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9 Commits
1c62f2783c
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| Author | SHA1 | Date | |
|---|---|---|---|
| 71b7b16bdd | |||
| 1936d90550 | |||
| 8bf74e51ea | |||
| 21e46713a7 | |||
| 726d56131c | |||
| 874901086d | |||
| a98577e206 | |||
| 9e90823858 | |||
| 269e62b5fb |
@@ -75,14 +75,18 @@ async function localDetect(imageData) {
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console.time('sw: post-process')
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const outputSize = res.shape[1]
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const output = {
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detections: []
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}
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let rawBoxes = []
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let rawScores = []
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let getScores, getBox, boxCalc
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for (var i = 0; i < rawRes.length; i++) {
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var getScores = rawRes[i].slice(4)
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for (let i = 0; i < rawRes.length; i++) {
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getScores = rawRes[i].slice(4)
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if (getScores.every( s => s < .05)) { continue }
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var getBox = rawRes[i].slice(0,4)
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var boxCalc = [
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getBox = rawRes[i].slice(0,4)
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boxCalc = [
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(getBox[0] - (getBox[2] / 2)) / modelWidth,
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(getBox[1] - (getBox[3] / 2)) / modelHeight,
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(getBox[0] + (getBox[2] / 2)) / modelWidth,
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@@ -101,7 +105,7 @@ async function localDetect(imageData) {
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let boxes_data = []
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let scores_data = []
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let classes_data = []
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for (var c = 0; c < outputSize - 4; c++) {
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for (let c = 0; c < outputSize - 4; c++) {
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structureScores = rawScores.map(x => x[c])
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tScores = tf.tensor1d(structureScores)
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resBoxes = await tf.image.nonMaxSuppressionAsync(tBoxes,tScores,10,0.5,.05)
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@@ -109,7 +113,7 @@ async function localDetect(imageData) {
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tf.dispose(resBoxes)
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if (validBoxes) {
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boxes_data.push(...rawBoxes.filter( (_, idx) => validBoxes.includes(idx)))
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var outputScores = structureScores.filter( (_, idx) => validBoxes.includes(idx))
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let outputScores = structureScores.filter( (_, idx) => validBoxes.includes(idx))
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scores_data.push(...outputScores)
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classes_data.push(...outputScores.fill(c))
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}
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@@ -119,18 +123,15 @@ async function localDetect(imageData) {
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tf.dispose(tBoxes)
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tf.dispose(tScores)
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tf.dispose(tRes)
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tf.dispose(resBoxes)
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const valid_detections_data = classes_data.length
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var output = {
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detections: []
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}
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for (var i =0; i < valid_detections_data; i++) {
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var [dLeft, dTop, dRight, dBottom] = boxes_data[i]
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for (let i =0; i < valid_detections_data; i++) {
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let [dLeft, dTop, dRight, dBottom] = boxes_data[i]
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output.detections.push({
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"top": dTop,
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"left": dLeft,
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"bottom": dBottom,
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"right": dRight,
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// "label": this.detectorLabels[classes_data[i]].name,
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"label": classes_data[i],
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"confidence": scores_data[i] * 100
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})
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@@ -155,7 +156,7 @@ async function videoFrame (vidData) {
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const rawRes = tf.transpose(res,[0,2,1]).arraySync()[0]
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if (rawRes) {
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for (var i = 0; i < rawRes.length; i++) {
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for (let i = 0; i < rawRes.length; i++) {
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let getScores = rawRes[i].slice(4)
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if (getScores.some( s => s > .5)) {
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let foundTarget = rawRes[i].slice(0,2)
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@@ -74,12 +74,14 @@
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}
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},
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async created () {
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document.addEventListener('wheel', event => {
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event.preventDefault()
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}, {passive: false})
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document.addEventListener('touchmove', event => {
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event.preventDefault()
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}, {passive: false})
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document.addEventListener('keydown', e => {
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if (e.code == 'KeyR') {
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console.log(f7.views.main.router.history)
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}
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if (e.code == 'KeyB') {
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f7.views.main.router.back()
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}
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})
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if (!window.cordova) {
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const confText = await fetch('./conf/conf.yaml')
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.then((mod) => { return mod.text() })
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@@ -18,7 +18,7 @@
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<meta name="msapplication-tap-highlight" content="no">
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<title>ALVINN</title>
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<% if (TARGET === 'web') { %>
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<meta name="apple-mobile-web-app-capable" content="yes">
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<meta name="mobile-web-app-capable" content="yes">
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<meta name="apple-mobile-web-app-status-bar-style" content="black-translucent">
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<link rel="apple-touch-icon" href="icons/apple-touch-icon.png">
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<link rel="icon" href="icons/favicon.png">
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157
src/js/structures.js
Normal file
157
src/js/structures.js
Normal file
@@ -0,0 +1,157 @@
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class Coordinate {
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constructor(x, y) {
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this.x = x
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this.y = y
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}
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toRefFrame(...frameArgs) {
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if (frameArgs.length == 0) {
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return {x: this.x, y: this.y}
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}
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let outFrames = []
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//Get Coordinates in Image Reference Frame
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if (frameArgs[0].tagName == 'IMG' && frameArgs[0].width && frameArgs[0].height) {
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outFrames.push({
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x: this.x * frameArgs[0].width,
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y: this.y * frameArgs[0].height
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})
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} else {
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throw new Error('Coordinate: invalid reference frame for frameType: Image')
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}
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//Get Coordinates in Canvas Reference Frame
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if (frameArgs[1]) {
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if (frameArgs[1].tagName == 'CANVAS' && frameArgs[1].width && frameArgs[1].height) {
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let imgWidth
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let imgHeight
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const imgAspect = frameArgs[0].width / frameArgs[0].height
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const rendAspect = frameArgs[1].width / frameArgs[1].height
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if (imgAspect >= rendAspect) {
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imgWidth = frameArgs[1].width
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imgHeight = frameArgs[1].width / imgAspect
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} else {
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imgWidth = frameArgs[1].height * imgAspect
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imgHeight = frameArgs[1].height
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}
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outFrames.push({
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x: (frameArgs[1].width - imgWidth) / 2 + this.x * imgWidth,
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y: (frameArgs[1].height - imgHeight) / 2 + this.y * imgHeight
