Modifier and Type | Method and Description |
---|---|
static Mat |
opencv_text.createOCRHMMTransitionsTable(BytePointer vocabulary,
StringVector lexicon) |
static void |
opencv_text.createOCRHMMTransitionsTable(BytePointer vocabulary,
StringVector lexicon,
GpuMat transition_probabilities_table) |
static void |
opencv_text.createOCRHMMTransitionsTable(BytePointer vocabulary,
StringVector lexicon,
Mat transition_probabilities_table)
\}
|
static void |
opencv_text.createOCRHMMTransitionsTable(BytePointer vocabulary,
StringVector lexicon,
UMat transition_probabilities_table) |
static Mat |
opencv_text.createOCRHMMTransitionsTable(String vocabulary,
StringVector lexicon) |
static void |
opencv_core.glob(BytePointer pattern,
StringVector result) |
static void |
opencv_core.glob(BytePointer pattern,
StringVector result,
boolean recursive) |
static void |
opencv_core.glob(String pattern,
StringVector result) |
static void |
opencv_core.glob(String pattern,
StringVector result,
boolean recursive) |
static boolean |
opencv_face.loadDatasetList(BytePointer imageList,
BytePointer annotationList,
StringVector images,
StringVector annotations)
\brief A utility to load list of paths to training image and annotation file.
|
static boolean |
opencv_face.loadDatasetList(String imageList,
String annotationList,
StringVector images,
StringVector annotations) |
static boolean |
opencv_face.loadTrainingData(String imageList,
String groundTruth,
StringVector images,
Point2fVectorVector facePoints,
float offset)
\brief A utility to load facial landmark information from the dataset.
|
static boolean |
opencv_face.loadTrainingData(String filename,
StringVector images,
Point2fVectorVector facePoints,
byte delim,
float offset)
\brief A utility to load facial landmark dataset from a single file.
|
static boolean |
opencv_face.loadTrainingData(StringVector filename,
Point2fVectorVector trainlandmarks,
StringVector trainimages)
\brief This function extracts the data for training from .txt files which contains the corresponding image name and landmarks.
|
static BytePointer |
opencv_stitching.matchesGraphAsString(StringVector pathes,
MatchesInfo pairwise_matches,
float conf_threshold) |
static void |
opencv_dnn.shrinkCaffeModel(BytePointer src,
BytePointer dst,
StringVector layersTypes)
\brief Convert all weights of Caffe network to half precision floating point.
|
static void |
opencv_dnn.shrinkCaffeModel(String src,
String dst,
StringVector layersTypes) |
Modifier and Type | Method and Description |
---|---|
StringVector |
FileNode.keys()
\brief Returns keys of a mapping node.
|
StringVector |
StringVector.push_back(BytePointer value) |
StringVector |
StringVector.push_back(String value) |
StringVector |
StringVector.put(BytePointer... array) |
StringVector |
StringVector.put(BytePointer value) |
StringVector |
StringVector.put(long i,
BytePointer value) |
StringVector |
StringVector.put(long i,
String value) |
StringVector |
StringVector.put(String... array) |
StringVector |
StringVector.put(String value) |
StringVector |
StringVector.put(StringVector x) |
Modifier and Type | Method and Description |
---|---|
StringVector |
StringVector.put(StringVector x) |
void |
FileStorage.write(BytePointer name,
StringVector val)
\overload
|
void |
FileStorage.write(String name,
StringVector val) |
Modifier and Type | Method and Description |
---|---|
StringVector |
Net.getLayerNames() |
StringVector |
Net.getUnconnectedOutLayersNames()
\brief Returns names of layers with unconnected outputs.
|
Modifier and Type | Method and Description |
---|---|
void |
Net.forward(GpuMatVector outputBlobs,
StringVector outBlobNames) |
void |
Net.forward(MatVector outputBlobs,
StringVector outBlobNames)
\brief Runs forward pass to compute outputs of layers listed in \p outBlobNames.
|
void |
Net.forward(UMatVector outputBlobs,
StringVector outBlobNames) |
void |
Net.forwardAndRetrieve(MatVectorVector outputBlobs,
StringVector outBlobNames)
\brief Runs forward pass to compute outputs of layers listed in \p outBlobNames.
|
void |
Net.getLayerTypes(StringVector layersTypes)
\brief Returns list of types for layer used in model.
|
void |
Net.setInputsNames(StringVector inputBlobNames)
\brief Sets outputs names of the network input pseudo layer.
