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opencv/modules/3d/test/test_odometry.cpp
Rostislav Vasilikhin 285218915c msvc cast warnings
2023-01-27 17:20:12 +01:00

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// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html
#include "test_precomp.hpp"
namespace opencv_test { namespace {
static
void dilateFrame(Mat& image, Mat& depth)
{
CV_Assert(!image.empty());
CV_Assert(image.type() == CV_8UC1);
CV_Assert(!depth.empty());
CV_Assert(depth.type() == CV_32FC1);
CV_Assert(depth.size() == image.size());
Mat mask(image.size(), CV_8UC1, Scalar(255));
for(int y = 0; y < depth.rows; y++)
for(int x = 0; x < depth.cols; x++)
if(cvIsNaN(depth.at<float>(y,x)) || depth.at<float>(y,x) > 10 || depth.at<float>(y,x) <= FLT_EPSILON)
mask.at<uchar>(y,x) = 0;
image.setTo(255, ~mask);
Mat minImage;
erode(image, minImage, Mat());
image.setTo(0, ~mask);
Mat maxImage;
dilate(image, maxImage, Mat());
depth.setTo(FLT_MAX, ~mask);
Mat minDepth;
erode(depth, minDepth, Mat());
depth.setTo(0, ~mask);
Mat maxDepth;
dilate(depth, maxDepth, Mat());
Mat dilatedMask;
dilate(mask, dilatedMask, Mat(), Point(-1,-1), 1);
for(int y = 0; y < depth.rows; y++)
for(int x = 0; x < depth.cols; x++)
if(!mask.at<uchar>(y,x) && dilatedMask.at<uchar>(y,x))
{
image.at<uchar>(y,x) = static_cast<uchar>(0.5f * (static_cast<float>(minImage.at<uchar>(y,x)) +
static_cast<float>(maxImage.at<uchar>(y,x))));
depth.at<float>(y,x) = 0.5f * (minDepth.at<float>(y,x) + maxDepth.at<float>(y,x));
}
}
class OdometryTest
{
public:
OdometryTest(OdometryType _otype,
OdometryAlgoType _algtype,
double _maxError1,
double _maxError5,
double _idError = DBL_EPSILON) :
otype(_otype),
algtype(_algtype),
maxError1(_maxError1),
maxError5(_maxError5),
idError(_idError)
{ }
void readData(Mat& image, Mat& depth) const;
static Mat getCameraMatrix()
{
float fx = 525.0f, // default
fy = 525.0f,
cx = 319.5f,
cy = 239.5f;
Matx33f K(fx, 0, cx,
0, fy, cy,
0, 0, 1);
return Mat(K);
}
static void generateRandomTransformation(Mat& R, Mat& t);
void run();
void checkUMats();
void prepareFrameCheck();
OdometryType otype;
OdometryAlgoType algtype;
double maxError1;
double maxError5;
double idError;
};
void OdometryTest::readData(Mat& image, Mat& depth) const
{
std::string dataPath = cvtest::TS::ptr()->get_data_path();
std::string imageFilename = dataPath + "/cv/rgbd/rgb.png";
std::string depthFilename = dataPath + "/cv/rgbd/depth.png";
image = imread(imageFilename, 0);
depth = imread(depthFilename, -1);
ASSERT_FALSE(image.empty()) << "Image " << imageFilename.c_str() << " can not be read" << std::endl;
ASSERT_FALSE(depth.empty()) << "Depth " << depthFilename.c_str() << "can not be read" << std::endl;
CV_DbgAssert(image.type() == CV_8UC1);
CV_DbgAssert(depth.type() == CV_16UC1);
{
Mat depth_flt;
depth.convertTo(depth_flt, CV_32FC1, 1.f/5000.f);