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})
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} else {
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throw new Error('Coordinate: invalid reference frame for frameType: Canvas')
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}
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}
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//Get Coordinates in Screen Reference Frame
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if (frameArgs[2]) {
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if (frameArgs[2].zoom && frameArgs[2].offset && frameArgs[2].offset.x !== undefined && frameArgs[2].offset.y !== undefined) {
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outFrames.push({
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x: outFrames[1].x * frameArgs[2].zoom + frameArgs[2].offset.x,
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y: outFrames[1].y * frameArgs[2].zoom + frameArgs[2].offset.y
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})
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} else {
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throw new Error('Coordinate: invalid reference frame for frameType: Screen')
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}
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}
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return outFrames
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}
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toString() {
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return `(x: ${this.x}, y: ${this.y})`
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}
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}
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export class StructureBox {
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constructor(top, left, bottom, right) {
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this.topLeft = new Coordinate(left, top)
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this.bottomRight = new Coordinate(right, bottom)
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}
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getBoxes(boxType, ...frameArgs) {
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let lowerH, lowerV, calcSide
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switch (boxType) {
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case 'point':
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lowerH = 'right'
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lowerV = 'bottom'
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break
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case 'side':
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lowerH = 'width'
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lowerV = 'height'
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calcSide = true
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break
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default:
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throw new Error(`StructureBox: invalid boxType - ${boxType}`)
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}
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if (frameArgs.length == 0) {
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return {
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left: this.topLeft.x,
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top: this.topLeft.y,
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[lowerH]: this.bottomRight.x - ((calcSide) ? this.topLeft.x : 0),
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[lowerV]: this.bottomRight.y - ((calcSide) ? this.topLeft.y : 0)
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}
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}
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const tL = this.topLeft.toRefFrame(...frameArgs)
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const bR = this.bottomRight.toRefFrame(...frameArgs)
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let outBoxes = []
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tL.forEach((cd, i) => {
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outBoxes.push({
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left: cd.x,
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top: cd.y,
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[lowerH]: bR[i].x - ((calcSide) ? cd.x : 0),
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[lowerV]: bR[i].y - ((calcSide) ? cd.y : 0)
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})
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})
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return outBoxes
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}
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}
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export class Structure {
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constructor(structResult) {
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this.label = structResult.label
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this.confidence = structResult.confidence
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this.box = new StructureBox(
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structResult.top,
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structResult.left,
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structResult.bottom,
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structResult.right
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)
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this.deleted = false
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this.index = -1
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this.passThreshold = true
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this.searched = false
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}
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get resultIndex() {
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return this.index
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}
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set resultIndex(newIdx) {
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this.index = newIdx
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}
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get isDeleted() {
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return this.deleted
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}
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set isDeleted(del) {
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this.deleted = !!del
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}
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get isSearched() {
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return this.searched
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}
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set isSearched(ser) {
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this.searched = !!ser
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}
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get aboveThreshold() {
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return this.passThreshold
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}
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setThreshold(level) {
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if (typeof level != 'number') {
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throw new Error(`Structure: invalid threshold level ${level}`)
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}
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this.passThreshold = this.confidence >= level
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}
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}
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@@ -3,11 +3,11 @@ import { f7 } from 'framework7-vue'
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export default {
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methods: {
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async openCamera(imContain) {
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var cameraLoaded = false
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let cameraLoaded = false
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const devicesList = await navigator.mediaDevices.enumerateDevices()
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this.videoDeviceAvailable = devicesList.some( d => d.kind == "videoinput")
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if (this.videoDeviceAvailable) {
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var vidConstraint = {
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let videoDeviceAvailable = devicesList.some( d => d.kind == "videoinput")
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if (videoDeviceAvailable) {
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let vidConstraint = {
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video: {
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width: {
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ideal: imContain.offsetWidth
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@@ -41,24 +41,24 @@ export default {
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tempCtx.drawImage(vidViewer, 0, 0)
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this.getImage(tempCVS.toDataURL())
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},
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async videoFrameDetectWorker (vidData) {
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async videoFrameDetectWorker (vidData, vidWorker) {
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const startDetection = () => {
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createImageBitmap(vidData).then(imVideoFrame => {
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this.vidWorker.postMessage({call: 'videoFrame', image: imVideoFrame}, [imVideoFrame])
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vidWorker.postMessage({call: 'videoFrame', image: imVideoFrame}, [imVideoFrame])
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})
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}
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vidData.addEventListener('resize',startDetection,{once: true})
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this.vidWorker.onmessage = (eVid) => {
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vidWorker.onmessage = (eVid) => {
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if (eVid.data.error) {
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console.log(eVid.data.message)
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f7.dialog.alert(`ALVINN AI model error: ${eVid.data.message}`)
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} else if (this.videoAvailable) {
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createImageBitmap(vidData).then(imVideoFrame => {
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this.vidWorker.postMessage({call: 'videoFrame', image: imVideoFrame}, [imVideoFrame])
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vidWorker.postMessage({call: 'videoFrame', image: imVideoFrame}, [imVideoFrame])
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})
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if (eVid.data.coords) {
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imageCtx.clearRect(0,0,imCanvas.width,imCanvas.height)
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for (var coord of eVid.data.coords) {
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for (let coord of eVid.data.coords) {
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let pointX = (imCanvas.width - imgWidth) / 2 + (coord[0] / eVid.data.modelWidth) * imgWidth - 10
