| Package | Description |
|---|---|
| org.opencv.core | |
| org.opencv.dnn | |
| org.opencv.features2d | |
| org.opencv.imgproc | |
| org.opencv.objdetect | |
| org.opencv.photo | |
| org.opencv.text | |
| org.opencv.video | |
| org.opencv.xfeatures2d |
| Modifier and Type | Method and Description |
|---|---|
static MatOfFloat |
MatOfFloat.fromNativeAddr(long addr) |
| Modifier and Type | Method and Description |
|---|---|
void |
DetectionModel.detect(Mat frame,
MatOfInt classIds,
MatOfFloat confidences,
MatOfRect boxes)
Given the
input frame, create input blob, run net and return result detections. |
void |
DetectionModel.detect(Mat frame,
MatOfInt classIds,
MatOfFloat confidences,
MatOfRect boxes,
float confThreshold)
Given the
input frame, create input blob, run net and return result detections. |
void |
DetectionModel.detect(Mat frame,
MatOfInt classIds,
MatOfFloat confidences,
MatOfRect boxes,
float confThreshold,
float nmsThreshold)
Given the
input frame, create input blob, run net and return result detections. |
static void |
Dnn.NMSBoxes(MatOfRect2d bboxes,
MatOfFloat scores,
float score_threshold,
float nms_threshold,
MatOfInt indices)
Performs non maximum suppression given boxes and corresponding scores.
|
static void |
Dnn.NMSBoxes(MatOfRect2d bboxes,
MatOfFloat scores,
float score_threshold,
float nms_threshold,
MatOfInt indices,
float eta)
Performs non maximum suppression given boxes and corresponding scores.
|
static void |
Dnn.NMSBoxes(MatOfRect2d bboxes,
MatOfFloat scores,
float score_threshold,
float nms_threshold,
MatOfInt indices,
float eta,
int top_k)
Performs non maximum suppression given boxes and corresponding scores.
|
static void |
Dnn.NMSBoxesRotated(MatOfRotatedRect bboxes,
MatOfFloat scores,
float score_threshold,
float nms_threshold,
MatOfInt indices) |
static void |
Dnn.NMSBoxesRotated(MatOfRotatedRect bboxes,
MatOfFloat scores,
float score_threshold,
float nms_threshold,
MatOfInt indices,
float eta) |
static void |
Dnn.NMSBoxesRotated(MatOfRotatedRect bboxes,
MatOfFloat scores,
float score_threshold,
float nms_threshold,
MatOfInt indices,
float eta,
int top_k) |
| Modifier and Type | Method and Description |
|---|---|
static BRISK |
BRISK.create(int thresh,
int octaves,
MatOfFloat radiusList,
MatOfInt numberList)
The BRISK constructor for a custom pattern, detection threshold and octaves
|
static BRISK |
BRISK.create(int thresh,
int octaves,
MatOfFloat radiusList,
MatOfInt numberList,
float dMax)
The BRISK constructor for a custom pattern, detection threshold and octaves
|
static BRISK |
BRISK.create(int thresh,
int octaves,
MatOfFloat radiusList,
MatOfInt numberList,
float dMax,
float dMin)
The BRISK constructor for a custom pattern, detection threshold and octaves
|
static BRISK |
BRISK.create(int thresh,
int octaves,
MatOfFloat radiusList,
MatOfInt numberList,
float dMax,
float dMin,
MatOfInt indexChange)
The BRISK constructor for a custom pattern, detection threshold and octaves
|
static BRISK |
BRISK.create(MatOfFloat radiusList,
MatOfInt numberList)
The BRISK constructor for a custom pattern
|
static BRISK |
BRISK.create(MatOfFloat radiusList,
MatOfInt numberList,
float dMax)
The BRISK constructor for a custom pattern
|
static BRISK |
BRISK.create(MatOfFloat radiusList,
MatOfInt numberList,
float dMax,
float dMin)
The BRISK constructor for a custom pattern
|
static BRISK |
BRISK.create(MatOfFloat radiusList,
MatOfInt numberList,
float dMax,
float dMin,
MatOfInt indexChange)
The BRISK constructor for a custom pattern
|
| Modifier and Type | Method and Description |
|---|---|
static void |
Imgproc.calcBackProject(List<Mat> images,
MatOfInt channels,
Mat hist,
Mat dst,
MatOfFloat ranges,
double scale) |
static void |
Imgproc.calcHist(List<Mat> images,
MatOfInt channels,
Mat mask,
Mat hist,
MatOfInt histSize,
MatOfFloat ranges) |
static void |
Imgproc.calcHist(List<Mat> images,
MatOfInt channels,
Mat mask,
Mat hist,
MatOfInt histSize,
MatOfFloat ranges,
boolean accumulate) |
| Modifier and Type | Method and Description |
|---|---|
MatOfFloat |
HOGDescriptor.get_svmDetector() |
static MatOfFloat |
HOGDescriptor.getDaimlerPeopleDetector()
Returns coefficients of the classifier trained for people detection (for 48x96 windows).
|
static MatOfFloat |
HOGDescriptor.getDefaultPeopleDetector()
Returns coefficients of the classifier trained for people detection (for 64x128 windows).
|
| Modifier and Type | Method and Description |
|---|---|
void |
HOGDescriptor.compute(Mat img,
MatOfFloat descriptors)
Computes HOG descriptors of given image.
|
void |
HOGDescriptor.compute(Mat img,
MatOfFloat descriptors,
Size winStride)
Computes HOG descriptors of given image.
|
void |
HOGDescriptor.compute(Mat img,
MatOfFloat descriptors,
Size winStride,
Size padding)
Computes HOG descriptors of given image.
