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andrew
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xwordjs
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Initial revision.

Andrew Klopper 6 年 前
コミット
4de086ce4f
共有8 個のファイルを変更した、1202 個の追加 と 0 個の削除を含む
分割表示 差分情報を表示
  1. 253 0
      index.html
  2. 4 0
      js/vendor/interact/interact.min.js
  3. 2 0
      js/vendor/load-image/load-image.all.min.js
  4. 45 0
      js/vendor/opencv/opencv.js
  5. 164 0
      js/vendor/opencv/utils.js
  6. 472 0
      js/vendor/panzoom/panzoom.js
  7. 7 0
      js/vendor/plotly/plotly-latest.min.js
  8. 255 0
      js/xword.js

+ 253 - 0
index.html
ファイルの表示 

@@ -0,0 +1,253 @@
1 
+<!DOCTYPE html>
2 
+<html>
3 
+    <head>
4 
+        <meta charset="UTF-8">
5 
+        <script src="js/vendor/interact/interact.min.js"></script>
6 
+        <script src="js/vendor/opencv/opencv.js"></script>
7 
+        <script src="js/vendor/load-image/load-image.all.min.js"></script>
8 
+        <script src="js/vendor/plotly/plotly-latest.min.js"></script>
9 
+        <script src="js/vendor/panzoom/panzoom.js"></script>
10 
+        <script src="js/xword.js"></script>
11 
+        <style>
12 
+            canvas {
13 
+                width: 400px;
14 
+            }
15 
+            #sourceImageContainer {
16 
+                width: 400px;
17 
+                overflow: hidden;
18 
+            }
19 
+            #sourceImage {
20 
+                position: relative;
21 
+                width: min-content;
22 
+            }
23 
+            #sourceImage canvas {
24 
+                width: auto;
25 
+            }
26 
+            #sourceImage .overlay {
27 
+                position: absolute;
28 
+                left: 0;
29 
+                top: 0;
30 
+            }
31 
+            .handle {
32 
+                position: absolute;
33 
+                box-sizing: border-box;
34 
+                width: 301px;
35 
+                height: 301px;
36 
+                border-radius: 50%;
37 
+                border: 6px solid red;
38 
+                transform: translate(-50%, -50%);
39 
+            }
40 
+            #graph {
41 
+                width: 1000px;
42 
+                height: 800px;
43 
+            }
44 
+        </style>
45 
+    </head>
46 
+    <body>
47 
+        <div>
48 
+            <input type="file" id="fileInput">
49 
+        </div>
50 
+        <div id="sourceImageContainer">
51 
+            <div id="sourceImage"></div>
52 
+        </div>
53 
+        <button id="recalculateButton">Recalculate</button>
54 
+        <div>
55 
+            <canvas id="output"></canvas>
56 
+        </div>
57 
+        <div id="graph"></div>
58 
+        <script>
59 
+            'use strict';
60 
+
61 
+            let sourceImage = document.getElementById("sourceImage");
62 
+            let sourceImageParent = sourceImage.parentElement;
63 
+            let fileInput = document.getElementById("fileInput");
64 
+
65 
+            let isSquare = true;
66 
+
67 
+            let gaussianBlurSize = 11;
68 
+            let adaptiveThresholdBlockSize = 11;
69 
+            let adaptiveThresholdMeanAdjustment = 2;
70 
+            let numDilations = 1;
71 
+
72 
+            let contourErosionKernelSize = 5;
73 
+            let contourErosionIterations = 5;
74 
+
75 
+            let lineDetectorElementSize = 51;
76 
+
77 
+            let samplingBlockSizeRatio = 0.25;
78 
+            let samplingThresholdQuantile = 0.3;
79 
+            let samplingThreshold = null;
80 
+
81 
+            let gridLineThickness = 4;
82 
+            let gridSquareInternalSize = 64;
83 
+            let gridMarginSize = 20;
84 
+
85 
+            let img = null;
86 
+            let zoomCallback = null;
87 
+
88 
+            let zoomer = Panzoom(sourceImage, {
89 
+                excludeClass: 'handle'
90 
+            });
91 
+            sourceImage.addEventListener('panzoomzoom', function(event) {
92 
+                if (zoomCallback != null) zoomCallback(event);
93 
+            });
94 
+
95 
+            sourceImageParent.addEventListener('wheel', function(event) {
96 
+                if (! event.shiftKey) return;