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let pointY = (imCanvas.height - imgHeight) / 2 + (coord[1] / eVid.data.modelHeight) * imgHeight - 10
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console.debug(`cx: ${pointX}, cy: ${pointY}`)
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@@ -72,8 +72,7 @@ export default {
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const imCanvas = this.$refs.image_cvs
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const imageCtx = imCanvas.getContext("2d")
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const target = this.$refs.target_image
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var imgWidth
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var imgHeight
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let imgWidth, imgHeight
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f7.utils.nextFrame(() => {
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imCanvas.width = imCanvas.clientWidth
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imCanvas.height = imCanvas.clientHeight
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@@ -56,7 +56,7 @@
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},
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computed: {
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commentText () {
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var text = f7.textEditor.get('.comment-editor').getValue()
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let text = f7.textEditor.get('.comment-editor').getValue()
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if (this.userEmail) {
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text += `\\n\\nSubmitted by: ${this.userEmail}`
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}
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@@ -65,9 +65,9 @@
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},
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methods: {
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sendFeedback () {
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var self = this
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var issueURL = `https://gitea.azgeorgis.net/api/v1/repos/Georgi_Lab/ALVINN_f7/issues?access_token=9af8ae15b1ee5a98afcb3083bb488e4cf3c683af`
|
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var xhr = new XMLHttpRequest()
|
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let self = this
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const issueURL = `https://gitea.azgeorgis.net/api/v1/repos/Georgi_Lab/ALVINN_f7/issues?access_token=9af8ae15b1ee5a98afcb3083bb488e4cf3c683af`
|
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let xhr = new XMLHttpRequest()
|
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xhr.open("POST", issueURL)
|
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xhr.setRequestHeader('Content-Type', 'application/json')
|
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xhr.setRequestHeader('accept', 'application/json')
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@@ -1,8 +1,8 @@
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<template>
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<f7-page name="detect" :id="detectorName + '-detect-page'">
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<f7-page name="detect" :id="detectorName + '-detect-page'" @wheel="(e = $event) => e.preventDefault()" @touchmove="(e = $event) => e.preventDefault()">
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<!-- Top Navbar -->
|
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<f7-navbar :sliding="false" :back-link="true" back-link-url="/" back-link-force>
|
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<f7-nav-title sliding>{{ regions[activeRegion] }}</f7-nav-title>
|
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<f7-nav-title sliding>{{ regionTitle }}</f7-nav-title>
|
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<f7-nav-right>
|
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<f7-link v-if="!isCordova" :icon-only="true" tooltip="Fullscreen" :icon-f7="isFullscreen ? 'viewfinder_circle_fill' : 'viewfinder'" @click="toggleFullscreen"></f7-link>
|
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<f7-link :icon-only="true" tooltip="ALVINN help" icon-f7="question_circle_fill" href="/help/"></f7-link>
|
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@@ -29,8 +29,9 @@
|
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@click="structureClick"
|
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:style="`display: ${(imageLoaded || videoAvailable) ? 'block' : 'none'}; flex: 1 1 0%; max-width: 100%; max-height: 100%; min-width: 0; min-height: 0; background-size: contain; background-position: center; background-repeat: no-repeat; z-index: 2;`"
|
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></canvas>
|
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<f7-link v-if="getInfoUrl && (selectedChip > -1)"
|
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:style="`left: ${infoLinkPos.x}px; top: ${infoLinkPos.y}px; transform: translate(-50%,-50%); background: hsla(${showResults[selectedChip].confidence / 100 * 120}deg, 100%, 50%, .5)`" class="structure-info"
|
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<f7-link v-if="getInfoUrl && (selectedChip > -1) && showResults[selectedChip]"
|
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:style="`left: ${infoLinkPos.x}px; top: ${infoLinkPos.y}px; transform: translate(-50%,-50%); background: hsla(${showResults[selectedChip].confidence / 100 * 120}deg, 100%, 50%, .5)`"
|
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class="structure-info"
|
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:icon-only="true"
|
||||
icon-f7="info"
|
||||
target="_blank"
|
||||
@@ -143,7 +144,22 @@
|
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import touchMixin from './touch-mixin'
|
||||
|
||||
import detectionWorker from '@/assets/detect-worker.js?worker&inline'
|
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import { Structure, StructureBox } from '../js/structures'
|
||||
|
||||
const regions = ['Thorax','Abdomen/Pelvis','Limbs','Head and Neck']
|
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let activeRegion = 4
|
||||
let classesList = []
|
||||
let imageLoadMode = "environment"
|
||||
let serverSettings = {}
|
||||
let otherSettings = {}
|
||||
let modelLocation = ''
|
||||
let miniLocation = ''
|
||||
let reloadModel = false
|
||||
let detectWorker = null
|
||||
let vidWorker = null
|
||||
let canvasMoving = false
|
||||
let imageLocation = new StructureBox(0, 0, 1, 1)
|
||||
|
||||
export default {
|
||||
mixins: [submitMixin, detectionMixin, cameraMixin, touchMixin],
|
||||
props: {
|
||||
@@ -155,38 +171,24 @@
|
||||
},
|
||||
data () {
|
||||
return {
|
||||
regions: ['Thorax','Abdomen/Pelvis','Limbs','Head and Neck'],
|
||||
resultData: {},
|
||||
selectedChip: -1,
|
||||
activeRegion: 4,
|
||||
classesList: [],
|
||||
imageLoaded: false,
|
||||
imageView: new Image(),
|
||||
imCvsLocation: {},
|
||||
imageLoadMode: "environment",
|
||||
detecting: false,
|
||||
detectPanel: false,
|
||||
showDetectSettings: false,
|
||||
detectorName: '',
|
||||
detectorLevel: 50,
|
||||
detectorLabels: [],
|
||||
serverSettings: {},
|
||||
otherSettings: {},
|
||||
isCordova: !!window.cordova,
|
||||
secureProtocol: location.protocol == 'https:',
|
||||
uploadUid: null,
|
||||
uploadDirty: false,
|
||||
modelLocation: '',
|
||||
miniLocation: '',
|
||||
modelLoading: true,
|
||||
reloadModel: false,
|
||||
videoDeviceAvailable: false,
|
||||
videoAvailable: false,
|
||||
cameraStream: null,
|
||||
infoLinkPos: {},
|
||||
detectWorker: null,
|
||||
vidWorker: null,
|
||||
canvasMoving: false,
|
||||
canvasOffset: {x: 0, y: 0},
|
||||
canvasZoom: 1,
|
||||
structureZoomed: false,
|
||||
@@ -198,44 +200,44 @@
|
||||
},
|
||||
created () {
|
||||
let loadOtherSettings = localStorage.getItem('otherSettings')
|
||||
if (loadOtherSettings) this.otherSettings = JSON.parse(loadOtherSettings)
|
||||
if (loadOtherSettings) otherSettings = JSON.parse(loadOtherSettings)
|
||||
this.detectorName = this.f7route.params.region
|
||||
switch (this.detectorName) {
|
||||
case 'thorax':
|
||||
this.activeRegion = 0
|
||||
activeRegion = 0
|
||||
break;
|
||||
case 'abdomen':
|
||||
this.activeRegion = 1
|
||||
activeRegion = 1
|
||||
break;
|
||||
case 'limbs':
|
||||
this.activeRegion = 2
|
||||
activeRegion = 2
|
||||
break;
|
||||
case 'head':
|
||||
this.activeRegion = 3
|
||||
activeRegion = 3
|
||||
break;
|
||||
}
|
||||
let modelJ = `../models/${this.detectorName}${this.otherSettings.mini ? '-mini' : ''}/model.json`
|
||||
let modelJ = `../models/${this.detectorName}${otherSettings.mini ? '-mini' : ''}/model.json`
|
||||
let miniJ = `../models/${this.detectorName}-mini/model.json`
|
||||
this.modelLocation = new URL(modelJ,import.meta.url).href
|
||||
this.miniLocation = new URL(miniJ,import.meta.url).href
|
||||
modelLocation = new URL(modelJ,import.meta.url).href
|
||||
miniLocation = new URL(miniJ,import.meta.url).href
|
||||
let classesJ = `../models/${this.detectorName}/classes.json`
|
||||
fetch(new URL(classesJ,import.meta.url).href)
|
||||
.then((mod) => { return mod.json() })
|
||||
.then((classes) => {
|
||||
this.classesList = classes
|
||||
this.detectorLabels = this.classesList.map( l => { return {'name': l, 'detect': true} } )
|
||||
classesList = classes
|
||||
this.detectorLabels = classesList.map( l => { return {'name': l, 'detect': true} } )
|
||||
})
|
||||
var loadServerSettings = localStorage.getItem('serverSettings')
|
||||
if (loadServerSettings) this.serverSettings = JSON.parse(loadServerSettings)
|
||||
const loadServerSettings = localStorage.getItem('serverSettings')
|
||||
if (loadServerSettings) serverSettings = JSON.parse(loadServerSettings)
|
||||
},
|
||||
mounted () {
|
||||
if (this.serverSettings && this.serverSettings.use) {
|
||||
if (serverSettings && serverSettings.use) {
|
||||
this.getRemoteLabels()
|
||||
this.modelLoading = false
|
||||
} else {
|
||||
this.modelLoading = true
|
||||
if (!this.useWorkers) {
|
||||
this.loadModel(this.modelLocation, true).then(() => {
|
||||
this.loadModel(modelLocation, true).then(() => {
|
||||
this.modelLoading = false
|
||||
}).catch((e) => {
|
||||
console.log(e.message)
|
||||
@@ -243,8 +245,8 @@
|
||||
this.modelLoading = false
|
||||
})
|
||||
} else {
|
||||
this.detectWorker = new detectionWorker()
|
||||
this.detectWorker.onmessage = (eMount) => {
|
||||
detectWorker = new detectionWorker()
|
||||
detectWorker.onmessage = (eMount) => {
|
||||
self = this
|
||||
if (eMount.data.error) {
|
||||
console.log(eMount.data.message)
|
||||
@@ -252,21 +254,24 @@
|
||||
}
|
||||
self.modelLoading = false
|
||||
}
|
||||
this.vidWorker = new detectionWorker()
|
||||
this.vidWorker.onmessage = (eMount) => {
|
||||
vidWorker = new detectionWorker()
|
||||
vidWorker.onmessage = (eMount) => {
|
||||
self = this
|
||||
if (eMount.data.error) {
|
||||
console.log(eMount.data.message)
|
||||
f7.dialog.alert(`ALVINN AI nano model error: ${eMount.data.message}`)
|
||||
}
|
||||
}
|
||||
this.detectWorker.postMessage({call: 'loadModel', weights: this.modelLocation, preload: true})
|
||||
this.vidWorker.postMessage({call: 'loadModel', weights: this.miniLocation, preload: true})
|
||||
detectWorker.postMessage({call: 'loadModel', weights: modelLocation, preload: true})
|
||||
vidWorker.postMessage({call: 'loadModel', weights: miniLocation, preload: true})
|
||||
}
|
||||
}
|
||||
window.onresize = (e) => { if (this.$refs.image_cvs) this.selectChip('redraw') }
|
||||
},
|
||||
computed: {
|
||||
regionTitle () {
|
||||
return regions[activeRegion]
|
||||
},
|
||||
message () {
|
||||
if (this.modelLoading) {
|
||||
return "Preparing ALVINN..."
