inline void bs::pattern::shiftPattern(cv::InputArray src, cv::OutputArray dst, const int direction, const int shift)
{
cv::Mat d;
cv::copyMakeBorder(src, d, shift, shift, shift, shift, cv::BORDER_WRAP);
const auto direc = static_cast<Direction>(direction);
switch (direc)
{
default:
break;
case Top:
d = d(cv::Rect(cv::Point(shift, 2 * shift), src.size()));
break;
case Bottom:
d = d(cv::Rect(cv::Point(shift, 0), src.size()));
break;
case Left:
d = d(cv::Rect(cv::Point(2 * shift, shift), src.size()));
break;
case Right:
d = d(cv::Rect(cv::Point(0, shift), src.size()));
break;
}
d.copyTo(dst);
return;
}
RadiometricResponse::RadiometricResponse(cv::InputArray _response, ChannelOrder order) : order_(order) {
if (_response.size().width != 256 || _response.size().height != 1)
BOOST_THROW_EXCEPTION(RadiometricResponseException("Radiometric response should have 1 x 256 size")
<< RadiometricResponseException::Size(_response.size()));
if (_response.type() != CV_32FC3)
BOOST_THROW_EXCEPTION(RadiometricResponseException("Radiometric response values should be 3-channel float")
<< RadiometricResponseException::Type(_response.type()));
response_ = _response.getMat();
cv::log(response_, log_response_);
cv::split(response_, response_channels_);
}
void Picture::setAnimation(const AnimationEnum &animationEnum,
const cv::InputArray &startImg, const cv::InputArray &endImg)
{
delete animation;
Mat startImage = startImg.getMat();
Mat endImage = endImg.getMat();
if (!startImg.empty() && startImg.size() != this->size())
cv::resize(startImg, startImage, this->size());
if (!endImg.empty() && endImg.size() != this->size())
cv::resize(endImg, endImage, this->size());
animation = AnimationFactory::createAnimation(animationEnum, startImage, endImage);
}
void showWindow(const string &winName, cv::InputArray mat)
{
Mat temp(mat.size(), mat.type());
mat.getMat().copyTo(temp);
namedWindow(winName, WINDOW_NORMAL); // Create a window for display.
imshow(winName, temp); // Show our image inside it.
}
void warmify(cv::InputArray src, cv::OutputArray dst, uchar delta)
{
CV_Assert(src.type() == CV_8UC3);
Mat imgSrc = src.getMat();
CV_Assert(imgSrc.data);
dst.create(src.size(), CV_8UC3);
Mat imgDst = dst.getMat();
imgDst = imgSrc + Scalar(0, delta, delta);
}
void findTemplateMatchCandidates(
cv::InputArray image,
cv::InputArray templ,
cv::InputArray templMask,
cv::OutputArray candidates,
cv::Size partitionSize,
int maxWeakErrors,
float maxMeanDifference)
{
TemplateMatchCandidates tmc;
tmc.setSourceImage(image.getMat());
tmc.setPartitionSize(partitionSize);
tmc.setTemplateSize(templ.size());
tmc.initialize();
candidates.create(
image.size().height - templ.size().height + 1,
image.size().width - templ.size().width + 1,
CV_8UC1);
cv::Mat mat1 = templ.getMat(), mat2 = templMask.getMat(), mat3 = candidates.getMat();
tmc.findCandidates(mat1, mat2, mat3, maxWeakErrors, maxMeanDifference);
}
void RadiometricResponse::directMap(cv::InputArray _E, cv::OutputArray _I) const {
if (_E.empty()) {
_I.clear();
return;
}
auto E = _E.getMat();
_I.create(_E.size(), CV_8UC3);
auto I = _I.getMat();
#if CV_MAJOR_VERSION > 2
E.forEach<cv::Vec3f>(
[&I, this](cv::Vec3f& v, const int* p) { I.at<cv::Vec3b>(p[0], p[1]) = inverseLUT(response_channels_, v); });
#else
for (int i = 0; i < E.rows; i++)
for (int j = 0; j < E.cols; j++) I.at<cv::Vec3b>(i, j) = inverseLUT(response_channels_, E.at<cv::Vec3f>(i, j));
#endif
}
void unprojectPointsFisheye( cv::InputArray distorted, cv::OutputArray undistorted, cv::InputArray K, cv::InputArray D, cv::InputArray R, cv::InputArray P)
{
// will support only 2-channel data now for points
CV_Assert(distorted.type() == CV_32FC2 || distorted.type() == CV_64FC2);
undistorted.create(distorted.size(), CV_MAKETYPE(distorted.depth(), 3));