97 
+                zoomer.zoomWithWheel(event, {disablePan: true});
98 
+            });
99 
+
100 
+            fileInput.onchange = function(e) {
101 
+                if (e.target.files.length > 0) {
102 
+                    loadImage(
103 
+                        e.target.files[0],
104 
+                        function(canvas) {
105 
+                            let imageWidth = canvas.width;
106 
+                            let imageHeight = canvas.height;
107 
+                            let imageScale = sourceImageParent.offsetWidth / imageWidth;
108 
+                            sourceImageParent.style.height = Math.round(imageHeight * imageScale) + 'px';
109 
+
110 
+                            if (img != null) {
111 
+                                img.delete();
112 
+                                img = null;
113 
+                            }
114 
+
115 
+                            while (sourceImage.firstChild) {
116 
+                                sourceImage.removeChild(sourceImage.firstChild);
117 
+                            }
118 
+                            sourceImage.appendChild(canvas);
119 
+
120 
+                            zoomer.setOptions({
121 
+                                minScale: imageScale,
122 
+                                maxScale: 1
123 
+                            });
124 
+                            zoomer.zoomToPoint(imageScale, {clientX: sourceImageParent.offsetLeft, clientY: sourceImageParent.offsetTop});
125 
+
126 
+                            let overlay = document.createElement('canvas');
127 
+                            overlay.className = 'overlay';
128 
+                            overlay.width = imageWidth;
129 
+                            overlay.height = imageHeight;
130 
+                            sourceImage.appendChild(overlay);
131 
+
132 
+                            let context = overlay.getContext('2d');
133 
+                            context.globalAlpha = 0.6;
134 
+                            context.strokeStyle = 'red';
135 
+
136 
+                            let handles = [];
137 
+
138 
+                            function getNewCorners() {
139 
+                                let corners = [];
140 
+                                handles.forEach(function(handle) {
141 
+                                    corners.push(new cv.Point(
142 
+                                        parseFloat(handle.dataset.left),
143 
+                                        parseFloat(handle.dataset.top)
144 
+                                    ));
145 
+                                });
146 
+                                return corners;
147 
+                            }
148 
+
149 
+                            function redrawOverlay() {
150 
+                                let corners = getNewCorners();
151 
+                                context.lineWidth = 1 / zoomer.getScale();
152 
+                                context.clearRect(0, 0, imageWidth, imageHeight);
153 
+                                context.beginPath();
154 
+                                let corner = corners[corners.length - 1];
155 
+                                context.moveTo(corner.x, corner.y);
156 
+                                corners.forEach(function(corner) {
157 
+                                    context.lineTo(corner.x, corner.y);
158 
+                                });
159 
+                                context.stroke();
160 
+                            }
161 
+
162 
+                            function dragMoveListener(event) {
163 
+                                let target = event.target;
164 
+                                let newLeft = Math.min(
165 
+                                    imageWidth - 1,
166 
+                                    Math.max(0, parseFloat(target.dataset.left) + event.dx / zoomer.getScale())
167 
+                                );
168 
+                                let newTop = Math.min(
169 
+                                    imageHeight - 1,
170 
+                                    Math.max(0, parseFloat(target.dataset.top) + event.dy / zoomer.getScale())
