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rapid: make correspondencies explicit for simpler data handling

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pull/2572/head
Pavel Rojtberg 5 years ago
parent 522a062cad
commit 00fe2ed971
3 changed files with 76 additions and 60 deletions
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  1. 25
      modules/rapid/include/opencv2/rapid.hpp
  2. 2
      modules/rapid/samples/track_marker.py
  3. 109
      modules/rapid/src/rapid.cpp

25
modules/rapid/include/opencv2/rapid.hpp
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@ -24,12 +24,12 @@ namespace rapid
/**
* Debug draw markers of matched correspondences onto a lineBundle
* @param bundle the lineBundle
* @param srcLocations the according source locations
* @param newLocations matched source locations
* @param cols column coordinates in the line bundle
* @param colors colors for the markers. Defaults to white.
*/
CV_EXPORTS_W void drawCorrespondencies(InputOutputArray bundle, InputArray srcLocations,
InputArray newLocations, InputArray colors = noArray());
CV_EXPORTS_W void drawCorrespondencies(InputOutputArray bundle, InputArray cols,
InputArray colors = noArray());
/**
* Debug draw search lines onto an image
* @param img the output image
@ -83,20 +83,22 @@ CV_EXPORTS_W void extractLineBundle(int len, InputArray ctl2d, InputArray img, O
* Find corresponding image locations by searching for a maximal sobel edge along the search line (a single
* row in the bundle)
* @param bundle the line bundle
* @param srcLocations the according source image location
* @param newLocations image locations with maximal edge along the search line
* @param cols correspondence-position per line in line-bundle-space
* @param response the sobel response for the selected point
*/
CV_EXPORTS_W void findCorrespondencies(InputArray bundle, InputArray srcLocations, OutputArray newLocations,
CV_EXPORTS_W void findCorrespondencies(InputArray bundle, OutputArray cols,
OutputArray response = noArray());
/**
* Filter corresponding 2d and 3d points based on mask
* Collect corresponding 2d and 3d points based on correspondencies and mask
* @param cols correspondence-position per line in line-bundle-space
* @param srcLocations the source image location
* @param pts2d 2d points
* @param pts3d 3d points
* @param mask mask containing non-zero values for the elements to be retained
*/
CV_EXPORTS_W void filterCorrespondencies(InputOutputArray pts2d, InputOutputArray pts3d, InputArray mask);
CV_EXPORTS_W void convertCorrespondencies(InputArray cols, InputArray srcLocations, OutputArray pts2d,
InputOutputArray pts3d = noArray(), InputArray mask = noArray());
/**
* High level function to execute a single rapid @cite harris1990rapid iteration
@ -104,7 +106,7 @@ CV_EXPORTS_W void filterCorrespondencies(InputOutputArray pts2d, InputOutputArra
* 1. @ref extractControlPoints
* 2. @ref extractLineBundle
* 3. @ref findCorrespondencies
* 4. @ref filterCorrespondencies
* 4. @ref convertCorrespondencies
* 5. @ref solvePnPRefineLM
*
* @param img the video frame
@ -115,10 +117,11 @@ CV_EXPORTS_W void filterCorrespondencies(InputOutputArray pts2d, InputOutputArra
* @param K camera matrix
* @param rvec rotation between mesh and camera. Input values are used as an initial solution.
* @param tvec translation between mesh and camera. Input values are used as an initial solution.
* @param rmsd the 2d reprojection difference
* @return ratio of search lines that could be extracted and matched
*/
CV_EXPORTS_W float rapid(InputArray img, int num, int len, InputArray pts3d, InputArray tris, InputArray K,
InputOutputArray rvec, InputOutputArray tvec);
InputOutputArray rvec, InputOutputArray tvec, CV_OUT double* rmsd = 0);
//! @}
} /* namespace rapid */
} /* namespace cv */

2
modules/rapid/samples/track_marker.py
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@ -35,7 +35,7 @@ while cv.waitKey(1) != 27:
# tracking and refinement with rapid
if rot is not None:
for i in range(5): # multiple iterations
ratio, rot, trans = cv.rapid.rapid(img, 40, line_len, obj_points, tris, K, rot, trans)
ratio, rot, trans = cv.rapid.rapid(img, 40, line_len, obj_points, tris, K, rot, trans)[:3]
if ratio < 0.8:
# bad quality, force re-detect
rot, trans = None, None

