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Update samples (opencv#10333)
* Update samples * Update calib3d.hpp * Update calib3d.hpp * Update calib3d.hpp * Update calib3d.hpp
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‎doc/js_tutorials/js_assets/js_houghlines_HoughLines.html

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@@ -41,7 +41,7 @@ <h2>Hough Lines Example</h2>
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<script src="utils.js" type="text/javascript"></script>
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<script id="codeSnippet" type="text/code-snippet">
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let src = cv.imread('canvasInput');
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let dst = cv.Mat.zeros(src.rows, src.cols, cv.CV_8U);
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let dst = cv.Mat.zeros(src.rows, src.cols, cv.CV_8UC3);
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let lines = new cv.Mat();
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cv.cvtColor(src, src, cv.COLOR_RGBA2GRAY, 0);
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cv.Canny(src, src, 50, 200, 3);

‎doc/js_tutorials/js_assets/js_houghlines_HoughLinesP.html

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@@ -41,7 +41,7 @@ <h2>Image HoughLinesP Example</h2>
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<script src="utils.js" type="text/javascript"></script>
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<script id="codeSnippet" type="text/code-snippet">
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let src = cv.imread('canvasInput');
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let dst = cv.Mat.zeros(src.rows, src.cols, cv.CV_8U);
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let dst = cv.Mat.zeros(src.rows, src.cols, cv.CV_8UC3);
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let lines = new cv.Mat();
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let color = new cv.Scalar(255, 0, 0);
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cv.cvtColor(src, src, cv.COLOR_RGBA2GRAY, 0);

‎doc/tutorials/features2d/homography/homography.markdown

Lines changed: 19 additions & 19 deletions
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@@ -89,31 +89,31 @@ This can be tested easily using a chessboard object and `findChessboardCorners()
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The first thing consists to detect the chessboard corners, the chessboard size (`patternSize`), here `9x6`, is required:
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92-
@snippet tutorial_homography_ex1_pose_from_homography.cpp find-chessboard-corners
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@snippet pose_from_homography.cpp find-chessboard-corners
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![](images/homography_pose_chessboard_corners.jpg)
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The object points expressed in the object frame can be computed easily knowing the size of a chessboard square:
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@snippet tutorial_homography_ex1_pose_from_homography.cpp compute-chessboard-object-points
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@snippet pose_from_homography.cpp compute-chessboard-object-points
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The coordinate `Z=0` must be removed for the homography estimation part:
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@snippet tutorial_homography_ex1_pose_from_homography.cpp compute-object-points
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@snippet pose_from_homography.cpp compute-object-points
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The image points expressed in the normalized camera can be computed from the corner points and by applying a reverse perspective transformation using the camera intrinsics and the distortion coefficients:
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@snippet tutorial_homography_ex1_pose_from_homography.cpp load-intrinsics
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@snippet pose_from_homography.cpp load-intrinsics
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@snippet tutorial_homography_ex1_pose_from_homography.cpp compute-image-points
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@snippet pose_from_homography.cpp compute-image-points
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The homography can then be estimated with:
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@snippet tutorial_homography_ex1_pose_from_homography.cpp estimate-homography
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@snippet pose_from_homography.cpp estimate-homography
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A quick solution to retrieve the pose from the homography matrix is (see \ref pose_ar "5"):
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@snippet tutorial_homography_ex1_pose_from_homography.cpp pose-from-homography
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@snippet pose_from_homography.cpp pose-from-homography
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\f[
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\begin{align*}
@@ -164,23 +164,23 @@ The following image shows the source image (left) and the chessboard view that w
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The first step consists to detect the chessboard corners in the source and desired images:
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@snippet tutorial_homography_ex2_perspective_correction.cpp find-corners
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@snippet perspective_correction.cpp find-corners
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The homography is estimated easily with:
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@snippet tutorial_homography_ex2_perspective_correction.cpp estimate-homography
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@snippet perspective_correction.cpp estimate-homography
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To warp the source chessboard view into the desired chessboard view, we use @ref cv::warpPerspective
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@snippet tutorial_homography_ex2_perspective_correction.cpp warp-chessboard
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@snippet perspective_correction.cpp warp-chessboard
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The result image is:
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![](images/homography_perspective_correction_chessboard_warp.jpg)
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To compute the coordinates of the source corners transformed by the homography:
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@snippet tutorial_homography_ex2_perspective_correction.cpp compute-transformed-corners
183+
@snippet perspective_correction.cpp compute-transformed-corners
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To check the correctness of the calculation, the matching lines are displayed:
186186