|
||||
@@ -279,17 +284,17 @@
|
||||
}
|
||||
},
|
||||
showResults () {
|
||||
var filteredResults = this.resultData.detections
|
||||
let filteredResults = this.resultData.detections
|
||||
if (!filteredResults) return []
|
||||
|
||||
var allSelect = this.detectorLabels.every( s => { return s.detect } )
|
||||
var selectedLabels = this.detectorLabels
|
||||
const allSelect = this.detectorLabels.every( s => { return s.detect } )
|
||||
const selectedLabels = this.detectorLabels
|
||||
.filter( l => { return l.detect })
|
||||
.map( l => { return l.name })
|
||||
filteredResults.forEach( (d, i) => {
|
||||
filteredResults[i].resultIndex = i
|
||||
filteredResults[i].aboveThreshold = d.confidence >= this.detectorLevel
|
||||
filteredResults[i].isSearched = allSelect || selectedLabels.includes(d.label)
|
||||
d.resultIndex = i
|
||||
d.setThreshold(this.detectorLevel)
|
||||
d.isSearched = allSelect || selectedLabels.includes(d.label)
|
||||
})
|
||||
|
||||
if (!filteredResults.some( s => s.resultIndex == this.selectedChip && s.aboveThreshold && s.isSearched && !s.isDeleted)) {
|
||||
@@ -310,7 +315,7 @@
|
||||
}
|
||||
},
|
||||
demoEnabled () {
|
||||
return this.otherSettings.demo || this.demoMode
|
||||
return otherSettings.demo || this.demoMode
|
||||
},
|
||||
infoLinkTarget () {
|
||||
if (!this.getInfoUrl) return ''
|
||||
@@ -324,8 +329,8 @@
|
||||
return `--chip-media-gradient: conic-gradient(from ${270 - (confFactor * 360 / 2)}deg, hsl(${confFactor * 120}deg, 100%, 50%) ${confFactor}turn, hsl(${confFactor * 120}deg, 50%, 66%) ${confFactor}turn)`
|
||||
},
|
||||
async setData () {
|
||||
if (this.detectWorker) {
|
||||
this.detectWorker.onmessage = (eDetect) => {
|
||||
if (detectWorker) {
|
||||
detectWorker.onmessage = (eDetect) => {
|
||||
self = this
|
||||
if (eDetect.data.error) {
|
||||
self.detecting = false
|
||||
@@ -334,13 +339,15 @@
|
||||
f7.dialog.alert(`ALVINN structure finding error: ${eDetect.data.message}`)
|
||||
} else if (eDetect.data.success == 'detection') {
|
||||
self.detecting = false
|
||||
self.resultData = eDetect.data.detections
|
||||
if (self.resultData) {
|
||||
self.resultData.detections.map(d => {d.label = self.detectorLabels[d.label].name})
|
||||
}
|
||||
self.resultData = {detections: []}
|
||||
eDetect.data.detections.detections.forEach((d) => {
|
||||
d.label = self.detectorLabels[d.label].name
|
||||
let detectedStructure = new Structure(d)
|
||||
self.resultData.detections.push(detectedStructure)
|
||||
})
|
||||
self.uploadDirty = true
|
||||
} else if (eDetect.data.success == 'model') {
|
||||
self.reloadModel = false
|
||||
reloadModel = false
|
||||
loadSuccess()
|
||||
}
|
||||
f7.utils.nextFrame(() => {
|
||||
@@ -352,26 +359,26 @@
|
||||
let loadSuccess = null
|
||||
let loadFailure = null
|
||||
let modelReloading = null
|
||||
if (!this.useWorkers && this.reloadModel) {
|
||||
await this.loadModel(this.modelLocation)
|
||||
this.reloadModel = false
|
||||
if (!this.useWorkers && reloadModel) {
|
||||
await this.loadModel(modelLocation)
|
||||
reloadModel = false
|
||||
} else {
|
||||
modelReloading = new Promise((res, rej) => {
|
||||
loadSuccess = res
|
||||
loadFailure = rej
|
||||
if (this.reloadModel) {
|
||||
this.detectWorker.postMessage({call: 'loadModel', weights: this.modelLocation})
|
||||
if (reloadModel) {
|
||||
detectWorker.postMessage({call: 'loadModel', weights: modelLocation})
|
||||
} else {
|
||||
loadSuccess()
|
||||
}
|
||||
})
|
||||
}
|
||||
|
||||
if (this.serverSettings && this.serverSettings.use) {
|
||||
if (serverSettings && serverSettings.use) {
|
||||
this.remoteDetect()
|
||||
} else if (this.useWorkers) {
|
||||
Promise.all([modelReloading,createImageBitmap(this.imageView)]).then(res => {
|
||||
this.detectWorker.postMessage({call: 'localDetect', image: res[1]}, [res[1]])
|
||||
detectWorker.postMessage({call: 'localDetect', image: res[1]}, [res[1]])
|
||||
})
|
||||
} else {
|
||||
createImageBitmap(this.imageView).then(res => {
|
||||
@@ -399,12 +406,12 @@
|
||||
}
|
||||
},
|
||||
async selectImage (mode) {
|
||||
this.imageLoadMode = mode
|
||||
imageLoadMode = mode
|
||||
if (this.isCordova && mode == "camera") {
|
||||
navigator.camera.getPicture(this.getImage, this.onFail, { quality: 50, destinationType: Camera.DestinationType.DATA_URL, correctOrientation: true });
|
||||
return
|
||||
}
|
||||
if (mode == "camera" && !this.otherSettings.disableVideo) {
|
||||
if (mode == "camera" && !otherSettings.disableVideo) {
|
||||
this.videoAvailable = await this.openCamera(this.$refs.image_container)
|
||||
if (this.videoAvailable) {
|
||||
this.selectedChip = -1
|
||||
@@ -412,14 +419,14 @@
|
||||
this.imageView.src = null
|
||||
this.$refs.image_cvs.style['background-image'] = 'none'
|
||||
this.resultData = {}
|
||||
var trackDetails = this.cameraStream.getVideoTracks()[0].getSettings()
|
||||
var vidElement = this.$refs.vid_viewer
|
||||
const trackDetails = this.cameraStream.getVideoTracks()[0].getSettings()
|
||||
let vidElement = this.$refs.vid_viewer
