Modifier and Type | Method and Description |
---|---|
static void |
opencv_features2d.computeRecallPrecisionCurve(DMatchVectorVector matches1to2,
ByteVectorVector correctMatches1to2Mask,
Point2fVector recallPrecisionCurve) |
static void |
opencv_face.drawFacemarks(Mat image,
Point2fVector points,
Scalar color)
\brief Utility to draw the detected facial landmark points
|
static int |
opencv_features2d.getNearestPoint(Point2fVector recallPrecisionCurve,
float l_precision) |
static float |
opencv_features2d.getRecall(Point2fVector recallPrecisionCurve,
float l_precision) |
Modifier and Type | Method and Description |
---|---|
Point2fVector[] |
Point2fVectorVector.get() |
Point2fVector |
Point2fVectorVector.Iterator.get() |
Point2fVector |
Point2fVectorVector.get(long i) |
Point2fVector |
Point2fVectorVector.pop_back() |
Point2fVector |
Point2fVector.push_back(Point2f value) |
Point2fVector |
Point2fVector.put(long i,
Point2f value) |
Point2fVector |
Point2fVector.put(Point2f... array) |
Point2fVector |
Point2fVector.put(Point2f value) |
Point2fVector |
Point2fVector.put(Point2fVector x) |
Modifier and Type | Method and Description |
---|---|
static void |
KeyPoint.convert(KeyPointVector keypoints,
Point2fVector points2f) |
static void |
KeyPoint.convert(KeyPointVector keypoints,
Point2fVector points2f,
int[] keypointIndexes) |
static void |
KeyPoint.convert(KeyPointVector keypoints,
Point2fVector points2f,
IntBuffer keypointIndexes) |
static void |
KeyPoint.convert(KeyPointVector keypoints,
Point2fVector points2f,
IntPointer keypointIndexes)
This method converts vector of keypoints to vector of points or the reverse, where each keypoint is
assigned the same size and the same orientation.
|
static void |
KeyPoint.convert(Point2fVector points2f,
KeyPointVector keypoints) |
static void |
KeyPoint.convert(Point2fVector points2f,
KeyPointVector keypoints,
float size,
float response,
int octave,
int class_id)
\overload
|
Point2fVectorVector.Iterator |
Point2fVectorVector.insert(Point2fVectorVector.Iterator pos,
Point2fVector value) |
Point2fVectorVector |
Point2fVectorVector.push_back(Point2fVector value) |
Point2fVectorVector |
Point2fVectorVector.put(long i,
Point2fVector value) |
Point2fVectorVector |
Point2fVectorVector.put(Point2fVector... array) |
Point2fVector |
Point2fVector.put(Point2fVector x) |
Point2fVectorVector |
Point2fVectorVector.put(Point2fVector value) |
Constructor and Description |
---|
Point2fVectorVector(Point2fVector... array) |
Point2fVectorVector(Point2fVector value) |
Modifier and Type | Method and Description |
---|---|
Point2fVector |
KeypointsModel.estimate(GpuMat frame) |
Point2fVector |
KeypointsModel.estimate(GpuMat frame,
float thresh) |
Point2fVector |
KeypointsModel.estimate(Mat frame) |
Point2fVector |
KeypointsModel.estimate(Mat frame,
float thresh)
\brief Given the \p input frame, create input blob, run net
|
Point2fVector |
KeypointsModel.estimate(UMat frame) |
Point2fVector |
KeypointsModel.estimate(UMat frame,
float thresh) |
Modifier and Type | Method and Description |
---|---|
Point2fVector |
FacemarkAAM.Model.Texture.base_shape()
basic shape, normalized to be fit in an image with current detection resolution
|
Point2fVector |
FacemarkAAM.Data.s0() |
Point2fVector |
FacemarkAAM.Model.s0()
the basic shape obtained from training dataset
|
Modifier and Type | Method and Description |
---|---|
boolean |
FacemarkTrain.addTrainingSample(Mat image,
Point2fVector landmarks)
\brief Add one training sample to the trainer.
|
FacemarkAAM.Model.Texture |
FacemarkAAM.Model.Texture.base_shape(Point2fVector setter) |
FacemarkAAM.Data |
FacemarkAAM.Data.s0(Point2fVector setter) |
FacemarkAAM.Model |
FacemarkAAM.Model.s0(Point2fVector setter) |
Modifier and Type | Method and Description |
---|---|
void |
Subdiv2D.getVoronoiFacetList(int[] idx,
Point2fVectorVector facetList,
Point2fVector facetCenters) |
void |
Subdiv2D.getVoronoiFacetList(IntBuffer idx,
Point2fVectorVector facetList,
Point2fVector facetCenters) |
void |
Subdiv2D.getVoronoiFacetList(IntPointer idx,
Point2fVectorVector facetList,
Point2fVector facetCenters)
\brief Returns a list of all Voronoi facets.
|
void |
Subdiv2D.insert(Point2fVector ptvec)
\brief Insert multiple points into a Delaunay triangulation.
|
Modifier and Type | Method and Description |
---|---|
Point2fVector |
SinusoidalPattern.Params.markersLocation() |
Modifier and Type | Method and Description |
---|---|
SinusoidalPattern.Params |
SinusoidalPattern.Params.markersLocation(Point2fVector setter) |
Modifier and Type | Method and Description |
---|---|
Point2fVector |
PCTSignatures.getSamplingPoints()
\brief Initial samples taken from the image.
|
Modifier and Type | Method and Description |
---|---|
static PCTSignatures |
PCTSignatures.create(Point2fVector initSamplingPoints,
int initSeedCount)
\brief Creates PCTSignatures algorithm using pre-generated sampling points
and number of clusterization seeds.
|
static PCTSignatures |
PCTSignatures.create(Point2fVector initSamplingPoints,
int[] initClusterSeedIndexes) |
static PCTSignatures |
PCTSignatures.create(Point2fVector initSamplingPoints,
IntBuffer initClusterSeedIndexes) |
static PCTSignatures |
PCTSignatures.create(Point2fVector initSamplingPoints,
IntPointer initClusterSeedIndexes)
\brief Creates PCTSignatures algorithm using pre-generated sampling points
and clusterization seeds indexes.
|
static void |
PCTSignatures.generateInitPoints(Point2fVector initPoints,
int count,
int pointDistribution)
\brief Generates initial sampling points according to selected point distribution.
|
void |
PCTSignatures.setSamplingPoints(Point2fVector samplingPoints)
\brief Sets sampling points used to sample the input image.
|
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