@@ -295,13 +295,13 @@ To transform a 3D point expressed in the camera 1 frame to the camera 2 frame:
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In this example, we will compute the camera displacement between two camera poses with respect to the chessboard object. The first step consists to compute the camera poses for the two images:
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298-
@snippet tutorial_homography_ex3_homography_from_camera_displacement.cpp compute-poses
298+
@snippet homography_from_camera_displacement.cpp compute-poses
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![](images/homography_camera_displacement_poses.jpg)
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The camera displacement can be computed from the camera poses using the formulas above:
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@snippet tutorial_homography_ex3_homography_from_camera_displacement.cpp compute-c2Mc1
304+
@snippet homography_from_camera_displacement.cpp compute-c2Mc1
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The homography related to a specific plane computed from the camera displacement is:
307307

@@ -320,27 +320,27 @@ the translation vector between the two camera frames.
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Here the normal vector `n` is the plane normal expressed in the camera frame 1 and can be computed as the cross product of 2 vectors (using 3 non collinear points that lie on the plane) or in our case directly with:
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323-
@snippet tutorial_homography_ex3_homography_from_camera_displacement.cpp compute-plane-normal-at-camera-pose-1
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@snippet homography_from_camera_displacement.cpp compute-plane-normal-at-camera-pose-1
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The distance `d` can be computed as the dot product between the plane normal and a point on the plane or by computing the [plane equation](http://mathworld.wolfram.com/Plane.html) and using the D coefficient:
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327-
@snippet tutorial_homography_ex3_homography_from_camera_displacement.cpp compute-plane-distance-to-the-camera-frame-1
327+
@snippet homography_from_camera_displacement.cpp compute-plane-distance-to-the-camera-frame-1
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The projective homography matrix \f$ \textbf{G} \f$ can be computed from the Euclidean homography \f$ \textbf{H} \f$ using the intrinsic matrix \f$ \textbf{K} \f$ (see @cite Malis), here assuming the same camera between the two plane views:
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\f[
332332
\textbf{G} = \gamma \textbf{K} \textbf{H} \textbf{K}^{-1}
333333
\f]
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335-
@snippet tutorial_homography_ex3_homography_from_camera_displacement.cpp compute-homography
335+
@snippet homography_from_camera_displacement.cpp compute-homography
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In our case, the Z-axis of the chessboard goes inside the object whereas in the homography figure it goes outside. This is just a matter of sign:
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339339
\f[
340340
^{2}\textrm{H}_{1} = \hspace{0.2em} ^{2}\textrm{R}_{1} + \hspace{0.1em} \frac{^{2}\textrm{t}_{1} \cdot n^T}{d}
341341
\f]
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343-
@snippet tutorial_homography_ex3_homography_from_camera_displacement.cpp compute-homography-from-camera-displacement
343+
@snippet homography_from_camera_displacement.cpp compute-homography-from-camera-displacement
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345345
We will now compare the projective homography computed from the camera displacement with the one estimated with @ref cv::findHomography
346346

