getuserbarcode
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An advanced barcode-scanner written in JavaScript
752 lines (667 loc) • 22.3 kB
JavaScript
import Cluster2 from './cluster';
import ArrayHelper from './array_helper';
const vec2 = {
clone: require('gl-vec2/clone'),
};
const vec3 = {
clone: require('gl-vec3/clone'),
};
/**
* @param x x-coordinate
* @param y y-coordinate
* @return ImageReference {x,y} Coordinate
*/
export function imageRef(x, y) {
var that = {
x: x,
y: y,
toVec2: function() {
return vec2.clone([this.x, this.y]);
},
toVec3: function() {
return vec3.clone([this.x, this.y, 1]);
},
round: function() {
this.x = this.x > 0.0 ? Math.floor(this.x + 0.5) : Math.floor(this.x - 0.5);
this.y = this.y > 0.0 ? Math.floor(this.y + 0.5) : Math.floor(this.y - 0.5);
return this;
}
};
return that;
};
/**
* Computes an integral image of a given grayscale image.
* @param imageDataContainer {ImageDataContainer} the image to be integrated
*/
export function computeIntegralImage2(imageWrapper, integralWrapper) {
var imageData = imageWrapper.data;
var width = imageWrapper.size.x;
var height = imageWrapper.size.y;
var integralImageData = integralWrapper.data;
var sum = 0, posA = 0, posB = 0, posC = 0, posD = 0, x, y;
// sum up first column
posB = width;
sum = 0;
for ( y = 1; y < height; y++) {
sum += imageData[posA];
integralImageData[posB] += sum;
posA += width;
posB += width;
}
posA = 0;
posB = 1;
sum = 0;
for ( x = 1; x < width; x++) {
sum += imageData[posA];
integralImageData[posB] += sum;
posA++;
posB++;
}
for ( y = 1; y < height; y++) {
posA = y * width + 1;
posB = (y - 1) * width + 1;
posC = y * width;
posD = (y - 1) * width;
for ( x = 1; x < width; x++) {
integralImageData[posA] +=
imageData[posA] + integralImageData[posB] + integralImageData[posC] - integralImageData[posD];
posA++;
posB++;
posC++;
posD++;
}
}
};
export function computeIntegralImage(imageWrapper, integralWrapper) {
var imageData = imageWrapper.data;
var width = imageWrapper.size.x;
var height = imageWrapper.size.y;
var integralImageData = integralWrapper.data;
var sum = 0;
// sum up first row
for (var i = 0; i < width; i++) {
sum += imageData[i];
integralImageData[i] = sum;
}
for (var v = 1; v < height; v++) {
sum = 0;
for (var u = 0; u < width; u++) {
sum += imageData[v * width + u];
integralImageData[((v) * width) + u] = sum + integralImageData[(v - 1) * width + u];
}
}
};
export function thresholdImage(imageWrapper, threshold, targetWrapper) {
if (!targetWrapper) {
targetWrapper = imageWrapper;
}
var imageData = imageWrapper.data, length = imageData.length, targetData = targetWrapper.data;
while (length--) {
targetData[length] = imageData[length] < threshold ? 1 : 0;
}
};
export function computeHistogram(imageWrapper, bitsPerPixel) {
if (!bitsPerPixel) {
bitsPerPixel = 8;
}
var imageData = imageWrapper.data,
length = imageData.length,
bitShift = 8 - bitsPerPixel,
bucketCnt = 1 << bitsPerPixel,
hist = new Int32Array(bucketCnt);
while (length--) {
hist[imageData[length] >> bitShift]++;
}
return hist;
};
export function sharpenLine(line) {
var i,
length = line.length,
left = line[0],
center = line[1],
right;
for (i = 1; i < length - 1; i++) {
right = line[i + 1];
// -1 4 -1 kernel
line[i - 1] = (((center * 2) - left - right)) & 255;
left = center;
center = right;
}
return line;
};
export function determineOtsuThreshold(imageWrapper, bitsPerPixel) {
if (!bitsPerPixel) {
bitsPerPixel = 8;
}
var hist,
threshold,
bitShift = 8 - bitsPerPixel;
function px(init, end) {
