vector<POI> POIFinder::GetPOIsInImage(IplImage *cv_image)
{
//Pre-processing
// Image originalImage(cv_image);
// Image grayImage = originalImage.getGrayScale();
/* IplImage *gray_image = cvCreateImage(cvGetSize(cv_image),cv_image->depth, 1);
if(cv_image->nChannels == 3)
{
cvCvtColor(cv_image, gray_image,CV_BGR2GRAY);
}
else
cvCopyImage(cv_image, gray_image);
Image grayImage(gray_image);*/
Image grayImage(cv_image);
//Core algorithm
vector<Blob> detectedBlobs = FindBlobs(grayImage);
vector<POI> newCoordinates;
for (unsigned int i = 0; i < detectedBlobs.size(); i++)
{
newCoordinates.push_back(POI(detectedBlobs[i].GetCentroid()));
//cout << "Novo POI: " << endl;
//Debug::printCvPoint2D32f(newCoordinates[newCoordinates.size()-1].getCoordinates2d());
};
return newCoordinates;
}
void faceDetector::detectFace()
{
if(FaceEnable)
{
detectObject(faceClassifier,grayImage,faces);
}
leftEyes.clear();
rightEyes.clear();
noses.clear();
mouth.clear();
std::sort(faces.begin(),faces.end(),rectSort);
if(faces.size() > 0)
{
FaceRIO = faces[0];
FaceDetected = true;
faceMat = grayImage(FaceRIO);
}
else
{
FaceRIO = Rect(-1,-1,-1,-1);
}
}
void DateWidget::paintEvent(QPaintEvent *event)
{
static QPixmap pix = QPixmap(":/calendar").scaled(DATEWIDGETWIDTH, 64);
QPainter painter(this);
painter.drawPixmap(QPoint(0, 0), isEnabled() ? pix : QPixmap::fromImage(grayImage(pix.toImage())));
QString month = mDate.toString("MMM");
QString year = mDate.toString("yyyy");
QString day = mDate.toString("dd");
QFont font = QFont("monospace", 10);
QFontMetrics metrics = QFontMetrics(font);
painter.setFont(font);
painter.setPen(QPen(QBrush(Qt::white), 0));
painter.setBrush(QBrush(Qt::white));
painter.drawText(QPoint(6, metrics.height() + 1), month);
painter.drawText(QPoint(DATEWIDGETWIDTH - metrics.width(year) - 6, metrics.height() + 1), year);
font.setPointSize(14);
metrics = QFontMetrics(font);
painter.setPen(QPen(QBrush(Qt::black), 0));
painter.setBrush(Qt::black);
painter.setFont(font);
painter.drawText(QPoint(DATEWIDGETWIDTH / 2 - metrics.width(day) / 2, 45), day);
if (hasFocus()) {
QStyleOptionFocusRect option;
option.initFrom(this);
option.backgroundColor = palette().color(QPalette::Background);
style()->drawPrimitive(QStyle::PE_FrameFocusRect, &option, &painter, this);
}
}
Mat faceDetector::getFaceMat()
{
if(isFaceDetected())
{
return grayImage(FaceRIO);
}
else
{
return Mat(16,16,CV_8UC1);
}
}
void CvxLSD::detect_lines(const vil_image_view<vxl_byte> & image, vcl_vector<LSDLineSegment> & line_segments)
{
assert(image.nplanes() == 3 || image.nplanes() == 1);
vil_image_view<vxl_byte> grayImage;
if (image.nplanes() == 3) {
vil_convert_planes_to_grey(image, grayImage);
}
else
{
grayImage = image;
}
double * imageData = NULL;
double * out = NULL;
int width = grayImage.ni();
int height = grayImage.nj();
int n = 0;
imageData = (double *) malloc( width * height * sizeof(double) );
assert(imageData);
for(int j=0; j<height; j++)
{
for(int i=0; i<width; i++)
{
imageData[i + j * width] = grayImage(i, j);
}
}
/* LSD call */
out = lsd(&n, imageData, width, height);
/* print output */
// printf("%d line segments found:\n",n);
line_segments.resize(n);
for(int i=0; i<n; i++)
{
double x1 = out[7*i + 0];
double y1 = out[7*i + 1];
double x2 = out[7*i + 2];