depth_flt.setTo(std::numeric_limits<float>::quiet_NaN(), depth_flt < FLT_EPSILON);
depth = depth_flt;
}
}
void OdometryTest::generateRandomTransformation(Mat& rvec, Mat& tvec)
{
const float maxRotation = (float)(3.f / 180.f * CV_PI); //rad
const float maxTranslation = 0.02f; //m
RNG& rng = theRNG();
rvec.create(3, 1, CV_64FC1);
tvec.create(3, 1, CV_64FC1);
randu(rvec, Scalar(-1000), Scalar(1000));
normalize(rvec, rvec, rng.uniform(0.007f, maxRotation));
randu(tvec, Scalar(-1000), Scalar(1000));
normalize(tvec, tvec, rng.uniform(0.008f, maxTranslation));
}
void OdometryTest::checkUMats()
{
Mat K = getCameraMatrix();
Mat image, depth;
readData(image, depth);
UMat uimage, udepth;
image.copyTo(uimage);
depth.copyTo(udepth);
OdometrySettings ods;
ods.setCameraMatrix(K);
Odometry odometry = Odometry(otype, ods, algtype);
OdometryFrame odf(udepth, uimage);
Mat calcRt;
uimage.release();
udepth.release();
odometry.prepareFrame(odf);
bool isComputed = odometry.compute(odf, odf, calcRt);
ASSERT_TRUE(isComputed);
double diff = cv::norm(calcRt, Mat::eye(4, 4, CV_64FC1));
ASSERT_LE(diff, idError) << "Incorrect transformation between the same frame (not the identity matrix)" << std::endl;
}
void OdometryTest::run()
{
Mat K = getCameraMatrix();
Mat image, depth;
readData(image, depth);
OdometrySettings ods;
ods.setCameraMatrix(K);
Odometry odometry = Odometry(otype, ods, algtype);
OdometryFrame odf(depth, image);
Mat calcRt;
// 1. Try to find Rt between the same frame (try masks also).
Mat mask(image.size(), CV_8UC1, Scalar(255));
odometry.prepareFrame(odf);
bool isComputed = odometry.compute(odf, odf, calcRt);
ASSERT_TRUE(isComputed) << "Can not find Rt between the same frame" << std::endl;
double ndiff = cv::norm(calcRt, Mat::eye(4,4,CV_64FC1));
ASSERT_LE(ndiff, idError) << "Incorrect transformation between the same frame (not the identity matrix)" << std::endl;
// 2. Generate random rigid body motion in some ranges several times (iterCount).
// On each iteration an input frame is warped using generated transformation.
// Odometry is run on the following pair: the original frame and the warped one.
// Comparing a computed transformation with an applied one we compute 2 errors:
// better_1time_count - count of poses which error is less than ground truth pose,
// better_5times_count - count of poses which error is 5 times less than ground truth pose.
int iterCount = 100;
int better_1time_count = 0;
int better_5times_count = 0;
for (int iter = 0; iter < iterCount; iter++)
{
Mat rvec, tvec;
generateRandomTransformation(rvec, tvec);
Affine3d rt(rvec, tvec);
Mat warpedImage, warpedDepth;
warpFrame(depth, image, noArray(), rt.matrix, K, warpedDepth, warpedImage);
dilateFrame(warpedImage, warpedDepth); // due to inaccuracy after warping
OdometryFrame odfSrc(depth, image);
OdometryFrame odfDst(warpedDepth, warpedImage);