var sum = 0, i;
for ( i = init; i <= end; i++) {
sum += hist[i];
}
return sum;
}
function mx(init, end) {
var i, sum = 0;
for ( i = init; i <= end; i++) {
sum += i * hist[i];
}
return sum;
}
function determineThreshold() {
var vet = [0], p1, p2, p12, k, m1, m2, m12,
max = (1 << bitsPerPixel) - 1;
hist = computeHistogram(imageWrapper, bitsPerPixel);
for ( k = 1; k < max; k++) {
p1 = px(0, k);
p2 = px(k + 1, max);
p12 = p1 * p2;
if (p12 === 0) {
p12 = 1;
}
m1 = mx(0, k) * p2;
m2 = mx(k + 1, max) * p1;
m12 = m1 - m2;
vet[k] = m12 * m12 / p12;
}
return ArrayHelper.maxIndex(vet);
}
threshold = determineThreshold();
return threshold << bitShift;
};
export function otsuThreshold(imageWrapper, targetWrapper) {
var threshold = determineOtsuThreshold(imageWrapper);
thresholdImage(imageWrapper, threshold, targetWrapper);
return threshold;
};
// local thresholding
export function computeBinaryImage(imageWrapper, integralWrapper, targetWrapper) {
computeIntegralImage(imageWrapper, integralWrapper);
if (!targetWrapper) {
targetWrapper = imageWrapper;
}
var imageData = imageWrapper.data;
var targetData = targetWrapper.data;
var width = imageWrapper.size.x;
var height = imageWrapper.size.y;
var integralImageData = integralWrapper.data;
var sum = 0, v, u, kernel = 3, A, B, C, D, avg, size = (kernel * 2 + 1) * (kernel * 2 + 1);
// clear out top & bottom-border
for ( v = 0; v <= kernel; v++) {
for ( u = 0; u < width; u++) {
targetData[((v) * width) + u] = 0;
targetData[(((height - 1) - v) * width) + u] = 0;
}
}
// clear out left & right border
for ( v = kernel; v < height - kernel; v++) {
for ( u = 0; u <= kernel; u++) {
targetData[((v) * width) + u] = 0;
targetData[((v) * width) + (width - 1 - u)] = 0;
}
}
for ( v = kernel + 1; v < height - kernel - 1; v++) {
for ( u = kernel + 1; u < width - kernel; u++) {
A = integralImageData[(v - kernel - 1) * width + (u - kernel - 1)];
B = integralImageData[(v - kernel - 1) * width + (u + kernel)];
C = integralImageData[(v + kernel) * width + (u - kernel - 1)];
D = integralImageData[(v + kernel) * width + (u + kernel)];
sum = D - C - B + A;
avg = sum / (size);
targetData[v * width + u] = imageData[v * width + u] > (avg + 5) ? 0 : 1;
}
}
};
export function cluster(points, threshold, property) {
var i, k, cluster, point, clusters = [];
if (!property) {
property = "rad";
}
function addToCluster(newPoint) {
var found = false;
for ( k = 0; k < clusters.length; k++) {
cluster = clusters[k];
if (cluster.fits(newPoint)) {
cluster.add(newPoint);
found = true;
}
}
return found;
}
// iterate over each cloud
for ( i = 0; i < points.length; i++) {
point = Cluster2.createPoint(points[i], i, property);
if (!addToCluster(point)) {
clusters.push(Cluster2.create(point, threshold));
}
}
return clusters;
};
export const Tracer = {
trace: function(points, vec) {
var iteration, maxIterations = 10, top = [], result = [], centerPos = 0, currentPos = 0;
function trace(idx, forward) {
var from, to, toIdx, predictedPos, thresholdX = 1, thresholdY = Math.abs(vec[1] / 10), found = false;
function match(pos, predicted) {
if (pos.x > (predicted.x - thresholdX)
&& pos.x < (predicted.x + thresholdX)
&& pos.y > (predicted.y - thresholdY)
&& pos.y < (predicted.y + thresholdY)) {
return true;
} else {
return false;
}
}
// check if the next index is within the vec specifications
// if not, check as long as the threshold is met
from = points[idx];
if (forward) {
predictedPos = {
x: from.x + vec[0],
y: from.y + vec[1]
};
} else {
predictedPos = {
