Chiebot-Mirror
/
opencv_contrib
8
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

remove warnings

Browse Source
pull/266/head
baisheng lai 10 years ago
parent fc471beb1e
commit d648cc8c86
4 changed files with 26 additions and 24 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 14
      modules/ccalib/include/opencv2/omnidir.hpp
  2. 10
      modules/ccalib/src/multiCameraCalibration.cpp
  3. 24
      modules/ccalib/src/omnidir.cpp
  4. 2
      modules/ccalib/tutorial/omnidir_tutorial.markdown

14
modules/ccalib/include/opencv2/omnidir.hpp
Unescape View File

@ -118,7 +118,7 @@ namespace omnidir
@param R Rotation transform between the original and object space : 3x3 1-channel, or vector: 3x1/1x3, with depth CV_32F or CV_64F
@param P New camera matrix (3x3) or new projection matrix (3x4)
@param size Undistorted image size.
@param m1type Type of the first output map that can be CV_32FC1 or CV_16SC2 . See convertMaps()
@param mltype Type of the first output map that can be CV_32FC1 or CV_16SC2 . See convertMaps()
for details.
@param map1 The first output map.
@param map2 The second output map.
@ -135,6 +135,7 @@ namespace omnidir
@param K Camera matrix \f$K = \vecthreethree{f_x}{s}{c_x}{0}{f_y}{c_y}{0}{0}{_1}\f$.
@param D Input vector of distortion coefficients \f$(k_1, k_2, p_1, p_2)\f$.
@param xi The parameter xi for CMei's model.
@param flags Flags indicates the rectification type, RECTIFY_PERSPECTIVE, RECTIFY_CYLINDRICAL, RECTIFY_LONGLATI and RECTIFY_STEREOGRAPHIC
@param Knew Camera matrix of the distorted image. If it is not assigned, it is just K.
@param new_size The new image size. By default, it is the size of distorted.
@param R Rotation matrix between the input and output images. By default, it is identity matrix.
@ -152,14 +153,14 @@ namespace omnidir
@param K Output calibrated camera matrix.
@param xi Output parameter xi for CMei's model
@param D Output distortion parameters \f$(k_1, k_2, p_1, p_2)\f$
@param omAll Output rotations for each calibration images
@param tAll Output translation for each calibration images
@param rvecs Output rotations for each calibration images
@param tvecs Output translation for each calibration images
@param flags The flags that control calibrate
@param criteria Termination criteria for optimization
@param idx Indices of images that pass initialization, which are really used in calibration. So the size of rvecs is the
same as idx.total().
*/
CV_EXPORTS_W double calibrate(InputArray patternPoints, InputArray imagePoints, Size size,
CV_EXPORTS_W double calibrate(InputArray objectPoints, InputArray imagePoints, Size size,
InputOutputArray K, InputOutputArray xi, InputOutputArray D, OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs,
int flags, TermCriteria criteria, OutputArray idx=noArray());
@ -172,7 +173,8 @@ namespace omnidir
It must be the same size and the same type as objectPoints.
@param imagePoints2 The corresponding image points of the second camera, with type vector<vector<Vec2f> >.
It must be the same size and the same type as objectPoints.
@param imageSize Image size of calibration images.
@param imageSize1 Image size of calibration images of the first camera.
@param imageSize2 Image size of calibration images of the second camera.
@param K1 Output camera matrix for the first camera.
@param xi1 Output parameter xi of Mei's model for the first camera
@param D1 Output distortion parameters \f$(k_1, k_2, p_1, p_2)\f$ for the first camera
@ -215,7 +217,7 @@ namespace omnidir
@param flag Flag of rectification type, RECTIFY_PERSPECTIVE or RECTIFY_LONGLATI
@param numDisparities The parameter 'numDisparities' in StereoSGBM, see StereoSGBM for details.
@param SADWindowSize The parameter 'SADWindowSize' in StereoSGBM, see StereoSGBM for details.
@param depth Depth map generated by stereo matching
@param disparity Disparity map generated by stereo matching
@param pointCloud Point cloud of 3D reconstruction, with type CV_64FC3
@param newSize Image size of rectified image, see omnidir::undistortImage
@param Knew New camera matrix of rectified image, see omnidir::undistortImage