odometry.prepareFrames(odfSrc, odfDst);
isComputed = odometry.compute(odfSrc, odfDst, calcRt);
if (!isComputed)
{
CV_LOG_INFO(NULL, "Iter " << iter << "; Odometry compute returned false");
continue;
}
Mat calcR = calcRt(Rect(0, 0, 3, 3)), calcRvec;
cv::Rodrigues(calcR, calcRvec);
calcRvec = calcRvec.reshape(rvec.channels(), rvec.rows);
Mat calcTvec = calcRt(Rect(3,0,1,3));
if (cvtest::debugLevel >= 10)
{
imshow("image", image);
imshow("warpedImage", warpedImage);
Mat resultImage, resultDepth;
warpFrame(depth, image, noArray(), calcRt, K, resultDepth, resultImage);
imshow("resultImage", resultImage);
waitKey(100);
}
// compare rotation
double possibleError = algtype == OdometryAlgoType::COMMON ? 0.015f : 0.01f;
Affine3f src = Affine3f(Vec3f(rvec), Vec3f(tvec));
Affine3f res = Affine3f(Vec3f(calcRvec), Vec3f(calcTvec));
Affine3f src_inv = src.inv();
Affine3f diff = res * src_inv;
double rdiffnorm = cv::norm(diff.rvec());
double tdiffnorm = cv::norm(diff.translation());
if (rdiffnorm < possibleError && tdiffnorm < possibleError)
better_1time_count++;
if (5. * rdiffnorm < possibleError && 5 * tdiffnorm < possibleError)
better_5times_count++;
CV_LOG_INFO(NULL, "Iter " << iter);
CV_LOG_INFO(NULL, "rdiff: " << Vec3f(diff.rvec()) << "; rdiffnorm: " << rdiffnorm);
CV_LOG_INFO(NULL, "tdiff: " << Vec3f(diff.translation()) << "; tdiffnorm: " << tdiffnorm);
CV_LOG_INFO(NULL, "better_1time_count " << better_1time_count << "; better_5time_count " << better_5times_count);
}
if(static_cast<double>(better_1time_count) < maxError1 * static_cast<double>(iterCount))
{
FAIL() << "Incorrect count of accurate poses [1st case]: "
<< static_cast<double>(better_1time_count) << " / "
<< maxError1 * static_cast<double>(iterCount) << std::endl;
}
if(static_cast<double>(better_5times_count) < maxError5 * static_cast<double>(iterCount))
{
FAIL() << "Incorrect count of accurate poses [2nd case]: "
<< static_cast<double>(better_5times_count) << " / "
<< maxError5 * static_cast<double>(iterCount) << std::endl;
}
}
void OdometryTest::prepareFrameCheck()
{
Mat K = getCameraMatrix();
Mat gtImage, gtDepth;
readData(gtImage, gtDepth);
OdometrySettings ods;
ods.setCameraMatrix(K);
Odometry odometry = Odometry(otype, ods, algtype);
OdometryFrame odf(gtDepth, gtImage);
odometry.prepareFrame(odf);
std::vector<int> iters;
ods.getIterCounts(iters);
size_t nlevels = iters.size();
Mat points, mask, depth, gray, rgb, scaled;
odf.getMask(mask);
int masknz = countNonZero(mask);
ASSERT_GT(masknz, 0);
odf.getDepth(depth);
Mat patchedDepth = depth.clone();
patchNaNs(patchedDepth, 0);
int depthnz = countNonZero(patchedDepth);
double depthNorm = cv::norm(depth, gtDepth, NORM_INF, mask);
ASSERT_LE(depthNorm, 0.0);
Mat gtGray;
if (otype == OdometryType::RGB || otype == OdometryType::RGB_DEPTH)
{
odf.getGrayImage(gray);
odf.getImage(rgb);
double rgbNorm = cv::norm(rgb, gtImage);