double y2 = out[7*i + 3];
double line_width = out[7*i + 4];
double p = out[7*i + 5];
double tmp = out[7*i + 6];
line_segments[i].seg_ = vgl_line_segment_2d<double>(vgl_point_2d<double>(x1, y1), vgl_point_2d<double>(x2, y2));
line_segments[i].width_ = line_width;
line_segments[i].angle_precision_ = p;
line_segments[i].NFA_ = tmp;
}
free( (void *) imageData );
free( (void *) out );
}
StarWidget::StarWidget(QWidget* parent, Qt::WindowFlags f):
QWidget(parent, f),
current(0)
{
if (!activeStar) {
activeStar = new QPixmap();
QSvgRenderer render(QString(":star"));
QPixmap renderedStar(IMG_SIZE, IMG_SIZE);
renderedStar.fill(Qt::transparent);
QPainter painter(&renderedStar);
render.render(&painter, QRectF(0, 0, IMG_SIZE, IMG_SIZE));
(*activeStar) = renderedStar;
}
if (!inactiveStar) {
inactiveStar = new QPixmap();
(*inactiveStar) = grayImage(activeStar);
}
}
StarWidget::StarWidget(QWidget *parent, Qt::WindowFlags f) : QWidget(parent, f),
current(0),
readOnly(false)
{
int dim = defaultIconMetrics().sz_small;
if (activeStar.isNull()) {
QSvgRenderer render(QString(":star"));
QPixmap renderedStar(dim, dim);
renderedStar.fill(Qt::transparent);
QPainter painter(&renderedStar);
render.render(&painter, QRectF(0, 0, dim, dim));
activeStar = renderedStar.toImage();
}
if (inactiveStar.isNull()) {
inactiveStar = grayImage(activeStar);
}
setFocusPolicy(Qt::StrongFocus);
}
void BriefDescriptorExtractor::computeImpl(const Mat& image, std::vector<KeyPoint>& keypoints, Mat& descriptors) const
{
// Construct integral image for fast smoothing (box filter)
Mat sum;
Mat grayImage(image.size(), CV_8UC1);
if( image.type() != CV_8U ) cvtColor( image, grayImage, COLOR_BGR2GRAY );
///TODO allow the user to pass in a precomputed integral image
//if(image.type() == CV_32S)
// sum = image;
//else
integral( grayImage, sum, CV_32S);
//Remove keypoints very close to the border
KeyPointsFilter::runByImageBorder(keypoints, image.size(), PATCH_SIZE/2 + KERNEL_SIZE/2);
descriptors = Mat::zeros((int)keypoints.size(), bytes_, CV_8U);
test_fn_(sum, keypoints, descriptors);
}
void BlinkAnalyser::receiveNewFrame(cv::Mat newFrame){
cv::cvtColor(newFrame,this->grayImage,cv::COLOR_BGR2GRAY);
if (this->faceDetector->detect(this->grayImage,5, this->faceBoundingBox)) { //调用FaceDetector，如果检测到脸
this->upperImage = grayImage(this->faceBoundingBox.returnUpperRect()); //截取图像的上半部分（准备检测人眼）
if(this->eyeDetector->detect(this->upperImage,this->eyesRects)){ //调用eyeDetector，如果检测到眼睛
if(this->isEyesOpen == false){
this->isEyesOpen = true;
this->blinkCount++;
}
Utils::drawRect(this->grayImage, eyesRects,this->faceBoundingBox.returnRect().x,this->faceBoundingBox.returnRect().y);
}else{ //如果没检测到眼睛
this->isEyesOpen = false;
}
Utils::drawRect(this->grayImage,this->faceBoundingBox);
}else{ //如果没检测到脸
this->blinkCount = 0;
}
if(blinkCount > this->blinkThreshold){
this->success();
}
//cv::moveWindow("BlinkAnalyser",200,160);
//cv::imshow("BlinkAnalyser", grayImage);
}
ImageGray GrayscaleImage::convertToGrayscale(ImageRGB & image) {
// Image size.
int width = image.width();
int height = image.height();
// The destination image.
ImageGray grayImage(width, height);
// For every pixel in the image.
for (int y = 0; y < height; y++) {
for (int x = 0; x < width; x++) {
// Get the pixel at position x,y.
