Modifier and Type | Method and Description |
---|---|
static void |
opencv_text.detectRegions(GpuMat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects) |
static void |
opencv_text.detectRegions(GpuMat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects,
int method,
BytePointer filename,
float minProbability) |
static void |
opencv_text.detectRegions(GpuMat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects,
int method,
String filename,
float minProbability) |
static void |
opencv_text.detectRegions(Mat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects) |
static void |
opencv_text.detectRegions(Mat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects,
int method,
BytePointer filename,
float minProbability)
\brief Extracts text regions from image.
|
static void |
opencv_text.detectRegions(Mat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects,
int method,
String filename,
float minProbability) |
static void |
opencv_text.detectRegions(UMat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects) |
static void |
opencv_text.detectRegions(UMat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects,
int method,
BytePointer filename,
float minProbability) |
static void |
opencv_text.detectRegions(UMat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects,
int method,
String filename,
float minProbability) |
static void |
opencv_text.erGrouping(GpuMat image,
GpuMat channel,
PointVectorVector regions,
RectVector groups_rects) |
static void |
opencv_text.erGrouping(GpuMat image,
GpuMat channel,
PointVectorVector regions,
RectVector groups_rects,
int method,
BytePointer filename,
float minProbablity) |
static void |
opencv_text.erGrouping(GpuMat image,
GpuMat channel,
PointVectorVector regions,
RectVector groups_rects,
int method,
String filename,
float minProbablity) |
static void |
opencv_text.erGrouping(GpuMat img,
GpuMatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects) |
static void |
opencv_text.erGrouping(GpuMat img,
GpuMatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects,
int method,
BytePointer filename,
float minProbablity) |
static void |
opencv_text.erGrouping(GpuMat img,
GpuMatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects,
int method,
String filename,
float minProbablity) |
static void |
opencv_text.erGrouping(GpuMat img,
MatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects) |
static void |
opencv_text.erGrouping(GpuMat img,
MatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects,
int method,
BytePointer filename,
float minProbablity) |
static void |
opencv_text.erGrouping(GpuMat img,
MatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects,
int method,
String filename,
float minProbablity) |
static void |
opencv_text.erGrouping(GpuMat img,
UMatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects) |
static void |
opencv_text.erGrouping(GpuMat img,
UMatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects,
int method,
BytePointer filename,
float minProbablity) |
static void |
opencv_text.erGrouping(GpuMat img,
UMatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects,
int method,
String filename,
float minProbablity) |
static void |
opencv_text.erGrouping(Mat img,
GpuMatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects) |
static void |
opencv_text.erGrouping(Mat img,
GpuMatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects,
int method,
BytePointer filename,
float minProbablity) |
static void |
opencv_text.erGrouping(Mat img,
GpuMatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects,
int method,
String filename,
float minProbablity) |
static void |
opencv_text.erGrouping(Mat image,
Mat channel,
PointVectorVector regions,
RectVector groups_rects) |
static void |
opencv_text.erGrouping(Mat image,
Mat channel,
PointVectorVector regions,
RectVector groups_rects,
int method,
BytePointer filename,
float minProbablity) |
static void |
opencv_text.erGrouping(Mat image,
Mat channel,
PointVectorVector regions,
RectVector groups_rects,
int method,
String filename,
float minProbablity) |
static void |
opencv_text.erGrouping(Mat img,
MatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects) |
static void |
opencv_text.erGrouping(Mat img,
MatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects,
int method,
BytePointer filename,
float minProbablity)
\brief Find groups of Extremal Regions that are organized as text blocks.
|
static void |
opencv_text.erGrouping(Mat img,
MatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects,
int method,
String filename,
float minProbablity) |
static void |
opencv_text.erGrouping(Mat img,
UMatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects) |
static void |
opencv_text.erGrouping(Mat img,
UMatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects,
int method,
BytePointer filename,
float minProbablity) |
static void |
opencv_text.erGrouping(Mat img,
UMatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects,
int method,
String filename,
float minProbablity) |
static void |
opencv_text.erGrouping(UMat img,
GpuMatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects) |
static void |
opencv_text.erGrouping(UMat img,
GpuMatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects,
int method,
BytePointer filename,
float minProbablity) |
static void |
opencv_text.erGrouping(UMat img,
GpuMatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects,
int method,
String filename,
float minProbablity) |
static void |
opencv_text.erGrouping(UMat img,
MatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects) |
static void |
opencv_text.erGrouping(UMat img,
MatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects,
int method,
BytePointer filename,
float minProbablity) |
static void |
opencv_text.erGrouping(UMat img,
MatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects,
int method,
String filename,
float minProbablity) |
static void |
opencv_text.erGrouping(UMat image,
UMat channel,
PointVectorVector regions,
RectVector groups_rects) |
static void |
opencv_text.erGrouping(UMat image,
UMat channel,
PointVectorVector regions,
RectVector groups_rects,
int method,
BytePointer filename,
float minProbablity) |
static void |
opencv_text.erGrouping(UMat image,
UMat channel,
PointVectorVector regions,
RectVector groups_rects,
int method,
String filename,
float minProbablity) |
static void |
opencv_text.erGrouping(UMat img,
UMatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects) |
static void |
opencv_text.erGrouping(UMat img,
UMatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects,
int method,
BytePointer filename,
float minProbablity) |
static void |
opencv_text.erGrouping(UMat img,
UMatVector channels,
ERStatVectorVector regions,
PointVectorVector groups,
RectVector groups_rects,
int method,
String filename,
float minProbablity) |
static boolean |
opencv_face.getFaces(Mat image,
RectVector faces,
CParams params)
\brief Default face detector
This function is mainly utilized by the implementation of a Facemark Algorithm.
