/** * Opens a new camera using openCV at a certain device index with * a given frame width and height, and a compression quality. * * @param cam the device index from 0. * @param width the frame width * @param height the frame height * @param quality the compression quality * * @throws RuntimeException if the camera could not be opened */ public CvCamera(int cam, int width, int height, int quality){ capture = new VideoCapture(); capture.open(cam); if(!capture.isOpened()) throw new RuntimeException("Unable to open camera " + cam); image = new Mat(); buffer = new MatOfByte(); compressParams = new MatOfInt(Imgcodecs.CV_IMWRITE_JPEG_QUALITY, quality); capture.set(Videoio.CAP_PROP_FRAME_WIDTH, width); capture.set(Videoio.CAP_PROP_FRAME_HEIGHT, height); camIndex = cam; this.quality = quality; }
public static void mixChannels(List<Mat> src, List<Mat> dst, MatOfInt fromTo) { Mat src_mat = Converters.vector_Mat_to_Mat(src); Mat dst_mat = Converters.vector_Mat_to_Mat(dst); Mat fromTo_mat = fromTo; mixChannels_0(src_mat.nativeObj, dst_mat.nativeObj, fromTo_mat.nativeObj); return; }
public static void convexHull(MatOfPoint points, MatOfInt hull) { Mat points_mat = points; Mat hull_mat = hull; convexHull_1(points_mat.nativeObj, hull_mat.nativeObj); return; }
public static void groupRectangles(MatOfRect rectList, MatOfInt weights, int groupThreshold) { Mat rectList_mat = rectList; Mat weights_mat = weights; groupRectangles_1(rectList_mat.nativeObj, weights_mat.nativeObj, groupThreshold); return; }
public void getVoronoiFacetList(MatOfInt idx, List<MatOfPoint2f> facetList, MatOfPoint2f facetCenters) { Mat idx_mat = idx; Mat facetList_mat = new Mat(); Mat facetCenters_mat = facetCenters; getVoronoiFacetList_0(nativeObj, idx_mat.nativeObj, facetList_mat.nativeObj, facetCenters_mat.nativeObj); Converters.Mat_to_vector_vector_Point2f(facetList_mat, facetList); facetList_mat.release(); return; }
public void getLeadingEdgeList(MatOfInt leadingEdgeList) { Mat leadingEdgeList_mat = leadingEdgeList; getLeadingEdgeList_0(nativeObj, leadingEdgeList_mat.nativeObj); return; }
public static void calcHist(List<Mat> images, MatOfInt channels, Mat mask, Mat hist, MatOfInt histSize, MatOfFloat ranges) { Mat images_mat = Converters.vector_Mat_to_Mat(images); Mat channels_mat = channels; Mat histSize_mat = histSize; Mat ranges_mat = ranges; calcHist_1(images_mat.nativeObj, channels_mat.nativeObj, mask.nativeObj, hist.nativeObj, histSize_mat.nativeObj, ranges_mat.nativeObj); return; }
public void detectMultiScale3(Mat image, MatOfRect objects, MatOfInt rejectLevels, MatOfDouble levelWeights) { Mat objects_mat = objects; Mat rejectLevels_mat = rejectLevels; Mat levelWeights_mat = levelWeights; detectMultiScale3_1(nativeObj, image.nativeObj, objects_mat.nativeObj, rejectLevels_mat.nativeObj, levelWeights_mat.nativeObj); return; }
public void detectMultiScale2(Mat image, MatOfRect objects, MatOfInt numDetections) { Mat objects_mat = objects; Mat numDetections_mat = numDetections; detectMultiScale2_1(nativeObj, image.nativeObj, objects_mat.nativeObj, numDetections_mat.nativeObj); return; }
public void getMemoryConsumption(int layerId, MatOfInt netInputShape, long[] weights, long[] blobs) { Mat netInputShape_mat = netInputShape; double[] weights_out = new double[1]; double[] blobs_out = new double[1]; getMemoryConsumption_1(nativeObj, layerId, netInputShape_mat.nativeObj, weights_out, blobs_out); if(weights!=null) weights[0] = (long)weights_out[0]; if(blobs!=null) blobs[0] = (long)blobs_out[0]; return; }
public void detectMultiScale2(Mat image, MatOfRect objects, MatOfInt numDetections, double scaleFactor, int minNeighbors, int flags, Size minSize, Size maxSize) { Mat objects_mat = objects; Mat numDetections_mat = numDetections; detectMultiScale2_0(nativeObj, image.nativeObj, objects_mat.nativeObj, numDetections_mat.nativeObj, scaleFactor, minNeighbors, flags, minSize.width, minSize.height, maxSize.width, maxSize.height); return; }