Rgb<unsigned char &> pixelRGB = image.at(x, y);
unsigned char& pixelGray = grayImage.at(x, y);
// Convert RGB to grayscale.
pixelGray = pixelRGB.red * 0.114 + pixelRGB.green * 0.587 + pixelRGB.blue * 0.299;
}
}
// Return the gray image.
return grayImage;
}
void LevelAnalyzedImage::analyze()
{
if ( inputImage_.empty() ) return;
cv::Mat grayImage;
{
std::lock_guard<std::mutex> lock(inputImageMutex_);
cv::cvtColor(inputImage_, grayImage, CV_BGR2GRAY);
}
// Noise reduction
cv::medianBlur(grayImage, grayImage, 5);
// Contrast collection
cv::Mat lut(1, 256, CV_8U);
for (int i = 0; i < 256; ++i) {
lut.at<unsigned char>(i) = (i < threshold_) ? (std::pow(i, 2) / threshold_) : (256 - std::pow(i, 2) / std::pow(256, 2));
// lut.at<unsigned char>(i) = 255 / (1 + std::exp(-contrast_ * (i - 128) / 255));
}
cv::LUT(grayImage, lut, grayImage);
// Check each cell color
std::vector<int> heights;
for (auto rect : targetRects_) { // copy
// To fill gaps
rect.width += 1;
rect.height += 1;
// Check ROI
if ( !(rect.x >= 0 && rect.width >= 0 && rect.x + rect.width <= grayImage.cols &&
rect.y >= 0 && rect.height >= 0 && rect.y + rect.height <= grayImage.rows) ) {
qDebug() << "targetRects contains invalid rect data.";
continue;
}
// Calculate average color
cv::Mat roiImage = grayImage(rect);
if (rect.width > 3 && rect.height > 3) {
rect.x += rect.width / 3;
rect.y += rect.height / 3;
rect.width /= 3;
rect.height /= 3;
}
cv::Mat averageRoiImage = grayImage(rect);
cv::Mat rowAverage, average;
cv::reduce(averageRoiImage, rowAverage, 0, CV_REDUCE_AVG);
cv::reduce(rowAverage, average, 1, CV_REDUCE_AVG);
// Set all pixels in ROI as its average color
auto averageValue = average.at<unsigned char>(0);
roiImage = cv::Scalar(averageValue);
// Set results
auto brickDetected = averageValue > threshold_ ? 1 : 0;
heights.push_back(brickDetected);
}
// check change
addHeightsCache(heights);
checkResult();
{
std::lock_guard<std::mutex> lock(mutex_);
cv::cvtColor(grayImage, image_, CV_GRAY2BGR);
emit imageChanged();
}
emit update();
}
//Processes a frame and returns output image
bool HiLight::processFrame(const cv::Mat& inputFrame, int* screen_position, double current_timestamp, char *results, bool* denoise_check, bool* first_bit_check, int* hilight_line_index, char* hilight_results_tmp )
{
*denoise_check = false;
*first_bit_check = false;
if(!initialized){
initialized = true;
for(int i = 0; i<grid_x; i++){
for(int j = 0; j<grid_y; j++ ){
for (int k = 0; k < first_bit_window; k++){
first_bit_color_window[i][j][k] = 0;
}
for (int k = 0; k < N; k++){
grid_color_intensity[i][j][k] = 0;
hilight_results_stack[i][j][k] = 0;
}
hilight_results[i][j] = 0;
}
}
if (isImage){
MVDR = true;
first_2_ratio = 0.6;//0.8
first_bit_voting = 0.5;//0.7
}else{
MVDR = false;
first_2_ratio = 0.8; //0.7
first_bit_voting = 0.7; //0.6
}
window_index = 0;
first_bit_detected = false;
first_bit_index = 0;
hilight_stack_index = 0;
start_time = current_timestamp;
current_time = current_timestamp;
denoise_start = false;
MVDR_index = 0;
bit_counter = 0;
results_stack_counter = 0;
fftSetup = vDSP_create_fftsetup(LOG_N, kFFTRadix2);
start_receiving = false;
counter_after_detect_1= 0;
first_bit_1_detected = false;
first_bit_2_detected = false;
hilight_first_bit_index = 0;
hilight_first_bit_counter = 0;
hilight_first_bit_position = 0;
if (screen_position[2] < screen_position[4]){
image_ROI_position[0].y = screen_position[2];
}else{
image_ROI_position[0].y = screen_position[4];
}
if (screen_position[1] < screen_position[7]){