|
||||
vidElement.width = trackDetails.width
|
||||
vidElement.height = trackDetails.height
|
||||
if (!this.useWorkers) {
|
||||
this.videoFrameDetect(vidElement)
|
||||
this.videoFrameDetect(vidElement, miniLocation)
|
||||
} else {
|
||||
this.videoFrameDetectWorker(vidElement)
|
||||
this.videoFrameDetectWorker(vidElement, vidWorker)
|
||||
}
|
||||
return
|
||||
}
|
||||
@@ -445,7 +452,6 @@
|
||||
return clip[0].getType("image/png");
|
||||
}).then(blob => {
|
||||
let clipImage = URL.createObjectURL(blob);
|
||||
console.log(clipImage)
|
||||
this.getImage(clipImage)
|
||||
}).catch(e => {
|
||||
console.log(e)
|
||||
@@ -473,33 +479,25 @@
|
||||
iChip = this.selectedChip
|
||||
}
|
||||
const [imCanvas, imageCtx] = this.resetView(true)
|
||||
let structLeft = this.imageView.width * this.resultData.detections[iChip].left
|
||||
let structTop = this.imageView.height * this.resultData.detections[iChip].top
|
||||
let structWidth = this.imageView.width * (this.resultData.detections[iChip].right - this.resultData.detections[iChip].left)
|
||||
let structHeight = this.imageView.height * (this.resultData.detections[iChip].bottom - this.resultData.detections[iChip].top)
|
||||
let structBox, cvsBox, screenBox
|
||||
[structBox, cvsBox, screenBox] = this.resultData.detections[iChip].box.getBoxes('side', this.imageView, imCanvas, {zoom: this.canvasZoom, offset: {...this.canvasOffset}})
|
||||
|
||||
const boxCoords = this.box2cvs(this.resultData.detections[iChip])[0]
|
||||
this.infoLinkPos.x = Math.min(Math.max(screenBox.left, 0),imCanvas.width)
|
||||
this.infoLinkPos.y = Math.min(Math.max(screenBox.top, 0), imCanvas.height)
|
||||
|
||||
let boxLeft = boxCoords.cvsLeft
|
||||
let boxTop = boxCoords.cvsTop
|
||||
let boxWidth = boxCoords.cvsRight - boxCoords.cvsLeft
|
||||
let boxHeight = boxCoords.cvsBottom - boxCoords.cvsTop
|
||||
this.infoLinkPos.x = Math.min(Math.max(boxCoords.cvsLeft * this.canvasZoom + this.canvasOffset.x, 0),imCanvas.width)
|
||||
this.infoLinkPos.y = Math.min(Math.max(boxCoords.cvsTop * this.canvasZoom + this.canvasOffset.y, 0), imCanvas.height)
|
||||
|
||||
let imageScale = Math.max(this.imageView.width / imCanvas.width, this.imageView.height / imCanvas.height)
|
||||
imageCtx.drawImage(this.imageView, structLeft, structTop, structWidth, structHeight, boxLeft, boxTop, boxWidth, boxHeight)
|
||||
const imageScale = Math.max(this.imageView.width / imCanvas.width, this.imageView.height / imCanvas.height)
|
||||
imageCtx.drawImage(this.imageView, structBox.left, structBox.top, structBox.width, structBox.height, cvsBox.left, cvsBox.top, cvsBox.width, cvsBox.height)
|
||||
imageCtx.save()
|
||||
imageCtx.arc(boxLeft, boxTop, 14 / this.canvasZoom, 0, 2 * Math.PI)
|
||||
imageCtx.arc(cvsBox.left, cvsBox.top, 14 / this.canvasZoom, 0, 2 * Math.PI)
|
||||
imageCtx.closePath()
|
||||
imageCtx.clip()
|
||||
imageCtx.drawImage(this.imageView,
|
||||
structLeft - (14 / this.canvasZoom * imageScale),
|
||||
structTop - (14 / this.canvasZoom * imageScale),
|
||||
structBox.left - (14 / this.canvasZoom * imageScale),
|
||||
structBox.top - (14 / this.canvasZoom * imageScale),
|
||||
(28 / this.canvasZoom * imageScale),
|
||||
(28 / this.canvasZoom * imageScale),
|
||||
boxLeft - (14 / this.canvasZoom),
|
||||
boxTop - (14 / this.canvasZoom),
|
||||
cvsBox.left - (14 / this.canvasZoom),
|
||||
cvsBox.top - (14 / this.canvasZoom),
|
||||
(28 / this.canvasZoom), (28 / this.canvasZoom))
|
||||
imageCtx.restore()
|
||||
this.selectedChip = iChip
|
||||
@@ -529,13 +527,9 @@
|
||||
imageCtx.strokeStyle = 'yellow'
|
||||
imageCtx.lineWidth = 3 / this.canvasZoom
|
||||
if (this.imageLoaded) {
|
||||
let imageLoc = this.box2cvs({top: 0,left: 0,right: 1,bottom: 1})
|
||||
this.imCvsLocation.top = imageLoc[0].cvsTop
|
||||
this.imCvsLocation.left = imageLoc[0].cvsLeft
|
||||
this.imCvsLocation.width = imageLoc[0].cvsRight - imageLoc[0].cvsLeft
|
||||
this.imCvsLocation.height = imageLoc[0].cvsBottom - imageLoc[0].cvsTop
|
||||
const imageLoc = imageLocation.getBoxes('side', this.imageView, imCanvas)
|
||||
if (drawChip) {imageCtx.globalAlpha = .5}
|
||||
imageCtx.drawImage(this.imageView, 0, 0, this.imageView.width, this.imageView.height, this.imCvsLocation.left, this.imCvsLocation.top, this.imCvsLocation.width, this.imCvsLocation.height)
|
||||
imageCtx.drawImage(this.imageView, 0, 0, this.imageView.width, this.imageView.height, imageLoc[1].left, imageLoc[1].top, imageLoc[1].width, imageLoc[1].height)
|
||||
if (drawChip) {imageCtx.globalAlpha = 1}
|
||||
}
|
||||
this.structureZoomed = false
|
||||
@@ -546,13 +540,13 @@
|
||||
if (this.videoAvailable) {
|
||||
this.closeCamera()
|
||||
this.detecting = true
|
||||
this.reloadModel = true
|
||||
reloadModel = true
|
||||
resolve(searchImage)
|
||||
} else if (this.isCordova && this.imageLoadMode == "camera") {
|
||||
} else if (this.isCordova && imageLoadMode == "camera") {
|
||||
this.detecting = true
|
||||
resolve('data:image/jpg;base64,' + searchImage)
|
||||
}
|
||||