171 
+                                );
172 
+                                target.dataset.left = newLeft;
173 
+                                target.dataset.top = newTop;
174 
+                                target.style.left = newLeft + 'px';
175 
+                                target.style.top = newTop + 'px';
176 
+                                redrawOverlay();
177 
+                            }
178 
+
179 
+                            function recalculate() {
180 
+                                let square = extractSquare(img, getNewCorners());
181 
+                                try {
182 
+                                    let numRows = getLineFrequency(square, lineDetectorElementSize, 1);
183 
+                                    let numCols = getLineFrequency(square, lineDetectorElementSize, 0);
184 
+                                    if (isSquare && (numRows !== numCols)) {
185 
+                                        console.log("WARNING: crossword is not square");
186 
+                                    }
187 
+                                    cv.imshow('output', square);
188 
+                                } finally {
189 
+                                    square.delete();
190 
+                                }
191 
+                            }
192 
+
193 
+                            document.getElementById('recalculateButton').onclick = recalculate;
194 
+                            zoomCallback = function(event) {
195 
+                                redrawOverlay();
196 
+                            };
197 
+
198 
+                            let src = cv.imread(canvas);
199 
+                            try {
200 
+                                //removeColours(src, src, 48);
201 
+                                //cv.imshow('output', src);
202 
+
203 
+                                cv.cvtColor(src, src, cv.COLOR_RGBA2GRAY, 0);
204 
+
205 
+                                img = new cv.Mat();
206 
+                                preprocessImage(src, img, gaussianBlurSize, adaptiveThresholdBlockSize, adaptiveThresholdMeanAdjustment, numDilations);
207 
+                                //cv.imshow('output', img);
208 
+                                let corners;
209 
+                                let biggest = findBiggestContour(img);
210 
+                                try {
211 
+                                    let eroded = erodeContour(img.size(), biggest, contourErosionKernelSize, contourErosionIterations);
212 
+                                    try {
213 
+                                        corners = getContourCorners(img.size(), eroded);
214 
+                                    } finally {
215 
+                                        eroded.delete();
216 
+                                    }
217 
+                                } finally {
218 
+                                    biggest.delete();
219 
+                                }
220 
+
221 
+                                corners.forEach(function(corner) {
222 
+                                    let handle = document.createElement('div');
223 
+                                    handle.className = 'handle';
224 
+                                    handle.dataset.left = corner.x;
225 
+                                    handle.dataset.top = corner.y;
226 
+                                    handle.style.left = handle.dataset.left + 'px';
227 
+                                    handle.style.top = handle.dataset.top + 'px';
228 
+                                    sourceImage.appendChild(handle);
229 
+                                    interact(handle).draggable({
230 
+                                        onmove: dragMoveListener
231 
+                                    });
232 
+                                    handles.push(handle);
233 
+                                });
234 
+
235 
+                                redrawOverlay();
236 
+                                recalculate();
237 
+
238 
+                            } finally {
239 
+                                src.delete();
240 
