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mirror of https://github.com/opencv/opencv.git synced 2026-07-29 23:33:05 +04:00

Add Charuco board support to multiview calibration sample (C++).

This commit is contained in:
lpanaf
2024-02-14 15:33:04 +03:00
committed by Alexander Smorkalov
parent cb3af0a08f
commit 9daad187af
+106 -27
View File
@@ -7,12 +7,14 @@
#include <opencv2/calib3d.hpp>
#include <opencv2/imgcodecs.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/objdetect.hpp>
#include <iostream>
#include <fstream>
// ! [detectPointsAndCalibrate_signature]
static void detectPointsAndCalibrate (cv::Size pattern_size, float pattern_scale, const std::string &pattern_type,
const std::vector<bool> &is_fisheye, const std::vector<std::string> &filenames)
static void detectPointsAndCalibrate (cv::Size pattern_size, float pattern_distance, const std::string &pattern_type,
const std::vector<bool> &is_fisheye, const std::vector<std::string> &filenames,
const cv::String* dict_path=nullptr)
// ! [detectPointsAndCalibrate_signature]
{
// ! [calib_init]
@@ -22,25 +24,25 @@ static void detectPointsAndCalibrate (cv::Size pattern_size, float pattern_scale
std::vector<cv::Size> image_sizes;
std::vector<cv::Mat> Ks, distortions, Ts, Rs;
cv::Mat rvecs0, tvecs0, errors_mat, output_pairs;
if (pattern_type == "checkerboard") {
if (pattern_type == "checkerboard" || pattern_type == "charuco") {
for (int i = 0; i < pattern_size.height; i++) {
for (int j = 0; j < pattern_size.width; j++) {
board[i*pattern_size.width+j] = cv::Point3f((float)j, (float)i, 0.f) * pattern_scale;
board[i*pattern_size.width+j] = cv::Point3f((float)j, (float)i, 0.f) * pattern_distance;
}
}
} else if (pattern_type == "circles") {
for (int i = 0; i < pattern_size.height; i++) {
for (int j = 0; j < pattern_size.width; j++) {
board[i*pattern_size.width+j] = cv::Point3f((float)j, (float)i, 0.f) * pattern_scale;
board[i*pattern_size.width+j] = cv::Point3f((float)j, (float)i, 0.f) * pattern_distance;
}
}
} else if (pattern_type == "acircles") {
for (int i = 0; i < pattern_size.height; i++) {
for (int j = 0; j < pattern_size.width; j++) {
if (i % 2 == 1) {
board[i*pattern_size.width+j] = cv::Point3f((j + .5f)*pattern_scale, (i/2 + .5f) * pattern_scale, 0.f);
board[i*pattern_size.width+j] = cv::Point3f((j + .5f)*pattern_distance, (i/2 + .5f) * pattern_distance, 0.f);
} else{
board[i*pattern_size.width+j] = cv::Point3f(j*pattern_scale, (i/2)*pattern_scale, 0);
board[i*pattern_size.width+j] = cv::Point3f(j*pattern_distance, (i/2)*pattern_distance, 0);
}
}
}
@@ -49,6 +51,33 @@ static void detectPointsAndCalibrate (cv::Size pattern_size, float pattern_scale
CV_Error(cv::Error::StsNotImplemented, "pattern_type is not implemented!");
}
// ! [calib_init]
// ! [charuco_detector]
cv::Ptr<cv::aruco::CharucoDetector> detector;
if (pattern_type == "charuco") {
CV_Assert(dict_path != nullptr);
cv::FileStorage fs(*dict_path, cv::FileStorage::READ);
CV_Assert(fs.isOpened());
int dict_int;
double square_size, marker_size;
fs["dictionary"] >> dict_int;
fs["square_size"] >> square_size;
fs["marker_size"] >> marker_size;
auto dictionary = cv::aruco::getPredefinedDictionary(dict_int);
// For charuco board, the size is defined to be the number of box (not inner corner)
auto charuco_board = cv::aruco::CharucoBoard(
cv::Size(pattern_size.width+1, pattern_size.height+1),
static_cast<float>(square_size), static_cast<float>(marker_size), dictionary);
// It is suggested to use refinement in detecting charuco board
auto detector_params = cv::aruco::DetectorParameters();
auto charuco_params = cv::aruco::CharucoParameters();
charuco_params.tryRefineMarkers = true;
detector_params.cornerRefinementMethod = cv::aruco::CORNER_REFINE_CONTOUR;
detector = cv::makePtr<cv::aruco::CharucoDetector>(charuco_board, charuco_params, detector_params);
}
// ! [charuco_detector]
// ! [detect_pattern]
int num_frames = -1;
for (const auto &filename : filenames) {
@@ -58,9 +87,10 @@ static void detectPointsAndCalibrate (cv::Size pattern_size, float pattern_scale
std::vector<cv::Mat> image_points_cameras;
bool save_img_size = true;
while (std::getline(file, img_file)) {
if (img_file.empty())
break;
std::cout << img_file << "\n";
if (img_file.empty()){
image_points_cameras.emplace_back(cv::Mat());
continue;
}
cv::Mat img = cv::imread(img_file), corners;
if (save_img_size) {
image_sizes.emplace_back(cv::Size(img.cols, img.rows));
@@ -80,6 +110,29 @@ static void detectPointsAndCalibrate (cv::Size pattern_size, float pattern_scale
{
success = cv::findCirclesGrid(img, pattern_size, corners, cv::CALIB_CB_ASYMMETRIC_GRID);
}
else if (pattern_type == "charuco")
{
std::vector<int> ids; cv::Mat corners_sub;
detector->detectBoard(img, corners_sub, ids);
corners.create(static_cast<int>(board.size()), 2, CV_32F);
