{"action":"created","comment":{"url":"https://api.github.com/repos/opencv/opencv/pulls/comments/207742118","pull_request_review_id":143416649,"id":207742118,"node_id":"MDI0OlB1bGxSZXF1ZXN0UmV2aWV3Q29tbWVudDIwNzc0MjExOA==","diff_hunk":"@@ -0,0 +1,788 @@\n+/*\n+  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.\n+\n+  By downloading, copying, installing or using the software you agree to this license.\n+  If you do not agree to this license, do not download, install,\n+  copy or use the software.\n+\n+\n+                          BSD 3-Clause License\n+\n+ Copyright (C) 2014, Olexa Bilaniuk, Hamid Bazargani & Robert Laganiere, all rights reserved.\n+\n+ Redistribution and use in source and binary forms, with or without modification,\n+ are permitted provided that the following conditions are met:\n+\n+   * Redistribution's of source code must retain the above copyright notice,\n+     this list of conditions and the following disclaimer.\n+\n+   * Redistribution's in binary form must reproduce the above copyright notice,\n+     this list of conditions and the following disclaimer in the documentation\n+     and/or other materials provided with the distribution.\n+\n+   * The name of the copyright holders may not be used to endorse or promote products\n+     derived from this software without specific prior written permission.\n+\n+ This software is provided by the copyright holders and contributors \"as is\" and\n+ any express or implied warranties, including, but not limited to, the implied\n+ warranties of merchantability and fitness for a particular purpose are disclaimed.\n+ In no event shall the Intel Corporation or contributors be liable for any direct,\n+ indirect, incidental, special, exemplary, or consequential damages\n+ (including, but not limited to, procurement of substitute goods or services;\n+ loss of use, data, or profits; or business interruption) however caused\n+ and on any theory of liability, whether in contract, strict liability,\n+ or tort (including negligence or otherwise) arising in any way out of\n+ the use of this software, even if advised of the possibility of such damage.\n+*/\n+\n+/**\n+ * Bilaniuk, Olexa, Hamid Bazargani, and Robert Laganiere. \"Fast Target\n+ * Recognition on Mobile Devices: Revisiting Gaussian Elimination for the\n+ * Estimation of Planar Homographies.\" In Computer Vision and Pattern\n+ * Recognition Workshops (CVPRW), 2014 IEEE Conference on, pp. 119-125.\n+ * IEEE, 2014.\n+ */\n+\n+#ifndef CHESSBOARD_HPP_\n+#define CHESSBOARD_HPP_\n+\n+#include \"opencv2/core.hpp\"\n+#include \"opencv2/features2d.hpp\"\n+#include <vector>\n+#include <set>\n+#include <map>\n+\n+namespace cv\n+{","path":"modules/calib3d/src/chessboard.hpp","position":56,"original_position":56,"commit_id":"92e923908dc1c010dc3868e6ef5b6ea56f04a8e3","original_commit_id":"92e923908dc1c010dc3868e6ef5b6ea56f04a8e3","user":{"login":"alalek","id":4981219,"node_id":"MDQ6VXNlcjQ5ODEyMTk=","avatar_url":"https://avatars0.githubusercontent.com/u/4981219?v=4","gravatar_id":"","url":"https://api.github.com/users/alalek","html_url":"https://github.com/alalek","followers_url":"https://api.github.com/users/alalek/followers","following_url":"https://api.github.com/users/alalek/following{/other_user}","gists_url":"https://api.github.com/users/alalek/gists{/gist_id}","starred_url":"https://api.github.com/users/alalek/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/alalek/subscriptions","organizations_url":"https://api.github.com/users/alalek/orgs","repos_url":"https://api.github.com/users/alalek/repos","events_url":"https://api.github.com/users/alalek/events{/privacy}","received_events_url":"https://api.github.com/users/alalek/received_events","type":"User","site_admin":false},"body":"Keep public API as simple as possible.\r\nAll implementation details should be moved into \"src\" folder or separate \".private.hpp\" headers under \"cv::details\" namespace or similar.","created_at":"2018-08-05T16:44:26Z","updated_at":"2018-08-05T16:46:21Z","html_url":"https://github.com/opencv/opencv/pull/12147#discussion_r207742118","pull_request_url":"https://api.github.com/repos/opencv/opencv/pulls/12147","author_association":"CONTRIBUTOR","_links":{"self":{"href":"https://api.github.com/repos/opencv/opencv/pulls/comments/207742118"},"html":{"href":"https://github.com/opencv/opencv/pull/12147#discussion_r207742118"},"pull_request":{"href":"https://api.github.com/repos/opencv/opencv/pulls/12147"}}},"pull_request":{"url":"https://api.github.com/repos/opencv/opencv/pulls/12147","id":206213352,"node_id":"MDExOlB1bGxSZXF1ZXN0MjA2MjEzMzUy","html_url":"https://github.com/opencv/opencv/pull/12147","diff_url":"https://github.com/opencv/opencv/pull/12147.diff","patch_url":"https://github.com/opencv/opencv/pull/12147.patch","issue_url":"https://api.github.com/repos/opencv/opencv/issues/12147","number":12147,"state":"open","locked":false,"title":"add new chessboard detector","user":{"login":"D-Alex","id":2762297,"node_id":"MDQ6VXNlcjI3NjIyOTc=","avatar_url":"https://avatars1.githubusercontent.com/u/2762297?v=4","gravatar_id":"","url":"https://api.github.com/users/D-Alex","html_url":"https://github.com/D-Alex","followers_url":"https://api.github.com/users/D-Alex/followers","following_url":"https://api.github.com/users/D-Alex/following{/other_user}","gists_url":"https://api.github.com/users/D-Alex/gists{/gist_id}","starred_url":"https://api.github.com/users/D-Alex/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/D-Alex/subscriptions","organizations_url":"https://api.github.com/users/D-Alex/orgs","repos_url":"https://api.github.com/users/D-Alex/repos","events_url":"https://api.github.com/users/D-Alex/events{/privacy}","received_events_url":"https://api.github.com/users/D-Alex/received_events","type":"User","site_admin":false},"body":"The chessboar detector is based on the paper.\r\nAccurate Detection and Localization of Checkerboard Corners for\r\nCalibration Alexander Duda, Udo Frese\r\nBritish Machine Vision Conference, o.A., 2018.\r\n\r\nIt utilizes point symmetry of checkerboard corners in combination with a\r\nlocalized Radon transform approximated by box filters to achieve high\r\nperformance even on large images. Here, tests have shown that the\r\nability to localize checkerboard corners is close to the theoretical\r\nlimit of 1/100 of a pixel while being considerably less sensitive\r\nto image noise than standard methods.\r\n\r\n\r\n### This pullrequest changes\r\n\r\n<!-- Please describe what your pullrequest is changing -->\r\nIt adds a new method cv::findChessboardCorners2 which is analog to findChessboardCorners but usually outperforms it in respect to detection rate, accuracy and speed.\r\n\r\n```\r\nforce_builders=linux,docs\r\n```","created_at":"2018-08-04T22:55:20Z","updated_at":"2018-08-05T16:46:21Z","closed_at":null,"merged_at":null,"merge_commit_sha":"33abb22a5c54c963bd5581e3a6683fb438244a83","assignee":null,"assignees":[],"requested_reviewers":[],"requested_teams":[],"labels":[{"id":241025225,"node_id":"MDU6TGFiZWwyNDEwMjUyMjU=","url":"https://api.github.com/repos/opencv/opencv/labels/category:%20calib3d","name":"category: 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