x: from.x - vec[0],
y: from.y - vec[1]
};
}
toIdx = forward ? idx + 1 : idx - 1;
to = points[toIdx];
while (to && ( found = match(to, predictedPos)) !== true && (Math.abs(to.y - from.y) < vec[1])) {
toIdx = forward ? toIdx + 1 : toIdx - 1;
to = points[toIdx];
}
return found ? toIdx : null;
}
for ( iteration = 0; iteration < maxIterations; iteration++) {
// randomly select point to start with
centerPos = Math.floor(Math.random() * points.length);
// trace forward
top = [];
currentPos = centerPos;
top.push(points[currentPos]);
while (( currentPos = trace(currentPos, true)) !== null) {
top.push(points[currentPos]);
}
if (centerPos > 0) {
currentPos = centerPos;
while (( currentPos = trace(currentPos, false)) !== null) {
top.push(points[currentPos]);
}
}
if (top.length > result.length) {
result = top;
}
}
return result;
}
};
export const DILATE = 1;
export const ERODE = 2;
export function dilate(inImageWrapper, outImageWrapper) {
var v,
u,
inImageData = inImageWrapper.data,
outImageData = outImageWrapper.data,
height = inImageWrapper.size.y,
width = inImageWrapper.size.x,
sum,
yStart1,
yStart2,
xStart1,
xStart2;
for ( v = 1; v < height - 1; v++) {
for ( u = 1; u < width - 1; u++) {
yStart1 = v - 1;
yStart2 = v + 1;
xStart1 = u - 1;
xStart2 = u + 1;
sum = inImageData[yStart1 * width + xStart1] + inImageData[yStart1 * width + xStart2] +
inImageData[v * width + u] +
inImageData[yStart2 * width + xStart1] + inImageData[yStart2 * width + xStart2];
outImageData[v * width + u] = sum > 0 ? 1 : 0;
}
}
};
export function erode(inImageWrapper, outImageWrapper) {
var v,
u,
inImageData = inImageWrapper.data,
outImageData = outImageWrapper.data,
height = inImageWrapper.size.y,
width = inImageWrapper.size.x,
sum,
yStart1,
yStart2,
xStart1,
xStart2;
for ( v = 1; v < height - 1; v++) {
for ( u = 1; u < width - 1; u++) {
yStart1 = v - 1;
yStart2 = v + 1;
xStart1 = u - 1;
xStart2 = u + 1;
sum = inImageData[yStart1 * width + xStart1] + inImageData[yStart1 * width + xStart2] +
inImageData[v * width + u] +
inImageData[yStart2 * width + xStart1] + inImageData[yStart2 * width + xStart2];
outImageData[v * width + u] = sum === 5 ? 1 : 0;
}
}
};
export function subtract(aImageWrapper, bImageWrapper, resultImageWrapper) {
if (!resultImageWrapper) {
resultImageWrapper = aImageWrapper;
}
var length = aImageWrapper.data.length,
aImageData = aImageWrapper.data,
bImageData = bImageWrapper.data,
cImageData = resultImageWrapper.data;
while (length--) {
cImageData[length] = aImageData[length] - bImageData[length];
}
};
export function bitwiseOr(aImageWrapper, bImageWrapper, resultImageWrapper) {
if (!resultImageWrapper) {
resultImageWrapper = aImageWrapper;
}
var length = aImageWrapper.data.length,
aImageData = aImageWrapper.data,
bImageData = bImageWrapper.data,
cImageData = resultImageWrapper.data;
while (length--) {
cImageData[length] = aImageData[length] || bImageData[length];
}
};
export function countNonZero(imageWrapper) {
var length = imageWrapper.data.length, data = imageWrapper.data, sum = 0;
while (length--) {
sum += data[length];
}
return sum;
};
export function topGeneric(list, top, scoreFunc) {
var i, minIdx = 0, min = 0, queue = [], score, hit, pos;
for ( i = 0; i < top; i++) {
queue[i] = {
score: 0,
item: null
};
}
for ( i = 0; i < list.length; i++) {
score = scoreFunc.apply(this, [list[i]]);
if (score > min) {
hit = queue[minIdx];
hit.score = score;
hit.item = list[i];
min = Number.MAX_VALUE;
for ( pos = 0; pos < top; pos++) {
if (queue[pos].score < min) {