ASSERT_LE(rgbNorm, 0.0);
if (gtImage.channels() == 3)
cvtColor(gtImage, gtGray, COLOR_BGR2GRAY);
else
gtGray = gtImage;
gtGray.convertTo(gtGray, CV_8U);
double grayNorm = cv::norm(gray, gtGray);
ASSERT_LE(grayNorm, 0.0);
}
odf.getProcessedDepth(scaled);
int scalednz = countNonZero(scaled);
EXPECT_EQ(scalednz, depthnz);
std::vector<Mat> gtPyrDepth, gtPyrMask;
//TODO: this depth calculation would become incorrect when we implement bilateral filtering, fixit
buildPyramid(gtDepth, gtPyrDepth, (int)nlevels - 1);
for (const auto& gd : gtPyrDepth)
{
Mat pm = (gd > ods.getMinDepth()) & (gd < ods.getMaxDepth());
gtPyrMask.push_back(pm);
}
size_t npyr = odf.getPyramidLevels();
ASSERT_EQ(npyr, nlevels);
Matx33f levelK = K;
for (size_t i = 0; i < nlevels; i++)
{
Mat depthi, cloudi, maski;
odf.getPyramidAt(maski, OdometryFramePyramidType::PYR_MASK, i);
ASSERT_FALSE(maski.empty());
double mnorm = cv::norm(maski, gtPyrMask[i]);
EXPECT_LE(mnorm, 16 * 255.0) << "Mask diff is too big at pyr level " << i;
odf.getPyramidAt(depthi, OdometryFramePyramidType::PYR_DEPTH, i);
ASSERT_FALSE(depthi.empty());
double dnorm = cv::norm(depthi, gtPyrDepth[i], NORM_INF, maski);
EXPECT_LE(dnorm, 8.e-7) << "Depth diff norm is too big at pyr level " << i;
odf.getPyramidAt(cloudi, OdometryFramePyramidType::PYR_CLOUD, i);
ASSERT_FALSE(cloudi.empty());
Mat gtCloud;
depthTo3d(depthi, levelK, gtCloud);
double cnorm = cv::norm(cloudi, gtCloud, NORM_INF, maski);
EXPECT_LE(cnorm, 0.0) << "Cloud diff norm is too big at pyr level " << i;
// downscale camera matrix for next pyramid level
levelK = 0.5f * levelK;
levelK(2, 2) = 1.f;
}
if (otype == OdometryType::RGB || otype == OdometryType::RGB_DEPTH)
{
std::vector<Mat> gtPyrImage;
buildPyramid(gtGray, gtPyrImage, (int)nlevels - 1);
for (size_t i = 0; i < nlevels; i++)
{
Mat rgbi, texi, dixi, diyi, maski;
odf.getPyramidAt(maski, OdometryFramePyramidType::PYR_MASK, i);
odf.getPyramidAt(rgbi, OdometryFramePyramidType::PYR_IMAGE, i);
ASSERT_FALSE(rgbi.empty());
double rnorm = cv::norm(rgbi, gtPyrImage[i], NORM_INF);
EXPECT_LE(rnorm, 1.0) << "RGB diff is too big at pyr level " << i;
odf.getPyramidAt(texi, OdometryFramePyramidType::PYR_TEXMASK, i);
ASSERT_FALSE(texi.empty());
int tnz = countNonZero(texi);
EXPECT_GE(tnz, 1000) << "Texture mask has too few valid pixels at pyr level " << i;
Mat gtDixi, gtDiyi;
Sobel(rgbi, gtDixi, CV_16S, 1, 0, ods.getSobelSize());
odf.getPyramidAt(dixi, OdometryFramePyramidType::PYR_DIX, i);
ASSERT_FALSE(dixi.empty());
double dixnorm = cv::norm(dixi, gtDixi, NORM_INF, maski);
EXPECT_LE(dixnorm, 0) << "dI/dx diff is too big at pyr level " << i;
Sobel(rgbi, gtDiyi, CV_16S, 0, 1, ods.getSobelSize());
odf.getPyramidAt(diyi, OdometryFramePyramidType::PYR_DIY, i);
ASSERT_FALSE(diyi.empty());
double diynorm = cv::norm(diyi, gtDiyi, NORM_INF, maski);
