//javadoc: calibrate(objectPoints, imagePoints, size, K, xi, D, rvecs, tvecs, flags, criteria)
public static double calibrate(List <Mat> objectPoints, List <Mat> imagePoints, Size size, Mat K, Mat xi, Mat D, List <Mat> rvecs, List <Mat> tvecs, int flags, TermCriteria criteria)
{
if (K != null)
{
K.ThrowIfDisposed();
}
if (xi != null)
{
xi.ThrowIfDisposed();
}
if (D != null)
{
D.ThrowIfDisposed();
}
#if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
Mat objectPoints_mat = Converters.vector_Mat_to_Mat(objectPoints);
Mat imagePoints_mat = Converters.vector_Mat_to_Mat(imagePoints);
Mat rvecs_mat = new Mat();
Mat tvecs_mat = new Mat();
double retVal = ccalib_Ccalib_calibrate_11(objectPoints_mat.nativeObj, imagePoints_mat.nativeObj, size.width, size.height, K.nativeObj, xi.nativeObj, D.nativeObj, rvecs_mat.nativeObj, tvecs_mat.nativeObj, flags, criteria.type, criteria.maxCount, criteria.epsilon);
Converters.Mat_to_vector_Mat(rvecs_mat, rvecs);
rvecs_mat.release();
Converters.Mat_to_vector_Mat(tvecs_mat, tvecs);
tvecs_mat.release();
return(retVal);
#else
return(-1);
#endif
}
//
// C++: double cv::omnidir::stereoCalibrate(vector_Mat& objectPoints, vector_Mat& imagePoints1, vector_Mat& imagePoints2, Size imageSize1, Size imageSize2, Mat& K1, Mat& xi1, Mat& D1, Mat& K2, Mat& xi2, Mat& D2, Mat& rvec, Mat& tvec, vector_Mat& rvecsL, vector_Mat& tvecsL, int flags, TermCriteria criteria, Mat& idx = Mat())
//
//javadoc: stereoCalibrate(objectPoints, imagePoints1, imagePoints2, imageSize1, imageSize2, K1, xi1, D1, K2, xi2, D2, rvec, tvec, rvecsL, tvecsL, flags, criteria, idx)
public static double stereoCalibrate(List <Mat> objectPoints, List <Mat> imagePoints1, List <Mat> imagePoints2, Size imageSize1, Size imageSize2, Mat K1, Mat xi1, Mat D1, Mat K2, Mat xi2, Mat D2, Mat rvec, Mat tvec, List <Mat> rvecsL, List <Mat> tvecsL, int flags, TermCriteria criteria, Mat idx)
{
if (K1 != null)
{
K1.ThrowIfDisposed();
}
if (xi1 != null)
{
xi1.ThrowIfDisposed();
}
if (D1 != null)
{
D1.ThrowIfDisposed();
}
if (K2 != null)
{
K2.ThrowIfDisposed();
}
if (xi2 != null)
{
xi2.ThrowIfDisposed();
}
if (D2 != null)
{
D2.ThrowIfDisposed();
}
if (rvec != null)
{
rvec.ThrowIfDisposed();
}
if (tvec != null)
{
tvec.ThrowIfDisposed();
}
if (idx != null)
{
idx.ThrowIfDisposed();
}
#if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
Mat objectPoints_mat = Converters.vector_Mat_to_Mat(objectPoints);
Mat imagePoints1_mat = Converters.vector_Mat_to_Mat(imagePoints1);
Mat imagePoints2_mat = Converters.vector_Mat_to_Mat(imagePoints2);
Mat rvecsL_mat = new Mat();
Mat tvecsL_mat = new Mat();
double retVal = ccalib_Ccalib_stereoCalibrate_10(objectPoints_mat.nativeObj, imagePoints1_mat.nativeObj, imagePoints2_mat.nativeObj, imageSize1.width, imageSize1.height, imageSize2.width, imageSize2.height, K1.nativeObj, xi1.nativeObj, D1.nativeObj, K2.nativeObj, xi2.nativeObj, D2.nativeObj, rvec.nativeObj, tvec.nativeObj, rvecsL_mat.nativeObj, tvecsL_mat.nativeObj, flags, criteria.type, criteria.maxCount, criteria.epsilon, idx.nativeObj);
Converters.Mat_to_vector_Mat(objectPoints_mat, objectPoints);
objectPoints_mat.release();
Converters.Mat_to_vector_Mat(imagePoints1_mat, imagePoints1);
imagePoints1_mat.release();
Converters.Mat_to_vector_Mat(imagePoints2_mat, imagePoints2);
imagePoints2_mat.release();
Converters.Mat_to_vector_Mat(rvecsL_mat, rvecsL);
rvecsL_mat.release();
