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Open Source Computer Vision Library
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386 lines
13 KiB
386 lines
13 KiB
/* |
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* This sample demonstrates the use of the function |
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* findTransformECC that implements the image alignment ECC algorithm |
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* |
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* |
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* The demo loads an image (defaults to fruits.jpg) and it artificially creates |
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* a template image based on the given motion type. When two images are given, |
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* the first image is the input image and the second one defines the template image. |
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* In the latter case, you can also parse the warp's initialization. |
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* |
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* Input and output warp files consist of the raw warp (transform) elements |
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* |
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* Authors: G. Evangelidis, INRIA, Grenoble, France |
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* M. Asbach, Fraunhofer IAIS, St. Augustin, Germany |
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*/ |
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#include <opencv2/highgui.hpp> |
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#include <opencv2/video.hpp> |
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#include <opencv2/imgproc.hpp> |
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#include <opencv2/core/utility.hpp> |
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#include <stdio.h> |
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#include <string> |
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#include <time.h> |
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#include <iostream> |
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#include <fstream> |
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using namespace cv; |
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using namespace std; |
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static void help(void); |
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static int readWarp(string iFilename, Mat& warp, int motionType); |
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static int saveWarp(string fileName, const Mat& warp, int motionType); |
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static void draw_warped_roi(Mat& image, const int width, const int height, Mat& W); |
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#define HOMO_VECTOR(H, x, y)\ |
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H.at<float>(0,0) = (float)(x);\ |
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H.at<float>(1,0) = (float)(y);\ |
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H.at<float>(2,0) = 1.; |
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#define GET_HOMO_VALUES(X, x, y)\ |
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(x) = static_cast<float> (X.at<float>(0,0)/X.at<float>(2,0));\ |
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(y) = static_cast<float> (X.at<float>(1,0)/X.at<float>(2,0)); |
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const std::string keys = |
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"{@inputImage | fruits.jpg | input image filename }" |
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"{@templateImage | | template image filename (optional)}" |
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"{@inputWarp | | input warp (matrix) filename (optional)}" |
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"{n numOfIter | 50 | ECC's iterations }" |
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"{e epsilon | 0.0001 | ECC's convergence epsilon }" |
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"{o outputWarp | outWarp.ecc | output warp (matrix) filename }" |
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"{m motionType | affine | type of motion (translation, euclidean, affine, homography) }" |
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"{v verbose | 0 | display initial and final images }" |
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"{w warpedImfile | warpedECC.png | warped input image }" |
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; |
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static void help(void) |
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{ |
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cout << "\nThis file demostrates the use of the ECC image alignment algorithm. When one image" |
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" is given, the template image is artificially formed by a random warp. When both images" |
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" are given, the initialization of the warp by command line parsing is possible. " |
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"If inputWarp is missing, the identity transformation initializes the algorithm. \n" << endl; |
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cout << "\nUsage example (one image): \n./ecc fruits.jpg -o=outWarp.ecc " |
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"-m=euclidean -e=1e-6 -N=70 -v=1 \n" << endl; |
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cout << "\nUsage example (two images with initialization): \n./ecc yourInput.png yourTemplate.png " |
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"yourInitialWarp.ecc -o=outWarp.ecc -m=homography -e=1e-6 -N=70 -v=1 -w=yourFinalImage.png \n" << endl; |
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} |
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static int readWarp(string iFilename, Mat& warp, int motionType){ |
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// it reads from file a specific number of raw values: |
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// 9 values for homography, 6 otherwise |
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CV_Assert(warp.type()==CV_32FC1); |
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int numOfElements; |
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if (motionType==MOTION_HOMOGRAPHY) |
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numOfElements=9; |
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else |
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numOfElements=6; |
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int i; |
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int ret_value; |
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ifstream myfile(iFilename.c_str()); |
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if (myfile.is_open()){ |
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float* matPtr = warp.ptr<float>(0); |
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for(i=0; i<numOfElements; i++){ |
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myfile >> matPtr[i]; |
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} |
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ret_value = 1; |
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} |
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else { |
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cout << "Unable to open file " << iFilename.c_str() << endl; |
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ret_value = 0; |
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} |
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return ret_value; |
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} |
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static int saveWarp(string fileName, const Mat& warp, int motionType) |
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{ |
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// it saves the raw matrix elements in a file |
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CV_Assert(warp.type()==CV_32FC1); |
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const float* matPtr = warp.ptr<float>(0); |
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int ret_value; |
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ofstream outfile(fileName.c_str()); |
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if( !outfile ) { |
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cerr << "error in saving " |
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<< "Couldn't open file '" << fileName.c_str() << "'!" << endl; |
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ret_value = 0; |
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} |
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else {//save the warp's elements |
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outfile << matPtr[0] << " " << matPtr[1] << " " << matPtr[2] << endl; |
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outfile << matPtr[3] << " " << matPtr[4] << " " << matPtr[5] << endl; |
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if (motionType==MOTION_HOMOGRAPHY){ |
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outfile << matPtr[6] << " " << matPtr[7] << " " << matPtr[8] << endl; |
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} |