image_ROI_position[0].x = screen_position[1];
}else{
image_ROI_position[0].x = screen_position[7];
}
if (screen_position[6] < screen_position[8]){
image_ROI_position[1].y = screen_position[8];
}else{
image_ROI_position[1].y = screen_position[6];
}
if (screen_position[5] < screen_position[3]){
image_ROI_position[1].x = screen_position[3];
}else{
image_ROI_position[1].x = screen_position[5];
}
if (isImage){
// Set grids points to calculate the grid position
for (int i = 0; i <= grid_x * grid_x_MVDR; i++){
grids_points_top_image[i].x = screen_position[1] + (screen_position[3] - screen_position[1]) / grid_x / grid_x_MVDR * i;
grids_points_top_image[i].y = screen_position[2] + (screen_position[4] - screen_position[2]) / grid_x / grid_x_MVDR * i;
grids_points_bottom_image[i].x = screen_position[7] + (screen_position[5] - screen_position[7]) / grid_x / grid_x_MVDR * i;
grids_points_bottom_image[i].y = screen_position[8] + (screen_position[6] - screen_position[8]) / grid_x / grid_x_MVDR * i;
}
for (int i = 0; i <= grid_y * grid_y_MVDR; i++){
grids_points_left_image[i].x = screen_position[1] + (screen_position[7] - screen_position[1]) / grid_y / grid_y_MVDR * i;
grids_points_left_image[i].y = screen_position[2] + (screen_position[8] - screen_position[2]) / grid_y / grid_y_MVDR * i;
grids_points_right_image[i].x = screen_position[3] + (screen_position[5] - screen_position[3]) / grid_y / grid_y_MVDR * i;
grids_points_right_image[i].y = screen_position[4] + (screen_position[6] - screen_position[4]) / grid_y / grid_y_MVDR * i;
}
for (int i = 0; i < grid_x * grid_x_MVDR; i++){
for (int j = 0; j < grid_y * grid_y_MVDR; j++){
cv::Point2f r1;
cv::Point2f r2;
cv::Point2f r3;
cv::Point2f r4;
intersection(grids_points_top_image[i], grids_points_bottom_image[i], grids_points_left_image[j], grids_points_right_image[j], r1);//top left
intersection(grids_points_top_image[i+1], grids_points_bottom_image[i+1], grids_points_left_image[j], grids_points_right_image[j], r2);//top right
intersection(grids_points_top_image[i+1], grids_points_bottom_image[i+1], grids_points_left_image[j+1], grids_points_right_image[j+1], r3);// bottom right
intersection(grids_points_top_image[i], grids_points_bottom_image[i], grids_points_left_image[j+1], grids_points_right_image[j+1], r4);//bottom left
//refine grid_position
if (r1.x <= r4.x){
grids_position_image[i][j][0].x = r4.x - image_ROI_position[0].x;
}else{
grids_position_image[i][j][0].x = r1.x - image_ROI_position[0].x;
}
if (r1.y <= r2.y){
grids_position_image[i][j][0].y = r2.y - image_ROI_position[0].y;
}else{
grids_position_image[i][j][0].y = r1.y - image_ROI_position[0].y;
}
if (r3.x <= r2.x){
grids_position_image[i][j][1].x = r3.x - image_ROI_position[0].x;
}else{
grids_position_image[i][j][1].x = r2.x - image_ROI_position[0].x;
}
if (r3.y <= r4.y){
grids_position_image[i][j][1].y = r3.y - image_ROI_position[0].y;
}else{
grids_position_image[i][j][1].y = r4.y - image_ROI_position[0].y;
}
}
}
}else{
// Set grids points to calculate the grid position
for (int i = 0; i <= grid_x; i++){
grids_points_top_video[i].x = screen_position[1] + (screen_position[3] - screen_position[1]) / grid_x * i;
grids_points_top_video[i].y = screen_position[2] + (screen_position[4] - screen_position[2]) / grid_x * i;
grids_points_bottom_video[i].x = screen_position[7] + (screen_position[5] - screen_position[7]) / grid_x * i;
grids_points_bottom_video[i].y = screen_position[8] + (screen_position[6] - screen_position[8]) / grid_x * i;