Converters.Mat_to_vector_Mat(tvecsL_mat, tvecsL);
tvecsL_mat.release();
return(retVal);
#else
return(-1);
#endif
}
//
// C++: vector_Mat cv::face::LBPHFaceRecognizer::getHistograms()
//
//javadoc: LBPHFaceRecognizer::getHistograms()
public List <Mat> getHistograms()
{
ThrowIfDisposed();
#if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
List <Mat> retVal = new List <Mat>();
Mat retValMat = new Mat(face_LBPHFaceRecognizer_getHistograms_10(nativeObj));
Converters.Mat_to_vector_Mat(retValMat, retVal);
return(retVal);
#else
return(null);
#endif
}
//
// C++: vector_Mat getProjections()
//
//javadoc: BasicFaceRecognizer::getProjections()
public List <Mat> getProjections()
{
ThrowIfDisposed();
#if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS) && !UNITY_EDITOR) || UNITY_5
List <Mat> retVal = new List <Mat>();
Mat retValMat = new Mat(face_BasicFaceRecognizer_getProjections_10(nativeObj));
Converters.Mat_to_vector_Mat(retValMat, retVal);
return(retVal);
#else
return(null);
#endif
}
//javadoc: imreadmulti(filename, mats)
public static bool imreadmulti(string filename, List <Mat> mats)
{
#if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
Mat mats_mat = new Mat();
bool retVal = imgcodecs_Imgcodecs_imreadmulti_11(filename, mats_mat.nativeObj);
Converters.Mat_to_vector_Mat(mats_mat, mats);
mats_mat.release();
return(retVal);
#else
return(false);
#endif
}
//
// C++: vector_Mat getTrainDescriptors()
//
//javadoc: javaDescriptorMatcher::getTrainDescriptors()
public List <Mat> getTrainDescriptors()
{
ThrowIfDisposed();
#if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS) && !UNITY_EDITOR) || UNITY_5
List <Mat> retVal = new List <Mat> ();
Mat retValMat = new Mat(features2d_DescriptorMatcher_getTrainDescriptors_10(nativeObj));
Converters.Mat_to_vector_Mat(retValMat, retVal);
return(retVal);
#else
return(null);
#endif
}
//
// C++: void getCovs(vector_Mat& covs)
//
//javadoc: EM::getCovs(covs)
public void getCovs(List <Mat> covs)
{
ThrowIfDisposed();
#if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS) && !UNITY_EDITOR) || UNITY_5
Mat covs_mat = new Mat();
ml_EM_getCovs_10(nativeObj, covs_mat.nativeObj);
Converters.Mat_to_vector_Mat(covs_mat, covs);
covs_mat.release();
return;
#else
return;
#endif
}
//
// C++: bool cv::structured_light::StructuredLightPattern::decode(vector_vector_Mat patternImages, Mat& disparityMap, vector_Mat blackImages = vector_Mat(), vector_Mat whiteImages = vector_Mat(), int flags = DECODE_3D_UNDERWORLD)
//
// Unknown type 'vector_vector_Mat' (I), skipping the function
//
// C++: bool cv::structured_light::StructuredLightPattern::generate(vector_Mat& patternImages)
//
//javadoc: StructuredLightPattern::generate(patternImages)
public bool generate(List <Mat> patternImages)
{
ThrowIfDisposed();
#if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
Mat patternImages_mat = new Mat();
bool retVal = structured_1light_StructuredLightPattern_generate_10(nativeObj, patternImages_mat.nativeObj);
Converters.Mat_to_vector_Mat(patternImages_mat, patternImages);
patternImages_mat.release();
return(retVal);
#else
return(false);
#endif
}
//
// C++: vector_Mat cv::dnn::Layer::finalize(vector_Mat inputs)
//
//javadoc: Layer::finalize(inputs)
public List <Mat> finalize(List <Mat> inputs)
{
ThrowIfDisposed();
#if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
Mat inputs_mat = Converters.vector_Mat_to_Mat(inputs);