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ret_value = 1; |
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} |
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return ret_value; |
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} |
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static void draw_warped_roi(Mat& image, const int width, const int height, Mat& W) |
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{ |
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Point2f top_left, top_right, bottom_left, bottom_right; |
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Mat H = Mat (3, 1, CV_32F); |
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Mat U = Mat (3, 1, CV_32F); |
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Mat warp_mat = Mat::eye (3, 3, CV_32F); |
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for (int y = 0; y < W.rows; y++) |
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for (int x = 0; x < W.cols; x++) |
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warp_mat.at<float>(y,x) = W.at<float>(y,x); |
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//warp the corners of rectangle |
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// top-left |
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HOMO_VECTOR(H, 1, 1); |
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gemm(warp_mat, H, 1, 0, 0, U); |
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GET_HOMO_VALUES(U, top_left.x, top_left.y); |
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// top-right |
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HOMO_VECTOR(H, width, 1); |
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gemm(warp_mat, H, 1, 0, 0, U); |
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GET_HOMO_VALUES(U, top_right.x, top_right.y); |
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// bottom-left |
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HOMO_VECTOR(H, 1, height); |
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gemm(warp_mat, H, 1, 0, 0, U); |
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GET_HOMO_VALUES(U, bottom_left.x, bottom_left.y); |
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// bottom-right |
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HOMO_VECTOR(H, width, height); |
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gemm(warp_mat, H, 1, 0, 0, U); |
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GET_HOMO_VALUES(U, bottom_right.x, bottom_right.y); |
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// draw the warped perimeter |
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line(image, top_left, top_right, Scalar(255,0,255)); |
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line(image, top_right, bottom_right, Scalar(255,0,255)); |
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line(image, bottom_right, bottom_left, Scalar(255,0,255)); |
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line(image, bottom_left, top_left, Scalar(255,0,255)); |
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} |
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int main (const int argc, const char * argv[]) |
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{ |
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CommandLineParser parser(argc, argv, keys); |
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parser.about("ECC demo"); |
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if (argc<2) { |
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parser.printMessage(); |
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help(); |
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return 1; |
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} |
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string imgFile = parser.get<string>(0); |
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string tempImgFile = parser.get<string>(1); |
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string inWarpFile = parser.get<string>(2); |
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int number_of_iterations = parser.get<int>("n"); |
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double termination_eps = parser.get<double>("e"); |
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string warpType = parser.get<string>("m"); |
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int verbose = parser.get<int>("v"); |
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string finalWarp = parser.get<string>("o"); |
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string warpedImFile = parser.get<string>("w"); |
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if (!(warpType == "translation" || warpType == "euclidean" |
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|| warpType == "affine" || warpType == "homography")) |
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{ |
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cerr << "Invalid motion transformation" << endl; |
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return -1; |
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} |
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int mode_temp; |
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if (warpType == "translation") |
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mode_temp = MOTION_TRANSLATION; |
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else if (warpType == "euclidean") |
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mode_temp = MOTION_EUCLIDEAN; |
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else if (warpType == "affine") |
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mode_temp = MOTION_AFFINE; |
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else |
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mode_temp = MOTION_HOMOGRAPHY; |
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Mat inputImage = imread(imgFile,0); |
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if (inputImage.empty()) |
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{ |
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cerr << "Unable to load the inputImage" << endl; |
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return -1; |
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} |
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Mat target_image; |
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Mat template_image; |
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if (tempImgFile!="") { |
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inputImage.copyTo(target_image); |
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template_image = imread(tempImgFile,0); |
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if (template_image.empty()){ |
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cerr << "Unable to load the template image" << endl; |
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return -1; |
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} |
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} |
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else{ //apply random waro to input image |
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resize(inputImage, target_image, Size(216, 216)); |
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Mat warpGround; |
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cv::RNG rng; |
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double angle; |
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switch (mode_temp) { |
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case MOTION_TRANSLATION: |
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warpGround = (Mat_<float>(2,3) << 1, 0, (rng.uniform(10.f, 20.f)), |
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0, 1, (rng.uniform(10.f, 20.f))); |
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warpAffine(target_image, template_image, warpGround, |
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Size(200,200), CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS+CV_WARP_INVERSE_MAP); |
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break; |
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case MOTION_EUCLIDEAN: |
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angle = CV_PI/30 + CV_PI*rng.uniform((double)-2.f, (double)2.f)/180; |
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warpGround = (Mat_<float>(2,3) << cos(angle), -sin(angle), (rng.uniform(10.f, 20.f)), |
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sin(angle), cos(angle), (rng.uniform(10.f, 20.f))); |
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warpAffine(target_image, template_image, warpGround, |
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Size(200,200), CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS+CV_WARP_INVERSE_MAP); |
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break; |
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case MOTION_AFFINE: |
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warpGround = (Mat_<float>(2,3) << (1-rng.uniform(-0.05f, 0.05f)), |
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(rng.uniform(-0.03f, 0.03f)), (rng.uniform(10.f, 20.f)), |
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(rng.uniform(-0.03f, 0.03f)), (1-rng.uniform(-0.05f, 0.05f)), |
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(rng.uniform(10.f, 20.f))); |
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warpAffine(target_image, template_image, warpGround, |