@@ -368,11 +368,11 @@ Visually, it is hard to distinguish a difference between the result image from t
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OpenCV 3 contains the function @ref cv::decomposeHomographyMat which allows to decompose the homography matrix to a set of rotations, translations and plane normals.
369369
First we will decompose the homography matrix computed from the camera displacement:
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371-
@snippet tutorial_homography_ex4_decompose_homography.cpp compute-homography-from-camera-displacement
371+
@snippet decompose_homography.cpp compute-homography-from-camera-displacement
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373373
The results of @ref cv::decomposeHomographyMat are:
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375-
@snippet tutorial_homography_ex4_decompose_homography.cpp decompose-homography-from-camera-displacement
375+
@snippet decompose_homography.cpp decompose-homography-from-camera-displacement
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377377
```
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Solution 0:

‎modules/calib3d/include/opencv2/calib3d.hpp

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@@ -306,6 +306,12 @@ optimization procedures like calibrateCamera, stereoCalibrate, or solvePnP .
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*/
307307
CV_EXPORTS_W void Rodrigues( InputArray src, OutputArray dst, OutputArray jacobian = noArray() );
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309+
/** @example pose_from_homography.cpp
310+
An example program about pose estimation from coplanar points
311+
312+
Check @ref tutorial_homography "the corresponding tutorial" for more details
313+
*/
314+
309315
/** @brief Finds a perspective transformation between two planes.
310316
311317
@param srcPoints Coordinates of the points in the original plane, a matrix of the type CV_32FC2
@@ -364,12 +370,6 @@ cannot be estimated, an empty one will be returned.
364370
@sa
365371
getAffineTransform, estimateAffine2D, estimateAffinePartial2D, getPerspectiveTransform, warpPerspective,
366372
perspectiveTransform
367-
368-
369-
@note
370-
- A example on calculating a homography for image matching can be found at
371-
opencv_source_code/samples/cpp/video_homography.cpp
372-
373373
*/
374374
CV_EXPORTS_W Mat findHomography( InputArray srcPoints, InputArray dstPoints,
375375
int method = 0, double ransacReprojThreshold = 3,
@@ -525,6 +525,12 @@ CV_EXPORTS_W void projectPoints( InputArray objectPoints,
525525
OutputArray jacobian = noArray(),
526526
double aspectRatio = 0 );
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528+
/** @example homography_from_camera_displacement.cpp
529+
An example program about homography from the camera displacement
530+
531+
Check @ref tutorial_homography "the corresponding tutorial" for more details
532+
*/
533+
528534
/** @brief Finds an object pose from 3D-2D point correspondences.
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530536
@param objectPoints Array of object points in the object coordinate space, Nx3 1-channel or

‎samples/cpp/dbt_face_detection.cpp

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@@ -8,8 +8,6 @@
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#include <opencv2/objdetect.hpp>
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#include <stdio.h>
11-
#include <string>
12-
#include <vector>
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using namespace std;
1513
using namespace cv;
@@ -84,7 +82,7 @@ int main(int , char** )
8482
do
8583
{
8684
VideoStream >> ReferenceFrame;
87-
cvtColor(ReferenceFrame, GrayFrame, COLOR_RGB2GRAY);
85+
cvtColor(ReferenceFrame, GrayFrame, COLOR_BGR2GRAY);
8886
Detector.process(GrayFrame);
8987
Detector.getObjects(Faces);
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‎samples/cpp/tutorial_code/Histograms_Matching/EqualizeHist_Demo.cpp

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@@ -15,20 +15,22 @@ using namespace std;
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/**
1616
* @function main
1717
*/
18-
int main( int, char** argv )
18+
int main( int argc, char** argv )
1919
{
2020
Mat src, dst;
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2222
const char* source_window = "Source image";
2323
const char* equalized_window = "Equalized Image";
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2525
/// Load image
26-
src = imread( argv[1], IMREAD_COLOR );
27-
26+
CommandLineParser parser( argc, argv, "{@input | ../data/lena.jpg | input image}" );
27+
src = imread( parser.get<String>( "@input" ), IMREAD_COLOR );
2828
if( src.empty() )
29-
{ cout<<"Usage: ./EqualizeHist_Demo <path_to_image>"<<endl;
30-