10
modules/ccalib/src/multiCameraCalibration.cpp
Unescape View File

@ -144,13 +144,13 @@ void multiCameraCalibration::loadImages()
{
int cameraVertex, timestamp;
std::string filename = file_list[i].substr(0, file_list[i].find('.'));
int spritPosition1 = filename.rfind('/');
int spritPosition2 = filename.rfind('\\');
if (spritPosition1!=(int)std::string::npos)
size_t spritPosition1 = filename.rfind('/');
size_t spritPosition2 = filename.rfind('\\');
if (spritPosition1!=std::string::npos)
{
filename = filename.substr(spritPosition1+1, filename.size() - 1);
}
else if(spritPosition2!= (int)std::string::npos)
else if(spritPosition2!= std::string::npos)
{
filename = filename.substr(spritPosition2+1, filename.size() - 1);
}
@ -383,7 +383,7 @@ void multiCameraCalibration::computeJacobianExtrinsic(const Mat& extrinsicParams
for (int edgeIdx = 0; edgeIdx < nEdge; ++edgeIdx)
{
int nPoints = _objectPointsForEachCamera[_edgeList[edgeIdx].cameraVertex][_edgeList[edgeIdx].photoIndex].total();
int nPoints = (int)_objectPointsForEachCamera[_edgeList[edgeIdx].cameraVertex][_edgeList[edgeIdx].photoIndex].total();
pointsLocation[edgeIdx+1] = pointsLocation[edgeIdx] + nPoints*2;
}

