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samples/cpp/image_alignment.cpp
An example using the image alignment ECC algorithm
/*
* This sample demonstrates the use of the function
* findTransformECC that implements the image alignment ECC algorithm
*
*
* The demo loads an image (defaults to fruits.jpg) and it artificially creates
* a template image based on the given motion type. When two images are given,
* the first image is the input image and the second one defines the template image.
* In the latter case, you can also parse the warp's initialization.
*
* Input and output warp files consist of the raw warp (transform) elements
*
* Authors: G. Evangelidis, INRIA, Grenoble, France
* M. Asbach, Fraunhofer IAIS, St. Augustin, Germany
*/
#include <opencv2/imgcodecs.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/video.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/core/utility.hpp>
#include <stdio.h>
#include <string>
#include <time.h>
#include <iostream>
#include <fstream>
using namespace cv;
using namespace std;
static void help(const char** argv);
#define HOMO_VECTOR(H, x, y)\
H.at<float>(0,0) = (float)(x);\
H.at<float>(1,0) = (float)(y);\
H.at<float>(2,0) = 1.;
#define GET_HOMO_VALUES(X, x, y)\
(x) = static_cast<float> (X.at<float>(0,0)/X.at<float>(2,0));\
(y) = static_cast<float> (X.at<float>(1,0)/X.at<float>(2,0));
const std::string keys =
"{@inputImage | fruits.jpg | input image filename }"
"{@templateImage | | template image filename (optional)}"
"{@inputWarp | | input warp (matrix) filename (optional)}"
"{n numOfIter | 50 | ECC's iterations }"
"{e epsilon | 0.0001 | ECC's convergence epsilon }"
"{o outputWarp | outWarp.ecc | output warp (matrix) filename }"
"{m motionType | affine | type of motion (translation, euclidean, affine, homography) }"
"{v verbose | 1 | display initial and final images }"
"{w warpedImfile | warpedECC.png | warped input image }"
"{h help | | print help message }"
;
static void help(const char** argv)
{
cout << "\nThis file demonstrates the use of the ECC image alignment algorithm. When one image"
" is given, the template image is artificially formed by a random warp. When both images"
" are given, the initialization of the warp by command line parsing is possible. "
"If inputWarp is missing, the identity transformation initializes the algorithm. \n" << endl;
cout << "\nUsage example (one image): \n"
<< argv[0]
<< " fruits.jpg -o=outWarp.ecc "
"-m=euclidean -e=1e-6 -N=70 -v=1 \n" << endl;
cout << "\nUsage example (two images with initialization): \n"
<< argv[0]
<< " yourInput.png yourTemplate.png "
"yourInitialWarp.ecc -o=outWarp.ecc -m=homography -e=1e-6 -N=70 -v=1 -w=yourFinalImage.png \n" << endl;
}
// it reads from file a specific number of raw values:
// 9 values for homography, 6 otherwise
int numOfElements;
if (motionType==MOTION_HOMOGRAPHY)
numOfElements=9;
else
numOfElements=6;
int i;
int ret_value;
ifstream myfile(iFilename.c_str());
if (myfile.is_open()){
for(i=0; i<numOfElements; i++){
myfile >> matPtr[i];
}
ret_value = 1;
}
else {
cout << "Unable to open file " << iFilename.c_str() << endl;
ret_value = 0;
}
return ret_value;
}
{
// it saves the raw matrix elements in a file
int ret_value;
ofstream outfile(fileName.c_str());
if( !outfile ) {
cerr << "error in saving "
<< "Couldn't open file '" << fileName.c_str() << "'!" << endl;
ret_value = 0;
}
else {//save the warp's elements
outfile << matPtr[0] << " " << matPtr[1] << " " << matPtr[2] << endl;
outfile << matPtr[3] << " " << matPtr[4] << " " << matPtr[5] << endl;
if (motionType==MOTION_HOMOGRAPHY){
outfile << matPtr[6] << " " << matPtr[7] << " " << matPtr[8] << endl;
}
ret_value = 1;
}
return ret_value;
}
{
Point2f top_left, top_right, bottom_left, bottom_right;
//warp the corners of rectangle
// top-left
HOMO_VECTOR(H, 1, 1);
gemm(warp_mat, H, 1, 0, 0, U);
// top-right
HOMO_VECTOR(H, width, 1);
gemm(warp_mat, H, 1, 0, 0, U);
// bottom-left
HOMO_VECTOR(H, 1, height);
gemm(warp_mat, H, 1, 0, 0, U);
// bottom-right