+                            }
241 
+                        },
242 
+                        {
243 
+                            orientation: true
244 
+                        }
245 
+                    );
246 
+                }
247 
+            };
248 
+        </script>
249 
+    </body>
250 
+</html>
251 
+<!--
252 
+vim:ts=4:sw=4:expandtab
253 
+-->

File diff suppressed because it is too large
+ 4 - 0
js/vendor/interact/interact.min.js


File diff suppressed because it is too large
+ 2 - 0
js/vendor/load-image/load-image.all.min.js


File diff suppressed because it is too large
+ 45 - 0
js/vendor/opencv/opencv.js


+ 164 - 0
js/vendor/opencv/utils.js
ファイルの表示 

@@ -0,0 +1,164 @@
1 
+function Utils(errorOutputId) { // eslint-disable-line no-unused-vars
2 
+    let self = this;
3 
+    this.errorOutput = document.getElementById(errorOutputId);
4 
+
5 
+    const OPENCV_URL = 'opencv.js';
6 
+    this.loadOpenCv = function(onloadCallback) {
7 
+        let script = document.createElement('script');
8 
+        script.setAttribute('async', '');
9 
+        script.setAttribute('type', 'text/javascript');
10 
+        script.addEventListener('load', () => {
11 
+            if (cv.getBuildInformation)
12 
+            {
13 
+                console.log(cv.getBuildInformation());
14 
+                onloadCallback();
15 
+            }
16 
+            else
17 
+            {
18 
+                // WASM
19 
+                cv['onRuntimeInitialized']=()=>{
20 
+                    console.log(cv.getBuildInformation());
21 
+                    onloadCallback();
22 
+                }
23 
+            }
24 
+        });
25 
+        script.addEventListener('error', () => {
26 
+            self.printError('Failed to load ' + OPENCV_URL);
27 
+        });
28 
+        script.src = OPENCV_URL;
29 
+        let node = document.getElementsByTagName('script')[0];
30 
+        node.parentNode.insertBefore(script, node);
31 
+    };
32 
+
33 
+    this.createFileFromUrl = function(path, url, callback) {
34 
+        let request = new XMLHttpRequest();
35 
+        request.open('GET', url, true);
36 
+        request.responseType = 'arraybuffer';
37 
+        request.onload = function(ev) {
38 
+            if (request.readyState === 4) {
39 
+                if (request.status === 200) {
40 
+                    let data = new Uint8Array(request.response);
41 
+                    cv.FS_createDataFile('/', path, data, true, false, false);
42 
+                    callback();
43 
+                } else {
44 
+                    self.printError('Failed to load ' + url + ' status: ' + request.status);
45 
+                }
46 
+            }
47 
+        };
48 
+        request.send();
49 
+    };
50 
+
51 
+    this.loadImageToCanvas = function(url, cavansId) {
52 
+        let canvas = document.getElementById(cavansId);
53 
+        let ctx = canvas.getContext('2d');
54 
+        let img = new Image();
55 
+        img.crossOrigin = 'anonymous';
56 
+        img.onload = function() {
57 
+            canvas.width = img.width;
58 
+            canvas.height = img.height;
59 
+            ctx.drawImage(img, 0, 0, img.width, img.height);
60 
+        };
61 
+        img.src = url;
62 
+    };
63 
+
64 
+    this.executeCode = function(textAreaId) {
65 
+        try {
66 
+            this.clearError();
67 
+            let code = document.getElementById(textAreaId).value;
68 
+            eval(code);
69 
+        } catch (err) {
70 
+            this.printError(err);
71 
+        }
72 
+    };
73 
+
74 
+    this.clearError = function() {
75 
+        this.errorOutput.innerHTML = '';
76 
+    };
77 
+
78 
+    this.printError = function(err) {
79 
+        if (typeof err === 'undefined') {
80 
+            err = '';
81 
+        } else if (typeof err === 'number') {
82 
+            if (!isNaN(err)) {
83 
+                if (typeof cv !== 'undefined') {
84 
+                    err = 'Exception: ' + cv.exceptionFromPtr(err).msg;
85 
+                }
86 
+            }
87 
+        } else if (typeof err === 'string') {
88 
+            let ptr = Number(err.split(' ')[0]);
89 