|
static boolean |
opencv_face.getFacesHAAR(Mat image,
RectVector faces,
String face_cascade_name) |
static void |
opencv_objdetect.groupRectangles_meanshift(RectVector rectList,
double[] foundWeights,
double[] foundScales) |
static void |
opencv_objdetect.groupRectangles_meanshift(RectVector rectList,
double[] foundWeights,
double[] foundScales,
double detectThreshold,
Size winDetSize) |
static void |
opencv_objdetect.groupRectangles_meanshift(RectVector rectList,
DoubleBuffer foundWeights,
DoubleBuffer foundScales) |
static void |
opencv_objdetect.groupRectangles_meanshift(RectVector rectList,
DoubleBuffer foundWeights,
DoubleBuffer foundScales,
double detectThreshold,
Size winDetSize) |
static void |
opencv_objdetect.groupRectangles_meanshift(RectVector rectList,
DoublePointer foundWeights,
DoublePointer foundScales) |
static void |
opencv_objdetect.groupRectangles_meanshift(RectVector rectList,
DoublePointer foundWeights,
DoublePointer foundScales,
double detectThreshold,
Size winDetSize)
\overload
|
static void |
opencv_objdetect.groupRectangles(RectVector rectList,
int groupThreshold) |
static void |
opencv_objdetect.groupRectangles(RectVector rectList,
int[] rejectLevels,
double[] levelWeights,
int groupThreshold) |
static void |
opencv_objdetect.groupRectangles(RectVector rectList,
int[] rejectLevels,
double[] levelWeights,
int groupThreshold,
double eps) |
static void |
opencv_objdetect.groupRectangles(RectVector rectList,
int[] weights,
int groupThreshold) |
static void |
opencv_objdetect.groupRectangles(RectVector rectList,
int[] weights,
int groupThreshold,
double eps) |
static void |
opencv_objdetect.groupRectangles(RectVector rectList,
IntBuffer rejectLevels,
DoubleBuffer levelWeights,
int groupThreshold) |
static void |
opencv_objdetect.groupRectangles(RectVector rectList,
IntBuffer rejectLevels,
DoubleBuffer levelWeights,
int groupThreshold,
double eps) |
static void |
opencv_objdetect.groupRectangles(RectVector rectList,
IntBuffer weights,
int groupThreshold) |
static void |
opencv_objdetect.groupRectangles(RectVector rectList,
IntBuffer weights,
int groupThreshold,
double eps) |
static void |
opencv_objdetect.groupRectangles(RectVector rectList,
int groupThreshold,
double eps)
\brief Groups the object candidate rectangles.
|
static void |
opencv_objdetect.groupRectangles(RectVector rectList,
int groupThreshold,
double eps,
int[] weights,
double[] levelWeights) |
static void |
opencv_objdetect.groupRectangles(RectVector rectList,
int groupThreshold,
double eps,
IntBuffer weights,
DoubleBuffer levelWeights) |
static void |
opencv_objdetect.groupRectangles(RectVector rectList,
int groupThreshold,
double eps,
IntPointer weights,
DoublePointer levelWeights)
\overload
|
static void |
opencv_objdetect.groupRectangles(RectVector rectList,
IntPointer rejectLevels,
DoublePointer levelWeights,
int groupThreshold) |
static void |
opencv_objdetect.groupRectangles(RectVector rectList,
IntPointer rejectLevels,
DoublePointer levelWeights,
int groupThreshold,
double eps)
\overload
|
static void |
opencv_objdetect.groupRectangles(RectVector rectList,
IntPointer weights,
int groupThreshold) |
static void |
opencv_objdetect.groupRectangles(RectVector rectList,
IntPointer weights,
int groupThreshold,
double eps)
\overload
|
static void |
opencv_dnn.NMSBoxes(RectVector bboxes,
float[] scores,
float score_threshold,
float nms_threshold,
int[] indices) |
static void |
opencv_dnn.NMSBoxes(RectVector bboxes,
float[] scores,
float score_threshold,
float nms_threshold,
int[] indices,
float eta,
int top_k) |
static void |
opencv_dnn.NMSBoxes(RectVector bboxes,
FloatBuffer scores,
float score_threshold,
float nms_threshold,
IntBuffer indices) |
static void |
opencv_dnn.NMSBoxes(RectVector bboxes,
FloatBuffer scores,
float score_threshold,
float nms_threshold,
IntBuffer indices,
float eta,
int top_k) |
static void |
opencv_dnn.NMSBoxes(RectVector bboxes,
FloatPointer scores,
float score_threshold,
float nms_threshold,
IntPointer indices) |
static void |
opencv_dnn.NMSBoxes(RectVector bboxes,
FloatPointer scores,
float score_threshold,
float nms_threshold,
IntPointer indices,
float eta,
int top_k)
\brief Performs non maximum suppression given boxes and corresponding scores.