|
void |
HOGDescriptor.compute(Mat img,
MatOfFloat descriptors,
Size winStride,
Size padding,
MatOfPoint locations)
Computes HOG descriptors of given image.
|
| Modifier and Type | Method and Description |
|---|---|
static void |
Photo.fastNlMeansDenoising(Mat src,
Mat dst,
MatOfFloat h)
Perform image denoising using Non-local Means Denoising algorithm
<http://www.ipol.im/pub/algo/bcm_non_local_means_denoising/> with several computational
optimizations.
|
static void |
Photo.fastNlMeansDenoising(Mat src,
Mat dst,
MatOfFloat h,
int templateWindowSize)
Perform image denoising using Non-local Means Denoising algorithm
<http://www.ipol.im/pub/algo/bcm_non_local_means_denoising/> with several computational
optimizations.
|
static void |
Photo.fastNlMeansDenoising(Mat src,
Mat dst,
MatOfFloat h,
int templateWindowSize,
int searchWindowSize)
Perform image denoising using Non-local Means Denoising algorithm
<http://www.ipol.im/pub/algo/bcm_non_local_means_denoising/> with several computational
optimizations.
|
static void |
Photo.fastNlMeansDenoising(Mat src,
Mat dst,
MatOfFloat h,
int templateWindowSize,
int searchWindowSize,
int normType)
Perform image denoising using Non-local Means Denoising algorithm
<http://www.ipol.im/pub/algo/bcm_non_local_means_denoising/> with several computational
optimizations.
|
static void |
Photo.fastNlMeansDenoisingMulti(List<Mat> srcImgs,
Mat dst,
int imgToDenoiseIndex,
int temporalWindowSize,
MatOfFloat h)
Modification of fastNlMeansDenoising function for images sequence where consecutive images have been
captured in small period of time.
|
static void |
Photo.fastNlMeansDenoisingMulti(List<Mat> srcImgs,
Mat dst,
int imgToDenoiseIndex,
int temporalWindowSize,
MatOfFloat h,
int templateWindowSize)
Modification of fastNlMeansDenoising function for images sequence where consecutive images have been
captured in small period of time.
|
static void |
Photo.fastNlMeansDenoisingMulti(List<Mat> srcImgs,
Mat dst,
int imgToDenoiseIndex,
int temporalWindowSize,
MatOfFloat h,
int templateWindowSize,
int searchWindowSize)
Modification of fastNlMeansDenoising function for images sequence where consecutive images have been
captured in small period of time.
|
static void |
Photo.fastNlMeansDenoisingMulti(List<Mat> srcImgs,
Mat dst,
int imgToDenoiseIndex,
int temporalWindowSize,
MatOfFloat h,
int templateWindowSize,
int searchWindowSize,
int normType)
Modification of fastNlMeansDenoising function for images sequence where consecutive images have been
captured in small period of time.
|
| Modifier and Type | Method and Description |
|---|---|
void |
TextDetectorCNN.detect(Mat inputImage,
MatOfRect Bbox,
MatOfFloat confidence) |
void |
TextDetector.detect(Mat inputImage,
MatOfRect Bbox,
MatOfFloat confidence)
Method that provides a quick and simple interface to detect text inside an image
|
| Modifier and Type | Method and Description |
|---|---|
static void |
Video.calcOpticalFlowPyrLK(Mat prevImg,
Mat nextImg,
MatOfPoint2f prevPts,
MatOfPoint2f nextPts,
MatOfByte status,
MatOfFloat err)
Calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with
pyramids.
|
static void |
Video.calcOpticalFlowPyrLK(Mat prevImg,
Mat nextImg,
MatOfPoint2f prevPts,
MatOfPoint2f nextPts,
MatOfByte status,
MatOfFloat err,
Size winSize)
Calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with
pyramids.
|
static void |
Video.calcOpticalFlowPyrLK(Mat prevImg,
Mat nextImg,
MatOfPoint2f prevPts,
MatOfPoint2f nextPts,
MatOfByte status,
MatOfFloat err,
Size winSize,
int maxLevel)
Calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with
pyramids.
|
static void |
Video.calcOpticalFlowPyrLK(Mat prevImg,
Mat nextImg,
MatOfPoint2f prevPts,
MatOfPoint2f nextPts,
MatOfByte status,
MatOfFloat err,
Size winSize,
int maxLevel,
TermCriteria criteria)
Calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with
pyramids.
|
static void |
Video.calcOpticalFlowPyrLK(Mat prevImg,
Mat nextImg,
MatOfPoint2f prevPts,
MatOfPoint2f nextPts,
MatOfByte status,
MatOfFloat err,
Size winSize,
int maxLevel,
TermCriteria criteria,
int flags)
Calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with
pyramids.
|
static void |
Video.calcOpticalFlowPyrLK(Mat prevImg,
Mat nextImg,
MatOfPoint2f prevPts,
MatOfPoint2f nextPts,
MatOfByte status,
MatOfFloat err,
Size winSize,
int maxLevel,
TermCriteria criteria,
int flags,
double minEigThreshold)
Calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with
pyramids.
|
| Modifier and Type | Method and Description |
|---|---|
void |
PCTSignaturesSQFD.computeQuadraticFormDistances(Mat sourceSignature,
List<Mat> imageSignatures,
MatOfFloat distances)
Computes Signature Quadratic Form Distance between the reference signature
and each of the other image signatures.
|
void |
PCTSignatures.setTranslations(MatOfFloat translations)
Translations of the individual axes of the feature space.
|
void |
PCTSignatures.setWeights(MatOfFloat weights)
Weights (multiplicative constants) that linearly stretch individual axes of the feature space.
|
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