init
This commit is contained in:
Andreas Wilms
207
PCSurvey/libs/ept/ParseBuffer.js
Normal file
207
PCSurvey/libs/ept/ParseBuffer.js
Normal file
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function parseEpt(event) {
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let buffer = event.data.buffer;
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let view = new DataView(buffer);
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let schema = event.data.schema;
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let scale = event.data.scale;
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let offset = event.data.offset;
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let mins = event.data.mins;
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let dimensions = schema.reduce((p, c) => {
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p[c.name] = c;
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return p;
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}, { });
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let dimOffset = (name) => {
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let offset = 0;
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for (var i = 0; i < schema.length; ++i) {
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if (schema[i].name == name) return offset;
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offset += schema[i].size;
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}
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return undefined;
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};
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let getExtractor = (name) => {
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let offset = dimOffset(name);
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let type = dimensions[name].type;
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let size = dimensions[name].size;
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if (type == 'signed') switch (size) {
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case 1: return (p) => view.getInt8(p + offset);
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case 2: return (p) => view.getInt16(p + offset, true);
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case 4: return (p) => view.getInt32(p + offset, true);
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case 8: return (p) => view.getInt64(p + offset, true);
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}
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if (type == 'unsigned') switch (size) {
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case 1: return (p) => view.getUint8(p + offset);
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case 2: return (p) => view.getUint16(p + offset, true);
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case 4: return (p) => view.getUint32(p + offset, true);
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case 8: return (p) => view.getUint64(p + offset, true);
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}
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if (type == 'float') switch (size) {
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case 4: return (p) => view.getFloat32(p + offset, true);
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case 8: return (p) => view.getFloat64(p + offset, true);
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}
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let str = JSON.stringify(dimensions[name]);
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throw new Error(`Invalid dimension specification for ${name}: ${str}`);
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};
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let pointSize = schema.reduce((p, c) => p + c.size, 0);
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let numPoints = buffer.byteLength / pointSize;
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let xyzBuffer, rgbBuffer, intensityBuffer, classificationBuffer,
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returnNumberBuffer, numberOfReturnsBuffer, pointSourceIdBuffer;
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let xyz, rgb, intensity, classification, returnNumber, numberOfReturns,
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pointSourceId;
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let xyzExtractor, rgbExtractor, intensityExtractor, classificationExtractor,
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returnNumberExtractor, numberOfReturnsExtractor, pointSourceIdExtractor;
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let twoByteColor = false;
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if (dimensions['X'] && dimensions['Y'] && dimensions['Z']) {
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xyzBuffer = new ArrayBuffer(numPoints * 4 * 3);
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xyz = new Float32Array(xyzBuffer);
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xyzExtractor = [
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getExtractor('X'),
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getExtractor('Y'),
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getExtractor('Z')
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];
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}
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if (dimensions['Red'] && dimensions['Green'] && dimensions['Blue']) {
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rgbBuffer = new ArrayBuffer(numPoints * 4);
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rgb = new Uint8Array(rgbBuffer);
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rgbExtractor = [
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getExtractor('Red'),
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getExtractor('Green'),
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getExtractor('Blue')
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];
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let r, g, b, pos;
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for (let i = 0; i < numPoints && !twoByteColor; ++i) {
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pos = i * pointSize;
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r = rgbExtractor[0](pos);
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g = rgbExtractor[1](pos);
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b = rgbExtractor[2](pos);
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if (r > 255 || g > 255 || b > 255) twoByteColor = true;
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}
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}
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if (dimensions['Intensity']) {
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intensityBuffer = new ArrayBuffer(numPoints * 4);
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intensity = new Float32Array(intensityBuffer);
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intensityExtractor = getExtractor('Intensity');
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}
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if (dimensions['Classification']) {
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classificationBuffer = new ArrayBuffer(numPoints);
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classification = new Uint8Array(classificationBuffer);