return -1;
31-
}
29+
{
30+
cout << "Could not open or find the image!\n" << endl;
31+
cout << "Usage: " << argv[0] << " <Input image>" << endl;
32+
return -1;
33+
}
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3335
/// Convert to grayscale
3436
cvtColor( src, src, COLOR_BGR2GRAY );

‎samples/cpp/tutorial_code/ImgProc/Morphology_1.cpp

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@@ -5,10 +5,11 @@
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*/
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#include "opencv2/imgproc.hpp"
8-
#include "opencv2/imgcodecs.hpp"
98
#include "opencv2/highgui.hpp"
9+
#include <iostream>
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1111
using namespace cv;
12+
using namespace std;
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1314
/// Global variables
1415
Mat src, erosion_dst, dilation_dst;
@@ -27,13 +28,17 @@ void Dilation( int, void* );
2728
/**
2829
* @function main
2930
*/
30-
int main( int, char** argv )
31+
int main( int argc, char** argv )
3132
{
3233
/// Load an image
33-
src = imread( argv[1], IMREAD_COLOR );
34-
34+
CommandLineParser parser( argc, argv, "{@input | ../data/chicky_512.png | input image}" );
35+
src = imread( parser.get<String>( "@input" ), IMREAD_COLOR );
3536
if( src.empty() )
36-
{ return -1; }
37+
{
38+
cout << "Could not open or find the image!\n" << endl;
39+
cout << "Usage: " << argv[0] << " <Input image>" << endl;
40+
return -1;
41+
}
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/// Create windows
3944
namedWindow( "Erosion Demo", WINDOW_AUTOSIZE );

‎samples/cpp/tutorial_code/ImgProc/Morphology_2.cpp

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#include "opencv2/imgproc.hpp"
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#include "opencv2/imgcodecs.hpp"
99
#include "opencv2/highgui.hpp"
10+
#include <iostream>
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using namespace cv;
1213

@@ -32,15 +33,14 @@ void Morphology_Operations( int, void* );
3233
int main( int argc, char** argv )
3334
{
3435
//![load]
35-
String imageName("../data/baboon.jpg"); // by default
36-
if (argc > 1)
36+
CommandLineParser parser( argc, argv, "{@input | ../data/baboon.jpg | input image}" );
37+
src = imread( parser.get<String>( "@input" ), IMREAD_COLOR );
38+
if (src.empty())
3739
{
38-
imageName = argv[1];
40+
std::cout << "Could not open or find the image!\n" << std::endl;
41+
std::cout << "Usage: " << argv[0] << " <Input image>" << std::endl;
42+
return -1;
3943
}
40-
src = imread(imageName, IMREAD_COLOR); // Load an image
41-
42-
if( src.empty() )
43-
{ return -1; }
4444
//![load]
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//![window]

‎samples/cpp/tutorial_code/ImgProc/morph_lines_detection/Morphology_3.cpp

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using namespace std;
1212
using namespace cv;
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14-
int main(int, char** argv)
14+
int main(int argc, char** argv)
1515
{
1616
//! [load_image]
17-
// Load the image
18-
Mat src = imread(argv[1]);
19-
20-
// Check if image is loaded fine
21-
if(src.empty()){
22-
printf(" Error opening image\n");
23-
printf(" Program Arguments: [image_path]\n");
17+
CommandLineParser parser(argc, argv, "{@input | ../data/notes.png | input image}");
18+
Mat src = imread(parser.get<String>("@input"), IMREAD_COLOR);
19+
if (src.empty())
20+
{
21+
cout << "Could not open or find the image!\n" << endl;
22+
cout << "Usage: " << argv[0] << " <Input image>" << endl;
2423
return -1;
2524
}
2625

‎samples/cpp/tutorial_code/ImgTrans/CannyDetector_Demo.cpp

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*/
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#include "opencv2/imgproc.hpp"
8-
#include "opencv2/imgcodecs.hpp"
98
#include "opencv2/highgui.hpp"
9+
#include <iostream>
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using namespace cv;
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5656
/**
5757
* @function main
5858
*/
59-
int main( int, char** argv )
59+
int main( int argc, char** argv )
6060
{
6161
//![load]
62-
src = imread( argv[1], IMREAD_COLOR ); // Load an image
62+
CommandLineParser parser( argc, argv, "{@input | ../data/fruits.jpg | input image}" );
63+
src = imread( parser.get<String>( "@input" ), IMREAD_COLOR ); // Load an image
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6465
if( src.empty() )
65-
{ return -1; }
66+
{
67+
std::cout << "Could not open or find the image!\n" << std::endl;
68+
std::cout << "Usage: " << argv[0] << " <Input image>" << std::endl;
69+
return -1;
70+
}
6671
//![load]
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6873
//![create_mat]

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