}
for (int i = 0; i <= grid_y; i++){
grids_points_left_video[i].x = screen_position[1] + (screen_position[7] - screen_position[1]) / grid_y * i;
grids_points_left_video[i].y = screen_position[2] + (screen_position[8] - screen_position[2]) / grid_y * i;
grids_points_right_video[i].x = screen_position[3] + (screen_position[5] - screen_position[3]) / grid_y * i;
grids_points_right_video[i].y = screen_position[4] + (screen_position[6] - screen_position[4]) / grid_y * i;
}
for (int i = 0; i < grid_x; i++){
for (int j = 0; j < grid_y; j++){
cv::Point2f r1;
cv::Point2f r2;
cv::Point2f r3;
cv::Point2f r4;
intersection(grids_points_top_video[i], grids_points_bottom_video[i], grids_points_left_video[j], grids_points_right_video[j], r1);//top left
intersection(grids_points_top_video[i+1], grids_points_bottom_video[i+1], grids_points_left_video[j], grids_points_right_video[j], r2);//top right
intersection(grids_points_top_video[i+1], grids_points_bottom_video[i+1], grids_points_left_video[j+1], grids_points_right_video[j+1], r3);// bottom right
intersection(grids_points_top_video[i], grids_points_bottom_video[i], grids_points_left_video[j+1], grids_points_right_video[j+1], r4);//bottom left
//refine grid_position
if (r1.x <= r4.x){
grids_position_video[i][j][0].x = r4.x - image_ROI_position[0].x;
}else{
grids_position_video[i][j][0].x = r1.x - image_ROI_position[0].x;
}
if (r1.y <= r2.y){
grids_position_video[i][j][0].y = r2.y - image_ROI_position[0].y;
}else{
grids_position_video[i][j][0].y = r1.y - image_ROI_position[0].y;
}
if (r3.x <= r2.x){
grids_position_video[i][j][1].x = r3.x - image_ROI_position[0].x;
}else{
grids_position_video[i][j][1].x = r2.x - image_ROI_position[0].x;
}
if (r3.y <= r4.y){
grids_position_video[i][j][1].y = r3.y - image_ROI_position[0].y;
}else{
grids_position_video[i][j][1].y = r4.y - image_ROI_position[0].y;
}
}
}
}
srcTri[0] = cv::Point2f( screen_position[2],screen_position[1] );
srcTri[1] = cv::Point2f( screen_position[4],screen_position[3] );
srcTri[2] = cv::Point2f( screen_position[6],screen_position[5] );
dist_top = sqrt(pow(screen_position[4]-screen_position[2],2.0) + pow(screen_position[3]-screen_position[1],2.0));
dstTri[0] = cv::Point2f( screen_position[2],screen_position[1] );
dstTri[1] = cv::Point2f( screen_position[2],screen_position[1] + dist_top );
dstTri[2] = cv::Point2f( screen_position[2] + (int)(dist_top*transmitter_screen_ratio),screen_position[1] + dist_top);
warp_mat = getAffineTransform( srcTri, dstTri );
}else{
current_time = current_timestamp;
}
//crop the transmitter screen from the captured image
cv::Mat image_ROI = inputFrame(cv::Range(image_ROI_position[0].y, image_ROI_position[1].y), cv::Range(image_ROI_position[0].x, image_ROI_position[1].x));
getGray_HiLight(image_ROI, grayImage);
image_ROI.release();
for (int c = 0; c < grid_x; c++){
for (int r = 0; r < grid_y; r++){
brightness[c][r] = 0;
}
}
if (isImage){
int brightness_c = 0;
int brightness_r = 0;
for (int c = 0; c < grid_x * grid_x_MVDR; c++){
for (int r = 0; r < grid_y * grid_y_MVDR; r++)
{
cv::Mat tile = grayImage(cv::Range(grids_position_image[c][r][0].y + grid_margin, grids_position_image[c][r][1].y - grid_margin)
, cv::Range(grids_position_image[c][r][0].x + grid_margin, grids_position_image[c][r][1].x - grid_margin));
cv::Scalar pixel_scalar = cv::mean(tile);
tile.release();
float brightness_tmp =pixel_scalar[0];
if (MVDR){
if(!denoise_start && MVDR_index < MVDR_frame){