|
Modifier and Type | Method and Description |
---|---|
void |
DnnSuperResImpl.upsampleMultioutput(GpuMat img,
MatVector imgs_new,
int[] scale_factors,
StringVector node_names) |
void |
DnnSuperResImpl.upsampleMultioutput(GpuMat img,
MatVector imgs_new,
IntBuffer scale_factors,
StringVector node_names) |
void |
DnnSuperResImpl.upsampleMultioutput(GpuMat img,
MatVector imgs_new,
IntPointer scale_factors,
StringVector node_names) |
void |
DnnSuperResImpl.upsampleMultioutput(Mat img,
MatVector imgs_new,
int[] scale_factors,
StringVector node_names) |
void |
DnnSuperResImpl.upsampleMultioutput(Mat img,
MatVector imgs_new,
IntBuffer scale_factors,
StringVector node_names) |
void |
DnnSuperResImpl.upsampleMultioutput(Mat img,
MatVector imgs_new,
IntPointer scale_factors,
StringVector node_names)
\brief Upsample via neural network of multiple outputs
|
void |
DnnSuperResImpl.upsampleMultioutput(UMat img,
MatVector imgs_new,
int[] scale_factors,
StringVector node_names) |
void |
DnnSuperResImpl.upsampleMultioutput(UMat img,
MatVector imgs_new,
IntBuffer scale_factors,
StringVector node_names) |
void |
DnnSuperResImpl.upsampleMultioutput(UMat img,
MatVector imgs_new,
IntPointer scale_factors,
StringVector node_names) |
Modifier and Type | Method and Description |
---|---|
void |
IndexParams.getAll(StringVector names,
int[] types,
StringVector strValues,
double[] numValues) |
void |
IndexParams.getAll(StringVector names,
IntBuffer types,
StringVector strValues,
DoubleBuffer numValues) |
void |
IndexParams.getAll(StringVector names,
IntPointer types,
StringVector strValues,
DoublePointer numValues) |
Modifier and Type | Method and Description |
---|---|
void |
TrainData.getNames(StringVector names)
\brief Returns vector of symbolic names captured in loadFromCSV()
|
Modifier and Type | Method and Description |
---|---|
boolean |
QRCodeDetector.decodeMulti(GpuMat img,
GpuMat points,
StringVector decoded_info) |
boolean |
QRCodeDetector.decodeMulti(GpuMat img,
GpuMat points,
StringVector decoded_info,
GpuMatVector straight_qrcode) |
boolean |
QRCodeDetector.decodeMulti(GpuMat img,
GpuMat points,
StringVector decoded_info,
MatVector straight_qrcode) |
boolean |
QRCodeDetector.decodeMulti(GpuMat img,
GpuMat points,
StringVector decoded_info,
UMatVector straight_qrcode) |
boolean |
QRCodeDetector.decodeMulti(Mat img,
Mat points,
StringVector decoded_info) |
boolean |
QRCodeDetector.decodeMulti(Mat img,
Mat points,
StringVector decoded_info,
GpuMatVector straight_qrcode) |
boolean |
QRCodeDetector.decodeMulti(Mat img,
Mat points,
StringVector decoded_info,
MatVector straight_qrcode)
\brief Decodes QR codes in image once it's found by the detect() method.
|
boolean |
QRCodeDetector.decodeMulti(Mat img,
Mat points,
StringVector decoded_info,
UMatVector straight_qrcode) |
boolean |
QRCodeDetector.decodeMulti(UMat img,
UMat points,
StringVector decoded_info) |
boolean |
QRCodeDetector.decodeMulti(UMat img,
UMat points,
StringVector decoded_info,
GpuMatVector straight_qrcode) |
boolean |
QRCodeDetector.decodeMulti(UMat img,
UMat points,
StringVector decoded_info,
MatVector straight_qrcode) |
boolean |
QRCodeDetector.decodeMulti(UMat img,
UMat points,
StringVector decoded_info,
UMatVector straight_qrcode) |
boolean |
QRCodeDetector.detectAndDecodeMulti(GpuMat img,
StringVector decoded_info) |
boolean |
QRCodeDetector.detectAndDecodeMulti(GpuMat img,
StringVector decoded_info,
GpuMat points,
GpuMatVector straight_qrcode) |
boolean |
QRCodeDetector.detectAndDecodeMulti(GpuMat img,
StringVector decoded_info,
GpuMat points,
MatVector straight_qrcode) |
boolean |
QRCodeDetector.detectAndDecodeMulti(GpuMat img,
StringVector decoded_info,
GpuMat points,
UMatVector straight_qrcode) |
boolean |
QRCodeDetector.detectAndDecodeMulti(Mat img,
StringVector decoded_info) |
boolean |
QRCodeDetector.detectAndDecodeMulti(Mat img,
StringVector decoded_info,
Mat points,
GpuMatVector straight_qrcode) |
boolean |
QRCodeDetector.detectAndDecodeMulti(Mat img,
StringVector decoded_info,
Mat points,
MatVector straight_qrcode)
\brief Both detects and decodes QR codes
|
boolean |
QRCodeDetector.detectAndDecodeMulti(Mat img,
StringVector decoded_info,
Mat points,
UMatVector straight_qrcode) |
boolean |
QRCodeDetector.detectAndDecodeMulti(UMat img,
StringVector decoded_info) |
boolean |
QRCodeDetector.detectAndDecodeMulti(UMat img,
StringVector decoded_info,
UMat points,
GpuMatVector straight_qrcode) |
boolean |
QRCodeDetector.detectAndDecodeMulti(UMat img,
StringVector decoded_info,
UMat points,
MatVector straight_qrcode) |
boolean |
QRCodeDetector.detectAndDecodeMulti(UMat img,
StringVector decoded_info,
UMat points,
UMatVector straight_qrcode) |
Modifier and Type | Method and Description |
---|---|
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.
|
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