+            if (!isNaN(ptr)) {
90 
+                if (typeof cv !== 'undefined') {
91 
+                    err = 'Exception: ' + cv.exceptionFromPtr(ptr).msg;
92 
+                }
93 
+            }
94 
+        } else if (err instanceof Error) {
95 
+            err = err.stack.replace(/\n/g, '<br>');
96 
+        }
97 
+        this.errorOutput.innerHTML = err;
98 
+    };
99 
+
100 
+    this.loadCode = function(scriptId, textAreaId) {
101 
+        let scriptNode = document.getElementById(scriptId);
102 
+        let textArea = document.getElementById(textAreaId);
103 
+        if (scriptNode.type !== 'text/code-snippet') {
104 
+            throw Error('Unknown code snippet type');
105 
+        }
106 
+        textArea.value = scriptNode.text.replace(/^\n/, '');
107 
+    };
108 
+
109 
+    this.addFileInputHandler = function(fileInputId, canvasId) {
110 
+        let inputElement = document.getElementById(fileInputId);
111 
+        inputElement.addEventListener('change', (e) => {
112 
+            let files = e.target.files;
113 
+            if (files.length > 0) {
114 
+                let imgUrl = URL.createObjectURL(files[0]);
115 
+                self.loadImageToCanvas(imgUrl, canvasId);
116 
+            }
117 
+        }, false);
118 
+    };
119 
+
120 
+    function onVideoCanPlay() {
121 
+        if (self.onCameraStartedCallback) {
122 
+            self.onCameraStartedCallback(self.stream, self.video);
123 
+        }
124 
+    };
125 
+
126 
+    this.startCamera = function(resolution, callback, videoId) {
127 
+        const constraints = {
128 
+            'qvga': {width: {exact: 320}, height: {exact: 240}},
129 
+            'vga': {width: {exact: 640}, height: {exact: 480}}};
130 
+        let video = document.getElementById(videoId);
131 
+        if (!video) {
132 
+            video = document.createElement('video');
133 
+        }
134 
+
135 
+        let videoConstraint = constraints[resolution];
136 
+        if (!videoConstraint) {
137 
+            videoConstraint = true;
138 
+        }
139 
+
140 
+        navigator.mediaDevices.getUserMedia({video: videoConstraint, audio: false})
141 
+            .then(function(stream) {
142 
+                video.srcObject = stream;
143 
+                video.play();
144 
+                self.video = video;
145 
+                self.stream = stream;
146 
+                self.onCameraStartedCallback = callback;
147 
+                video.addEventListener('canplay', onVideoCanPlay, false);
148 
+            })
149 
+            .catch(function(err) {
150 
+                self.printError('Camera Error: ' + err.name + ' ' + err.message);
151 
+            });
152 
+    };
153 
+
154 
+    this.stopCamera = function() {
155 
+        if (this.video) {
156 
+            this.video.pause();
157 
+            this.video.srcObject = null;
158 
+            this.video.removeEventListener('canplay', onVideoCanPlay);
159 
+        }
160 
+        if (this.stream) {
161 
+            this.stream.getVideoTracks()[0].stop();
162 
+        }
163 
+    };
164 
+};

File diff suppressed because it is too large
+ 472 - 0
js/vendor/panzoom/panzoom.js


File diff suppressed because it is too large
+ 7 - 0
js/vendor/plotly/plotly-latest.min.js


+ 255 - 0
js/xword.js
ファイルの表示 

@@ -0,0 +1,255 @@
1 
+// vim:ts=4:sw=4:expandtab
2 
+
3 
+'use strict';
4 
+
5 
+function plot(elementId, seriesList) {
6 
+    let plots = [];
7 
+    for (let i = 0; i < seriesList.length; i++) {
8 
+        let y = seriesList[i];
9 
+        let x = [];
10 
+        for (let i = 0; i < y.length; i++) {
11 
+            x.push(i);
12 
+        }
13 
+        plots.push({x: x, y: y});
14 
+    }
15 
+    Plotly.plot(document.getElementById(elementId), plots);
16 
+}
17 
+
18 
+function removeColours(src, dst, threshold) {
19 
+    let from = src.data32S;
20 
+    let to = dst.data32S;
21 
+    let pixels = src.rows * src.cols;
22 
+    for (let i = 0; i < pixels; i++) {
23 
+        let pixel = from[i];
24 
+        let r = pixel & 0xFF;
25 
+        let g = (pixel >> 8) & 0xFF;
26 
+        let b = (pixel >> 16) & 0xFF;
27 
