public SaliencyResult saliencyalgorithmInterface(ImageObj imgobj, String method) {
// TODO Auto-generated method stub
float min = Float.MAX_VALUE;
float max = Float.MIN_VALUE;
String imgpath = imgobj.getSourcePath();
int k_num = imgobj.getK_num();
SaliencyResult result = new SaliencyResult();
Mat img = Highgui.imread(imgpath, Highgui.CV_LOAD_IMAGE_GRAYSCALE);
Mat saliencyMap = new Mat();
saliencyMap.create(img.rows(), img.cols(), CvType.CV_16U);
int HistGram[] = new int[256];
int Gray[] = new int[img.cols() * img.rows()];
int Dist[] = new int[256];
float DistMap[] = new float[img.rows() * img.cols()];
for (int row = 0; row < img.rows(); row++) {
int CurIndex = row * img.cols();
for (int col = 0; col < img.cols(); col++) {
HistGram[(int) (img.get(row, col)[0])]++;
Gray[CurIndex] = (int) (img.get(row, col)[0]);
CurIndex++;
}
}
for (int Y = 0; Y < 256; Y++) {
int Value = 0;
for (int X = 0; X < 256; X++) Value += Math.abs(Y - X) * HistGram[X];
Dist[Y] = Value;
}
for (int row = 0; row < img.rows(); row++) {
int CurIndex = row * img.cols();
for (int col = 0; col < img.cols(); col++) {
DistMap[CurIndex] = Dist[Gray[CurIndex]];
if (DistMap[CurIndex] < min) min = DistMap[CurIndex];
if (DistMap[CurIndex] > max) max = DistMap[CurIndex];
CurIndex++;
}
}
for (int row = 0; row < img.rows(); row++) {
int CurIndex = row * img.cols();
for (int col = 0; col < img.cols(); col++) {
saliencyMap.put(row, col, partTwo((DistMap[CurIndex] - min) / (max - min) * 255));
CurIndex++;
}
}
new findMarkUtil();
int nums[] = null;
if (method == "kmeans") {
nums = findMarkUtil.findMarkUtil_kmeans(saliencyMap, k_num, 255, 0, 5);
} else if (method == "random") {
nums = findMarkUtil.findMarkUtil_random(saliencyMap, k_num, 255);
}
result.setK_num(k_num);
result.setSource(imgpath);
result.setResult(nums);
result.setSaliency(saliencyMap);
return result;
}
private void prepareSpherify(Bitmap bitmap) {
int insideCircleOutRadius;
int topY, footY, withinHeight;
if (!OpenCVLoader.initDebug()) {
// Handle initialization error
AppFunctions.showToast(activity.getApplicationContext(), "OpenGL initialization error!");
activity.finish();
}
if (srcImage == null) {
srcImage = new Mat();
srcImage.create(bitmap.getHeight(), bitmap.getWidth(), CvType.CV_8UC3);
Bitmap myBitmap32 = bitmap.copy(Bitmap.Config.ARGB_8888, true);
Utils.bitmapToMat(myBitmap32, srcImage);
Imgproc.cvtColor(srcImage, srcImage, Imgproc.COLOR_BGR2RGB, 4);
}
Utils.bitmapToMat(bitmap, srcImage);
// cropImage();
seamlessEdges(srcImage);
mSrcWidth = srcImage.cols();
mSrcHeight = srcImage.rows();
halfGenImageSize = genImageSize / 2;
spherifiedImage = new Mat();
spherifiedImage.create(genImageSize, genImageSize, CvType.CV_8UC4);
insideCircleOutRadius = (int) (genImageSize / 12);
topY = (int) (mSrcHeight * (topMargin));
footY = (int) (mSrcHeight * (footMargin));
withinHeight = topY - footY;
scale = withinHeight / ((double) (croppedImageSize / 2 - insideCircleOutRadius));
offset = (int) (footY - scale * insideCircleOutRadius);
numProcesses = Runtime.getRuntime().availableProcessors();
if (numProcesses < 3) numProcesses = 1;
else numProcesses = 3;
}
public void setSpherifiedImage(Bitmap bitmap) {
spherifiedImage = new Mat();
