New approach using a roi and drawContours method
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#include <opencv2/opencv.hpp>
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#include <opencv2/opencv.hpp>
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#include <iostream>
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#include <iostream>
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#include <direct.h>
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#include <input.h>
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#include <input.h>
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#include <processing.h>
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#include <processing.h>
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@ -34,20 +35,63 @@ void sweep_em_all(int thresholdBinary, int videoHeight, int videoWidth, int gaus
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void in_depth_processing_chain(int thresholdBinary, int videoHeight, int videoWidth, int gaussKernelSize, int thresholdCanny1, int thresholdCanny2, int apertureSizeCanny)
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void in_depth_processing_chain(int thresholdBinary, int videoHeight, int videoWidth, int gaussKernelSize, int thresholdCanny1, int thresholdCanny2, int apertureSizeCanny)
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{
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{
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std::string outputFolder = "C:\\Users\\User\\Desktop\\temp";
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Input input(videoHeight, videoWidth);
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Input input(videoHeight, videoWidth);
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Mat image = input.readFile("C:\\Users\\User\\Desktop\\Studium\\02_Master_MSY\\2. Semester Winter 22 23\\Projekt\\Line-Following-Robot\\Test_data");
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std::string outputFolder = "C:\\Users\\User\\Desktop\\temp";
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imwrite(outputFolder + "\\01_input.jpg", image);
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std::string inputFolder = "C:\\Users\\User\\Desktop\\Studium\\02_Master_MSY\\2. Semester Winter 22 23\\Projekt\\Line-Following-Robot\\AutonomousMode\\Test_data";
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cvtColor(image, image, COLOR_BGR2GRAY);
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imwrite(outputFolder + "\\02_color_convert.jpg", image);
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GaussianBlur(image, image, Size(gaussKernelSize, gaussKernelSize), 0);
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imwrite(outputFolder + "\\03_gauss.jpg", image);
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threshold(image, image, thresholdBinary, 255, THRESH_BINARY);
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imwrite(outputFolder + "\\04_threshold.jpg", image);
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Canny(image, image, thresholdCanny1, thresholdCanny2, apertureSizeCanny);
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imwrite(outputFolder + "\\05_canny.jpg", image);
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std::vector<std::string> filenames;
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cv::glob(inputFolder, filenames);
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//filenames.begin(), filenames.end()
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int i = 0;
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for(std::vector<std::string>::iterator it = filenames.begin(); it != filenames.end(); it++)
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{
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std::string current_output = outputFolder + "\\" + to_string(i);
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std::cout << current_output << std::endl;
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const char* current_output_char = current_output.c_str();
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_mkdir(current_output_char);
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std::string inputFile = inputFolder + "\\image" + to_string(i+1) + ".jpeg";
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Mat original_image = input.readFile(inputFile);
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imwrite(current_output + "\\00_input.jpg", original_image);
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Rect roi = Rect(0, original_image.rows*(7.5/12.0), original_image.cols, original_image.rows/12);
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Mat image = original_image(roi);
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imwrite(current_output + "\\01_roi.jpg", image);
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cvtColor(image, image, COLOR_BGR2GRAY);
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imwrite(current_output + "\\02_color_convert.jpg", image);
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GaussianBlur(image, image, Size(gaussKernelSize, gaussKernelSize), 0);
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imwrite(current_output + "\\03_gauss.jpg", image);
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threshold(image, image, thresholdBinary, 255, THRESH_BINARY);
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imwrite(current_output + "\\04_threshold.jpg", image);
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// Opening (reduces noise)
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Mat kernel(5,5, CV_8UC1,1);
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morphologyEx(image, image, 2, kernel);
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imwrite(current_output + "\\05_opening.jpg", image);
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//Canny(image, image, thresholdCanny1, thresholdCanny2, apertureSizeCanny);
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//imwrite(outputFolder + "\\06_canny.jpg", image);
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vector<vector<Point> > contours;
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vector<Vec4i> hierarchy;
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findContours(image,contours, hierarchy, RETR_LIST, CHAIN_APPROX_SIMPLE);
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for( int i = 0; i< contours.size(); i++ ) // iterate through each contour.
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{
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double a = contourArea( contours[i],false); // Find the area of contour
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if(a > 3500)
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{
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drawContours(original_image, contours, i, Scalar(0,255,255), 1, 8, hierarchy, 0, Point(0,original_image.rows*(7.5/12.0)));
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}
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}
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imwrite(current_output + "\\06_contours.jpg", original_image);
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i++;
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}
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}
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}
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