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Size(200,200), CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS+CV_WARP_INVERSE_MAP); |
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break; |
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case MOTION_HOMOGRAPHY: |
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warpGround = (Mat_<float>(3,3) << (1-rng.uniform(-0.05f, 0.05f)), |
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(rng.uniform(-0.03f, 0.03f)), (rng.uniform(10.f, 20.f)), |
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(rng.uniform(-0.03f, 0.03f)), (1-rng.uniform(-0.05f, 0.05f)),(rng.uniform(10.f, 20.f)), |
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(rng.uniform(0.0001f, 0.0003f)), (rng.uniform(0.0001f, 0.0003f)), 1.f); |
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warpPerspective(target_image, template_image, warpGround, |
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Size(200,200), CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS+CV_WARP_INVERSE_MAP); |
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break; |
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} |
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} |
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const int warp_mode = mode_temp; |
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// initialize or load the warp matrix |
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Mat warp_matrix; |
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if (warpType == "homography") |
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warp_matrix = Mat::eye(3, 3, CV_32F); |
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else |
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warp_matrix = Mat::eye(2, 3, CV_32F); |
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if (inWarpFile!=""){ |
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int readflag = readWarp(inWarpFile, warp_matrix, warp_mode); |
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if ((!readflag) || warp_matrix.empty()) |
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{ |
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cerr << "-> Check warp initialization file" << endl << flush; |
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return -1; |
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} |
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} |
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else { |
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printf("\n ->Perfomarnce Warning: Identity warp ideally assumes images of " |
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"similar size. If the deformation is strong, the identity warp may not " |
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"be a good initialization. \n"); |
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} |
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if (number_of_iterations > 200) |
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cout << "-> Warning: too many iterations " << endl; |
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if (warp_mode != MOTION_HOMOGRAPHY) |
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warp_matrix.rows = 2; |
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// start timing |
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const double tic_init = (double) getTickCount (); |
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double cc = findTransformECC (template_image, target_image, warp_matrix, warp_mode, |
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TermCriteria (TermCriteria::COUNT+TermCriteria::EPS, |
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number_of_iterations, termination_eps)); |
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if (cc == -1) |
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{ |
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cerr << "The execution was interrupted. The correlation value is going to be minimized." << endl; |
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cerr << "Check the warp initialization and/or the size of images." << endl << flush; |
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} |
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// end timing |
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const double toc_final = (double) getTickCount (); |
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const double total_time = (toc_final-tic_init)/(getTickFrequency()); |
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if (verbose){ |
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cout << "Alignment time (" << warpType << " transformation): " |
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<< total_time << " sec" << endl << flush; |
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// cout << "Final correlation: " << cc << endl << flush; |
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} |
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// save the final warp matrix |
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saveWarp(finalWarp, warp_matrix, warp_mode); |
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if (verbose){ |
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cout << "\nThe final warp has been saved in the file: " << finalWarp << endl << flush; |
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} |
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// save the final warped image |
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Mat warped_image = Mat(template_image.rows, template_image.cols, CV_32FC1); |
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if (warp_mode != MOTION_HOMOGRAPHY) |
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warpAffine (target_image, warped_image, warp_matrix, warped_image.size(), |
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CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS+CV_WARP_INVERSE_MAP); |
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else |
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warpPerspective (target_image, warped_image, warp_matrix, warped_image.size(), |
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CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS+CV_WARP_INVERSE_MAP); |
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//save the warped image |
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imwrite(warpedImFile, warped_image); |
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// display resulting images |
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if (verbose) |
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{ |
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cout << "The warped image has been saved in the file: " << warpedImFile << endl << flush; |
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namedWindow ("image", CV_WINDOW_AUTOSIZE); |
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namedWindow ("template", CV_WINDOW_AUTOSIZE); |
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namedWindow ("warped image", CV_WINDOW_AUTOSIZE); |
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namedWindow ("error (black: no error)", CV_WINDOW_AUTOSIZE); |
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moveWindow ("template", 350, 350); |
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moveWindow ("warped image", 600, 300); |
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moveWindow ("error (black: no error)", 900, 300); |
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// draw boundaries of corresponding regions |
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Mat identity_matrix = Mat::eye(3,3,CV_32F); |
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draw_warped_roi (target_image, template_image.cols-2, template_image.rows-2, warp_matrix); |
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draw_warped_roi (template_image, template_image.cols-2, template_image.rows-2, identity_matrix); |
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Mat errorImage; |
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subtract(template_image, warped_image, errorImage); |
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double max_of_error; |
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minMaxLoc(errorImage, NULL, &max_of_error); |
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// show images |
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cout << "Press any key to exit the demo (you might need to click on the images before)." << endl << flush; |
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imshow ("image", target_image); |
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waitKey (200); |
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imshow ("template", template_image); |
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waitKey (200); |
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imshow ("warped image", warped_image); |
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waitKey(200); |
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imshow ("error (black: no error)", abs(errorImage)*255/max_of_error); |
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waitKey(0); |
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} |
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// done |
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return 0; |
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}
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