EXPECT_LE(diynorm, 0) << "dI/dy diff is too big at pyr level " << i;
}
}
if (otype == OdometryType::DEPTH || otype == OdometryType::RGB_DEPTH)
{
Ptr<RgbdNormals> normalComputer = odometry.getNormalsComputer();
ASSERT_FALSE(normalComputer.empty());
Mat normals;
odf.getNormals(normals);
std::vector<Mat> gtPyrNormals;
buildPyramid(normals, gtPyrNormals, (int)nlevels - 1);
for (size_t i = 0; i < nlevels; i++)
{
Mat gtNormal = gtPyrNormals[i];
CV_Assert(gtNormal.type() == CV_32FC4);
for (int y = 0; y < gtNormal.rows; y++)
{
Vec4f *normals_row = gtNormal.ptr<Vec4f>(y);
for (int x = 0; x < gtNormal.cols; x++)
{
Vec4f n4 = normals_row[x];
Point3f n(n4[0], n4[1], n4[2]);
double nrm = cv::norm(n);
n *= 1.f / nrm;
normals_row[x] = Vec4f(n.x, n.y, n.z, 0);
}
}
Mat normmaski;
odf.getPyramidAt(normmaski, OdometryFramePyramidType::PYR_NORMMASK, i);
ASSERT_FALSE(normmaski.empty());
int nnm = countNonZero(normmaski);
EXPECT_GE(nnm, 1000) << "Normals mask has too few valid pixels at pyr level " << i;
Mat ptsi;
odf.getPyramidAt(ptsi, OdometryFramePyramidType::PYR_CLOUD, i);
Mat normi;
odf.getPyramidAt(normi, OdometryFramePyramidType::PYR_NORM, i);
ASSERT_FALSE(normi.empty());
double nnorm = cv::norm(normi, gtNormal, NORM_INF, normmaski);
EXPECT_LE(nnorm, 1.8e-7) << "Normals diff is too big at pyr level " << i;
if (i == 0)
{
double pnnorm = cv::norm(normals, normi, NORM_INF, normmaski);
EXPECT_GE(pnnorm, 0);
}
}
}
}
/****************************************************************************************\
* Tests registrations *
\****************************************************************************************/
TEST(RGBD_Odometry_Rgb, algorithmic)
{
OdometryTest test(OdometryType::RGB, OdometryAlgoType::COMMON, 0.99, 0.99);
test.run();
}
TEST(RGBD_Odometry_ICP, algorithmic)
{
OdometryTest test(OdometryType::DEPTH, OdometryAlgoType::COMMON, 0.99, 0.99);
test.run();
}
TEST(RGBD_Odometry_RgbdICP, algorithmic)
{
OdometryTest test(OdometryType::RGB_DEPTH, OdometryAlgoType::COMMON, 0.99, 0.99);
test.run();
}
TEST(RGBD_Odometry_FastICP, algorithmic)
{
OdometryTest test(OdometryType::DEPTH, OdometryAlgoType::FAST, 0.99, 0.87, 1.84e-5);
test.run();
}
TEST(RGBD_Odometry_Rgb, UMats)
{
OdometryTest test(OdometryType::RGB, OdometryAlgoType::COMMON, 0.99, 0.99);
test.checkUMats();
}
TEST(RGBD_Odometry_ICP, UMats)
{
OdometryTest test(OdometryType::DEPTH, OdometryAlgoType::COMMON, 0.99, 0.99);
test.checkUMats();
}
TEST(RGBD_Odometry_RgbdICP, UMats)
{
OdometryTest test(OdometryType::RGB_DEPTH, OdometryAlgoType::COMMON, 0.99, 0.99);
test.checkUMats();
}
TEST(RGBD_Odometry_FastICP, UMats)
{
// OpenCL version has slightly less accuracy than CPU version
OdometryTest test(OdometryType::DEPTH, OdometryAlgoType::FAST, 0.99, 0.99, 1.84e-5);
test.checkUMats();
}
TEST(RGBD_Odometry_Rgb, prepareFrame)
{
OdometryTest test(OdometryType::RGB, OdometryAlgoType::COMMON, 0.99, 0.99);
