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modules/js/test/test_objdetect.js

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+// //////////////////////////////////////////////////////////////////////////////////////
+//
+//  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
+    cv.FS_createLazyFile('/', 'haarcascade_frontalface_default.xml', // eslint-disable-line new-cap
+                         'haarcascade_frontalface_default.xml', true, false);
+}
+
+QUnit.module('Object Detection', {});
+QUnit.test('Cascade classification', function(assert) {
+    // Group rectangle
+    {
+        let rectList = new cv.RectVector();
+        let weights = new cv.IntVector();
+        let groupThreshold = 1;
+        const eps = 0.2;
+
+        let rect1 = new cv.Rect(1, 2, 3, 4);
+        let rect2 = new cv.Rect(1, 4, 2, 3);
+
+        rectList.push_back(rect1);
+        rectList.push_back(rect2);
+
+        cv.groupRectangles(rectList, weights, groupThreshold, eps);
+
+
+        rectList.delete();
+        weights.delete();
+    }
+
+    // CascadeClassifier
+    {
+        let classifier = new cv.CascadeClassifier();
+        const modelPath = '/haarcascade_frontalface_default.xml';
+
+        assert.equal(classifier.empty(), true);
+
+
+        classifier.load(modelPath);
+        assert.equal(classifier.empty(), false);
+
+        let image = cv.Mat.eye({height: 10, width: 10}, cv.CV_8UC3);
+        let objects = new cv.RectVector();
+        let numDetections = new cv.IntVector();
+        const scaleFactor = 1.1;
+        const minNeighbors = 3;
+        const flags = 0;
+        const minSize = {height: 0, width: 0};
+        const maxSize = {height: 10, width: 10};
+
+        classifier.detectMultiScale2(image, objects, numDetections, scaleFactor,
+                                     minNeighbors, flags, minSize, maxSize);
+
+        // test default parameters
+        classifier.detectMultiScale2(image, objects, numDetections, scaleFactor,
+                                     minNeighbors, flags, minSize);
+        classifier.detectMultiScale2(image, objects, numDetections, scaleFactor,
+                                     minNeighbors, flags);
+        classifier.detectMultiScale2(image, objects, numDetections, scaleFactor,
+                                     minNeighbors);
+        classifier.detectMultiScale2(image, objects, numDetections, scaleFactor);
+
+        classifier.delete();
+        objects.delete();
+        numDetections.delete();
+    }
+
+    // HOGDescriptor
+    {
+        let hog = new cv.HOGDescriptor();
+        let mat = new cv.Mat({height: 10, width: 10}, cv.CV_8UC1);
+        let descriptors = new cv.FloatVector();
+        let locations = new cv.PointVector();
+
+
+        assert.equal(hog.winSize.height, 128);
+        assert.equal(hog.winSize.width, 64);
+        assert.equal(hog.nbins, 9);
+        assert.equal(hog.derivAperture, 1);
+        assert.equal(hog.winSigma, -1);
+        assert.equal(hog.histogramNormType, 0);
+        assert.equal(hog.nlevels, 64);
+
+        hog.nlevels = 32;
+        assert.equal(hog.nlevels, 32);
+
+        hog.delete();
+        mat.delete();
+        descriptors.delete();
+        locations.delete();
+    }
+});