min = queue[pos].score;
minIdx = pos;
}
}
}
}
return queue;
};
export function grayArrayFromImage(htmlImage, offsetX, ctx, array) {
ctx.drawImage(htmlImage, offsetX, 0, htmlImage.width, htmlImage.height);
var ctxData = ctx.getImageData(offsetX, 0, htmlImage.width, htmlImage.height).data;
computeGray(ctxData, array);
};
export function grayArrayFromContext(ctx, size, offset, array) {
var ctxData = ctx.getImageData(offset.x, offset.y, size.x, size.y).data;
computeGray(ctxData, array);
};
export function grayAndHalfSampleFromCanvasData(canvasData, size, outArray) {
var topRowIdx = 0;
var bottomRowIdx = size.x;
var endIdx = Math.floor(canvasData.length / 4);
var outWidth = size.x / 2;
var outImgIdx = 0;
var inWidth = size.x;
var i;
while (bottomRowIdx < endIdx) {
for ( i = 0; i < outWidth; i++) {
outArray[outImgIdx] = (
(0.299 * canvasData[topRowIdx * 4 + 0] +
0.587 * canvasData[topRowIdx * 4 + 1] +
0.114 * canvasData[topRowIdx * 4 + 2]) +
(0.299 * canvasData[(topRowIdx + 1) * 4 + 0] +
0.587 * canvasData[(topRowIdx + 1) * 4 + 1] +
0.114 * canvasData[(topRowIdx + 1) * 4 + 2]) +
(0.299 * canvasData[(bottomRowIdx) * 4 + 0] +
0.587 * canvasData[(bottomRowIdx) * 4 + 1] +
0.114 * canvasData[(bottomRowIdx) * 4 + 2]) +
(0.299 * canvasData[(bottomRowIdx + 1) * 4 + 0] +
0.587 * canvasData[(bottomRowIdx + 1) * 4 + 1] +
0.114 * canvasData[(bottomRowIdx + 1) * 4 + 2])) / 4;
outImgIdx++;
topRowIdx = topRowIdx + 2;
bottomRowIdx = bottomRowIdx + 2;
}
topRowIdx = topRowIdx + inWidth;
bottomRowIdx = bottomRowIdx + inWidth;
}
};
export function computeGray(imageData, outArray, config) {
var l = (imageData.length / 4) | 0,
i,
singleChannel = config && config.singleChannel === true;
if (singleChannel) {
for (i = 0; i < l; i++) {
outArray[i] = imageData[i * 4 + 0];
}
} else {
for (i = 0; i < l; i++) {
outArray[i] =
0.299 * imageData[i * 4 + 0] + 0.587 * imageData[i * 4 + 1] + 0.114 * imageData[i * 4 + 2];
}
}
};
export function loadImageArray(src, callback, canvas) {
if (!canvas) {
canvas = document.createElement('canvas');
}
var img = new Image();
img.callback = callback;
img.onload = function() {
canvas.width = this.width;
canvas.height = this.height;
var ctx = canvas.getContext('2d');
ctx.drawImage(this, 0, 0);
var array = new Uint8Array(this.width * this.height);
ctx.drawImage(this, 0, 0);
var data = ctx.getImageData(0, 0, this.width, this.height).data;
computeGray(data, array);
this.callback(array, {
x: this.width,
y: this.height
}, this);
};
img.src = src;
};
/**
* @param inImg {ImageWrapper} input image to be sampled
* @param outImg {ImageWrapper} to be stored in
*/
export function halfSample(inImgWrapper, outImgWrapper) {
var inImg = inImgWrapper.data;
var inWidth = inImgWrapper.size.x;
var outImg = outImgWrapper.data;
var topRowIdx = 0;
var bottomRowIdx = inWidth;
var endIdx = inImg.length;
var outWidth = inWidth / 2;
var outImgIdx = 0;
while (bottomRowIdx < endIdx) {
for (var i = 0; i < outWidth; i++) {
outImg[outImgIdx] = Math.floor(
(inImg[topRowIdx] + inImg[topRowIdx + 1] + inImg[bottomRowIdx] + inImg[bottomRowIdx + 1]) / 4);
outImgIdx++;
topRowIdx = topRowIdx + 2;
bottomRowIdx = bottomRowIdx + 2;
}
topRowIdx = topRowIdx + inWidth;
bottomRowIdx = bottomRowIdx + inWidth;
}
};
export function hsv2rgb(hsv, rgb) {
var h = hsv[0],
s = hsv[1],
v = hsv[2],
c = v * s,
x = c * (1 - Math.abs((h / 60) % 2 - 1)),
m = v - c,
r = 0,
g = 0,
b = 0;
rgb = rgb || [0, 0, 0];
if (h < 60) {
r = c;
g = x;
} else if (h < 120) {
r = x;
g = c;
} else if (h < 180) {