List <Mat> retVal = new List <Mat>();
Mat retValMat = new Mat(dnn_Layer_finalize_10(nativeObj, inputs_mat.nativeObj));
Converters.Mat_to_vector_Mat(retValMat, retVal);
return(retVal);
#else
return(null);
#endif
}
//
// C++: vector_Mat Algorithm::getMatVector(string name)
//
public List <Mat> getMatVector(string name)
{
ThrowIfDisposed();
#if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS) && !UNITY_EDITOR) || UNITY_5
List <Mat> retVal = new List <Mat> ();
Mat retValMat = new Mat(core_Algorithm_getMatVector_10(nativeObj, name));
Converters.Mat_to_vector_Mat(retValMat, retVal);
return(retVal);
#else
return(null);
#endif
}
//javadoc: Net::forward(outputBlobs)
public void forward(List <Mat> outputBlobs)
{
ThrowIfDisposed();
#if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
Mat outputBlobs_mat = new Mat();
dnn_Net_forward_13(nativeObj, outputBlobs_mat.nativeObj);
Converters.Mat_to_vector_Mat(outputBlobs_mat, outputBlobs);
outputBlobs_mat.release();
return;
#else
return;
#endif
}
//
// C++: void cv::dnn::Layer::finalize(vector_Mat inputs, vector_Mat& outputs)
//
//javadoc: Layer::finalize(inputs, outputs)
public void finalize(List <Mat> inputs, List <Mat> outputs)
{
ThrowIfDisposed();
#if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
Mat inputs_mat = Converters.vector_Mat_to_Mat(inputs);
Mat outputs_mat = new Mat();
dnn_Layer_finalize_11(nativeObj, inputs_mat.nativeObj, outputs_mat.nativeObj);
Converters.Mat_to_vector_Mat(outputs_mat, outputs);
outputs_mat.release();
return;
#else
return;
#endif
}
//
// C++: void cv::dnn::imagesFromBlob(Mat blob_, vector_Mat& images_)
//
//javadoc: imagesFromBlob(blob_, images_)
public static void imagesFromBlob(Mat blob_, List <Mat> images_)
{
if (blob_ != null)
{
blob_.ThrowIfDisposed();
}
#if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
Mat images__mat = new Mat();
dnn_Dnn_imagesFromBlob_10(blob_.nativeObj, images__mat.nativeObj);
Converters.Mat_to_vector_Mat(images__mat, images_);
images__mat.release();
return;
#else
return;
#endif
}
//javadoc: buildOpticalFlowPyramid(img, pyramid, winSize, maxLevel)
public static int buildOpticalFlowPyramid(Mat img, List <Mat> pyramid, Size winSize, int maxLevel)
{
if (img != null)
{
img.ThrowIfDisposed();
}
#if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
Mat pyramid_mat = new Mat();
int retVal = video_Video_buildOpticalFlowPyramid_11(img.nativeObj, pyramid_mat.nativeObj, winSize.width, winSize.height, maxLevel);
Converters.Mat_to_vector_Mat(pyramid_mat, pyramid);
pyramid_mat.release();
return(retVal);
#else
return(-1);
#endif
}
//javadoc: computeNMChannels(_src, _channels)
public static void computeNMChannels(Mat _src, List <Mat> _channels)
{
if (_src != null)
{
_src.ThrowIfDisposed();
}
#if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
Mat _channels_mat = new Mat();
text_Text_computeNMChannels_11(_src.nativeObj, _channels_mat.nativeObj);
Converters.Mat_to_vector_Mat(_channels_mat, _channels);
_channels_mat.release();
return;
#else
return;
#endif
}
//
// C++: int buildOpticalFlowPyramid(Mat img, vector_Mat& pyramid, Size winSize, int maxLevel, bool withDerivatives = true, int pyrBorder = BORDER_REFLECT_101, int derivBorder = BORDER_CONSTANT, bool tryReuseInputImage = true)
//
//javadoc: buildOpticalFlowPyramid(img, pyramid, winSize, maxLevel, withDerivatives, pyrBorder, derivBorder, tryReuseInputImage)
