[TASK] Implement generic gaussian blur filter.
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@ -12,14 +12,108 @@
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class CannyEdgeMachine {
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private:
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LazyImage* img;
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LazyImage* original;
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LazyImage* working_copy;
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int width;
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int height;
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int pixels;
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double* gradient_magnitude;
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double* maximum_magnitude;
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int* binary_edge_pixels;
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int* gradient_x;
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int* gradient_y;
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// Params
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double t_low;
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double t_high;
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public:
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CannyEdgeMachine(){
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// TODO
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CannyEdgeMachine(LazyImage* original, LazyImage* working_copy){
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this->original = original;
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this->working_copy = working_copy;
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this->width = this->original->width();
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this->height = this->original->height();
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this->pixels = this->width * this->height;
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this->gradient_magnitude = (double*) malloc(sizeof(double) * this->pixels);
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this->maximum_magnitude = (double*) malloc(sizeof(double) * this->pixels);
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this->binary_edge_pixels = (int*) malloc(sizeof(int) * this->pixels);
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this->gradient_x = (int*) malloc(sizeof(int) * this->pixels);
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this->gradient_y = (int*) malloc(sizeof(int) * this->pixels);
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};
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~CannyEdgeMachine() {
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// TODO
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free(this->gradient_magnitude);
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free(this->maximum_magnitude);
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free(this->binary_edge_pixels);
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free(this->gradient_x);
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free(this->gradient_y);
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};
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void setThresholdValues(double t_low, double t_high) {
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this->t_low = t_low;
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this->t_high = t_high;
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};
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void reset(void) {
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for(int i=0; i<this->pixels; i++) {
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this->gradient_magnitude = 0;
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this->maximum_magnitude = 0;
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this->binary_edge_pixels = 0;
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this->gradient_x = 0;
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this->gradient_y = 0;
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}
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};
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void doGaussBlur(int filter_width=3) {
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// build the gauss filter
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int* filter = (int*) malloc(sizeof(int) * filter_width* filter_width);
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int sum_weights = 0;
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for(int i=0; i<filter_width; i++) {
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for(int j=0; j<filter_width; j++) {
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filter[i*filter_width + j] = pow(2, i) * pow(2, j);
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sum_weights += filter[i*filter_width + j];
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}
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}
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// apply gauss filter
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int filter_offset = (filter_width+1)/2;
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for(int x=0+filter_offset; x<this->width-filter_offset; x++) {
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for(int y=0+filter_offset; y<this->width-filter_offset; y++) {
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int sum_intensity = 0;
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int h, s, l;
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for(int fx=0; fx<filter_width; fx++) {
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int dx = fx - (filter_width / 2);
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for(int fy=0; fy<filter_width; fy++) {
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int dy = fy - (filter_width / 2);
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QColor color = QColor::fromRgb(this->original->getImage()->pixel(x+dx, y+dy));
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color.getHsl(&h, &s, &l);
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sum_intensity += (l * filter[fy*filter_width + fx]);
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}
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}
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QColor color = QColor::fromRgb(original->getImage()->pixel(x, y));
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color.getHsl(&h, &s, &l);
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l = qRound((1.0*sum_intensity) / (1.0*sum_weights));
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if(l > 255) l = 255;
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if(l < 0) l = 0;
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color.setHsl(h, s, l);
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this->working_copy->getImage()->setPixel(x, y, color.rgb());
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}
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}
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free(filter);
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};
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void work() {
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this->reset();
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for(int x=0; x<this->width; x++) {
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for(int y=0; y<this->height; y++) {
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//this->gradient_magnitude = sqrt(...)
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}
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}
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};
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};
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@ -650,7 +650,14 @@ void ImageViewer::applyBasicFilterWithOverflowHandling() {
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*/
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void ImageViewer::runCannyEdge(void) {
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//TODO
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CannyEdgeMachine cem = CannyEdgeMachine();
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// Blur with Gauss (1,2,1 2,4,2 1,2,1) (delta=3, otherwise bigger matrix)
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// THEN do x/y gradients with (-0.5, 0, 0.5)
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CannyEdgeMachine cem = CannyEdgeMachine(original, working_copy);
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cem.setThresholdValues(0, 0); //TODO
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cem.work();
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}
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/****************************************************************************************
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@ -917,6 +924,8 @@ void ImageViewer::generateControlPanels() {
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run_canny_edge = new QPushButton("Run canny edge algorithm!");
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QObject::connect(run_canny_edge, SIGNAL(clicked()), this, SLOT(runCannyEdge()));
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task_tab5_scrolllayout->addWidget(run_canny_edge);
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tabWidget->addTab(task_tab5_widget, "Task #5");
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//Show it
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@ -298,8 +298,15 @@ class LazyImage {
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//std::cout << output_r << "," << output_g << "," << output_b << std::endl << std::endl;
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QColor result = QColor(output_r, output_g, output_b);
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return result;
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};
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};
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int width(void) {
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return this->img->width();
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};
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int height(void) {
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return this->img->height();
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};
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};
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