grid_color_intensity_MVDR[c][r][MVDR_index] = brightness_tmp;
if ( c == grid_x * grid_x_MVDR -1 && r == grid_y * grid_y_MVDR - 1){
MVDR_index++;
}
}else if(!denoise_start && MVDR_index >= MVDR_frame){
denoise_start = true;
*denoise_check = true;
get_MVDR_weighting(grid_color_intensity_MVDR, MVDR_weighting);
//print MVDR matrix
if (isDebug){
for (int i = 0; i < grid_x * grid_x_MVDR; i++){
for (int j = 0; j < grid_y * grid_y_MVDR; j++){
printf("%f\t", MVDR_weighting[i][j]);
}
printf("\n");
}
}
}else{
brightness_c = floor(c*1.0/grid_x_MVDR);
brightness_r = floor(r*1.0/grid_y_MVDR);
brightness[brightness_c][brightness_r] = brightness[brightness_c][brightness_r] + brightness_tmp * MVDR_weighting[c][r];
}
}else{
brightness_c = floor(c*1.0/grid_x_MVDR);
brightness_r = floor(r*1.0/grid_y_MVDR);
brightness[brightness_c][brightness_r] = brightness[brightness_c][brightness_r] + brightness_tmp;
}
}
}
}else{
for (int c = 0; c < grid_x; c++){
for (int r = 0; r < grid_y; r++)
{
cv::Mat tile = grayImage(cv::Range(grids_position_video[c][r][0].y + grid_margin, grids_position_video[c][r][1].y - grid_margin)
, cv::Range(grids_position_video[c][r][0].x + grid_margin, grids_position_video[c][r][1].x - grid_margin));
cv::Scalar pixel_scalar = cv::mean(tile);
tile.release();
float brightness_tmp =pixel_scalar[0];
brightness[c][r] = brightness_tmp;
}
}
}
if (denoise_start || !MVDR){
for (int c = 0; c < grid_x; c++){
for (int r = 0; r < grid_y; r++){
if (window_index<(N-1)) {
grid_color_intensity[c][r][window_index] = brightness[c][r];
window_index++;
}else{
int i;
float fft_sum_N_over_2 = 0;
for (i = 1; i < N; i++){
grid_color_intensity[c][r][i-1] = grid_color_intensity[c][r][i];
}
grid_color_intensity[c][r][N-1] = brightness[c][r];
for (i = 0; i < N/2; i++){
fft_sum_N_over_2 = fft_sum_N_over_2 + grid_color_intensity[c][r][2*i] - grid_color_intensity[c][r][2*i+1];
}
// Initialize the input buffer with a sinusoid
// We need complex buffers in two different formats!
tempSplitComplex.realp = new float[N/2];
tempSplitComplex.imagp = new float[N/2];
// ----------------------------------------------------------------
// Forward FFT
// Scramble-pack the real data into complex buffer in just the way that's
// required by the real-to-complex FFT function that follows.
vDSP_ctoz((DSPComplex*)grid_color_intensity[c][r], 2, &tempSplitComplex, 1, N/2);
// Do real->complex forward FFT
vDSP_fft_zrip(fftSetup, &tempSplitComplex, 1, LOG_N, kFFTDirection_Forward);
int max_pulse_index = object_pulse_threashold;
float max_pulse = -100;
float object_pulse_power_1 = LinearToDecibel(pow (fft_sum_N_over_2, 2.0)/ N);
float object_pulse_power_2;
int object_pulse_force;
int object_pulse;
for (int k = object_pulse_threashold; k < N/2; k++)
{
float spectrum = LinearToDecibel((pow (tempSplitComplex.realp[k], 2.0) + pow (tempSplitComplex.imagp[k], 2.0))/ 4/ N);
if (max_pulse<spectrum){
max_pulse = spectrum;
max_pulse_index = k;
}
if(k == object_pulse_2){
object_pulse_power_2 = spectrum;
}
}
delete tempSplitComplex.realp;
delete tempSplitComplex.imagp;
if(max_pulse < object_pulse_power_1 && object_pulse_power_1 > -25){
object_pulse = 1;
}else if(max_pulse == object_pulse_power_2){
object_pulse = 2;
}else{
object_pulse = 0;
}
if(object_pulse_power_1 >= object_pulse_power_2){
object_pulse_force = 1;
}else{
object_pulse_force = 2;
}
//decode data by find the peak frequency power
if (first_bit_detected){
if (first_bit_1_detected && isCalibrate){
hilight_first_bit_stack[c][r][hilight_first_bit_index] = object_pulse_force;
