Merge pull request #1153 from atinfinity:fixed_aruco_tutorial

modules/aruco/tutorials/aruco_board_detection/aruco_board_detection.markdown

@@ -30,7 +30,7 @@ The aruco module allows the use of Boards. The main class is the ```cv::aruco::B
     class  Board {
     public:
         std::vector<std::vector<cv::Point3f> > objPoints;
-        cv::aruco::Dictionary dictionary;
+        cv::Ptr<cv::aruco::Dictionary> dictionary;
         std::vector<int> ids;
     };
 ```
@@ -57,10 +57,10 @@ The aruco module provides a specific function, ```estimatePoseBoard()```, to per
     cv::Mat cameraMatrix, distCoeffs;
     readCameraParameters(cameraMatrix, distCoeffs);
     // assume we have a function to create the board object
-    cv::aruco::Board board = createBoard();
+    cv::Ptr<cv::aruco::Board> board = cv::aruco::Board::create();
     ...
-    vector< int > markerIds;
-    vector< vector<Point2f> > markerCorners;
+    std::vector<int> markerIds;
+    std::vector<std::vector<cv::Point2f>> markerCorners;
     cv::aruco::detectMarkers(inputImage, board.dictionary, markerCorners, markerIds);
     // if at least one marker detected
     if(markerIds.size() > 0) {
@@ -137,9 +137,9 @@ After creating a Grid Board, we probably want to print it and use it. A function
 of a ```GridBoard``` is provided in ```cv::aruco::GridBoard::draw()```. For example:
 
 ``` c++
-    cv::aruco::GridBoard board = cv::aruco::GridBoard::create(5, 7, 0.04, 0.01, dictionary);
+    cv::Ptr<cv::aruco::GridBoard> board = cv::aruco::GridBoard::create(5, 7, 0.04, 0.01, dictionary);
     cv::Mat boardImage;
-    board.draw( cv::Size(600, 500), boardImage, 10, 1 );
+    board->draw( cv::Size(600, 500), boardImage, 10, 1 );
 ```
 
 - The first parameter is the size of the output image in pixels. In this case 600x500 pixels. If this is not proportional
@@ -170,8 +170,8 @@ Finally, a full example of board detection:
     // camera parameters are read from somewhere
     readCameraParameters(cameraMatrix, distCoeffs);
 
-    cv::aruco::Dictionary dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
-    cv::aruco::GridBoard board = cv::aruco::GridBoard::create(5, 7, 0.04, 0.01, dictionary);
+    cv::Ptr<cv::aruco::Dictionary> dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
+    cv::Ptr<cv::aruco::GridBoard> board = cv::aruco::GridBoard::create(5, 7, 0.04, 0.01, dictionary);
 
     while (inputVideo.grab()) {
         cv::Mat image, imageCopy;
@@ -256,10 +256,10 @@ internal bits are not analyzed at all and only the corner distances are evaluate
 This is an example of using the  ```refineDetectedMarkers()``` function:
 
 ``` c++
-    cv::aruco::Dictionary dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
-    cv::aruco::GridBoard board = cv::aruco::GridBoard::create(5, 7, 0.04, 0.01, dictionary);
-    vector< int > markerIds;
-    vector< vector<Point2f> > markerCorners, rejectedCandidates;
+    cv::Ptr<cv::aruco::Dictionary> dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
+    cv::Ptr<cv::aruco::GridBoard> board = cv::aruco::GridBoard::create(5, 7, 0.04, 0.01, dictionary);
+    std::vector<int> markerIds;
+    std::vector<std::vector<cv::Point2f>> markerCorners, rejectedCandidates;
     cv::aruco::detectMarkers(inputImage, dictionary, markerCorners, markerIds, cv::aruco::DetectorParameters(), rejectedCandidates);
 
     cv::aruco::refineDetectedMarkersinputImage, board, markerCorners, markerIds, rejectedCandidates);