g = c;
b = x;
} else if (h < 240) {
g = x;
b = c;
} else if (h < 300) {
r = x;
b = c;
} else if (h < 360) {
r = c;
b = x;
}
rgb[0] = ((r + m) * 255) | 0;
rgb[1] = ((g + m) * 255) | 0;
rgb[2] = ((b + m) * 255) | 0;
return rgb;
};
export function _computeDivisors(n) {
var largeDivisors = [],
divisors = [],
i;
for (i = 1; i < Math.sqrt(n) + 1; i++) {
if (n % i === 0) {
divisors.push(i);
if (i !== n / i) {
largeDivisors.unshift(Math.floor(n / i));
}
}
}
return divisors.concat(largeDivisors);
};
function _computeIntersection(arr1, arr2) {
var i = 0,
j = 0,
result = [];
while (i < arr1.length && j < arr2.length) {
if (arr1[i] === arr2[j]) {
result.push(arr1[i]);
i++;
j++;
} else if (arr1[i] > arr2[j]) {
j++;
} else {
i++;
}
}
return result;
};
export function calculatePatchSize(patchSize, imgSize) {
var divisorsX = _computeDivisors(imgSize.x),
divisorsY = _computeDivisors(imgSize.y),
wideSide = Math.max(imgSize.x, imgSize.y),
common = _computeIntersection(divisorsX, divisorsY),
nrOfPatchesList = [8, 10, 15, 20, 32, 60, 80],
nrOfPatchesMap = {
"x-small": 5,
"small": 4,
"medium": 3,
"large": 2,
"x-large": 1
},
nrOfPatchesIdx = nrOfPatchesMap[patchSize] || nrOfPatchesMap.medium,
nrOfPatches = nrOfPatchesList[nrOfPatchesIdx],
desiredPatchSize = Math.floor(wideSide / nrOfPatches),
optimalPatchSize;
function findPatchSizeForDivisors(divisors) {
var i = 0,
found = divisors[Math.floor(divisors.length / 2)];
while (i < (divisors.length - 1) && divisors[i] < desiredPatchSize) {
i++;
}
if (i > 0) {
if (Math.abs(divisors[i] - desiredPatchSize) > Math.abs(divisors[i - 1] - desiredPatchSize)) {
found = divisors[i - 1];
} else {
found = divisors[i];
}
}
if (desiredPatchSize / found < nrOfPatchesList[nrOfPatchesIdx + 1] / nrOfPatchesList[nrOfPatchesIdx] &&
desiredPatchSize / found > nrOfPatchesList[nrOfPatchesIdx - 1] / nrOfPatchesList[nrOfPatchesIdx] ) {
return {x: found, y: found};
}
return null;
}
optimalPatchSize = findPatchSizeForDivisors(common);
if (!optimalPatchSize) {
optimalPatchSize = findPatchSizeForDivisors(_computeDivisors(wideSide));
if (!optimalPatchSize) {
optimalPatchSize = findPatchSizeForDivisors((_computeDivisors(desiredPatchSize * nrOfPatches)));
}
}
return optimalPatchSize;
};
export function _parseCSSDimensionValues(value) {
var dimension = {
value: parseFloat(value),
unit: value.indexOf("%") === value.length - 1 ? "%" : "%"
};
return dimension;
};
export const _dimensionsConverters = {
top: function(dimension, context) {
if (dimension.unit === "%") {
return Math.floor(context.height * (dimension.value / 100));
}
},
right: function(dimension, context) {
if (dimension.unit === "%") {
return Math.floor(context.width - (context.width * (dimension.value / 100)));
}
},
bottom: function(dimension, context) {
if (dimension.unit === "%") {
return Math.floor(context.height - (context.height * (dimension.value / 100)));
}
},
left: function(dimension, context) {
if (dimension.unit === "%") {
return Math.floor(context.width * (dimension.value / 100));
}
}
};
export function computeImageArea(inputWidth, inputHeight, area) {
var context = {width: inputWidth, height: inputHeight};
var parsedArea = Object.keys(area).reduce(function(result, key) {
var value = area[key],
parsed = _parseCSSDimensionValues(value),
calculated = _dimensionsConverters[key](parsed, context);
result[key] = calculated;
return result;
}, {});
return {
sx: parsedArea.left,
sy: parsedArea.top,
sw: parsedArea.right - parsedArea.left,
sh: parsedArea.bottom - parsedArea.top
};
};