109
modules/rapid/src/rapid.cpp
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@ -223,19 +223,13 @@ static void compute1DSobel(const Mat& src, Mat& dst)
}
}
void findCorrespondencies(InputArray bundle, InputArray _srcLocations, OutputArray _newLocations,
OutputArray _response)
void findCorrespondencies(InputArray bundle, OutputArray _cols, OutputArray _response)
{
CV_Assert(bundle.size() == _srcLocations.size());
CV_CheckTypeEQ(_srcLocations.type(), CV_16SC2, "Vec2s data type expected");
Mat_<uchar> sobel;
compute1DSobel(bundle.getMat(), sobel);
_newLocations.create(sobel.rows, 1, CV_16SC2);
Mat newLocations = _newLocations.getMat();
Mat srcLocations = _srcLocations.getMat();
_cols.create(sobel.rows, 1, CV_32S);
Mat_<int> cols = _cols.getMat();
Mat_<uchar> response;
if (_response.needed()) {
@ -267,64 +261,75 @@ void findCorrespondencies(InputArray bundle, InputArray _srcLocations, OutputArr
if (!response.empty())
response(i) = mx;
newLocations.at<Vec2s>(i, 0) = srcLocations.at<Vec2s>(i, pos);
cols(i) = pos;
}
}
void drawCorrespondencies(InputOutputArray _bundle, InputArray _srcLocations, InputArray _newLocations,
InputArray _colors)
void drawCorrespondencies(InputOutputArray _bundle, InputArray _cols, InputArray _colors)
{
CV_CheckTypeEQ(_srcLocations.type(), CV_16SC2, "Vec2s data type expected");
CV_CheckTypeEQ(_newLocations.type(), CV_16SC2, "Vec2s data type expected");
CV_Assert(_bundle.size() == _srcLocations.size());
CV_Assert(_colors.empty() || _colors.rows() == _srcLocations.rows());
CV_CheckTypeEQ(_cols.type(), CV_32S, "cols must be of int type");
CV_Assert(_bundle.rows() == _cols.rows());
CV_Assert(_colors.empty() || _colors.rows() == _cols.rows());
Mat bundle = _bundle.getMat();
Mat_<Vec2s> srcLocations = _srcLocations.getMat();
Mat_<Vec2s> newLocations = _newLocations.getMat();
Mat_<int> cols = _cols.getMat();
Mat_<Vec4d> colors = _colors.getMat();
for (int i = 0; i < bundle.rows; i++) {
const Vec2s& ref = newLocations(i);
for (int j = 1; j < bundle.cols - 1; j++) {
if (ref == srcLocations(i, j)) {
bundle(Rect(Point(j, i), Size(1, 1))) = colors.empty() ? Scalar::all(255) : colors(i);
}
}
bundle(Rect(Point(cols(i), i), Size(1, 1))) = colors.empty() ? Scalar::all(255) : colors(i);
}
}
void filterCorrespondencies(InputOutputArray _pts2d, InputOutputArray _pts3d, InputArray _mask)
void convertCorrespondencies(InputArray _cols, InputArray _srcLocations, OutputArray _pts2d,
InputOutputArray _pts3d, InputArray _mask)
{
CV_CheckTypeEQ(_mask.type(), CV_8UC1, "mask must be of uchar type");
CV_Assert(_pts2d.rows() == _pts3d.rows() && _pts2d.rows() == _mask.rows());
CV_CheckTypeEQ(_cols.type(), CV_32S, "cols must be of int type");
CV_CheckTypeEQ(_srcLocations.type(), CV_16SC2, "Vec2s data type expected");
CV_Assert(_srcLocations.rows() == _cols.rows());
Mat_<cv::Vec2s> srcLocations = _srcLocations.getMat();
Mat_<int> cols = _cols.getMat();
Mat pts2d = _pts2d.getMat();
Mat pts3d = _pts3d.getMat();
Mat_<uchar> mask = _mask.getMat();
Mat pts2d = Mat(0, 1, CV_16SC2);
pts2d.reserve(cols.rows);
Mat opts3d(0, 1, pts3d.type());
opts3d.reserve(mask.rows);
Mat opts2d(0, 1, pts2d.type());
opts2d.reserve(mask.rows);
Mat_<uchar> mask;
if (!_mask.empty())
{
CV_CheckTypeEQ(_mask.type(), CV_8UC1, "mask must be of uchar type");
CV_Assert(_cols.rows() == _mask.rows());
mask = _mask.getMat();
}
Mat pts3d;
Mat opts3d;
if(!_pts3d.empty())
{
CV_Assert(_cols.rows() == _pts3d.rows());
pts3d = _pts3d.getMat();
opts3d.create(0, 1, pts3d.type());
opts3d.reserve(cols.rows);
}
for (int i = 0; i < mask.rows; i++) {
if (!mask(i))
for (int i = 0; i < cols.rows; i++) {
if (!mask.empty() && !mask(i))
continue;
opts2d.push_back(pts2d.row(i));
opts3d.push_back(pts3d.row(i));
pts2d.push_back(srcLocations(i, cols(i)));
if(!pts3d.empty())
opts3d.push_back(pts3d.row(i));
}
Mat(opts3d).copyTo(_pts3d);
Mat(opts2d).copyTo(_pts2d);
pts2d.copyTo(_pts2d);
if(!pts3d.empty())
opts3d.copyTo(_pts3d);
}
float rapid(InputArray img, int num, int len, InputArray vtx, InputArray tris, InputArray K,
InputOutputArray rvec, InputOutputArray tvec)
InputOutputArray rvec, InputOutputArray tvec, double* rmsd)
{
CV_Assert(num >= 3);
Mat pts2d, pts3d, correspondencies;
Mat pts2d, pts3d;
extractControlPoints(num, len, vtx, rvec, tvec, K, img.size(), tris, pts2d, pts3d);
if (pts2d.empty())
return 0;
@ -332,18 +337,26 @@ float rapid(InputArray img, int num, int len, InputArray vtx, InputArray tris, I
Mat lineBundle, imgLoc;
extractLineBundle(len, pts2d, img, lineBundle, imgLoc);
Mat response;
findCorrespondencies(lineBundle, imgLoc, correspondencies, response);
Mat cols, response;
findCorrespondencies(lineBundle, cols, response);
const uchar sobel_thresh = 20;
filterCorrespondencies(correspondencies, pts3d, response > sobel_thresh);
Mat mask = response > sobel_thresh;
convertCorrespondencies(cols, imgLoc, pts2d, pts3d, mask);
if(rmsd)
{
cols.copyTo(cols, mask);
cols -= len + 1;
*rmsd = std::sqrt(norm(cols, NORM_L2SQR) / cols.rows);
}
if (correspondencies.rows < 3)
if (pts2d.rows < 3)
return 0;
solvePnPRefineLM(pts3d, correspondencies, K, cv::noArray(), rvec, tvec);
solvePnPRefineLM(pts3d, pts2d, K, cv::noArray(), rvec, tvec);
return float(correspondencies.rows) / num;
return float(pts2d.rows) / num;
}
} /* namespace rapid */

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