|
static void |
opencv_optflow.segmentMotion(GpuMat mhi,
GpuMat segmask,
RectVector boundingRects,
double timestamp,
double segThresh) |
static void |
opencv_optflow.segmentMotion(Mat mhi,
Mat segmask,
RectVector boundingRects,
double timestamp,
double segThresh)
\brief Splits a motion history image into a few parts corresponding to separate independent motions (for
example, left hand, right hand).
|
static void |
opencv_optflow.segmentMotion(UMat mhi,
UMat segmask,
RectVector boundingRects,
double timestamp,
double segThresh) |
static void |
opencv_highgui.selectROIs(BytePointer windowName,
GpuMat img,
RectVector boundingBoxes) |
static void |
opencv_highgui.selectROIs(BytePointer windowName,
GpuMat img,
RectVector boundingBoxes,
boolean showCrosshair,
boolean fromCenter) |
static void |
opencv_highgui.selectROIs(BytePointer windowName,
Mat img,
RectVector boundingBoxes) |
static void |
opencv_highgui.selectROIs(BytePointer windowName,
Mat img,
RectVector boundingBoxes,
boolean showCrosshair,
boolean fromCenter)
\brief Selects ROIs on the given image.
|
static void |
opencv_highgui.selectROIs(BytePointer windowName,
UMat img,
RectVector boundingBoxes) |
static void |
opencv_highgui.selectROIs(BytePointer windowName,
UMat img,
RectVector boundingBoxes,
boolean showCrosshair,
boolean fromCenter) |
static void |
opencv_highgui.selectROIs(String windowName,
GpuMat img,
RectVector boundingBoxes) |
static void |
opencv_highgui.selectROIs(String windowName,
GpuMat img,
RectVector boundingBoxes,
boolean showCrosshair,
boolean fromCenter) |
static void |
opencv_highgui.selectROIs(String windowName,
Mat img,
RectVector boundingBoxes) |
static void |
opencv_highgui.selectROIs(String windowName,
Mat img,
RectVector boundingBoxes,
boolean showCrosshair,
boolean fromCenter) |
static void |
opencv_highgui.selectROIs(String windowName,
UMat img,
RectVector boundingBoxes) |
static void |
opencv_highgui.selectROIs(String windowName,
UMat img,
RectVector boundingBoxes,
boolean showCrosshair,
boolean fromCenter) |
Modifier and Type | Method and Description |
---|---|
RectVector[] |
RectVectorVector.get() |
RectVector |
RectVectorVector.Iterator.get() |
RectVector |
RectVectorVector.get(long i) |
RectVector |
RectVectorVector.pop_back() |
RectVector |
RectVector.push_back(Rect value) |
RectVector |
RectVector.put(long i,
Rect value) |
RectVector |
RectVector.put(Rect... array) |
RectVector |
RectVector.put(Rect value) |
RectVector |
RectVector.put(RectVector x) |
Modifier and Type | Method and Description |
---|---|
RectVectorVector.Iterator |
RectVectorVector.insert(RectVectorVector.Iterator pos,
RectVector value) |
RectVectorVector |
RectVectorVector.push_back(RectVector value) |
RectVectorVector |
RectVectorVector.put(long i,
RectVector value) |
RectVectorVector |
RectVectorVector.put(RectVector... array) |
RectVector |
RectVector.put(RectVector x) |
RectVectorVector |
RectVectorVector.put(RectVector value) |
Constructor and Description |
---|
RectVectorVector(RectVector... array) |
RectVectorVector(RectVector value) |
Modifier and Type | Method and Description |
---|---|
void |
CudaCascadeClassifier.convert(GpuMat gpu_objects,
RectVector objects) |
void |
CudaCascadeClassifier.convert(Mat gpu_objects,
RectVector objects)
\brief Converts objects array from internal representation to standard vector.