}
if(current_time - start_time >= N / 60.0 * (bit_counter + 1)){
hilight_results[c][r] = get_hilight_results(hilight_results_stack[c][r], hilight_stack_index);
hilight_results_stack[c][r][0] = object_pulse_force;
}else{
hilight_results_stack[c][r][hilight_stack_index] = object_pulse_force;
}
}else{
first_bit_color_window[c][r][first_bit_index] = object_pulse;
}
}
}
}
if (first_bit_1_detected && isCalibrate){
hilight_first_bit_timestamp[hilight_first_bit_index++] = current_time;
}if(first_bit_2_detected && isCalibrate){
first_bit_2_detected = false;
hilight_first_bit_counter++;
if (hilight_first_bit_counter == N/2){
calibrate_first_bit_position();
}
}
if (first_bit_detected){
if(current_time - start_time >= N / 60.0 * (bit_counter + 1)){
int counter_for_2 = 0;
for (int i = 0; i < grid_x; i++){
for (int j = 0; j < grid_y; j++){
if (isDebug || start_receiving){
printf("%d ",hilight_results[i][j]);
}
if (hilight_results[i][j] == 2){
counter_for_2++;
}
}
}
if (isDebug || start_receiving){
printf("\n");
}
hilight_stack_index = 1;
bit_counter++;
if (!start_receiving){
counter_after_detect_1++;
if (counter_after_detect_1 > 3){
reset();
}else{
if(counter_for_2 >= (double)grid_x * grid_y * first_2_ratio){
first_bit_2_detected = true;
start_receiving = true;
*first_bit_check = true;
if (isDebug){
printf("\n");
}
}
}
return false;
}else{
int results_counter_tmp =0;
for (int i = 0; i < grid_x; i++){
for (int j = 0; j < grid_y; j++){
output_bit_stack[results_stack_counter++] = hilight_results[i][j];
hilight_results_tmp[results_counter_tmp++] = hilight_results[i][j] + '0' - 1;
}
}
hilight_line_index[0] = results_stack_counter/grid_x/grid_y;
if (results_stack_counter == output_bit_stck_length){
results_stack_counter = 0;
get_char_from_bits(output_bit_stack, results);
printf("%s\n",results);
if (demo){
debug_reset();
return true;
}else{
debug_reset();
return false;
}
}else{
return false;
}
}
}else{
hilight_stack_index++;
}
}else{
if(first_bit_index<first_bit_window-1){
first_bit_index++;
}else{
first_bit_detected = detect_first_bit(first_bit_color_window);
if (first_bit_detected){
if (isCalibrate){
first_bit_1_detected = true;
}
start_time = current_time;
}
}
}
}
return false;
}
// init application and run
int Run()
{
CBitmapCapture capture(DEMO_IMAGE);
// open camera
if (!capture.OpenCamera())
{
printf("error: could not open camera\n");
return 1;
}
const int width = capture.GetWidth();
const int height = capture.GetHeight();
// create temp image for the image processing
CByteImage image(width, height, capture.GetType());
CByteImage grayImage(width, height, CByteImage::eGrayScale);
CByteImage tempImage(width, height, CByteImage::eGrayScale);
CByteImage visualizationImage(width, height, CByteImage::eRGB24);
CByteImage *pImage = ℑ
// create an application handler
CApplicationHandlerInterface *pApplicationHandler = CreateApplicationHandler();
pApplicationHandler->Reset();
// create a main window
m_pMainWindow = CreateMainWindow(0, 0, width, height + 190, "Hough Line Detection Demo");
// events are sent to this class, hence this class needs to have the CMainWindowEventInterface
m_pMainWindow->SetEventCallback(this);
// create an image widget to display a window
WIDGET_HANDLE pImageWidget = m_pMainWindow->AddImage(0, 190, width, height);
// add a label and a slider for the low threshold
WIDGET_HANDLE pLabelCannyLow = m_pMainWindow->AddLabel(15, 15, 200, 30, "Canny low threshold: 0");