modules/aruco/tutorials/aruco_calibration/aruco_calibration.markdown

@@ -33,7 +33,7 @@ visible in all the viewpoints.
 The function to calibrate is ```calibrateCameraCharuco()```. Example:
 
 ``` c++
-    aruco::CharucoBoard board = ... // create charuco board
+    cv::Ptr<aruco::CharucoBoard> board = ... // create charuco board
     cv::Size imgSize = ... // camera image size
 
     std::vector<std::vector<cv::Point2f>> allCharucoCorners;
@@ -44,7 +44,7 @@ The function to calibrate is ```calibrateCameraCharuco()```. Example:
 
     // After capturing in several viewpoints, start calibration
     cv::Mat cameraMatrix, distCoeffs;
-    std::vector< Mat > rvecs, tvecs;
+    std::vector<cv::Mat> rvecs, tvecs;
     int calibrationFlags = ... // Set calibration flags (same than in calibrateCamera() function)
 
     double repError = cv::aruco::calibrateCameraCharuco(allCharucoCorners, allCharucoIds, board, imgSize, cameraMatrix, distCoeffs, rvecs, tvecs, calibrationFlags);
@@ -81,7 +81,7 @@ requires the detections of an ArUco board from different viewpoints.
 Example of ```calibrateCameraAruco()``` use:
 
 ``` c++
-    aruco::Board board = ... // create aruco board
+    cv::Ptr<aruco::Board> board = ... // create aruco board
     cv::Size imgSize = ... // camera image size
 
     std::vector<std::vector<cv::Point2f>> allCornersConcatenated;
@@ -93,7 +93,7 @@ Example of ```calibrateCameraAruco()``` use:
 
     // After capturing in several viewpoints, start calibration
     cv::Mat cameraMatrix, distCoeffs;
-    std::vector< Mat > rvecs, tvecs;
+    std::vector<cv::Mat> rvecs, tvecs;
     int calibrationFlags = ... // Set calibration flags (same than in calibrateCamera() function)
 
     double repError = cv::aruco::calibrateCameraAruco(allCornersConcatenated, allIdsConcatenated, markerCounterPerFrame, board, imgSize, cameraMatrix, distCoeffs, rvecs, tvecs, calibrationFlags);

modules/aruco/tutorials/aruco_detection/aruco_detection.markdown

@@ -20,7 +20,7 @@ a popular library for detection of square fiducial markers developed by Rafael M
 
 The aruco functionalities are included in:
 ``` c++
-    \#include <opencv2/aruco.hpp>
+    #include <opencv2/aruco.hpp>
 ```
 
 
@@ -71,7 +71,7 @@ For example, lets analyze the following call:
 
 ``` c++
     cv::Mat markerImage;
-    cv::aruco::Dictionary dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
+    cv::Ptr<cv::aruco::Dictionary> dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
     cv::aruco::drawMarker(dictionary, 23, 200, markerImage, 1);
 ```
 
@@ -156,10 +156,10 @@ An example of marker detection:
 ``` c++
     cv::Mat inputImage;
     ...
-    vector< int > markerIds;
-    vector< vector<Point2f> > markerCorners, rejectedCandidates;
-    cv::aruco::DetectorParameters parameters;
-    cv::aruco::Dictionary dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
+    std::vector<int> markerIds;
+    std::vector<std::vector<cv::Point2f>> markerCorners, rejectedCandidates;
+    cv::Ptr<cv::aruco::DetectorParameters> parameters;
+    cv::Ptr<cv::aruco::Dictionary> dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
     cv::aruco::detectMarkers(inputImage, dictionary, markerCorners, markerIds, parameters, rejectedCandidates);
 ```
 
@@ -204,7 +204,7 @@ camera:
 ``` c++
     cv::VideoCapture inputVideo;
     inputVideo.open(0);
-    cv::aruco::Dictionary dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
+    cv::Ptr<cv::aruco::Dictionary> dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
     while (inputVideo.grab()) {
         cv::Mat image, imageCopy;
         inputVideo.retrieve(image);
@@ -263,9 +263,9 @@ information).
 The aruco module provides a function to estimate the poses of all the detected markers:
 