CV_Assert(P.empty() || P.size() == cv::Size(3, 3) || P.size() == cv::Size(4, 3));
CV_Assert(R.empty() || R.size() == cv::Size(3, 3) || R.total() * R.channels() == 3);
CV_Assert(D.total() == 4 && K.size() == cv::Size(3, 3) && (K.depth() == CV_32F || K.depth() == CV_64F));
cv::Vec2d f, c;
if (K.depth() == CV_32F)
{
cv::Matx33f camMat = K.getMat();
f = cv::Vec2f(camMat(0, 0), camMat(1, 1));
c = cv::Vec2f(camMat(0, 2), camMat(1, 2));
}
else
{
cv::Matx33d camMat = K.getMat();
f = cv::Vec2d(camMat(0, 0), camMat(1, 1));
c = cv::Vec2d(camMat(0, 2), camMat(1, 2));
}
cv::Vec4d k = D.depth() == CV_32F ? (cv::Vec4d)*D.getMat().ptr<cv::Vec4f>(): *D.getMat().ptr<cv::Vec4d>();
cv::Matx33d RR = cv::Matx33d::eye();
if (!R.empty() && R.total() * R.channels() == 3)
{
cv::Vec3d rvec;
R.getMat().convertTo(rvec, CV_64F);
RR = cv::Affine3d(rvec).rotation();
}
else if (!R.empty() && R.size() == cv::Size(3, 3))
R.getMat().convertTo(RR, CV_64F);
if(!P.empty())
{
cv::Matx33d PP;
P.getMat().colRange(0, 3).convertTo(PP, CV_64F);
RR = PP * RR;
}
// start undistorting
const cv::Vec2f* srcf = distorted.getMat().ptr<cv::Vec2f>();
const cv::Vec2d* srcd = distorted.getMat().ptr<cv::Vec2d>();
cv::Vec3f* dstf = undistorted.getMat().ptr<cv::Vec3f>();
cv::Vec3d* dstd = undistorted.getMat().ptr<cv::Vec3d>();
size_t n = distorted.total();
int sdepth = distorted.depth();
for(size_t i = 0; i < n; i++ )
{
cv::Vec2d pi = sdepth == CV_32F ? (cv::Vec2d)srcf[i] : srcd[i]; // image point
cv::Vec2d pw((pi[0] - c[0])/f[0], (pi[1] - c[1])/f[1]); // world point
double theta_d = sqrt(pw[0]*pw[0] + pw[1]*pw[1]);
double theta = theta_d;
if (theta_d > 1e-8)
{
// compensate distortion iteratively
for(int j = 0; j < 10; j++ )
{
double theta2 = theta*theta, theta4 = theta2*theta2, theta6 = theta4*theta2, theta8 = theta6*theta2;
theta = theta_d / (1 + k[0] * theta2 + k[1] * theta4 + k[2] * theta6 + k[3] * theta8);
}
}
double z = std::cos(theta);
double r = std::sin(theta);
cv::Vec3d pu = cv::Vec3d(r*pw[0], r*pw[1], z); //undistorted point
// reproject
cv::Vec3d pr = RR * pu; // rotated point optionally multiplied by new camera matrix
cv::Vec3d fi; // final
normalize(pr, fi);
if( sdepth == CV_32F )
dstf[i] = fi;
else
dstd[i] = fi;
}
}
bool VideoWriter_IntelMFX::write_one(cv::InputArray bgr)
{
mfxStatus res;
mfxFrameSurface1 *workSurface = 0;
mfxSyncPoint sync;
if (!bgr.empty() && (bgr.dims() != 2 || bgr.type() != CV_8UC3 || bgr.size() != frameSize))
{
MSG(cerr << "MFX: invalid frame passed to encoder: "
<< "dims/depth/cn=" << bgr.dims() << "/" << bgr.depth() << "/" << bgr.channels()
<< ", size=" << bgr.size() << endl);
return false;
}
if (!bgr.empty())
{
workSurface = pool->getFreeSurface();
if (!workSurface)
{
// not enough surfaces
MSG(cerr << "MFX: Failed to get free surface" << endl);
return false;
}
const int rows = workSurface->Info.Height;
const int cols = workSurface->Info.Width;
Mat Y(rows, cols, CV_8UC1, workSurface->Data.Y, workSurface->Data.Pitch);
Mat UV(rows / 2, cols, CV_8UC1, workSurface->Data.UV, workSurface->Data.Pitch);
to_nv12(bgr, Y, UV);
CV_Assert(Y.ptr() == workSurface->Data.Y);
CV_Assert(UV.ptr() == workSurface->Data.UV);
}
while (true)
{
outSurface = 0;
DBG(cout << "Calling with surface: " << workSurface << endl);
res = encoder->EncodeFrameAsync(NULL, workSurface, &bs->stream, &sync);
if (res == MFX_ERR_NONE)
{
res = session->SyncOperation(sync, 1000); // 1 sec, TODO: provide interface to modify timeout
if (res == MFX_ERR_NONE)
{
// ready to write
if (!bs->write())
{
MSG(cerr << "MFX: Failed to write bitstream" << endl);
return false;
}
else
{
DBG(cout << "Write bitstream" << endl);
return true;
}
}
else
{
MSG(cerr << "MFX: Sync error: " << res << endl);
return false;
}
}
else if (res == MFX_ERR_MORE_DATA)
{
DBG(cout << "ERR_MORE_DATA" << endl);
return false;
}
else if (res == MFX_WRN_DEVICE_BUSY)