if (this.imageLoadMode == 'clipboard') {
|
||||
if (imageLoadMode == 'clipboard') {
|
||||
this.detecting = true
|
||||
resolve(searchImage)
|
||||
}
|
||||
@@ -561,7 +555,7 @@
|
||||
this.detecting = true
|
||||
resolve(reader.result)
|
||||
},{once: true})
|
||||
if (this.imageLoadMode == 'sample') {
|
||||
if (imageLoadMode == 'sample') {
|
||||
fetch(`${this.isCordova ? 'https://localhost' : '.'}/samples/${this.detectorName}-${searchImage}.jpeg`).then( resp => {
|
||||
return resp.blob()
|
||||
}).then(respBlob => {
|
||||
@@ -589,12 +583,8 @@
|
||||
imCanvas.width = imCanvas.clientWidth
|
||||
imCanvas.height = imCanvas.clientHeight
|
||||
const imageCtx = imCanvas.getContext("2d")
|
||||
let imageLoc = this.box2cvs({top: 0,left: 0,right: 1,bottom: 1})
|
||||
this.imCvsLocation.top = imageLoc[0].cvsTop
|
||||
this.imCvsLocation.left = imageLoc[0].cvsLeft
|
||||
this.imCvsLocation.width = imageLoc[0].cvsRight - imageLoc[0].cvsLeft
|
||||
this.imCvsLocation.height = imageLoc[0].cvsBottom - imageLoc[0].cvsTop
|
||||
imageCtx.drawImage(this.imageView, 0, 0, this.imageView.width, this.imageView.height, this.imCvsLocation.left, this.imCvsLocation.top, this.imCvsLocation.width, this.imCvsLocation.height)
|
||||
const imageLoc = imageLocation.getBoxes('side', this.imageView, imCanvas)
|
||||
imageCtx.drawImage(this.imageView, 0, 0, this.imageView.width, this.imageView.height, imageLoc[1].left, imageLoc[1].top, imageLoc[1].width, imageLoc[1].height)
|
||||
f7.utils.nextFrame(() => {
|
||||
this.setData()
|
||||
})
|
||||
@@ -604,7 +594,7 @@
|
||||
})
|
||||
},
|
||||
async submitData () {
|
||||
var uploadData = this.showResults
|
||||
let uploadData = this.showResults
|
||||
.filter( d => { return d.aboveThreshold && d.isSearched && !d.isDeleted })
|
||||
.map( r => { return {"top": r.top, "left": r.left, "bottom": r.bottom, "right": r.right, "label": r.label}})
|
||||
this.uploadUid = await this.uploadData(this.imageView.src.split(',')[1],uploadData,this.uploadUid)
|
||||
@@ -621,50 +611,28 @@
|
||||
if (li >= numBoxes) li -= numBoxes
|
||||
return li
|
||||
}
|
||||
let boxCoords = this.box2cvs(this.showResults)
|
||||
let boxCoords = []
|
||||
this.resultData.detections.forEach(d => {
|
||||
let cvsBox = d.box.getBoxes('point',this.imageView,this.$refs.image_cvs)[1]
|
||||
cvsBox.clickable = d.aboveThreshold && d.isSearched && !d.isDeleted
|
||||
boxCoords.push(cvsBox)
|
||||
})
|
||||
const numBoxes = boxCoords.length
|
||||
let clickX = (e.offsetX - this.canvasOffset.x) / this.canvasZoom
|
||||
let clickY = (e.offsetY - this.canvasOffset.y) / this.canvasZoom
|
||||
let boxEnd = boxCoords.splice(0, this.selectedChip)
|
||||
boxCoords = boxCoords.concat(boxEnd)
|
||||
var findBox = boxCoords.findIndex( (r, i) => {
|
||||
const findBox = boxCoords.findIndex( (r, i) => {
|
||||
let di = loopIndex(i)
|
||||
if (di == this.selectedChip ) return false
|
||||
return r.cvsLeft <= clickX &&
|
||||
r.cvsRight >= clickX &&
|
||||
r.cvsTop <= clickY &&
|
||||
r.cvsBottom >= clickY &&
|
||||
this.resultData.detections[di].aboveThreshold &&
|
||||
this.resultData.detections[di].isSearched &&
|
||||
!this.resultData.detections[di].isDeleted
|
||||
return r.clickable &&
|
||||
r.left <= clickX &&
|
||||
r.right >= clickX &&
|
||||
r.top <= clickY &&
|
||||
r.bottom >= clickY
|
||||
})
|
||||
this.selectChip(findBox >= 0 ? this.resultData.detections[loopIndex(findBox)].resultIndex : this.selectedChip)
|
||||
},
|
||||
box2cvs(boxInput) {
|
||||
if (!boxInput || boxInput.length == 0) return []
|
||||
const boxList = boxInput.length ? boxInput : [boxInput]
|
||||
const imCanvas = this.$refs.image_cvs
|
||||
var imgWidth
|
||||
var imgHeight
|
||||
const imgAspect = this.imageView.width / this.imageView.height
|
||||
const rendAspect = imCanvas.width / imCanvas.height
|
||||
if (imgAspect >= rendAspect) {
|
||||
imgWidth = imCanvas.width
|
||||
imgHeight = imCanvas.width / imgAspect
|
||||
} else {
|
||||
imgWidth = imCanvas.height * imgAspect
|
||||
imgHeight = imCanvas.height
|
||||
}
|
||||
const cvsCoords = boxList.map( (d, i) => {
|
||||
return {
|
||||
"cvsLeft": (imCanvas.width - imgWidth) / 2 + d.left * imgWidth,
|
||||
"cvsRight": (imCanvas.width - imgWidth) / 2 + d.right * imgWidth,
|
||||
"cvsTop": (imCanvas.height - imgHeight) / 2 + d.top * imgHeight,
|
||||
"cvsBottom": (imCanvas.height - imgHeight) / 2 + d.bottom * imgHeight
|
||||
}
|
||||
})
|
||||
return cvsCoords
|
||||
},
|
||||
toggleSettings() {
|
||||
this.showDetectSettings = !this.showDetectSettings
|
||||
f7.utils.nextFrame(() => {
|
||||
@@ -672,13 +640,13 @@
|
||||
})
|
||||
},
|
||||
startMove() {
|
||||
this.canvasMoving = true
|
||||
canvasMoving = true
|
||||
},
|
||||
endMove() {
|
||||
this.canvasMoving = false
|
||||
canvasMoving = false
|
||||
},
|
||||
makeMove(event) {
|
||||
if (this.canvasMoving) {
|
||||
if (canvasMoving) {
|
||||
this.canvasOffset.x += event.movementX
|
||||
this.canvasOffset.y += event.movementY
|
||||
this.selectChip("redraw")
|
||||
@@ -704,11 +672,11 @@
|
||||