24
modules/ccalib/src/omnidir.cpp
Unescape View File

@ -894,7 +894,7 @@ void cv::omnidir::internal::computeJacobian(InputArrayOfArrays objectPoints, Inp
int nPointsAll = 0;
for (int i = 0; i < n; ++i)
{
nPointsAll += objectPoints.getMat(i).total();
nPointsAll += (int)objectPoints.getMat(i).total();
}
//Mat J = Mat::zeros(2*n*objectPoints.getMat(0).total(), 10+6*n, CV_64F);
@ -940,8 +940,8 @@ void cv::omnidir::internal::computeJacobian(InputArrayOfArrays objectPoints, Inp
Mat(JIn.t()*JEx).copyTo(JTJ(Rect(i*6, 6*n, 6, 10)));
JTE(Rect(0, 6*n, 1, 10)) = JTE(Rect(0, 6*n,1, 10)) + JIn.t() * projError.reshape(1, 2*projError.total());
JTE(Rect(0, i*6, 1, 6)) = JEx.t() * projError.reshape(1, 2*projError.total());
JTE(Rect(0, 6*n, 1, 10)) = JTE(Rect(0, 6*n,1, 10)) + JIn.t() * projError.reshape(1, 2*(int)projError.total());
JTE(Rect(0, i*6, 1, 6)) = JEx.t() * projError.reshape(1, 2*(int)projError.total());
//int nPoints = objectPoints.getMat(i).total();
//JIn.copyTo(J(Rect(6*n, i*nPoints*2, 10, nPoints*2)));
@ -970,8 +970,8 @@ void cv::omnidir::internal::computeJacobianStereo(InputArrayOfArrays objectPoint
CV_Assert((imagePoints1.total() == imagePoints2.total()) && (imagePoints1.total() == objectPoints.total()));
// compute Jacobian matrix by naive way
int n_img = objectPoints.total();
int n_points = objectPoints.getMat(0).total();
int n_img = (int)objectPoints.total();
int n_points = (int)objectPoints.getMat(0).total();
Mat J = Mat::zeros(4 * n_points * n_img, 20 + 6 * (n_img + 1), CV_64F);
Mat exAll = Mat::zeros(4 * n_points * n_img, 1, CV_64F);
double *para = parameters.getMat().ptr<double>();
@ -1298,7 +1298,7 @@ double cv::omnidir::calibrate(InputArray patternPoints, InputArray imagePoints,
if (idx.needed())
{
idx.create(1, _idx.total(), CV_32S);
idx.create(1, (int)_idx.total(), CV_Assert_32S);
_idx.copyTo(idx.getMat());
}
@ -1620,7 +1620,7 @@ void cv::omnidir::stereoReconstruct(InputArray image1, InputArray image2, InputA
}
}
}
int nPoints;
int nPoints = 0;
if (pointType == XYZ)
{
nPoints = (int)_pointCloud.size();
@ -1638,7 +1638,7 @@ void cv::omnidir::internal::encodeParameters(InputArray K, InputArrayOfArrays om
{
CV_Assert(K.type() == CV_64F && K.size() == Size(3,3));
CV_Assert(distoaration.total() == 4 && distoaration.type() == CV_64F);
int n = omAll.total();
int n = (int)omAll.total();
Mat _omAll = omAll.getMat(), _tAll = tAll.getMat();
Mat tmp = Mat(_omAll.at<Vec3d>(0)).reshape(1,3).clone();
Matx33d _K = K.getMat();
@ -1771,7 +1771,7 @@ void cv::omnidir::internal::encodeParametersStereo(InputArray K1, InputArray K2,
if(T.empty())
T.create(3, 1, CV_64F);
int n = (parameters.total() - 20) / 6 - 1;
int n = ((int)parameters.total() - 20) / 6 - 1;
if(omL.empty())
omL.create(1, n, CV_64FC3);
@ -1839,7 +1839,7 @@ void cv::omnidir::internal::estimateUncertainties(InputArrayOfArrays objectPoint
int nPointsAll = 0;
for (int i = 0; i < n; ++i)
{
nPointsAll += objectPoints.getMat(i).total();
nPointsAll += (int)objectPoints.getMat(i).total();
}
Mat reprojError = Mat(nPointsAll, 1, CV_64FC2);
@ -1907,7 +1907,7 @@ void cv::omnidir::internal::estimateUncertaintiesStereo(InputArrayOfArrays objec
CV_Assert(!objectPoints.empty() && objectPoints.type() == CV_64FC3);
CV_Assert(!imagePoints1.empty() && imagePoints1.type() == CV_64FC2 && imagePoints1.total() == objectPoints.total());
CV_Assert(!imagePoints2.empty() && imagePoints2.type() == CV_64FC2 && imagePoints1.total() == imagePoints2.total());
int n_img = objectPoints.total();
int n_img = (int)objectPoints.total();
CV_Assert((int)parameters.total() == (6*(n_img+1)+20));
Mat _K1, _K2, _D1, _D2;
@ -1917,7 +1917,7 @@ void cv::omnidir::internal::estimateUncertaintiesStereo(InputArrayOfArrays objec
double _xi1, _xi2;
internal::decodeParametersStereo(_parameters, _K1, _K2, _om, _T, _omL, _tL, _D1, _D2, _xi1, _xi2);
int n_points = objectPoints.getMat(0).total();
int n_points = (int)objectPoints.getMat(0).total();
Mat reprojErrorAll = Mat::zeros(2*n_points*n_img, 1, CV_64FC2);
// error for left image

2
modules/ccalib/tutorial/omnidir_tutorial.markdown
Unescape View File

@ -68,7 +68,7 @@ Your can specify ```flags``` to fix parameters during calibration. Use 'plus' op
Stereo Calibration
--------------------------
Stereo calibration is to calibrate two cameras together. The output parameters include camera parameters of two cameras and the relative pose of them. To recover the relative pose, two cameras must observe the same pattern at the same time, so the ```objectPoints``` of two cameras are the same.
Stereo calibration is to calibrate two cameras together. The output parameters include camera parameters of two cameras and the relative pose of them. To recover the relative pose, two cameras must observe the same pattern at the same time, so the ```objectPoints``` of two cameras are the same.
Now detect image corners for both cameras as discussed above to get ```imagePoints1``` and ```imagePoints2```. Then compute the shared ```objectPoints```.

Write Preview
Loading…
Cancel
Save