HOMO_VECTOR(H, width, height);
gemm(warp_mat, H, 1, 0, 0, U);
// draw the warped perimeter
}
int main (const int argc, const char * argv[])
{
CommandLineParser parser(argc, argv, keys);
parser.about("ECC demo");
parser.printMessage();
help(argv);
string imgFile = parser.get<string>(0);
string tempImgFile = parser.get<string>(1);
string inWarpFile = parser.get<string>(2);
int number_of_iterations = parser.get<int>("n");
double termination_eps = parser.get<double>("e");
string warpType = parser.get<string>("m");
int verbose = parser.get<int>("v");
string finalWarp = parser.get<string>("o");
string warpedImFile = parser.get<string>("w");
if (!parser.check())
{
parser.printErrors();
return -1;
}
if (!(warpType == "translation" || warpType == "euclidean"
|| warpType == "affine" || warpType == "homography"))
{
cerr << "Invalid motion transformation" << endl;
return -1;
}
int mode_temp;
if (warpType == "translation")
mode_temp = MOTION_TRANSLATION;
else if (warpType == "euclidean")
mode_temp = MOTION_EUCLIDEAN;
else if (warpType == "affine")
mode_temp = MOTION_AFFINE;
else
mode_temp = MOTION_HOMOGRAPHY;
{
cerr << "Unable to load the inputImage" << endl;
return -1;
}
Mat target_image;
Mat template_image;
if (tempImgFile!="") {
inputImage.copyTo(target_image);
template_image = imread(samples::findFile(tempImgFile), IMREAD_GRAYSCALE);
if (template_image.empty()){
cerr << "Unable to load the template image" << endl;
return -1;
}
}
else{ //apply random warp to input image
Mat warpGround;
double angle;
switch (mode_temp) {
case MOTION_TRANSLATION:
warpGround = (Mat_<float>(2,3) << 1, 0, (rng.uniform(10.f, 20.f)),
0, 1, (rng.uniform(10.f, 20.f)));
warpAffine(target_image, template_image, warpGround,
Size(200,200), INTER_LINEAR + WARP_INVERSE_MAP);
break;
case MOTION_EUCLIDEAN:
warpAffine(target_image, template_image, warpGround,
Size(200,200), INTER_LINEAR + WARP_INVERSE_MAP);
break;
case MOTION_AFFINE:
warpGround = (Mat_<float>(2,3) << (1-rng.uniform(-0.05f, 0.05f)),
(rng.uniform(-0.03f, 0.03f)), (rng.uniform(10.f, 20.f)),
(rng.uniform(-0.03f, 0.03f)), (1-rng.uniform(-0.05f, 0.05f)),
(rng.uniform(10.f, 20.f)));
warpAffine(target_image, template_image, warpGround,
Size(200,200), INTER_LINEAR + WARP_INVERSE_MAP);
break;
case MOTION_HOMOGRAPHY:
warpGround = (Mat_<float>(3,3) << (1-rng.uniform(-0.05f, 0.05f)),
(rng.uniform(-0.03f, 0.03f)), (rng.uniform(10.f, 20.f)),
(rng.uniform(-0.03f, 0.03f)), (1-rng.uniform(-0.05f, 0.05f)),(rng.uniform(10.f, 20.f)),
(rng.uniform(0.0001f, 0.0003f)), (rng.uniform(0.0001f, 0.0003f)), 1.f);
warpPerspective(target_image, template_image, warpGround,
Size(200,200), INTER_LINEAR + WARP_INVERSE_MAP);
break;
}
}
const int warp_mode = mode_temp;
// initialize or load the warp matrix
Mat warp_matrix;
if (warpType == "homography")
warp_matrix = Mat::eye(3, 3, CV_32F);
else
warp_matrix = Mat::eye(2, 3, CV_32F);
if (inWarpFile!=""){
int readflag = readWarp(inWarpFile, warp_matrix, warp_mode);
if ((!readflag) || warp_matrix.empty())
{
cerr << "-> Check warp initialization file" << endl << flush;
return -1;
}
}
else {
printf("\n ->Performance Warning: Identity warp ideally assumes images of "
"similar size. If the deformation is strong, the identity warp may not "
"be a good initialization. \n");
}
if (number_of_iterations > 200)
cout << "-> Warning: too many iterations " << endl;
if (warp_mode != MOTION_HOMOGRAPHY)
warp_matrix.rows = 2;
// start timing
const double tic_init = (double) getTickCount ();
double cc = findTransformECC (template_image, target_image, warp_matrix, warp_mode,
TermCriteria (TermCriteria::COUNT+TermCriteria::EPS,
number_of_iterations, termination_eps));
if (cc == -1)
{
cerr << "The execution was interrupted. The correlation value is going to be minimized." << endl;
cerr << "Check the warp initialization and/or the size of images." << endl << flush;
}
// end timing
const double toc_final = (double) getTickCount ();
if (verbose){
cout << "Alignment time (" << warpType << " transformation): "
