TEST_CASE("FullTopKSortTest")
{
unsigned int k = 8;
unsigned int indices[8] = { 0, 1, 2, 3, 4, 5, 6, 7 };
float values[8] = { 0, 7, 6, 5, 4, 3, 2, 500 };
armnn::TopKSort(k, indices, values, 8);
CHECK(indices[0] == 7);
CHECK(indices[1] == 1);
CHECK(indices[2] == 2);
CHECK(indices[3] == 3);
CHECK(indices[4] == 4);
CHECK(indices[5] == 5);
CHECK(indices[6] == 6);
CHECK(indices[7] == 0);
}
TEST_CASE("IouTest")
{
float boxI[4] = { 0.0f, 0.0f, 10.0f, 10.0f };
float boxJ[4] = { 1.0f, 1.0f, 11.0f, 11.0f };
float iou = armnn::IntersectionOverUnion(boxI, boxJ);
CHECK(iou == doctest::Approx(0.68).epsilon(0.001f));
}
TEST_CASE("NmsFunction")
{
std::vector<float> boxCorners({
0.0f, 0.0f, 1.0f, 1.0f,
0.0f, 0.1f, 1.0f, 1.1f,
0.0f, -0.1f, 1.0f, 0.9f,
0.0f, 10.0f, 1.0f, 11.0f,
0.0f, 10.1f, 1.0f, 11.1f,
0.0f, 100.0f, 1.0f, 101.0f
});
std::vector<float> scores({ 0.9f, 0.75f, 0.6f, 0.93f, 0.5f, 0.3f });
std::vector<unsigned int> result =
armnn::NonMaxSuppression(6, boxCorners, scores, 0.0, 3, 0.5);
CHECK(result.size() == 3);
CHECK(result[0] == 3);
CHECK(result[1] == 0);
CHECK(result[2] == 5);
}
void DetectionPostProcessTestImpl(bool useRegularNms,
const std::vector<float>& expectedDetectionBoxes,
const std::vector<float>& expectedDetectionClasses,
const std::vector<float>& expectedDetectionScores,
const std::vector<float>& expectedNumDetections)
{
armnn::TensorInfo boxEncodingsInfo({ 1, 6, 4 }, armnn::DataType::Float32);
armnn::TensorInfo scoresInfo({ 1, 6, 3 }, armnn::DataType::Float32);
armnn::TensorInfo anchorsInfo({ 6, 4 }, armnn::DataType::Float32);
armnn::TensorInfo detectionBoxesInfo({ 1, 3, 4 }, armnn::DataType::Float32);
armnn::TensorInfo detectionScoresInfo({ 1, 3 }, armnn::DataType::Float32);
armnn::TensorInfo detectionClassesInfo({ 1, 3 }, armnn::DataType::Float32);
armnn::TensorInfo numDetectionInfo({ 1 }, armnn::DataType::Float32);
armnn::DetectionPostProcessDescriptor desc;
desc.m_UseRegularNms = useRegularNms;
desc.m_MaxDetections = 3;
desc.m_MaxClassesPerDetection = 1;
desc.m_DetectionsPerClass =1;
desc.m_NmsScoreThreshold = 0.0;
desc.m_NmsIouThreshold = 0.5;
desc.m_NumClasses = 2;
desc.m_ScaleY = 10.0;
desc.m_ScaleX = 10.0;
desc.m_ScaleH = 5.0;
desc.m_ScaleW = 5.0;
std::vector<float> boxEncodings({
0.0f, 0.0f, 0.0f, 0.0f,
0.0f, 1.0f, 0.0f, 0.0f,
0.0f, -1.0f, 0.0f, 0.0f,
0.0f, 0.0f, 0.0f, 0.0f,
0.0f, 1.0f, 0.0f, 0.0f,
0.0f, 0.0f, 0.0f, 0.0f
});
std::vector<float> scores({
0.0f, 0.9f, 0.8f,
0.0f, 0.75f, 0.72f,
0.0f, 0.6f, 0.5f,
0.0f, 0.93f, 0.95f,
0.0f, 0.5f, 0.4f,
0.0f, 0.3f, 0.2f
});
std::vector<float> anchors({
0.5f, 0.5f, 1.0f, 1.0f,
0.5f, 0.5f, 1.0f, 1.0f,
0.5f, 0.5f, 1.0f, 1.0f,
0.5f, 10.5f, 1.0f, 1.0f,
0.5f, 10.5f, 1.0f, 1.0f,
0.5f, 100.5f, 1.0f, 1.0f
});
auto boxEncodingsDecoder = armnn::MakeDecoder<float>(boxEncodingsInfo, boxEncodings.data());
auto scoresDecoder = armnn::MakeDecoder<float>(scoresInfo, scores.data());
auto anchorsDecoder = armnn::MakeDecoder<float>(anchorsInfo, anchors.data());
std::vector<float> detectionBoxes(detectionBoxesInfo.GetNumElements());
std::vector<float> detectionScores(detectionScoresInfo.GetNumElements());
std::vector<float> detectionClasses(detectionClassesInfo.GetNumElements());
std::vector<float> numDetections(1);
armnn::DetectionPostProcess(boxEncodingsInfo,
scoresInfo,
anchorsInfo,
detectionBoxesInfo,
detectionClassesInfo,
detectionScoresInfo,
numDetectionInfo,
desc,
*boxEncodingsDecoder,
*scoresDecoder,
*anchorsDecoder,
detectionBoxes.data(),
detectionClasses.data(),
detectionScores.data(),
numDetections.data());
CHECK(std::equal(detectionBoxes.begin(),
detectionBoxes.end(),
expectedDetectionBoxes.begin(),
expectedDetectionBoxes.end()));
CHECK(std::equal(detectionScores.begin(), detectionScores.end(),
expectedDetectionScores.begin(), expectedDetectionScores.end()));
CHECK(std::equal(detectionClasses.begin(), detectionClasses.end(),
expectedDetectionClasses.begin(), expectedDetectionClasses.end()));
CHECK(std::equal(numDetections.begin(), numDetections.end(),
expectedNumDetections.begin(), expectedNumDetections.end()));
}
TEST_CASE("RegularNmsDetectionPostProcess")
{
std::vector<float> expectedDetectionBoxes({
0.0f, 10.0f, 1.0f, 11.0f,
0.0f, 10.0f, 1.0f, 11.0f,
0.0f, 0.0f, 0.0f, 0.0f
});
std::vector<float> expectedDetectionScores({ 0.95f, 0.93f, 0.0f });
std::vector<float> expectedDetectionClasses({ 1.0f, 0.0f, 0.0f });
std::vector<float> expectedNumDetections({ 2.0f });
DetectionPostProcessTestImpl(true, expectedDetectionBoxes, expectedDetectionClasses,
expectedDetectionScores, expectedNumDetections);
}
TEST_CASE("FastNmsDetectionPostProcess")
{
std::vector<float> expectedDetectionBoxes({
0.0f, 10.0f, 1.0f, 11.0f,
0.0f, 0.0f, 1.0f, 1.0f,
0.0f, 100.0f, 1.0f, 101.0f
});
std::vector<float> expectedDetectionScores({ 0.95f, 0.9f, 0.3f });
std::vector<float> expectedDetectionClasses({ 1.0f, 0.0f, 0.0f });
std::vector<float> expectedNumDetections({ 3.0f });
DetectionPostProcessTestImpl(false, expectedDetectionBoxes, expectedDetectionClasses,
expectedDetectionScores, expectedNumDetections);
}
}