if (ids.size() < 4)
success = false;
else {
success = true;
int head = 0;
for (int i = 0; i < static_cast<int>(board.size()); i++) {
if (head < static_cast<int>(ids.size()) && ids[head] == i) {
corners.at<float>(i, 0) = corners_sub.at<float>(head, 0);
corners.at<float>(i, 1) = corners_sub.at<float>(head, 1);
head++;
} else {
// points outside of frame border are dropped by calibrateMultiview
corners.at<float>(i, 0) = -1.;
corners.at<float>(i, 1) = -1.;
}
}
}
}
cv::Mat corners2;
corners.convertTo(corners2, CV_32FC2);
@@ -116,22 +169,22 @@ static void detectPointsAndCalibrate (cv::Size pattern_size, float pattern_scale
std::cout << "average RMSE over detection mask " << rmse << "\n";
for (int c = 0; c < (int)Rs.size(); c++) {
std::cout << "camera " << c << '\n';
std::cout << Rs[c] << " rotation\n";
std::cout << Ts[c] << " translation\n";
std::cout << Ks[c] << " intrinsic matrix\n";
std::cout << distortions[c] << " distortion\n";
std::cout << "rotation\n" << Rs[c] << "\n";
std::cout << "translation\n" << Ts[c] << "\n";
std::cout << "intrinsic matrix\n" << Ks[c] << "\n";
std::cout << "distortion\n" << distortions[c] << "\n";
}
}
int main (int argc, char **argv) {
cv::String keys =
"{help h usage ? || print help }"
"{pattern_width || pattern grid width}"
"{pattern_height || pattern grid height}"
"{pattern_scale || pattern scale}"
"{pattern_type | checkerboard | pattern type, e.g., checkerboard or acircles}"
"{pattern_size || (inner) grid width, (inner) grid height }"
"{pattern_distance || pattern scale}"
"{pattern_type | checkerboard | pattern type, e.g., checkerboard or acircles or charuco (recommended)}"
"{is_fisheye || cameras type fisheye (1), pinhole(0), separated by comma (no space)}"
"{files_with_images || files containing path to image names separated by comma (no space)}";
"{filenames || files containing path to image names separated by comma (no space)}"
"{board_dict_path || file containing dictionary information (required field: dictionary, square_size, marker_size). Needed if pattern_type is charuco.}";
cv::CommandLineParser parser(argc, argv, keys);
if (parser.has("help")) {
@@ -139,13 +192,33 @@ int main (int argc, char **argv) {
return 0;
}
CV_Assert(parser.has("pattern_width") && parser.has("pattern_height") && parser.has("pattern_type") &&
parser.has("is_fisheye") && parser.has("files_with_images"));
CV_Assert(parser.has("pattern_size") && parser.has("pattern_type") &&
parser.has("is_fisheye") && parser.has("filenames"));
CV_Assert(parser.get<cv::String>("pattern_type") == "checkerboard" ||
parser.get<cv::String>("pattern_type") == "circles" ||
parser.get<cv::String>("pattern_type") == "acircles");
parser.get<cv::String>("pattern_type") == "acircles" ||
parser.get<cv::String>("pattern_type") == "charuco"
);
if (parser.get<cv::String>("pattern_type") == "charuco")
CV_Assert(parser.has("board_dict_path"));
cv::Size pattern_size;
const cv::String pattern_size_str = parser.get<cv::String>("pattern_size");
std::string temp_str;
int pattern_size_count = 0;
for (char i : pattern_size_str) {
if (i == ',') {
if (pattern_size_count == 0)
pattern_size.width = std::stoi(temp_str);
pattern_size_count++;
temp_str = "";
} else {
temp_str += i;
}
}
CV_Assert(pattern_size_count == 1);
pattern_size.height = std::stoi(temp_str);
const cv::Size pattern_size (parser.get<int>("pattern_width"), parser.get<int>("pattern_height"));
std::vector<bool> is_fisheye;
const cv::String is_fisheye_str = parser.get<cv::String>("is_fisheye");
for (char i : is_fisheye_str) {
@@ -155,10 +228,10 @@ int main (int argc, char **argv) {
is_fisheye.push_back(true);
}
}
const cv::String files_with_images_str = parser.get<cv::String>("files_with_images");
const cv::String filenames_str = parser.get<cv::String>("filenames");
std::vector<std::string> filenames;
std::string temp_str;
for (char i : files_with_images_str) {
temp_str = "";
for (char i : filenames_str) {
if (i == ',') {
filenames.emplace_back(temp_str);
temp_str = "";
@@ -168,6 +241,12 @@ int main (int argc, char **argv) {
}
filenames.emplace_back(temp_str);
CV_CheckEQ(filenames.size(), is_fisheye.size(), "filenames size must be equal to number of cameras!");
detectPointsAndCalibrate (pattern_size, parser.get<float>("pattern_scale"), parser.get<cv::String>("pattern_type"), is_fisheye, filenames);
if (parser.has("board_dict_path")) {
cv::String board_dict_path = parser.get<cv::String>("board_dict_path");
detectPointsAndCalibrate (pattern_size, parser.get<float>("pattern_distance"), parser.get<cv::String>("pattern_type"), is_fisheye, filenames, &board_dict_path);
} else {
detectPointsAndCalibrate (pattern_size, parser.get<float>("pattern_distance"), parser.get<cv::String>("pattern_type"), is_fisheye, filenames);
}
return 0;
}