|
void |
CudaCascadeClassifier.convert(UMat gpu_objects,
RectVector objects) |
void |
HOG.detectMultiScale(GpuMat img,
RectVector found_locations) |
void |
HOG.detectMultiScale(GpuMat img,
RectVector found_locations,
double[] confidences) |
void |
HOG.detectMultiScale(GpuMat img,
RectVector found_locations,
DoubleBuffer confidences) |
void |
HOG.detectMultiScale(GpuMat img,
RectVector found_locations,
DoublePointer confidences) |
void |
HOG.detectMultiScale(Mat img,
RectVector found_locations) |
void |
HOG.detectMultiScale(Mat img,
RectVector found_locations,
double[] confidences) |
void |
HOG.detectMultiScale(Mat img,
RectVector found_locations,
DoubleBuffer confidences) |
void |
HOG.detectMultiScale(Mat img,
RectVector found_locations,
DoublePointer confidences)
\brief Performs object detection with a multi-scale window.
|
void |
HOG.detectMultiScale(UMat img,
RectVector found_locations) |
void |
HOG.detectMultiScale(UMat img,
RectVector found_locations,
double[] confidences) |
void |
HOG.detectMultiScale(UMat img,
RectVector found_locations,
DoubleBuffer confidences) |
void |
HOG.detectMultiScale(UMat img,
RectVector found_locations,
DoublePointer confidences) |
void |
HOG.detectMultiScaleWithoutConf(GpuMat img,
RectVector found_locations) |
void |
HOG.detectMultiScaleWithoutConf(Mat img,
RectVector found_locations)
\brief Performs object detection with a multi-scale window.
|
void |
HOG.detectMultiScaleWithoutConf(UMat img,
RectVector found_locations) |
Modifier and Type | Method and Description |
---|---|
void |
DetectionModel.detect(GpuMat frame,
int[] classIds,
float[] confidences,
RectVector boxes) |
void |
DetectionModel.detect(GpuMat frame,
int[] classIds,
float[] confidences,
RectVector boxes,
float confThreshold,
float nmsThreshold) |
void |
DetectionModel.detect(GpuMat frame,
IntBuffer classIds,
FloatBuffer confidences,
RectVector boxes) |
void |
DetectionModel.detect(GpuMat frame,
IntBuffer classIds,
FloatBuffer confidences,
RectVector boxes,
float confThreshold,
float nmsThreshold) |
void |
DetectionModel.detect(GpuMat frame,
IntPointer classIds,
FloatPointer confidences,
RectVector boxes) |
void |
DetectionModel.detect(GpuMat frame,
IntPointer classIds,
FloatPointer confidences,
RectVector boxes,
float confThreshold,
float nmsThreshold) |
void |
DetectionModel.detect(Mat frame,
int[] classIds,
float[] confidences,
RectVector boxes) |
void |
DetectionModel.detect(Mat frame,
int[] classIds,
float[] confidences,
RectVector boxes,
float confThreshold,
float nmsThreshold) |
void |
DetectionModel.detect(Mat frame,
IntBuffer classIds,
FloatBuffer confidences,
RectVector boxes) |
void |
DetectionModel.detect(Mat frame,
IntBuffer classIds,
FloatBuffer confidences,
RectVector boxes,
float confThreshold,
float nmsThreshold) |
void |
DetectionModel.detect(Mat frame,
IntPointer classIds,
FloatPointer confidences,
RectVector boxes) |
void |
DetectionModel.detect(Mat frame,
IntPointer classIds,
FloatPointer confidences,
RectVector boxes,
float confThreshold,
float nmsThreshold)
\brief Given the \p input frame, create input blob, run net and return result detections.
|
void |
DetectionModel.detect(UMat frame,
int[] classIds,
float[] confidences,
RectVector boxes) |
void |
DetectionModel.detect(UMat frame,
int[] classIds,
float[] confidences,
RectVector boxes,
float confThreshold,
float nmsThreshold) |
void |
DetectionModel.detect(UMat frame,
IntBuffer classIds,
FloatBuffer confidences,
RectVector boxes) |
void |
DetectionModel.detect(UMat frame,
IntBuffer classIds,
FloatBuffer confidences,
RectVector boxes,
float confThreshold,
float nmsThreshold) |
void |
DetectionModel.detect(UMat frame,
IntPointer classIds,
FloatPointer confidences,
RectVector boxes) |
void |
DetectionModel.detect(UMat frame,
IntPointer classIds,
FloatPointer confidences,
RectVector boxes,
float confThreshold,
float nmsThreshold) |
Modifier and Type | Method and Description |
---|---|
boolean |
Facemark.fit(Mat image,
RectVector faces,
Point2fVectorVector landmarks)
\brief Detect facial landmarks from an image.
|
boolean |
FacemarkAAM.fitConfig(Mat image,
RectVector roi,
Point2fVectorVector _landmarks,
FacemarkAAM.Config runtime_params)
overload with additional Config structures
|
boolean |
FacemarkKazemi.getFaces(Mat image,
RectVector faces)
get faces using the custom detector
|
boolean |
FacemarkTrain.getFaces(Mat image,
RectVector faces)
\brief Detect faces from a given image using default or user defined face detector.