{
DBG(cout << "Waiting for device" << endl);
sleep(1);
continue;
}
else
{
MSG(cerr << "MFX: Bad status: " << res << endl);
return false;
}
}
}
void savePointCloud(const std::string file, cv::InputArray point_cloud, const bool is_binary, cv::InputArray color_image, const bool remove_miss_point)
{
const cv::Mat points = point_cloud.getMat();
const bool color_cloud = (!color_image.empty() && (point_cloud.size() == color_image.size()));
if (points.empty())
return;
if (points.type() != CV_32FC1)
points.reshape(1, 3);
if (color_cloud)
{
const cv::Mat im = color_image.getMat();
pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
for (int row = 0; row < points.rows; ++row)
{
const auto ptr = points.ptr<cv::Vec3f>(row);
const auto ptr_image = im.ptr<cv::Vec3b>(row);
for (int col = 0; col < points.cols; ++col)
{
const auto val = ptr[col];
const auto color = ptr_image[col];
if (!remove_miss_point || (remove_miss_point && val[2] < 9999.9f))
{
pcl::PointXYZRGB p;
p.x = val[0], p.y = val[1], p.z = val[2], p.r = color[0], p.g = color[1], p.b = color[2];
cloud->push_back(p);
}
}
}
if (cloud->size() == 0)
return;
else if (is_binary)
pcl::io::savePLYFileBinary(file, *cloud);
else
pcl::io::savePLYFileASCII(file, *cloud);
}
else
{
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>);
for (int row = 0; row < points.rows; ++row)
{
const auto ptr = points.ptr<cv::Vec3f>(row);
for (int col = 0; col < points.cols; ++col)
{
const auto val = ptr[col];
if (!remove_miss_point || (remove_miss_point && val[2] < 9999.9f))
cloud->push_back(pcl::PointXYZ(val[0], val[1], val[2]));
}
}
if (cloud->size() == 0)
return;
else if (is_binary)
pcl::io::savePLYFileBinary(file, *cloud);
else
pcl::io::savePLYFileASCII(file, *cloud);
}
return;
}
void CvSVM_OCL::predict( cv::InputArray _samples, cv::OutputArray _results ) const
{
_results.create(_samples.size().height, 1, CV_32F);
CvMat samples = _samples.getMat(), results = _results.getMat();
predict(&samples, &results);
}
void disparityFitPlane(cv::InputArray disparity, cv::InputArray image, cv::OutputArray dest, int slicRegionSize, float slicRegularization, float slicMinRegionRatio, int slicMaxIteration, int ransacNumofSample, float ransacThreshold)
{
//disparityFitTest(ransacNumofSample, ransacThreshold);
//cv::FileStorage pointxml("planePoint.xml", cv::FileStorage::WRITE); int err = 0;
Mat segment;
SLIC(image, segment, slicRegionSize, slicRegularization, slicMinRegionRatio, slicMaxIteration);
vector<vector<Point3f>> points;
SLICSegment2Vector3D_<float>(segment, disparity, 0, points);
Mat disp32f = Mat::zeros(dest.size(), CV_32F);
for (int i = 0; i < points.size(); ++i)
{
if (points[i].size() < 3)
{
if (!points[i].empty())
{
for (int j = 0; j < points[i].size(); ++j)
{
points[i][j].z = 0.f;
}
}
}
else
{
Point3f abc;
fitPlaneRANSAC(points[i], abc, ransacNumofSample, ransacThreshold, 1);
//for refinement(if nessesary)
int v = countArrowablePointDistanceZ(points[i], abc, ransacThreshold);
/*double rate = (double)v / points[i].size() * 100;
int itermax = 1;
for (int n = 0; n < itermax;n++)
{
if (rate < 30)
{
//pointxml <<format("point%03d",err++)<< points[i];
fitPlaneRANSAC(points[i], abc, ransacNumofSample, ransacThreshold, 1);
v = countArrowablePointDistanceZ(points[i], abc, ransacThreshold);
rate = (double)v / points[i].size() * 100;
}
}*/
for (int j = 0; j < points[i].size(); ++j)
{
points[i][j].z = points[i][j].x*abc.x + points[i][j].y*abc.y + abc.z;
}
}
}
SLICVector3D2Signal(points, image.size(), disp32f);
if (disparity.depth() == CV_32F)
{
disp32f.copyTo(dest);
}
else if (disparity.depth() == CV_8U || disparity.depth() == CV_16U || disparity.depth() == CV_16S || disparity.depth() == CV_32S)
{
disp32f.convertTo(dest, disparity.type(), 1.0, 0.5);
}
else
{
disp32f.convertTo(dest, disparity.type());
}
}