 ``` c++
-    Mat cameraMatrix, distCoeffs;
+    cv::Mat cameraMatrix, distCoeffs;
     ...
-    vector< Vec3d > rvecs, tvecs;
+    std::vector<cv::Vec3d> rvecs, tvecs;
     cv::aruco::estimatePoseSingleMarkers(corners, 0.05, cameraMatrix, distCoeffs, rvecs, tvecs);
 ```
 
@@ -303,7 +303,7 @@ A basic full example for pose estimation from single markers:
     // camera parameters are read from somewhere
     readCameraParameters(cameraMatrix, distCoeffs);
 
-    cv::aruco::Dictionary dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
+    cv::Ptr<cv::aruco::Dictionary> dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
 
     while (inputVideo.grab()) {
         cv::Mat image, imageCopy;
@@ -318,7 +318,7 @@ A basic full example for pose estimation from single markers:
         if (ids.size() > 0) {
             cv::aruco::drawDetectedMarkers(imageCopy, corners, ids);
 
-            vector< Mat > rvecs, tvecs;
+            std::vector<cv::Mat> rvecs, tvecs;
             cv::aruco::estimatePoseSingleMarkers(corners, 0.05, cameraMatrix, distCoeffs, rvecs, tvecs);
             // draw axis for each marker
             for(int i=0; i<ids.size(); i++)
@@ -374,7 +374,7 @@ This is the easiest way to select a dictionary. The aruco module includes a set
  of a variety of marker sizes and number of markers. For instance:
 
 ``` c++
-    cv::aruco::Dictionary dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
+    cv::Ptr<cv::aruco::Dictionary> dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
 ```
 
 DICT_6X6_250 is an example of predefined dictionary of markers with 6x6 bits and a total of 250
@@ -390,7 +390,7 @@ The dictionary can be generated automatically to adjust to the desired number of
 the inter-marker distance is optimized:
 
 ``` c++
-    cv::aruco::Dictionary dictionary = cv::aruco::generateCustomDictionary(36, 5);
+    cv::Ptr<cv::aruco::Dictionary> dictionary = cv::aruco::generateCustomDictionary(36, 5);
 ```
 
 This will generate a customized dictionary composed by 36 markers of 5x5 bits. The process can take several
@@ -432,7 +432,7 @@ Fortunately, a marker can be easily transformed to this form using the static me
 For example:
 
 ``` c++
-    Dictionary dictionary;
+    cv::aruco::Dictionary dictionary;
     // markers of 6x6 bits
     dictionary.markerSize = 6;
     // maximum number of bit corrections
@@ -440,10 +440,11 @@ For example:
 
     // lets create a dictionary of 100 markers
     for(int i=0; i<100; i++)
+    {
         // assume generateMarkerBits() generate a new marker in binary format, so that
         // markerBits is a 6x6 matrix of CV_8UC1 type, only containing 0s and 1s
         cv::Mat markerBits = generateMarkerBits();
-        cv::Mat markerCompressed = getByteListFromBits(markerBits);
+        cv::Mat markerCompressed = cv::aruco::Dictionary::getByteListFromBits(markerBits);
         // add the marker as a new row
         dictionary.bytesList.push_back(markerCompressed);
     }

modules/aruco/tutorials/charuco_detection/charuco_detection.markdown

@@ -29,7 +29,7 @@ The aruco module provides the ```cv::aruco::CharucoBoard``` class that represent
 This class, as the rest of ChArUco functionalities, are defined in:
 
 ``` c++
-    \#include <opencv2/aruco/charuco.hpp>
+    #include <opencv2/aruco/charuco.hpp>
 ```
 
 To define a ```CharucoBoard```, it is necesary:
@@ -60,9 +60,9 @@ Once we have our ```CharucoBoard``` object, we can create an image to print it.
 ```CharucoBoard::draw()``` method:
 