|
Modifier and Type | Method and Description |
---|---|
void |
MSER.detectRegions(GpuMat image,
PointVectorVector msers,
RectVector bboxes) |
void |
MSER.detectRegions(Mat image,
PointVectorVector msers,
RectVector bboxes)
\brief Detect %MSER regions
|
void |
MSER.detectRegions(UMat image,
PointVectorVector msers,
RectVector bboxes) |
Modifier and Type | Method and Description |
---|---|
void |
DetectionBasedTracker.IDetector.detect(Mat image,
RectVector objects) |
void |
CascadeClassifier.detectMultiScale(GpuMat image,
RectVector objects) |
void |
HOGDescriptor.detectMultiScale(GpuMat img,
RectVector foundLocations) |
void |
HOGDescriptor.detectMultiScale(GpuMat img,
RectVector foundLocations,
double[] foundWeights) |
void |
HOGDescriptor.detectMultiScale(GpuMat img,
RectVector foundLocations,
double[] foundWeights,
double hitThreshold,
Size winStride,
Size padding,
double scale,
double finalThreshold,
boolean useMeanshiftGrouping) |
void |
HOGDescriptor.detectMultiScale(GpuMat img,
RectVector foundLocations,
DoubleBuffer foundWeights) |
void |
HOGDescriptor.detectMultiScale(GpuMat img,
RectVector foundLocations,
DoubleBuffer foundWeights,
double hitThreshold,
Size winStride,
Size padding,
double scale,
double finalThreshold,
boolean useMeanshiftGrouping) |
void |
CascadeClassifier.detectMultiScale(GpuMat image,
RectVector objects,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize) |
void |
BaseCascadeClassifier.detectMultiScale(GpuMat image,
RectVector objects,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize) |
void |
HOGDescriptor.detectMultiScale(GpuMat img,
RectVector foundLocations,
DoublePointer foundWeights) |
void |
HOGDescriptor.detectMultiScale(GpuMat img,
RectVector foundLocations,
DoublePointer foundWeights,
double hitThreshold,
Size winStride,
Size padding,
double scale,
double finalThreshold,
boolean useMeanshiftGrouping) |
void |
HOGDescriptor.detectMultiScale(GpuMat img,
RectVector foundLocations,
double hitThreshold,
Size winStride,
Size padding,
double scale,
double finalThreshold,
boolean useMeanshiftGrouping) |
void |
BaseCascadeClassifier.detectMultiScale(GpuMat image,
RectVector objects,
int[] rejectLevels,
double[] levelWeights,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize,
boolean outputRejectLevels) |
void |
BaseCascadeClassifier.detectMultiScale(GpuMat image,
RectVector objects,
int[] numDetections,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize) |
void |
BaseCascadeClassifier.detectMultiScale(GpuMat image,
RectVector objects,
IntBuffer rejectLevels,
DoubleBuffer levelWeights,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize,
boolean outputRejectLevels) |
void |
BaseCascadeClassifier.detectMultiScale(GpuMat image,
RectVector objects,
IntBuffer numDetections,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize) |
void |
BaseCascadeClassifier.detectMultiScale(GpuMat image,
RectVector objects,
IntPointer numDetections,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize) |
void |
BaseCascadeClassifier.detectMultiScale(GpuMat image,
RectVector objects,
IntPointer rejectLevels,
DoublePointer levelWeights,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize,
boolean outputRejectLevels) |
void |
CascadeClassifier.detectMultiScale(Mat image,
RectVector objects) |
void |
HOGDescriptor.detectMultiScale(Mat img,
RectVector foundLocations) |
void |
HOGDescriptor.detectMultiScale(Mat img,
RectVector foundLocations,
double[] foundWeights) |
void |
HOGDescriptor.detectMultiScale(Mat img,
RectVector foundLocations,
double[] foundWeights,
double hitThreshold,
Size winStride,
Size padding,
double scale,
double finalThreshold,
boolean useMeanshiftGrouping) |
void |
HOGDescriptor.detectMultiScale(Mat img,
RectVector foundLocations,
DoubleBuffer foundWeights) |
void |
HOGDescriptor.detectMultiScale(Mat img,
RectVector foundLocations,
DoubleBuffer foundWeights,
double hitThreshold,
Size winStride,
Size padding,
double scale,
double finalThreshold,
boolean useMeanshiftGrouping) |
void |
CascadeClassifier.detectMultiScale(Mat image,
RectVector objects,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize)
\brief Detects objects of different sizes in the input image.