+        to[i] = from[i] | (Math.max(r, g, b) - Math.min(r, g, b) > threshold ? 0xFFFFFF : 0);
28 
+    }
29 
+}
30 
+
31 
+function preprocessImage(src, dst, gaussianBlurSize, adaptiveThresholdBlockSize, adaptiveThresholdMeanAdjustment, numDilations) {
32 
+    cv.GaussianBlur(src, dst, new cv.Size(gaussianBlurSize, gaussianBlurSize), 0);
33 
+    cv.adaptiveThreshold(dst, dst, 255, cv.ADAPTIVE_THRESH_GAUSSIAN_C, cv.THRESH_BINARY_INV, adaptiveThresholdBlockSize, adaptiveThresholdMeanAdjustment);
34 
+    let kernel = cv.getStructuringElement(cv.MORPH_CROSS, new cv.Size(3, 3));
35 
+    try {
36 
+        cv.dilate(dst, dst, kernel, new cv.Point(-1, -1), numDilations);
37 
+    } finally {
38 
+        kernel.delete();
39 
+    }
40 
+}
41 
+
42 
+function morphOpenImage(src, dst, kernelSize, iterations) {
43 
+    let kernel = cv.getStructuringElement(cv.MORPH_RECT, kernelSize);
44 
+    try {
45 
+        cv.morphologyEx(src, dst, cv.MORPH_OPEN, kernel, new cv.Point(-1, -1), iterations);
46 
+    } finally {
47 
+        kernel.delete();
48 
+    }
49 
+}
50 
+
51 
+function findBiggestContour(img) {
52 
+    let contours = new cv.MatVector();
53 
+    try {
54 
+        let hierarchy = new cv.Mat();
55 
+        try {
56 
+            cv.findContours(img, contours, hierarchy, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE);
57 
+
58 
+            let biggest = null;
59 
+            let maxArea = 0;
60 
+            for (let i = 0; i < contours.size(); i++) {
61 
+                let contour = contours.get(i);
62 
+                let area = cv.contourArea(contour);
63 
+                if (area > maxArea) {
64 
+                    maxArea = area;
65 
+                    if (biggest !== null) {
66 
+                        biggest.delete();
67 
+                    }
68 
+                    biggest = contour;
69 
+                } else {
70 
+                    contour.delete();
71 
+                }
72 
+            }
73 
+            return biggest;
74 
+        } finally {
75 
+            hierarchy.delete();
76 
+        }
77 
+    } finally {
78 
+        contours.delete();
79 
+    }
80 
+}
81 
+
82 
+function erodeContour(imageSize, contour, kernelSize, iterations) {
83 
+    let contourImg = cv.Mat.zeros(imageSize.height, imageSize.width, cv.CV_8U);
84 
+    try {
85 
+        let contours = new cv.MatVector();
86 
+        try {
87 
+            contours.push_back(contour);
88 
+            cv.drawContours(contourImg, contours, 0, new cv.Scalar(255), -1);
89 
+        } finally {
90 
+            contours.delete();
91 
+        }
92 
+        morphOpenImage(contourImg, contourImg, new cv.Size(kernelSize, kernelSize), iterations);
93 
+        return findBiggestContour(contourImg);
94 
+    } finally {
95 
+        contourImg.delete();
96 
+    }
97 
+}
98 
+
99 
+function getContourCorners(imageSize, contour) {
100 
+    let topLeft = new cv.Point(imageSize.width, imageSize.height);
101 
+    let topRight = new cv.Point(-1, imageSize.height);
102 
+    let bottomLeft = new cv.Point(imageSize.width, -1);
103 
+    let bottomRight = new cv.Point(-1, -1);
104 
+    for (let i = 0; i < contour.rows; i++) {
105 
+        let vertex = new cv.Point(contour.data32S[i * 2], contour.data32S[i * 2 + 1]);
106 
+        let sum = vertex.x + vertex.y;
107 
+        let diff = vertex.x - vertex.y;
108 
+        if (sum < topLeft.x + topLeft.y) {
109 
+            topLeft = vertex;
110 
+        }
111 
+        if (sum > bottomRight.x + bottomRight.y) {
112 
+            bottomRight = vertex;
113 
+        }
114 
+        if (diff < bottomLeft.x - bottomLeft.y) {
115 
+            bottomLeft = vertex;
116 
+        }
117 
+        if (diff > topRight.x - topRight.y) {
118 
+            topRight = vertex;
119 
+        }
120 
+    }
121 
+    return [topLeft, topRight, bottomRight, bottomLeft];
122 
+}
123 
+
124 
+function segmentLength(p1, p2) {
125 
+    let dx = p1.x - p2.x;
126 
+    let dy = p1.y - p2.y;
127 
+    return Math.sqrt(dx ** 2 + dy ** 2);
128 
+}
129 
+
130 
+function getLongestSide(corners) {
131 
+    let previous = corners[corners.length - 1];
132 
+    let max = 0;
133 