<< total_time << " sec" << endl << flush;
// cout << "Final correlation: " << cc << endl << flush;
}
// save the final warp matrix
saveWarp(finalWarp, warp_matrix, warp_mode);
if (verbose){
cout << "\nThe final warp has been saved in the file: " << finalWarp << endl << flush;
}
// save the final warped image
if (warp_mode != MOTION_HOMOGRAPHY)
INTER_LINEAR + WARP_INVERSE_MAP);
else
warpPerspective (target_image, warped_image, warp_matrix, warped_image.size(),
INTER_LINEAR + WARP_INVERSE_MAP);
//save the warped image
imwrite(warpedImFile, warped_image);
// display resulting images
if (verbose)
{
cout << "The warped image has been saved in the file: " << warpedImFile << endl << flush;
namedWindow ("image", WINDOW_AUTOSIZE);
namedWindow ("template", WINDOW_AUTOSIZE);
namedWindow ("warped image", WINDOW_AUTOSIZE);
namedWindow ("error (black: no error)", WINDOW_AUTOSIZE);
moveWindow ("image", 20, 300);
moveWindow ("template", 300, 300);
moveWindow ("warped image", 600, 300);
moveWindow ("error (black: no error)", 900, 300);
// draw boundaries of corresponding regions
Mat errorImage;
subtract(template_image, warped_image, errorImage);
double max_of_error;
minMaxLoc(errorImage, NULL, &max_of_error);
// show images
cout << "Press any key to exit the demo (you might need to click on the images before)." << endl << flush;
imshow ("image", target_image);
waitKey (200);
imshow ("template", template_image);
waitKey (200);
imshow ("warped image", warped_image);
waitKey(200);
waitKey(0);
}
// done
return 0;
}
int rows
the number of rows and columns or (-1, -1) when the matrix has more than 2 dimensions
Definition: mat.hpp:2137
The class defining termination criteria for iterative algorithms.
Definition: types.hpp:886
void subtract(InputArray src1, InputArray src2, OutputArray dst, InputArray mask=noArray(), int dtype=-1)
Calculates the per-element difference between two arrays or array and a scalar.
void minMaxLoc(InputArray src, double *minVal, double *maxVal=0, Point *minLoc=0, Point *maxLoc=0, InputArray mask=noArray())
Finds the global minimum and maximum in an array.
void gemm(InputArray src1, InputArray src2, double alpha, InputArray src3, double beta, OutputArray dst, int flags=0)
Performs generalized matrix multiplication.
#define CV_Assert(expr)
Checks a condition at runtime and throws exception if it fails.
Definition: base.hpp:342
Quat< T > cos(const Quat< T > &q)
Quat< T > sin(const Quat< T > &q)
void imshow(const String &winname, InputArray mat)
Displays an image in the specified window.
void moveWindow(const String &winname, int x, int y)
Moves the window to the specified position.
CV_EXPORTS_W bool imwrite(const String &filename, InputArray img, const std::vector< int > ¶ms=std::vector< int >())
Saves an image to a specified file.
CV_EXPORTS_W Mat imread(const String &filename, int flags=IMREAD_COLOR)
Loads an image from a file.
void line(InputOutputArray img, Point pt1, Point pt2, const Scalar &color, int thickness=1, int lineType=LINE_8, int shift=0)
Draws a line segment connecting two points.
void warpAffine(InputArray src, OutputArray dst, InputArray M, Size dsize, int flags=INTER_LINEAR, int borderMode=BORDER_CONSTANT, const Scalar &borderValue=Scalar())
Applies an affine transformation to an image.
void resize(InputArray src, OutputArray dst, Size dsize, double fx=0, double fy=0, int interpolation=INTER_LINEAR)
Resizes an image.
void warpPerspective(InputArray src, OutputArray dst, InputArray M, Size dsize, int flags=INTER_LINEAR, int borderMode=BORDER_CONSTANT, const Scalar &borderValue=Scalar())
Applies a perspective transformation to an image.
double findTransformECC(InputArray templateImage, InputArray inputImage, InputOutputArray warpMatrix, int motionType, TermCriteria criteria, InputArray inputMask, int gaussFiltSize)
Finds the geometric transform (warp) between two images in terms of the ECC criterion .
"black box" representation of the file storage associated with a file on disk.
Definition: core.hpp:106
STL namespace.