m_pSliderCannyLow = m_pMainWindow->AddSlider(15, 30, 200, 40, 0, 1020, 102, m_nCannyLowThreshold);
// add a label and a slider for the high threshold
WIDGET_HANDLE pLabelCannyHigh = m_pMainWindow->AddLabel(15, 70, 200, 30, "Canny high threshold: 0");
m_pSliderCannyHigh = m_pMainWindow->AddSlider(15, 85, 200, 40, 0, 1020, 102, m_nCannyHighThreshold);
// add a label and a slider for the number of lines to extract
WIDGET_HANDLE pLabelLines = m_pMainWindow->AddLabel(260, 15, 200, 30, "Circles to extract: 0 lines");
m_pSliderLinesToExtract = m_pMainWindow->AddSlider(260, 30, 200, 40, 0, 30, 5, m_nCirclesToExtract);
// add labels/sliders for specifying the radius interval of interest
WIDGET_HANDLE pLabelMinRadius = m_pMainWindow->AddLabel(260, 70, 200, 30, "Min radius: 0");
m_pSliderMinRadius = m_pMainWindow->AddSlider(260, 85, 200, 40, 1, 200, 5, m_nMinRadius);
WIDGET_HANDLE pLabelMaxRadius = m_pMainWindow->AddLabel(260, 125, 200, 30, "Max radius: 0");
m_pSliderMaxRadius = m_pMainWindow->AddSlider(260, 140, 200, 40, 1, 200, 5, m_nMaxRadius);
// add a button to toggle between the original image and the processed one
m_pButton = m_pMainWindow->AddButton(510, 80, 110, 35, "Show Edges");
// add a labels to display processing stats
WIDGET_HANDLE pLabelMS = m_pMainWindow->AddLabel(560, 15, 70, 20, "0 ms");
WIDGET_HANDLE pLabelFPS = m_pMainWindow->AddLabel(560, 45, 70, 20, "0 fps");
// make the window visible
m_pMainWindow->Show();
char buffer[1024];
CVec3dArray resultListCircles(50);
CDynamicArrayTemplate<int> resultHits(50);
CVec2dArray edgePoints(10000), edgeDirections(10000);
// main loop
while (!pApplicationHandler->ProcessEventsAndGetExit())
{
if (!capture.CaptureImage(&pImage))
break;
// this is for visualization purposes only
ImageProcessor::ConvertImage(pImage, &visualizationImage);
get_timer_value(true);
// convert input image to grayscale image
ImageProcessor::ConvertImage(&image, &tempImage, true);
// smooth image
ImageProcessor::GaussianSmooth3x3(&tempImage, &grayImage);
// detect edges with Canny edge detector
ImageProcessor::Canny(&grayImage, edgePoints, edgeDirections, m_nCannyLowThreshold, m_nCannyHighThreshold);
// detect lines with Hough transform
ImageProcessor::HoughTransformCircles(edgePoints, edgeDirections, width, height, m_nMinRadius, m_nMaxRadius, m_nCirclesToExtract, 1, resultListCircles, resultHits, &visualizationImage);
const unsigned int t = get_timer_value();
// display the speed stats
sprintf(buffer, "%2.2f ms", t / 1000.0f);
m_pMainWindow->SetText(pLabelMS, buffer);
sprintf(buffer, "%3.2f fps", 1000000.0f / t);
m_pMainWindow->SetText(pLabelFPS, buffer);
sprintf(buffer, "Canny low threshold: %i", m_nCannyLowThreshold);
m_pMainWindow->SetText(pLabelCannyLow, buffer);
sprintf(buffer, "Canny high threshold: %i", m_nCannyHighThreshold);
m_pMainWindow->SetText(pLabelCannyHigh, buffer);
sprintf(buffer, "Min radius: %i", m_nMinRadius);
m_pMainWindow->SetText(pLabelMinRadius, buffer);
sprintf(buffer, "Max radius: %i", m_nMaxRadius);
m_pMainWindow->SetText(pLabelMaxRadius, buffer);
sprintf(buffer, "Circles to extract: %i", m_nCirclesToExtract);
m_pMainWindow->SetText(pLabelLines, buffer);
// display either the original image or the processed image
if (m_bShowEdges)
{
ImageProcessor::Canny(&grayImage, &grayImage, m_nCannyLowThreshold, m_nCannyHighThreshold);
m_pMainWindow->SetImage(pImageWidget, &grayImage);
}
else
m_pMainWindow->SetImage(pImageWidget, &visualizationImage);
}
delete m_pMainWindow;
delete pApplicationHandler;
return 0;
}