test.prepareFrameCheck();
}
TEST(RGBD_Odometry_ICP, prepareFrame)
{
OdometryTest test(OdometryType::DEPTH, OdometryAlgoType::COMMON, 0.99, 0.99);
test.prepareFrameCheck();
}
TEST(RGBD_Odometry_RgbdICP, prepareFrame)
{
OdometryTest test(OdometryType::RGB_DEPTH, OdometryAlgoType::COMMON, 0.99, 0.99);
test.prepareFrameCheck();
}
TEST(RGBD_Odometry_FastICP, prepareFrame)
{
OdometryTest test(OdometryType::DEPTH, OdometryAlgoType::FAST, 0.99, 0.99, FLT_EPSILON);
test.prepareFrameCheck();
}
struct WarpFrameTest
{
WarpFrameTest() :
srcDepth(), srcRgb(), srcMask(),
dstDepth(), dstRgb(), dstMask(),
warpedDepth(), warpedRgb(), warpedMask()
{}
void run(bool needRgb, bool scaleDown, bool checkMask, bool identityTransform, int depthType, int imageType);
Mat srcDepth, srcRgb, srcMask;
Mat dstDepth, dstRgb, dstMask;
Mat warpedDepth, warpedRgb, warpedMask;
};
void WarpFrameTest::run(bool needRgb, bool scaleDown, bool checkMask, bool identityTransform, int depthType, int rgbType)
{
std::string dataPath = cvtest::TS::ptr()->get_data_path();
std::string srcDepthFilename = dataPath + "/cv/rgbd/depth.png";
std::string srcRgbFilename = dataPath + "/cv/rgbd/rgb.png";
// The depth was generated using the script at testdata/cv/rgbd/warped_depth_generator/warp_test.py
std::string warpedDepthFilename = dataPath + "/cv/rgbd/warpedDepth.png";
std::string warpedRgbFilename = dataPath + "/cv/rgbd/warpedRgb.png";
srcDepth = imread(srcDepthFilename, IMREAD_UNCHANGED);
ASSERT_FALSE(srcDepth.empty()) << "Depth " << srcDepthFilename.c_str() << "can not be read" << std::endl;
if (identityTransform)
{
warpedDepth = srcDepth;
}
else
{
warpedDepth = imread(warpedDepthFilename, IMREAD_UNCHANGED);
ASSERT_FALSE(warpedDepth.empty()) << "Depth " << warpedDepthFilename.c_str() << "can not be read" << std::endl;
}
ASSERT_TRUE(srcDepth.type() == CV_16UC1);
ASSERT_TRUE(warpedDepth.type() == CV_16UC1);
Mat epsSrc = srcDepth > 0, epsWarped = warpedDepth > 0;
const double depthFactor = 5000.0;
// scale float types only
double depthScaleCoeff = scaleDown ? ( depthType == CV_16U ? 1. : 1./depthFactor ) : 1.;
double transScaleCoeff = scaleDown ? ( depthType == CV_16U ? depthFactor : 1. ) : depthFactor;
Mat srcDepthCvt, warpedDepthCvt;
srcDepth.convertTo(srcDepthCvt, depthType, depthScaleCoeff);
srcDepth = srcDepthCvt;
warpedDepth.convertTo(warpedDepthCvt, depthType, depthScaleCoeff);
warpedDepth = warpedDepthCvt;
Scalar badVal;
switch (depthType)
{
case CV_16U:
badVal = 0;
break;
case CV_32F:
badVal = std::numeric_limits<float>::quiet_NaN();
break;
case CV_64F:
badVal = std::numeric_limits<double>::quiet_NaN();
break;
default:
CV_Error(Error::StsBadArg, "Unsupported depth data type");
}
srcDepth.setTo(badVal, ~epsSrc);
warpedDepth.setTo(badVal, ~epsWarped);
if (checkMask)
{
srcMask = epsSrc; warpedMask = epsWarped;
}
else
{