spherifiedImage.create(bitmap.getHeight(), bitmap.getWidth(), CvType.CV_8UC3);
Utils.bitmapToMat(bitmap, spherifiedImage);
genImageSize = spherifiedImage.cols();
croppedImageSize = (int) (genImageSize * Math.sin(Math.PI / 4.0));
halfGenImageSize = genImageSize / 2;
}
/**
* @param inputImg
* @param minValue
* @param maxValue
* @return Mat
*/
public static Mat thresholding(Mat inputImg, Integer minValue, Integer maxValue) {
Mat frame = inputImg;
// яскравість
// frame.convertTo(frame , -1, 10d * 33 / 100, 0);
// Imgproc.medianBlur(frame,frame, 17);
// Core.bitwise_not(frame,frame );
// Mat frame = new Mat(image.rows(), image.cols(), image.type());
// frame.convertTo(frame, -1, 10d * 20 / 100, 0);
Mat hsvImg = new Mat();
List<Mat> hsvPlanes = new ArrayList<>();
Mat thresholdImg = new Mat();
int thresh_type = Imgproc.THRESH_BINARY_INV;
// if (this.inverse.isSelected())
// thresh_type = Imgproc.THRESH_BINARY;
// threshold the image with the average hue value
// System.out.println("size " +frame.size());
hsvImg.create(frame.size(), CvType.CV_8U);
// Imgproc.cvtColor(frame, hsvImg, Imgproc.COLOR_BGR2HSV);
Core.split(hsvImg, hsvPlanes);
// get the average hue value of the image
// double threshValue = PreProcessingOperation.getHistAverage(hsvImg, hsvPlanes.get(0));
// System.out.println(threshValue);
/*
if(threshValue > 40){
maxValue = 160;
}else{
maxValue = 40;
}*/
// Imgproc.threshold(hsvPlanes.get(1), thresholdImg, minValue , maxValue , thresh_type);
Imgproc.blur(thresholdImg, thresholdImg, new Size(27, 27));
// dilate to fill gaps, erode to smooth edges
Imgproc.dilate(thresholdImg, thresholdImg, new Mat(), new Point(-1, -1), 1);
Imgproc.erode(thresholdImg, thresholdImg, new Mat(), new Point(-1, -1), 1);
Imgproc.threshold(thresholdImg, thresholdImg, minValue, maxValue, Imgproc.THRESH_BINARY);
// create the new image
Mat foreground = new Mat(frame.size(), CvType.CV_8UC3, new Scalar(255, 255, 255));
Core.bitwise_not(thresholdImg, foreground);
frame.copyTo(foreground, thresholdImg);
///////////////////////////////////////////////////////////////////////////////////////
///
////
return foreground;
/*Mat hsvImg = new Mat();
List<Mat> hsvPlanes = new ArrayList<>();
Mat thresholdImg = new Mat();
int thresh_type = Imgproc.THRESH_BINARY_INV;
// threshold the image with the average hue value
hsvImg.create(inputImg.size(), CvType.CV_8U);
Imgproc.cvtColor(inputImg, hsvImg, Imgproc.COLOR_BGR2HSV);
Core.split(hsvImg, hsvPlanes);
// get the average hue value of the image
double threshValue = PreProcessingOperation.getHistAverage(hsvImg, hsvPlanes.get(0));
Imgproc.threshold(hsvPlanes.get(0), thresholdImg, minValue,
maxValue, thresh_type);
Imgproc.blur(thresholdImg, thresholdImg, new Size(3, 3));
// dilate to fill gaps, erode to smooth edges
Imgproc.dilate(thresholdImg, thresholdImg, new Mat(), new Point(-1, -1), 3);
Imgproc.erode(thresholdImg, thresholdImg, new Mat(), new Point(-1, -1), 1);
Imgproc.threshold(thresholdImg, thresholdImg, minValue,
maxValue, Imgproc.THRESH_BINARY);
// create the new image
Mat foreground = new Mat(inputImg.size(), CvType.CV_8UC3, new Scalar(255, 255, 255));
inputImg.copyTo(foreground, thresholdImg);
Core.bitwise_not(foreground,foreground);
return foreground;*/
}