 ``` c++
-    cv::aruco::CharucoBoard board = cv::aruco::CharucoBoard::create(5, 7, 0.04, 0.02, dictionary);
+    cv::Ptr<cv::aruco::CharucoBoard> board = cv::aruco::CharucoBoard::create(5, 7, 0.04, 0.02, dictionary);
     cv::Mat boardImage;
-    board.draw( cv::Size(600, 500), boardImage, 10, 1 );
+    board->draw( cv::Size(600, 500), boardImage, 10, 1 );
 ```
 
 - The first parameter is the size of the output image in pixels. In this case 600x500 pixels. If this is not proportional
@@ -94,8 +94,8 @@ in the board.
 
 So, a detected ChArUco board consists in:
 
-- ```vector<Point2f> charucoCorners``` : list of image positions of the detected corners.
-- ```vector <int> charucoIds``` : ids for each of the detected corners in ```charucoCorners```.
+- ```std::vector<cv::Point2f> charucoCorners``` : list of image positions of the detected corners.
+- ```std::vector<int> charucoIds``` : ids for each of the detected corners in ```charucoCorners```.
 
 The detection of the ChArUco corners is based on the previous detected markers. So that, first markers are detected, and then
 ChArUco corners are interpolated from markers.
@@ -107,11 +107,11 @@ The function that detect the ChArUco corners is ```cv::aruco::interpolateCorners
     cv::Mat cameraMatrix, distCoeffs;
     // camera parameters are read from somewhere
     readCameraParameters(cameraMatrix, distCoeffs);
-    cv::aruco::Dictionary dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
-    cv::aruco::CharucoBoard board = cv::aruco::CharucoBoard::create(5, 7, 0.04, 0.02, dictionary);
+    cv::Ptr<cv::aruco::Dictionary> dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
+    cv::Ptr<cv::aruco::CharucoBoard> board = cv::aruco::CharucoBoard::create(5, 7, 0.04, 0.02, dictionary);
     ...
-    vector< int > markerIds;
-    vector< vector<Point2f> > markerCorners;
+    std::vector<int> markerIds;
+    std::vector<std::vector<cv::Point2f>> markerCorners;
     cv::aruco::detectMarkers(inputImage, board.dictionary, markerCorners, markerIds);
 
     // if at least one marker detected
@@ -136,13 +136,13 @@ are optional. A similar example without these parameters would be:
 
 ``` c++
     cv::Mat inputImage;
-    cv::aruco::Dictionary dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
-    cv::aruco::CharucoBoard board = cv::aruco::CharucoBoard::create(5, 7, 0.04, 0.02, dictionary);
+    cv::Ptr<cv::aruco::Dictionary> dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
+    cv::Ptr<cv::aruco::CharucoBoard> board = cv::aruco::CharucoBoard::create(5, 7, 0.04, 0.02, dictionary);
     ...
-    vector< int > markerIds;
-    vector< vector<Point2f> > markerCorners;
-    DetectorParameters params;
-    params.doCornerRefinement = false;
+    std::vector<int> markerIds;
+    std::vector<std::vector<cv::Point2f>> markerCorners;
+    cv::Ptr<cv::aruco::DetectorParameters> params;
+    params->doCornerRefinement = false;
     cv::aruco::detectMarkers(inputImage, board.dictionary, markerCorners, markerIds, params);
 
     // if at least one marker detected
@@ -203,11 +203,11 @@ Finally, this is a full example of ChArUco detection (without using calibration
     cv::VideoCapture inputVideo;
     inputVideo.open(0);
 
-    cv::aruco::Dictionary dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
-    cv::aruco::CharucoBoard board = cv::aruco::CharucoBoard::create(5, 7, 0.04, 0.02, dictionary);
+    cv::Ptr<cv::aruco::Dictionary> dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
+    cv::Ptr<cv::aruco::CharucoBoard> board = cv::aruco::CharucoBoard::create(5, 7, 0.04, 0.02, dictionary);
 
-    DetectorParameters params;
-    params.doCornerRefinement = false;
+    cv::Ptr<cv::aruco::DetectorParameters> params;
+    params->doCornerRefinement = false;
 
     while (inputVideo.grab()) {
         cv::Mat image, imageCopy;
@@ -286,8 +286,8 @@ A full example of ChArUco detection with pose estimation:
     // camera parameters are read from somewhere
     readCameraParameters(cameraMatrix, distCoeffs);
 
-    cv::aruco::Dictionary dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
-    cv::aruco::CharucoBoard board = cv::aruco::CharucoBoard::create(5, 7, 0.04, 0.02, dictionary);
+    cv::Ptr<cv::aruco::Dictionary> dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
+    cv::Ptr<cv::aruco::CharucoBoard> board = cv::aruco::CharucoBoard::create(5, 7, 0.04, 0.02, dictionary);
 
     while (inputVideo.grab()) {
         cv::Mat image, imageCopy;

modules/aruco/tutorials/charuco_diamond_detection/charuco_diamond_detection.markdown

@@ -46,7 +46,7 @@ For instance:
 
 ``` c++
     cv::Mat diamondImage;
-    cv::aruco::Dictionary dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
+    cv::Ptr<cv::aruco::Dictionary> dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
     cv::aruco::drawCharucoDiamond(dictionary, cv::Vec4i(45,68,28,74), 200, 120, markerImage);
 ```