|
void |
BaseCascadeClassifier.detectMultiScale(Mat image,
RectVector objects,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize) |
void |
HOGDescriptor.detectMultiScale(Mat img,
RectVector foundLocations,
DoublePointer foundWeights) |
void |
HOGDescriptor.detectMultiScale(Mat img,
RectVector foundLocations,
DoublePointer foundWeights,
double hitThreshold,
Size winStride,
Size padding,
double scale,
double finalThreshold,
boolean useMeanshiftGrouping)
\brief Detects objects of different sizes in the input image.
|
void |
HOGDescriptor.detectMultiScale(Mat img,
RectVector foundLocations,
double hitThreshold,
Size winStride,
Size padding,
double scale,
double finalThreshold,
boolean useMeanshiftGrouping)
\brief Detects objects of different sizes in the input image.
|
void |
BaseCascadeClassifier.detectMultiScale(Mat image,
RectVector objects,
int[] rejectLevels,
double[] levelWeights,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize,
boolean outputRejectLevels) |
void |
BaseCascadeClassifier.detectMultiScale(Mat image,
RectVector objects,
int[] numDetections,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize) |
void |
BaseCascadeClassifier.detectMultiScale(Mat image,
RectVector objects,
IntBuffer rejectLevels,
DoubleBuffer levelWeights,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize,
boolean outputRejectLevels) |
void |
BaseCascadeClassifier.detectMultiScale(Mat image,
RectVector objects,
IntBuffer numDetections,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize) |
void |
BaseCascadeClassifier.detectMultiScale(Mat image,
RectVector objects,
IntPointer numDetections,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize) |
void |
BaseCascadeClassifier.detectMultiScale(Mat image,
RectVector objects,
IntPointer rejectLevels,
DoublePointer levelWeights,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize,
boolean outputRejectLevels) |
void |
CascadeClassifier.detectMultiScale(UMat image,
RectVector objects) |
void |
HOGDescriptor.detectMultiScale(UMat img,
RectVector foundLocations) |
void |
HOGDescriptor.detectMultiScale(UMat img,
RectVector foundLocations,
double[] foundWeights) |
void |
HOGDescriptor.detectMultiScale(UMat img,
RectVector foundLocations,
double[] foundWeights,
double hitThreshold,
Size winStride,
Size padding,
double scale,
double finalThreshold,
boolean useMeanshiftGrouping) |
void |
HOGDescriptor.detectMultiScale(UMat img,
RectVector foundLocations,
DoubleBuffer foundWeights) |
void |
HOGDescriptor.detectMultiScale(UMat img,
RectVector foundLocations,
DoubleBuffer foundWeights,
double hitThreshold,
Size winStride,
Size padding,
double scale,
double finalThreshold,
boolean useMeanshiftGrouping) |
void |
CascadeClassifier.detectMultiScale(UMat image,
RectVector objects,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize) |
void |
BaseCascadeClassifier.detectMultiScale(UMat image,
RectVector objects,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize) |
void |
HOGDescriptor.detectMultiScale(UMat img,
RectVector foundLocations,
DoublePointer foundWeights) |
void |
HOGDescriptor.detectMultiScale(UMat img,
RectVector foundLocations,
DoublePointer foundWeights,
double hitThreshold,
Size winStride,
Size padding,
double scale,
double finalThreshold,
boolean useMeanshiftGrouping) |
void |
HOGDescriptor.detectMultiScale(UMat img,
RectVector foundLocations,
double hitThreshold,
Size winStride,
Size padding,
double scale,
double finalThreshold,
boolean useMeanshiftGrouping) |
void |
BaseCascadeClassifier.detectMultiScale(UMat image,
RectVector objects,
int[] rejectLevels,
double[] levelWeights,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize,
boolean outputRejectLevels) |
void |
BaseCascadeClassifier.detectMultiScale(UMat image,
RectVector objects,
int[] numDetections,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize) |
void |
BaseCascadeClassifier.detectMultiScale(UMat image,
RectVector objects,
IntBuffer rejectLevels,
DoubleBuffer levelWeights,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize,
boolean outputRejectLevels) |
void |
BaseCascadeClassifier.detectMultiScale(UMat image,
RectVector objects,
IntBuffer numDetections,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize) |
void |
BaseCascadeClassifier.detectMultiScale(UMat image,
RectVector objects,
IntPointer numDetections,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize) |
void |
BaseCascadeClassifier.detectMultiScale(UMat image,
RectVector objects,
IntPointer rejectLevels,
DoublePointer levelWeights,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize,