+    for (let i = 0; i < corners.length; i++) {
134 
+        let current = corners[i];
135 
+        let length = segmentLength(previous, current);
136 
+        if (length > max) {
137 
+            max = length;
138 
+        }
139 
+        previous = current;
140 
+    }
141 
+    return max;
142 
+}
143 
+
144 
+function extractSquare(img, corners) {
145 
+    let longest = getLongestSide(corners);
146 
+    let end = longest - 1;
147 
+    let sourceRect = cv.matFromArray(4, 1, cv.CV_32FC2, [corners[0].x, corners[0].y, corners[1].x, corners[1].y, corners[2].x, corners[2].y, corners[3].x, corners[3].y]);
148 
+    try {
149 
+        let destRect = cv.matFromArray(4, 1, cv.CV_32FC2, [0, 0, end, 0, end, end, 0, end]);
150 
+        try {
151 
+            let m = cv.getPerspectiveTransform(sourceRect, destRect);
152 
+            try {
153 
+                let destImg = new cv.Mat();
154 
+                try {
155 
+                    cv.warpPerspective(img, destImg, m, new cv.Size(longest, longest));
156 
+                    return destImg;
157 
+                } catch (err) {
158 
+                    destImg.delete();
159 
+                    throw err;
160 
+                }
161 
+            } finally {
162 
+                m.delete();
163 
+            }
164 
+        } finally {
165 
+            destRect.delete();
166 
+        }
167 
+    } finally {
168 
+        sourceRect.delete();
169 
+    }
170 
+}
171 
+
172 
+function indexOfMax(arr) {
173 
+    return arr.reduce((iMax, x, i, arr) => x > arr[iMax] ? i : iMax, 0);
174 
+}
175 
+
176 
+function getFundamentalFrequency(mag) {
177 
+    mag = mag.slice(0, Math.ceil(mag.length / 2));
178 
+    mag[0] = 0;
179 
+    return indexOfMax(mag);
180 
+}
181 
+
182 
+function createMatVector(length) {
183 
+    let vec = new cv.MatVector();
184 
+    try {
185 
+        let mat = new cv.Mat();
186 
+        try {
187 
+            for (let i = 0; i < length; i++) {
188 
+                vec.push_back(mat);
189 
+            }
190 
+        } finally {
191 
+            mat.delete();
192 
+        }
193 
+        return vec;
194 
+    } catch (err) {
195 
+        vec.delete();
196 
+        throw err;
197 
+    }
198 
+}
199 
+
200 
+function getLineFFT(img, lineDetectorElementSize, axis) {
201 
+    let lines = new cv.Mat();
202 
+    try {
203 
+        morphOpenImage(img, lines, axis === 1 ? new cv.Size(lineDetectorElementSize, 1) : new cv.Size(1, lineDetectorElementSize), 1);
204 
+        let sums = new cv.Mat();
205 
+        try {
206 
+            cv.reduce(lines, sums, axis, cv.REDUCE_SUM, cv.CV_32FC1);
207 
+            let fft = new cv.Mat();
208 
+            try {
209 
+                cv.dft(sums, fft, cv.DFT_COMPLEX_OUTPUT, 0);
210 
+                return fft;
211 
+            } catch (err) {
212 
+                fft.delete();
213 
+                throw err;
214 
+            }
215 
+        } finally {
216 
+            sums.delete();
217 
+        }
218 
+    } finally {
219 
+        lines.delete();
220 
+    }
221 
+}
222 
+
223 
+function getFFTMagnitude(fft) {
224 
+    let planes = createMatVector(2);
225 
+    try {
226 
+        cv.split(fft, planes);
227 
+        let real = planes.get(0);
228 
+        try {
229 
+            let imag = planes.get(1);
230 
+            try {
231 
+                let ret = [];
232 
+                let length = Math.max(real.cols, real.rows);
233 
+                for (let i = 0; i < length; i++) {
234 
+                    ret.push(Math.sqrt(real.data32F[i] ** 2 + imag.data32F[i] ** 2))
235 
+                }
236 
+                return ret;
237 
+            } finally {
238 
+                imag.delete();
239 
+            }
240 
+        } finally {
241 
+            real.delete();
242 
+        }
243 
+    } finally {
244 
+        planes.delete();
245 
+    }
246 
+}
247 
+
248 
+function getLineFrequency(img, lineDetectorElementSize, axis) {
249 
+    let fft = getLineFFT(img, lineDetectorElementSize, axis);
250 
+    try {
251 
+        return getFundamentalFrequency(getFFTMagnitude(fft));
252 
+    } finally {
253 
+        fft.delete();
254 
+    }
255 
+}