// ////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // By downloading, copying, installing or using the software you agree to this license. // If you do not agree to this license, do not download, install, // copy or use the software. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2013, OpenCV Foundation, all rights reserved. // Third party copyrights are property of their respective owners. // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's in binary form must reproduce the above copyright notice, // this list of conditions and the following disclaimer in the documentation // and/or other materials provided with the distribution. // // * The name of the copyright holders may not be used to endorse or promote products // derived from this software without specific prior written permission. // // This software is provided by the copyright holders and contributors "as is" and // any express or implied warranties, including, but not limited to, the implied // warranties of merchantability and fitness for a particular purpose are disclaimed. // In no event shall the Intel Corporation or contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict liability, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // // // ////////////////////////////////////////////////////////////////////////////////////// // Author: Sajjad Taheri, University of California, Irvine. sajjadt[at]uci[dot]edu // // LICENSE AGREEMENT // Copyright (c) 2015 The Regents of the University of California (Regents) // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are met: // 1. Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // 2. Redistributions in binary form must reproduce the above copyright // notice, this list of conditions and the following disclaimer in the // documentation and/or other materials provided with the distribution. // 3. Neither the name of the University nor the // names of its contributors may be used to endorse or promote products // derived from this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS ''AS IS'' AND ANY // EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED // WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE // DISCLAIMED. IN NO EVENT SHALL CONTRIBUTORS BE LIABLE FOR ANY // DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES // (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; // LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND // ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // if (typeof module !== 'undefined' && module.exports) { // The environment is Node.js var cv = require('./opencv.js'); // eslint-disable-line no-var } QUnit.module('Object Detection', {}); QUnit.test('QR code detect and decode', function (assert) { { const detector = new cv.QRCodeDetector(); let mat = cv.Mat.ones(800, 600, cv.CV_8U); assert.ok(mat); // test detect let points = new cv.Mat(); let qrCodeFound = detector.detect(mat, points); assert.equal(points.rows, 0) assert.equal(points.cols, 0) assert.equal(qrCodeFound, false); // test detectMult qrCodeFound = detector.detectMulti(mat, points); assert.equal(points.rows, 0) assert.equal(points.cols, 0) assert.equal(qrCodeFound, false); // test decode (with random numbers) let decodeTestPoints = cv.matFromArray(1, 4, cv.CV_32FC2, [10, 20, 30, 40, 60, 80, 90, 100]); let qrCodeContent = detector.decode(mat, decodeTestPoints); assert.equal(typeof qrCodeContent, 'string'); assert.equal(qrCodeContent, ''); //test detectAndDecode qrCodeContent = detector.detectAndDecode(mat); assert.equal(typeof qrCodeContent, 'string'); assert.equal(qrCodeContent, ''); // test decodeCurved qrCodeContent = detector.decodeCurved(mat, decodeTestPoints); assert.equal(typeof qrCodeContent, 'string'); assert.equal(qrCodeContent, ''); decodeTestPoints.delete(); points.delete(); mat.delete(); } }); QUnit.test('Aruco-based QR code detect', function (assert) { { let qrcode_params = new cv.QRCodeDetectorAruco_Params(); let detector = new cv.QRCodeDetectorAruco(); let mat = cv.Mat.ones(800, 600, cv.CV_8U); assert.ok(mat); detector.setDetectorParameters(qrcode_params); let points = new cv.Mat(); let qrCodeFound = detector.detect(mat, points); assert.equal(points.rows, 0) assert.equal(points.cols, 0) assert.equal(qrCodeFound, false); qrcode_params.delete(); detector.delete(); points.delete(); mat.delete(); } }); QUnit.test('Bar code detect', function (assert) { { let detector = new cv.barcode_BarcodeDetector(); let mat = cv.Mat.ones(800, 600, cv.CV_8U); assert.ok(mat); let points = new cv.Mat(); let codeFound = detector.detect(mat, points); assert.equal(points.rows, 0) assert.equal(points.cols, 0) assert.equal(codeFound, false); codeContent = detector.detectAndDecode(mat); assert.equal(typeof codeContent, 'string'); assert.equal(codeContent, ''); detector.delete(); points.delete(); mat.delete(); } }); QUnit.test('Aruco detector', function (assert) { { let dictionary = cv.getPredefinedDictionary(cv.DICT_4X4_50); let aruco_image = new cv.Mat(); let detectorParameters = new cv.aruco_DetectorParameters(); let refineParameters = new cv.aruco_RefineParameters(10, 3, true); let detector = new cv.aruco_ArucoDetector(dictionary, detectorParameters,refineParameters); let corners = new cv.MatVector(); let ids = new cv.Mat(); dictionary.generateImageMarker(10, 128, aruco_image); assert.ok(!aruco_image.empty()); detector.detectMarkers(aruco_image, corners, ids); dictionary.delete(); aruco_image.delete(); detectorParameters.delete(); refineParameters.delete(); detector.delete(); corners.delete(); ids.delete(); } }); QUnit.test('Charuco detector', function (assert) { { let dictionary = new cv.getPredefinedDictionary(cv.DICT_4X4_50); let boardIds = new cv.Mat(); let board = new cv.aruco_CharucoBoard(new cv.Size(3, 5), 64, 32, dictionary, boardIds); let charucoParameters = new cv.aruco_CharucoParameters(); let detectorParameters = new cv.aruco_DetectorParameters(); let refineParameters = new cv.aruco_RefineParameters(10, 3, true); let detector = new cv.aruco_CharucoDetector(board, charucoParameters, detectorParameters, refineParameters); let board_image = new cv.Mat(); let corners = new cv.Mat(); let ids = new cv.Mat(); board.generateImage(new cv.Size(300, 500), board_image); assert.ok(!board_image.empty()); detector.detectBoard(board_image, corners, ids); assert.ok(!corners.empty()); assert.ok(!ids.empty()); dictionary.delete(); boardIds.delete(); board.delete(); board_image.delete(); charucoParameters.delete(); detectorParameters.delete(); refineParameters.delete(); detector.delete(); corners.delete(); ids.delete(); } });