boolean outputRejectLevels) |
void |
CascadeClassifier.detectMultiScale2(GpuMat image,
RectVector objects,
int[] numDetections) |
void |
CascadeClassifier.detectMultiScale2(GpuMat image,
RectVector objects,
int[] numDetections,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize) |
void |
CascadeClassifier.detectMultiScale2(GpuMat image,
RectVector objects,
IntBuffer numDetections) |
void |
CascadeClassifier.detectMultiScale2(GpuMat image,
RectVector objects,
IntBuffer numDetections,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize) |
void |
CascadeClassifier.detectMultiScale2(GpuMat image,
RectVector objects,
IntPointer numDetections) |
void |
CascadeClassifier.detectMultiScale2(GpuMat image,
RectVector objects,
IntPointer numDetections,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize) |
void |
CascadeClassifier.detectMultiScale2(Mat image,
RectVector objects,
int[] numDetections) |
void |
CascadeClassifier.detectMultiScale2(Mat image,
RectVector objects,
int[] numDetections,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize) |
void |
CascadeClassifier.detectMultiScale2(Mat image,
RectVector objects,
IntBuffer numDetections) |
void |
CascadeClassifier.detectMultiScale2(Mat image,
RectVector objects,
IntBuffer numDetections,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize) |
void |
CascadeClassifier.detectMultiScale2(Mat image,
RectVector objects,
IntPointer numDetections) |
void |
CascadeClassifier.detectMultiScale2(Mat image,
RectVector objects,
IntPointer numDetections,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize)
\overload
|
void |
CascadeClassifier.detectMultiScale2(UMat image,
RectVector objects,
int[] numDetections) |
void |
CascadeClassifier.detectMultiScale2(UMat image,
RectVector objects,
int[] numDetections,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize) |
void |
CascadeClassifier.detectMultiScale2(UMat image,
RectVector objects,
IntBuffer numDetections) |
void |
CascadeClassifier.detectMultiScale2(UMat image,
RectVector objects,
IntBuffer numDetections,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize) |
void |
CascadeClassifier.detectMultiScale2(UMat image,
RectVector objects,
IntPointer numDetections) |
void |
CascadeClassifier.detectMultiScale2(UMat image,
RectVector objects,
IntPointer numDetections,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize) |
void |
CascadeClassifier.detectMultiScale3(GpuMat image,
RectVector objects,
int[] rejectLevels,
double[] levelWeights) |
void |
CascadeClassifier.detectMultiScale3(GpuMat image,
RectVector objects,
int[] rejectLevels,
double[] levelWeights,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize,
boolean outputRejectLevels) |
void |
CascadeClassifier.detectMultiScale3(GpuMat image,
RectVector objects,
IntBuffer rejectLevels,
DoubleBuffer levelWeights) |
void |
CascadeClassifier.detectMultiScale3(GpuMat image,
RectVector objects,
IntBuffer rejectLevels,
DoubleBuffer levelWeights,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize,
boolean outputRejectLevels) |
void |
CascadeClassifier.detectMultiScale3(GpuMat image,
RectVector objects,
IntPointer rejectLevels,
DoublePointer levelWeights) |
void |
CascadeClassifier.detectMultiScale3(GpuMat image,
RectVector objects,
IntPointer rejectLevels,
DoublePointer levelWeights,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize,
boolean outputRejectLevels) |
void |
CascadeClassifier.detectMultiScale3(Mat image,
RectVector objects,
int[] rejectLevels,
double[] levelWeights) |
void |
CascadeClassifier.detectMultiScale3(Mat image,
RectVector objects,
int[] rejectLevels,
double[] levelWeights,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize,
boolean outputRejectLevels) |
void |
CascadeClassifier.detectMultiScale3(Mat image,
RectVector objects,
IntBuffer rejectLevels,
DoubleBuffer levelWeights) |
void |
CascadeClassifier.detectMultiScale3(Mat image,
RectVector objects,
IntBuffer rejectLevels,
DoubleBuffer levelWeights,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize,
boolean outputRejectLevels) |
void |
CascadeClassifier.detectMultiScale3(Mat image,
RectVector objects,
IntPointer rejectLevels,
DoublePointer levelWeights) |
void |
CascadeClassifier.detectMultiScale3(Mat image,
RectVector objects,
IntPointer rejectLevels,
DoublePointer levelWeights,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize,
boolean outputRejectLevels)
\overload
This function allows you to retrieve the final stage decision certainty of classification.