},
|
||||
zoomToSelected() {
|
||||
const imCanvas = this.$refs.image_cvs
|
||||
const boxCoords = this.box2cvs(this.resultData.detections[this.selectedChip])[0]
|
||||
const boxWidth = boxCoords.cvsRight - boxCoords.cvsLeft
|
||||
const boxHeight = boxCoords.cvsBottom - boxCoords.cvsTop
|
||||
const boxMidX = (boxCoords.cvsRight + boxCoords.cvsLeft ) / 2
|
||||
const boxMidY = (boxCoords.cvsBottom + boxCoords.cvsTop ) / 2
|
||||
const boxCoords = this.resultData.detections[this.selectedChip].box.getBoxes('point', this.imageView, imCanvas)
|
||||
const boxWidth = boxCoords[1].right - boxCoords[1].left
|
||||
const boxHeight = boxCoords[1].bottom - boxCoords[1].top
|
||||
const boxMidX = (boxCoords[1].right + boxCoords[1].left ) / 2
|
||||
const boxMidY = (boxCoords[1].bottom + boxCoords[1].top ) / 2
|
||||
const zoomFactor = Math.min(imCanvas.width / boxWidth * .9, imCanvas.height / boxHeight * .9, 8)
|
||||
this.canvasZoom = zoomFactor
|
||||
this.canvasOffset.x = -(boxMidX * zoomFactor) + imCanvas.width / 2
|
||||
|
||||
@@ -46,11 +46,11 @@ export default {
|
||||
let rawBoxes = []
|
||||
let rawScores = []
|
||||
|
||||
for (var i = 0; i < rawRes.length; i++) {
|
||||
var getScores = rawRes[i].slice(4)
|
||||
for (let i = 0; i < rawRes.length; i++) {
|
||||
const getScores = rawRes[i].slice(4)
|
||||
if (getScores.every( s => s < .05)) { continue }
|
||||
var getBox = rawRes[i].slice(0,4)
|
||||
var boxCalc = [
|
||||
const getBox = rawRes[i].slice(0,4)
|
||||
const boxCalc = [
|
||||
(getBox[0] - (getBox[2] / 2)) / modelWidth,
|
||||
(getBox[1] - (getBox[3] / 2)) / modelHeight,
|
||||
(getBox[0] + (getBox[2] / 2)) / modelWidth,
|
||||
@@ -69,7 +69,7 @@ export default {
|
||||
let boxes_data = []
|
||||
let scores_data = []
|
||||
let classes_data = []
|
||||
for (var c = 0; c < outputSize - 4; c++) {
|
||||
for (let c = 0; c < outputSize - 4; c++) {
|
||||
structureScores = rawScores.map(x => x[c])
|
||||
tScores = tf.tensor1d(structureScores)
|
||||
resBoxes = await tf.image.nonMaxSuppressionAsync(tBoxes,tScores,10,0.5,.05)
|
||||
@@ -77,7 +77,7 @@ export default {
|
||||
tf.dispose(resBoxes)
|
||||
if (validBoxes) {
|
||||
boxes_data.push(...rawBoxes.filter( (_, idx) => validBoxes.includes(idx)))
|
||||
var outputScores = structureScores.filter( (_, idx) => validBoxes.includes(idx))
|
||||
let outputScores = structureScores.filter( (_, idx) => validBoxes.includes(idx))
|
||||
scores_data.push(...outputScores)
|
||||
classes_data.push(...outputScores.fill(c))
|
||||
}
|
||||
@@ -88,11 +88,11 @@ export default {
|
||||
tf.dispose(tScores)
|
||||
tf.dispose(tRes)
|
||||
const valid_detections_data = classes_data.length
|
||||
var output = {
|
||||
const output = {
|
||||
detections: []
|
||||
}
|
||||
for (var i =0; i < valid_detections_data; i++) {
|
||||
var [dLeft, dTop, dRight, dBottom] = boxes_data[i]
|
||||
for (let i =0; i < valid_detections_data; i++) {
|
||||
const [dLeft, dTop, dRight, dBottom] = boxes_data[i]
|
||||
output.detections.push({
|
||||
"top": dTop,
|
||||
"left": dLeft,
|
||||
@@ -110,9 +110,9 @@ export default {
|
||||
return output || { detections: [] }
|
||||
},
|
||||
getRemoteLabels() {
|
||||
var self = this
|
||||
var modelURL = `http://${this.serverSettings.address}:${this.serverSettings.port}/detectors`
|
||||
var xhr = new XMLHttpRequest()
|
||||
let self = this
|
||||
const modelURL = `http://${this.serverSettings.address}:${this.serverSettings.port}/detectors`
|
||||
let xhr = new XMLHttpRequest()
|
||||
xhr.open("GET", modelURL)
|
||||
xhr.setRequestHeader('Content-Type', 'application/json')
|
||||
xhr.timeout = 10000
|
||||
@@ -124,8 +124,8 @@ export default {
|
||||
f7.dialog.alert(`ALVINN has encountered an error: ${errorResponse.error}`)
|
||||
return
|
||||
}
|
||||
var detectors = JSON.parse(xhr.response).detectors
|
||||
var findLabel = detectors
|
||||
const detectors = JSON.parse(xhr.response).detectors
|
||||
let findLabel = detectors
|
||||
.find( d => { return d.name == self.detectorName } )?.labels
|
||||
.filter( l => { return l != "" } ).sort()
|
||||
.map( l => { return {'name': l, 'detect': true} } )
|
||||
@@ -139,9 +139,9 @@ export default {
|
||||
xhr.send()
|
||||
},
|
||||
remoteDetect() {
|
||||
var self = this
|
||||
var modelURL = `http://${this.serverSettings.address}:${this.serverSettings.port}/detect`
|
||||
var xhr = new XMLHttpRequest()
|
||||
let self = this
|
||||
const modelURL = `http://${this.serverSettings.address}:${this.serverSettings.port}/detect`
|
||||
let xhr = new XMLHttpRequest()
|
||||
xhr.open("POST", modelURL)
|
||||
xhr.timeout = 10000
|
||||
xhr.ontimeout = this.remoteTimeout
|
||||
@@ -158,7 +158,7 @@ export default {
|
||||
self.uploadDirty = true
|
||||
}
|
||||
|
||||
var doodsData = {
|
||||
const doodsData = {
|
||||
"detector_name": this.detectorName,
|
||||
"detect": {
|
||||
"*": 1
|
||||
@@ -172,8 +172,8 @@ export default {
|
||||
this.detecting = false
|
||||
f7.dialog.alert('No connection to remote ALVINN instance. Please check app settings.')