srcMask = Mat(); warpedMask = Mat();
}
if (needRgb)
{
srcRgb = imread(srcRgbFilename, rgbType == CV_8UC1 ? IMREAD_GRAYSCALE : IMREAD_COLOR);
ASSERT_FALSE(srcRgb.empty()) << "Image " << srcRgbFilename.c_str() << "can not be read" << std::endl;
if (identityTransform)
{
srcRgb.copyTo(warpedRgb, epsSrc);
}
else
{
warpedRgb = imread(warpedRgbFilename, rgbType == CV_8UC1 ? IMREAD_GRAYSCALE : IMREAD_COLOR);
ASSERT_FALSE (warpedRgb.empty()) << "Image " << warpedRgbFilename.c_str() << "can not be read" << std::endl;
}
if (rgbType == CV_8UC4)
{
Mat newSrcRgb, newWarpedRgb;
cvtColor(srcRgb, newSrcRgb, COLOR_RGB2RGBA);
srcRgb = newSrcRgb;
// let's keep alpha channel
std::vector<Mat> warpedRgbChannels;
split(warpedRgb, warpedRgbChannels);
warpedRgbChannels.push_back(epsWarped);
merge(warpedRgbChannels, newWarpedRgb);
warpedRgb = newWarpedRgb;
}
ASSERT_TRUE(srcRgb.type() == rgbType);
ASSERT_TRUE(warpedRgb.type() == rgbType);
}
else
{
srcRgb = Mat(); warpedRgb = Mat();
}
// test data used to generate warped depth and rgb
// the script used to generate is in opencv_extra repo
// at testdata/cv/rgbd/warped_depth_generator/warp_test.py
double fx = 525.0, fy = 525.0,
cx = 319.5, cy = 239.5;
Matx33d K(fx, 0, cx,
0, fy, cy,
0, 0, 1);
cv::Affine3d rt;
cv::Vec3d tr(-0.04, 0.05, 0.6);
rt = identityTransform ? cv::Affine3d() : cv::Affine3d(cv::Vec3d(0.1, 0.2, 0.3), tr * transScaleCoeff);
warpFrame(srcDepth, srcRgb, srcMask, rt.matrix, K, dstDepth, dstRgb, dstMask);
}
typedef std::pair<int, int> WarpFrameInputTypes;
typedef testing::TestWithParam<WarpFrameInputTypes> WarpFrameInputs;
TEST_P(WarpFrameInputs, checkTypes)
{
const double shortl2diff = 233.983;
const double shortlidiff = 1;
const double floatl2diff = 0.038209;
const double floatlidiff = 0.00020004;
int depthType = GetParam().first;
int rgbType = GetParam().second;
WarpFrameTest w;
// scale down does not happen on CV_16U
// to avoid integer overflow
w.run(/* needRgb */ true, /* scaleDown*/ true,
/* checkMask */ true, /* identityTransform */ false, depthType, rgbType);
double rgbDiff = cv::norm(w.dstRgb, w.warpedRgb, NORM_L2);
double maskDiff = cv::norm(w.dstMask, w.warpedMask, NORM_L2);
EXPECT_EQ(0, maskDiff);
EXPECT_EQ(0, rgbDiff);
double l2diff = cv::norm(w.dstDepth, w.warpedDepth, NORM_L2, w.warpedMask);
double lidiff = cv::norm(w.dstDepth, w.warpedDepth, NORM_INF, w.warpedMask);
double l2threshold = depthType == CV_16U ? shortl2diff : floatl2diff;
double lithreshold = depthType == CV_16U ? shortlidiff : floatlidiff;
EXPECT_LE(l2diff, l2threshold);
EXPECT_LE(lidiff, lithreshold);
}
INSTANTIATE_TEST_CASE_P(RGBD_Odometry, WarpFrameInputs, ::testing::Values(
WarpFrameInputTypes { CV_16U, CV_8UC3 },
WarpFrameInputTypes { CV_32F, CV_8UC3 },
WarpFrameInputTypes { CV_64F, CV_8UC3 },
WarpFrameInputTypes { CV_32F, CV_8UC1 },
WarpFrameInputTypes { CV_32F, CV_8UC4 }));