public static boolean imwrite(String filename, Mat img, MatOfInt params) { Mat params_mat = params; boolean retVal = imwrite_0(filename, img.nativeObj, params_mat.nativeObj); return retVal; }
public static void calcBackProject(List<Mat> images, MatOfInt channels, Mat hist, Mat dst, MatOfFloat ranges, double scale) { Mat images_mat = Converters.vector_Mat_to_Mat(images); Mat channels_mat = channels; Mat ranges_mat = ranges; calcBackProject_0(images_mat.nativeObj, channels_mat.nativeObj, hist.nativeObj, dst.nativeObj, ranges_mat.nativeObj, scale); return; }
public long getFLOPS(MatOfInt netInputShape) { Mat netInputShape_mat = netInputShape; long retVal = getFLOPS_0(nativeObj, netInputShape_mat.nativeObj); return retVal; }
public static BRISK create(MatOfFloat radiusList, MatOfInt numberList, float dMax, float dMin, MatOfInt indexChange) { Mat radiusList_mat = radiusList; Mat numberList_mat = numberList; Mat indexChange_mat = indexChange; BRISK retVal = new BRISK(create_2(radiusList_mat.nativeObj, numberList_mat.nativeObj, dMax, dMin, indexChange_mat.nativeObj)); return retVal; }
public static void calcHist(List<Mat> images, MatOfInt channels, Mat mask, Mat hist, MatOfInt histSize, MatOfFloat ranges, boolean accumulate) { Mat images_mat = Converters.vector_Mat_to_Mat(images); Mat channels_mat = channels; Mat histSize_mat = histSize; Mat ranges_mat = ranges; calcHist_0(images_mat.nativeObj, channels_mat.nativeObj, mask.nativeObj, hist.nativeObj, histSize_mat.nativeObj, ranges_mat.nativeObj, accumulate); return; }
public void detectMultiScale3(Mat image, MatOfRect objects, MatOfInt rejectLevels, MatOfDouble levelWeights, double scaleFactor, int minNeighbors, int flags, Size minSize, Size maxSize, boolean outputRejectLevels) { Mat objects_mat = objects; Mat rejectLevels_mat = rejectLevels; Mat levelWeights_mat = levelWeights; detectMultiScale3_0(nativeObj, image.nativeObj, objects_mat.nativeObj, rejectLevels_mat.nativeObj, levelWeights_mat.nativeObj, scaleFactor, minNeighbors, flags, minSize.width, minSize.height, maxSize.width, maxSize.height, outputRejectLevels); return; }
public static BRISK create(int thresh, int octaves, MatOfFloat radiusList, MatOfInt numberList, float dMax, float dMin, MatOfInt indexChange) { Mat radiusList_mat = radiusList; Mat numberList_mat = numberList; Mat indexChange_mat = indexChange; BRISK retVal = new BRISK(create_0(thresh, octaves, radiusList_mat.nativeObj, numberList_mat.nativeObj, dMax, dMin, indexChange_mat.nativeObj)); return retVal; }
public static void convexHull(MatOfPoint points, MatOfInt hull, boolean clockwise) { Mat points_mat = points; Mat hull_mat = hull; convexHull_0(points_mat.nativeObj, hull_mat.nativeObj, clockwise); return; }
public static PCTSignatures create(MatOfPoint2f initSamplingPoints, MatOfInt initClusterSeedIndexes) { Mat initSamplingPoints_mat = initSamplingPoints; Mat initClusterSeedIndexes_mat = initClusterSeedIndexes; PCTSignatures retVal = new PCTSignatures(create_3(initSamplingPoints_mat.nativeObj, initClusterSeedIndexes_mat.nativeObj)); return retVal; }
public static boolean imencode(String ext, Mat img, MatOfByte buf, MatOfInt params) { Mat buf_mat = buf; Mat params_mat = params; boolean retVal = imencode_0(ext, img.nativeObj, buf_mat.nativeObj, params_mat.nativeObj); return retVal; }
public static BRISK create(MatOfFloat radiusList, MatOfInt numberList, float dMax, float dMin, MatOfInt indexChange) { Mat radiusList_mat = radiusList; Mat numberList_mat = numberList; Mat indexChange_mat = indexChange; BRISK retVal = new BRISK(create_4(radiusList_mat.nativeObj, numberList_mat.nativeObj, dMax, dMin, indexChange_mat.nativeObj)); return retVal; }
public static FREAK create(boolean orientationNormalized, boolean scaleNormalized, float patternScale, int nOctaves, MatOfInt selectedPairs) { Mat selectedPairs_mat = selectedPairs; FREAK retVal = new FREAK(create_0(orientationNormalized, scaleNormalized, patternScale, nOctaves, selectedPairs_mat.nativeObj)); return retVal; }
