Sample code of vignette calibration.

Author: nynyg

modules/photometric_calib/samples/vignette_calibration.cpp

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+#include <string>
+#include <iostream>
+#include <iomanip>
+#include <vector>
+
+#include "opencv2/opencv.hpp"
+#include "opencv2/core.hpp"
+#include "opencv2/highgui.hpp"
+#include "opencv2/photometric_calib.hpp"
+#include "opencv2/imgproc/imgproc.hpp"
+
+using namespace std;
+using namespace cv;
+
+int main(int argc, char** argv)
+{
+    // Please down load the sample dataset from:
+    // https://www.dropbox.com/s/5x48uhc7k2bgjcj/GSoC2017_PhotometricCalib_Sample_Data.zip?dl=0
+    // By unzipping the file, you would get a folder named /GSoC2017_PhotometricCalib_Sample_Data which contains 2 subfolders:
+    // response_calib, vignette_calib
+    // in this sample, we will use the data in the folder vignette_calib
+
+    // Prefix for the data, e.g. /Users/Yelen/GSoC2017_PhotometricCalib_Sample
+    string userPrefix = "/Users/Yelen/GSoC2017_PhotometricCalib_Sample_Data/";
+    // The path for the images used for response calibration
+    string imageFolderPath = userPrefix + "vignette_calib/images";
+    // The yaml file which contains the timestamps and exposure times for each image used for vignette calibration
+    string timePath = userPrefix + "vignette_calib/times.yaml";
+    // The yaml file which contains the camera intrinsics and extrinsics.
+    // Note that the images are already rectified, so the distortion parameters are 0s
+    string cameraPath = userPrefix + "vignette_calib/camera.yaml";
+    // The pcalib file. Vignette calibration can be performed only when provided with pcalib file.
+    // We use the identical pcalib.yaml file generated by response_calibration.cpp
+    // You can refer to the code in response_calibration.cpp for details
+    string gammaPath = userPrefix + "vignette_calib/pcalib.yaml";
+
+    // Construct a photometric_calib::VignetteCalib object by giving path of image, path of time file, camera parameter file, pcalib file and specify the format of images
+    photometric_calib::VignetteCalib vigCal(imageFolderPath, timePath, cameraPath, gammaPath, "jpg");
+
+    // Debug mode will visualize the optimization process and generate some temporary data
+    bool debug = true;
+    // Calibration of camera response function begins
+    vigCal.calib(debug);
+
+    // You can also use fast mode, but with much memory (potentially with 10GB+)
+    // vigCal.calibFast(debug);
+
+    // The result and some intermediate data are stored in the folder ./vignetteCalibResult in which
+    // vignette.png and vignetteSmoothed.png are the vignette images.
+    // In practice, vignetteSomoothed.png is used, since it doesn't have the black boarders.
+    Mat vigSmoothed = imread("./vignetteCalibResult/vignetteSmoothed.png", CV_LOAD_IMAGE_UNCHANGED);
+    // As shown as Fig.4 in the paper from J.Engel, et al. in the paper A Photometrically Calibrated Benchmark For Monocular Visual Odometry
+    namedWindow( "Vignette Smoothed", WINDOW_AUTOSIZE );
+    imshow("Vignette Smoothed", vigSmoothed);
+
+    // To see the vignette-calibrated image, we can use VignetteRemover
+    Mat oriImg = imread(imageFolderPath + "/00480.jpg", CV_LOAD_IMAGE_UNCHANGED);
+    photometric_calib::GammaRemover gammaRemover(gammaPath, oriImg.cols, oriImg.rows);
+    photometric_calib::VignetteRemover vignetteRemover("./vignetteCalibResult/vignetteSmoothed.png", gammaPath, oriImg.cols, oriImg.rows);
+    Mat resCaliImg = gammaRemover.getUnGammaImageMat(oriImg);
+    Mat vigCaliImg = vignetteRemover.getUnVignetteImageMat(oriImg);
+
+    // Visualization
+    namedWindow( "Original Image", WINDOW_AUTOSIZE );
+    imshow("Original Image", oriImg);
+    namedWindow( "Gamma Removed Image", WINDOW_AUTOSIZE );
+    imshow("Gamma Removed Image", resCaliImg);
+    namedWindow( "Vignette Removed Image", WINDOW_AUTOSIZE );
+    imshow("Vignette Removed Image", vigCaliImg);
+
+    waitKey(0);
+
+    return 0;
+}