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classificationExtractor = getExtractor('Classification');
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}
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if (dimensions['ReturnNumber']) {
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returnNumberBuffer = new ArrayBuffer(numPoints);
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returnNumber = new Uint8Array(returnNumberBuffer);
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returnNumberExtractor = getExtractor('ReturnNumber');
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}
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if (dimensions['NumberOfReturns']) {
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numberOfReturnsBuffer = new ArrayBuffer(numPoints);
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numberOfReturns = new Uint8Array(numberOfReturnsBuffer);
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numberOfReturnsExtractor = getExtractor('NumberOfReturns');
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}
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if (dimensions['PointSourceId']) {
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pointSourceIdBuffer = new ArrayBuffer(numPoints * 2);
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pointSourceId = new Uint16Array(pointSourceIdBuffer);
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pointSourceIdExtractor = getExtractor('PointSourceId');
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}
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let mean = [0, 0, 0];
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let bounds = {
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min: [Number.MAX_VALUE, Number.MAX_VALUE, Number.MAX_VALUE],
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max: [-Number.MAX_VALUE, -Number.MAX_VALUE, -Number.MAX_VALUE],
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};
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let x, y, z, r, g, b;
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for (let i = 0; i < numPoints; ++i) {
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let pos = i * pointSize;
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if (xyz) {
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x = xyzExtractor[0](pos) * scale.x + offset.x - mins[0];
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y = xyzExtractor[1](pos) * scale.y + offset.y - mins[1];
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z = xyzExtractor[2](pos) * scale.z + offset.z - mins[2];
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mean[0] += x / numPoints;
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mean[1] += y / numPoints;
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mean[2] += z / numPoints;
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bounds.min[0] = Math.min(bounds.min[0], x);
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bounds.min[1] = Math.min(bounds.min[1], y);
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bounds.min[2] = Math.min(bounds.min[2], z);
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bounds.max[0] = Math.max(bounds.max[0], x);
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bounds.max[1] = Math.max(bounds.max[1], y);
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bounds.max[2] = Math.max(bounds.max[2], z);
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xyz[3 * i + 0] = x;
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xyz[3 * i + 1] = y;
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xyz[3 * i + 2] = z;
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}
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if (rgb) {
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r = rgbExtractor[0](pos);
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g = rgbExtractor[1](pos);
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b = rgbExtractor[2](pos);
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if (twoByteColor) {
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r /= 256;
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g /= 256;
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b /= 256;
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}
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rgb[4 * i + 0] = r;
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rgb[4 * i + 1] = g;
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rgb[4 * i + 2] = b;
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}
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if (intensity) intensity[i] = intensityExtractor(pos);
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if (classification) classification[i] = classificationExtractor(pos);
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if (returnNumber) returnNumber[i] = returnNumberExtractor(pos);
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if (numberOfReturns) numberOfReturns[i] = numberOfReturnsExtractor(pos);
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if (pointSourceId) pointSourceId[i] = pointSourceIdExtractor(pos);
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}
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let indicesBuffer = new ArrayBuffer(numPoints * 4);
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let indices = new Uint32Array(indicesBuffer);
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for (let i = 0; i < numPoints; ++i) {
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indices[i] = i;
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}
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let message = {
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numPoints: numPoints,
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tightBoundingBox: bounds,
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mean: mean,
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position: xyzBuffer,
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color: rgbBuffer,
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intensity: intensityBuffer,
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classification: classificationBuffer,
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returnNumber: returnNumberBuffer,
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numberOfReturns: numberOfReturnsBuffer,
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pointSourceId: pointSourceIdBuffer,
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indices: indicesBuffer
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};
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let transferables = [
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message.position,
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message.color,
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message.intensity,
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message.classification,
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message.returnNumber,
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message.numberOfReturns,
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message.pointSourceId,
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message.indices
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].filter((v) => v);
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postMessage(message, transferables);
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}
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