|
||||
},
|
||||
async videoFrameDetect (vidData) {
|
||||
await this.loadModel(this.miniLocation)
|
||||
async videoFrameDetect (vidData, miniModel) {
|
||||
await this.loadModel(miniModel)
|
||||
const [modelWidth, modelHeight] = model.inputs[0].shape.slice(1, 3)
|
||||
const imCanvas = this.$refs.image_cvs
|
||||
const imageCtx = imCanvas.getContext("2d")
|
||||
@@ -182,8 +182,7 @@ export default {
|
||||
imCanvas.width = imCanvas.clientWidth
|
||||
imCanvas.height = imCanvas.clientHeight
|
||||
imageCtx.clearRect(0,0,imCanvas.width,imCanvas.height)
|
||||
var imgWidth
|
||||
var imgHeight
|
||||
let imgWidth, imgHeight
|
||||
const imgAspect = vidData.width / vidData.height
|
||||
const rendAspect = imCanvas.width / imCanvas.height
|
||||
if (imgAspect >= rendAspect) {
|
||||
@@ -204,7 +203,7 @@ export default {
|
||||
|
||||
let rawCoords = []
|
||||
if (rawRes) {
|
||||
for (var i = 0; i < rawRes.length; i++) {
|
||||
for (let i = 0; i < rawRes.length; i++) {
|
||||
let getScores = rawRes[i].slice(4)
|
||||
if (getScores.some( s => s > .5)) {
|
||||
let foundTarget = rawRes[i].slice(0,2)
|
||||
@@ -214,7 +213,7 @@ export default {
|
||||
}
|
||||
|
||||
imageCtx.clearRect(0,0,imCanvas.width,imCanvas.height)
|
||||
for (var coord of rawCoords) {
|
||||
for (let coord of rawCoords) {
|
||||
console.log(`x: ${coord[0]}, y: ${coord[1]}`)
|
||||
let pointX = (imCanvas.width - imgWidth) / 2 + (coord[0] / modelWidth) * imgWidth -5
|
||||
let pointY = (imCanvas.height - imgHeight) / 2 + (coord[1] / modelHeight) * imgHeight -5
|
||||
|
||||
@@ -91,7 +91,7 @@
|
||||
computed: {
|
||||
otherIp () {
|
||||
let filteredIps = {}
|
||||
for (var oldIp in this.serverSettings.previous) {
|
||||
for (let oldIp in this.serverSettings.previous) {
|
||||
if (oldIp != this.serverSettings.address) {
|
||||
filteredIps[oldIp] = this.serverSettings.previous[oldIp]
|
||||
}
|
||||
@@ -109,12 +109,12 @@
|
||||
}
|
||||
},
|
||||
created () {
|
||||
var loadServerSettings = localStorage.getItem('serverSettings')
|
||||
const loadServerSettings = localStorage.getItem('serverSettings')
|
||||
if (loadServerSettings) this.serverSettings = JSON.parse(loadServerSettings)
|
||||
if (!this.serverSettings.previous) this.serverSettings.previous = {}
|
||||
var loadThemeSettings = localStorage.getItem('themeSettings')
|
||||
const loadThemeSettings = localStorage.getItem('themeSettings')
|
||||
if (loadThemeSettings) this.themeSettings = JSON.parse(loadThemeSettings)
|
||||
var loadOtherSettings = localStorage.getItem('otherSettings')
|
||||
const loadOtherSettings = localStorage.getItem('otherSettings')
|
||||
if (loadOtherSettings) this.otherSettings = JSON.parse(loadOtherSettings)
|
||||
},
|
||||
methods: {
|
||||
@@ -136,7 +136,7 @@
|
||||
)
|
||||
saveSetting.then(
|
||||
() => {
|
||||
var toast = f7.toast.create({
|
||||
const toast = f7.toast.create({
|
||||
text: 'Settings saved',
|
||||
closeTimeout: 2000
|
||||
})
|
||||
@@ -144,7 +144,7 @@
|
||||
this.isDirty = false;
|
||||
},
|
||||
() => {
|
||||
var toast = f7.toast.create({
|
||||
const toast = f7.toast.create({
|
||||
text: 'ERROR: No settings saved',
|
||||
closeTimeout: 2000
|
||||
})
|
||||
|
||||
@@ -63,7 +63,7 @@
|
||||
return store()
|
||||
},
|
||||
created () {
|
||||
var loadOtherSettings = localStorage.getItem('otherSettings')
|
||||
const loadOtherSettings = localStorage.getItem('otherSettings')
|
||||
if (loadOtherSettings) this.otherSettings = JSON.parse(loadOtherSettings)
|
||||
fetch(`${this.isCordova ? 'https://localhost' : '.'}/models/thorax/descript.json`)
|
||||
.then((mod) => { return mod.json() })
|
||||
|
||||
@@ -5,8 +5,8 @@ export default {
|
||||
newUid (length) {
|
||||
const uidLength = length || 16
|
||||
const uidChars = 'abcdefghijklmnopqrstuvwxyz0123456789'
|
||||
var uid = []
|
||||
for (var i = 0; i < uidLength; i++) {
|
||||
let uid = []
|
||||
for (let i = 0; i < uidLength; i++) {
|
||||
uid.push(uidChars.charAt(Math.floor(Math.random() * ((i < 4) ? 26 : 36))))
|
||||
}
|
||||
return uid.join('')
|
||||
@@ -14,24 +14,23 @@ export default {
|
||||
uploadData (imagePayload, classPayload, prevUid) {
|
||||
let uploadImage = new Promise (resolve => {
|
||||
const dataUid = prevUid || this.newUid(16)
|
||||
var byteChars = window.atob(imagePayload)
|
||||
var byteArrays = []
|
||||
var len = byteChars.length
|
||||
let byteChars = window.atob(imagePayload)
|
||||
let byteArrays = []
|
||||
|
||||
for (var offset = 0; offset < len; offset += 1024) {
|
||||
var slice = byteChars.slice(offset, offset + 1024)
|
||||
var byteNumbers = new Array(slice.length)
|
||||
for (var i = 0; i < slice.length; i++) {
|
||||
for (let offset = 0; offset < byteChars.length; offset += 1024) {
|
||||
let slice = byteChars.slice(offset, offset + 1024)
|
||||
let byteNumbers = new Array(slice.length)
|
||||
for (let i = 0; i < slice.length; i++) {
|
||||
byteNumbers[i] = slice.charCodeAt(i)
|
||||
}
|
||||
|
||||
var byteArray = new Uint8Array(byteNumbers)
|
||||
let byteArray = new Uint8Array(byteNumbers)
|
||||
byteArrays.push(byteArray)
|
||||
}
|
||||
var imageBlob = new Blob(byteArrays, {type: 'image/jpeg'})
|
||||
const imageBlob = new Blob(byteArrays, {type: 'image/jpeg'})
|
||||
|
||||
var xhrJpg = new XMLHttpRequest()
|
||||
var uploadUrl = `https://nextcloud.azgeorgis.net/public.php/webdav/${dataUid}.jpeg`
|
||||
let xhrJpg = new XMLHttpRequest()
|
||||
let uploadUrl = `https://nextcloud.azgeorgis.net/public.php/webdav/${dataUid}.jpeg`
|
||||
xhrJpg.open("PUT", uploadUrl)
|
||||
xhrJpg.setRequestHeader('Content-Type', 'image/jpeg')
|
||||
xhrJpg.setRequestHeader('X-Method-Override', 'PUT')
|
||||
@@ -39,8 +38,8 @@ export default {
|
||||
xhrJpg.setRequestHeader("Authorization", "Basic " + btoa("LKBm3H6JdSaywyg:"))
|
||||
xhrJpg.send(imageBlob)
|
||||
|
||||
var xhrTxt = new XMLHttpRequest()
|
||||
var uploadUrl = `https://nextcloud.azgeorgis.net/public.php/webdav/${dataUid}.txt`
|
||||
let xhrTxt = new XMLHttpRequest()
|
||||
uploadUrl = `https://nextcloud.azgeorgis.net/public.php/webdav/${dataUid}.txt`
|
||||
xhrTxt.open("PUT", uploadUrl)
|
||||
xhrTxt.setRequestHeader('Content-Type', 'text/plain')
|
||||
xhrTxt.setRequestHeader('X-Method-Override', 'PUT')
|
||||
@@ -51,7 +50,7 @@ export default {
|
||||
resolve(dataUid)
|
||||
})
|
||||
return uploadImage.then((newUid) => {
|
||||
var toast = f7.toast.create({
|
||||
const toast = f7.toast.create({
|
||||
text: 'Detections Uploaded: thank you.',
|
||||
closeTimeout: 2000
|
||||
})
|
||||
|
||||
@@ -25,7 +25,6 @@ export default {
|
||||
moveTouch(event) {
|
||||
switch (event.touches.length) {
|
||||
case 1:
|
||||
console.log(event)
|
||||
this.canvasOffset.x += event.touches[0].clientX - this.touchPrevious.x
|
||||
this.canvasOffset.y += event.touches[0].clientY - this.touchPrevious.y
|
||||
this.touchPrevious = {x: event.touches[0].clientX, y: event.touches[0].clientY}
|
||||
|
||||
Reference in New Issue
Block a user