|
void |
CascadeClassifier.detectMultiScale3(UMat image,
RectVector objects,
int[] rejectLevels,
double[] levelWeights) |
void |
CascadeClassifier.detectMultiScale3(UMat image,
RectVector objects,
int[] rejectLevels,
double[] levelWeights,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize,
boolean outputRejectLevels) |
void |
CascadeClassifier.detectMultiScale3(UMat image,
RectVector objects,
IntBuffer rejectLevels,
DoubleBuffer levelWeights) |
void |
CascadeClassifier.detectMultiScale3(UMat image,
RectVector objects,
IntBuffer rejectLevels,
DoubleBuffer levelWeights,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize,
boolean outputRejectLevels) |
void |
CascadeClassifier.detectMultiScale3(UMat image,
RectVector objects,
IntPointer rejectLevels,
DoublePointer levelWeights) |
void |
CascadeClassifier.detectMultiScale3(UMat image,
RectVector objects,
IntPointer rejectLevels,
DoublePointer levelWeights,
double scaleFactor,
int minNeighbors,
int flags,
Size minSize,
Size maxSize,
boolean outputRejectLevels) |
void |
HOGDescriptor.detectMultiScaleROI(GpuMat img,
RectVector foundLocations,
DetectionROI locations) |
void |
HOGDescriptor.detectMultiScaleROI(GpuMat img,
RectVector foundLocations,
DetectionROI locations,
double hitThreshold,
int groupThreshold) |
void |
HOGDescriptor.detectMultiScaleROI(Mat img,
RectVector foundLocations,
DetectionROI locations) |
void |
HOGDescriptor.detectMultiScaleROI(Mat img,
RectVector foundLocations,
DetectionROI locations,
double hitThreshold,
int groupThreshold)
\brief evaluate specified ROI and return confidence value for each location in multiple scales
|
void |
HOGDescriptor.detectMultiScaleROI(UMat img,
RectVector foundLocations,
DetectionROI locations) |
void |
HOGDescriptor.detectMultiScaleROI(UMat img,
RectVector foundLocations,
DetectionROI locations,
double hitThreshold,
int groupThreshold) |
void |
DetectionBasedTracker.getObjects(RectVector result) |
void |
HOGDescriptor.groupRectangles(RectVector rectList,
double[] weights,
int groupThreshold,
double eps) |
void |
HOGDescriptor.groupRectangles(RectVector rectList,
DoubleBuffer weights,
int groupThreshold,
double eps) |
void |
HOGDescriptor.groupRectangles(RectVector rectList,
DoublePointer weights,
int groupThreshold,
double eps)
\brief Groups the object candidate rectangles.
|
Modifier and Type | Method and Description |
---|---|
void |
TextDetectorCNN.detect(GpuMat inputImage,
RectVector Bbox,
FloatVector confidence) |
void |
TextDetector.detect(GpuMat inputImage,
RectVector Bbox,
FloatVector confidence) |
void |
TextDetectorCNN.detect(Mat inputImage,
RectVector Bbox,
FloatVector confidence)
\overload
|
void |
TextDetector.detect(Mat inputImage,
RectVector Bbox,
FloatVector confidence)
\brief Method that provides a quick and simple interface to detect text inside an image
|
void |
TextDetectorCNN.detect(UMat inputImage,
RectVector Bbox,
FloatVector confidence) |
void |
TextDetector.detect(UMat inputImage,
RectVector Bbox,
FloatVector confidence) |
void |
OCRHolisticWordRecognizer.run(Mat image,
BytePointer output_text,
RectVector component_rects,
StringVector component_texts,
FloatVector component_confidences,
int component_level) |
void |
BaseOCR.run(Mat image,
BytePointer output_text,
RectVector component_rects,
StringVector component_texts,
FloatVector component_confidences,
int component_level) |
void |
OCRBeamSearchDecoder.run(Mat image,
BytePointer output_text,
RectVector component_rects,
StringVector component_texts,
FloatVector component_confidences,
int component_level)
\brief Recognize text using Beam Search.
|
void |
OCRTesseract.run(Mat image,
BytePointer output_text,
RectVector component_rects,
StringVector component_texts,
FloatVector component_confidences,
int component_level)
\brief Recognize text using the tesseract-ocr API.
|
void |
OCRHMMDecoder.run(Mat image,
BytePointer output_text,
RectVector component_rects,
StringVector component_texts,
FloatVector component_confidences,
int component_level)
\brief Recognize text using HMM.
|
void |
OCRHolisticWordRecognizer.run(Mat image,
Mat mask,
BytePointer output_text,
RectVector component_rects,
StringVector component_texts,
FloatVector component_confidences,
int component_level)
\brief Recognize text using a segmentation based word-spotting/classifier cnn.
|
void |
BaseOCR.run(Mat image,
Mat mask,
BytePointer output_text,
RectVector component_rects,
StringVector component_texts,
FloatVector component_confidences,
int component_level) |
void |
OCRBeamSearchDecoder.run(Mat image,
Mat mask,
BytePointer output_text,
RectVector component_rects,
StringVector component_texts,
FloatVector component_confidences,
int component_level) |
void |
OCRTesseract.run(Mat image,
Mat mask,
BytePointer output_text,
RectVector component_rects,
StringVector component_texts,
FloatVector component_confidences,
int component_level) |
void |
OCRHMMDecoder.run(Mat image,
Mat mask,
BytePointer output_text,
RectVector component_rects,
StringVector component_texts,
FloatVector component_confidences,
int component_level)
\brief Recognize text using HMM.
|
Modifier and Type | Method and Description |
---|---|
RectVector |
CvHaarEvaluator.FeatureHaar.getAreas() |
Modifier and Type | Method and Description |
---|---|
void |
SelectiveSearchSegmentation.process(RectVector rects)
\brief Based on all images, graph segmentations and stragies, computes all possible rects and return them
|
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