TEST(RGBD_Odometry_WarpFrame, identity)
{
WarpFrameTest w;
w.run(/* needRgb */ true, /* scaleDown*/ true, /* checkMask */ true, /* identityTransform */ true, CV_32F, CV_8UC3);
double rgbDiff = cv::norm(w.dstRgb, w.warpedRgb, NORM_L2);
double maskDiff = cv::norm(w.dstMask, w.warpedMask, NORM_L2);
ASSERT_EQ(0, rgbDiff);
ASSERT_EQ(0, maskDiff);
double depthDiff = cv::norm(w.dstDepth, w.warpedDepth, NORM_L2, w.dstMask);
ASSERT_LE(depthDiff, DBL_EPSILON);
}
TEST(RGBD_Odometry_WarpFrame, noRgb)
{
WarpFrameTest w;
w.run(/* needRgb */ false, /* scaleDown*/ true, /* checkMask */ true, /* identityTransform */ false, CV_32F, CV_8UC3);
double maskDiff = cv::norm(w.dstMask, w.warpedMask, NORM_L2);
ASSERT_EQ(0, maskDiff);
double l2diff = cv::norm(w.dstDepth, w.warpedDepth, NORM_L2, w.warpedMask);
double lidiff = cv::norm(w.dstDepth, w.warpedDepth, NORM_INF, w.warpedMask);
ASSERT_LE(l2diff, 0.038209);
ASSERT_LE(lidiff, 0.00020004);
}
TEST(RGBD_Odometry_WarpFrame, nansAreMasked)
{
WarpFrameTest w;
w.run(/* needRgb */ true, /* scaleDown*/ true, /* checkMask */ false, /* identityTransform */ false, CV_32F, CV_8UC3);
double rgbDiff = cv::norm(w.dstRgb, w.warpedRgb, NORM_L2);
ASSERT_EQ(0, rgbDiff);
Mat goodVals = (w.warpedDepth == w.warpedDepth);
double l2diff = cv::norm(w.dstDepth, w.warpedDepth, NORM_L2, goodVals);
double lidiff = cv::norm(w.dstDepth, w.warpedDepth, NORM_INF, goodVals);
ASSERT_LE(l2diff, 0.038209);
ASSERT_LE(lidiff, 0.00020004);
}
TEST(RGBD_Odometry_WarpFrame, bigScale)
{
WarpFrameTest w;
w.run(/* needRgb */ true, /* scaleDown*/ false, /* checkMask */ true, /* identityTransform */ false, CV_32F, CV_8UC3);
double rgbDiff = cv::norm(w.dstRgb, w.warpedRgb, NORM_L2);
double maskDiff = cv::norm(w.dstMask, w.warpedMask, NORM_L2);
ASSERT_EQ(0, maskDiff);
ASSERT_EQ(0, rgbDiff);
double l2diff = cv::norm(w.dstDepth, w.warpedDepth, NORM_L2, w.warpedMask);
double lidiff = cv::norm(w.dstDepth, w.warpedDepth, NORM_INF, w.warpedMask);
ASSERT_LE(l2diff, 191.026565);
ASSERT_LE(lidiff, 0.99951172);
}
TEST(RGBD_DepthTo3D, mask)
{
std::string dataPath = cvtest::TS::ptr()->get_data_path();
std::string srcDepthFilename = dataPath + "/cv/rgbd/depth.png";
Mat srcDepth = imread(srcDepthFilename, IMREAD_UNCHANGED);
ASSERT_FALSE(srcDepth.empty()) << "Depth " << srcDepthFilename.c_str() << "can not be read" << std::endl;
ASSERT_TRUE(srcDepth.type() == CV_16UC1);
Mat srcMask = srcDepth > 0;
// test data used to generate warped depth and rgb
// the script used to generate is in opencv_extra repo
// at testdata/cv/rgbd/warped_depth_generator/warp_test.py
double fx = 525.0, fy = 525.0,
cx = 319.5, cy = 239.5;
Matx33d intr(fx, 0, cx,
0, fy, cy,
0, 0, 1);
Mat srcCloud;
depthTo3d(srcDepth, intr, srcCloud, srcMask);
size_t npts = countNonZero(srcMask);
ASSERT_EQ(npts, srcCloud.total());
}
}} // namespace
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