public static int buildOpticalFlowPyramid(Mat img, List <Mat> pyramid, Size winSize, int maxLevel, bool withDerivatives, int pyrBorder, int derivBorder, bool tryReuseInputImage)
{
if (img != null)
{
img.ThrowIfDisposed();
}
#if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS) && !UNITY_EDITOR) || UNITY_5
Mat pyramid_mat = new Mat();
int retVal = video_Video_buildOpticalFlowPyramid_10(img.nativeObj, pyramid_mat.nativeObj, winSize.width, winSize.height, maxLevel, withDerivatives, pyrBorder, derivBorder, tryReuseInputImage);
Converters.Mat_to_vector_Mat(pyramid_mat, pyramid);
return(retVal);
#else
return(-1);
#endif
}
//
// C++: void javaDescriptorExtractor::compute(vector_Mat images, vector_vector_KeyPoint& keypoints, vector_Mat& descriptors)
//
/**
* <p>Computes the descriptors for a set of keypoints detected in an image (first
* variant) or image set (second variant).</p>
*
* @param images Image set.
* @param keypoints Input collection of keypoints. Keypoints for which a
* descriptor cannot be computed are removed and the remaining ones may be
* reordered. Sometimes new keypoints can be added, for example:
* <code>SIFT</code> duplicates a keypoint with several dominant orientations
* (for each orientation).
* @param descriptors Computed descriptors. In the second variant of the method
* <code>descriptors[i]</code> are descriptors computed for a <code>keypoints[i]</code>.
* Row <code>j</code> is the <code>keypoints</code> (or <code>keypoints[i]</code>)
* is the descriptor for keypoint <code>j</code>-th keypoint.
*
* @see <a href="http://docs.opencv.org/modules/features2d/doc/common_interfaces_of_descriptor_extractors.html#descriptorextractor-compute">org.opencv.features2d.DescriptorExtractor.compute</a>
*/
public void compute(List <Mat> images, List <MatOfKeyPoint> keypoints, List <Mat> descriptors)
{
ThrowIfDisposed();
#if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS) && !UNITY_EDITOR) || UNITY_5
Mat images_mat = Converters.vector_Mat_to_Mat(images);
List <Mat> keypoints_tmplm = new List <Mat> ((keypoints != null) ? keypoints.Count : 0);
Mat keypoints_mat = Converters.vector_vector_KeyPoint_to_Mat(keypoints, keypoints_tmplm);
Mat descriptors_mat = new Mat();
features2d_DescriptorExtractor_compute_11(nativeObj, images_mat.nativeObj, keypoints_mat.nativeObj, descriptors_mat.nativeObj);
Converters.Mat_to_vector_vector_KeyPoint(keypoints_mat, keypoints);
Converters.Mat_to_vector_Mat(descriptors_mat, descriptors);
return;
#else
return;
#endif
}
//
// C++: void cv::structured_light::SinusoidalPattern::findProCamMatches(Mat projUnwrappedPhaseMap, Mat camUnwrappedPhaseMap, vector_Mat& matches)
//
//javadoc: SinusoidalPattern::findProCamMatches(projUnwrappedPhaseMap, camUnwrappedPhaseMap, matches)
public void findProCamMatches(Mat projUnwrappedPhaseMap, Mat camUnwrappedPhaseMap, List <Mat> matches)
{
ThrowIfDisposed();
if (projUnwrappedPhaseMap != null)
{
projUnwrappedPhaseMap.ThrowIfDisposed();
}
if (camUnwrappedPhaseMap != null)
{
camUnwrappedPhaseMap.ThrowIfDisposed();
}
#if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
Mat matches_mat = new Mat();
structured_1light_SinusoidalPattern_findProCamMatches_10(nativeObj, projUnwrappedPhaseMap.nativeObj, camUnwrappedPhaseMap.nativeObj, matches_mat.nativeObj);
Converters.Mat_to_vector_Mat(matches_mat, matches);
matches_mat.release();
return;
#else
return;
#endif
}
