Add worker video detection

Signed-off-by: Justin Georgi <justin.georgi@gmail.com>
This commit is contained in:
2024-07-24 12:00:48 -07:00
parent cd6cad9e73
commit 77b108af6c
3 changed files with 79 additions and 113 deletions

View File

@@ -23,6 +23,14 @@ self.onconnect = (e) => {
})
e.data.image.close()
break
case 'videoFrame':
videoFrame(e.data.image).then((franeDet) =>{
port.postMessage({succes: true, coords: franeDet.cds, modelWidth: franeDet.mW, modelHeight: franeDet.mH})
}).catch((err) => {
port.postMessage({error: true, message: err.message})
})
e.data.image.close()
break
default:
console.log('Worker message incoming:')
console.log(e)
@@ -207,29 +215,10 @@ function remoteTimeout () {
f7.dialog.alert('No connection to remote ALVINN instance. Please check app settings.')
}
async function videoFrameDetect (vidData) {
await this.loadModel(this.miniLocation)
async function videoFrame (vidData) {
const [modelWidth, modelHeight] = model.inputs[0].shape.slice(1, 3)
const imCanvas = this.$refs.image_cvs
const imageCtx = imCanvas.getContext("2d")
const target = this.$refs.target_image
await tf.nextFrame();
imCanvas.width = imCanvas.clientWidth
imCanvas.height = imCanvas.clientHeight
imageCtx.clearRect(0,0,imCanvas.width,imCanvas.height)
var imgWidth
var imgHeight
const imgAspect = vidData.width / vidData.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
}
while (this.videoAvailable) {
console.time('frame-process')
let rawCoords = []
try {
const input = tf.tidy(() => {
return tf.image.resizeBilinear(tf.browser.fromPixels(vidData), [modelWidth, modelHeight]).div(255.0).expandDims(0)
@@ -237,7 +226,6 @@ async function videoFrameDetect (vidData) {
const res = model.predict(input)
const rawRes = tf.transpose(res,[0,2,1]).arraySync()[0]
let rawCoords = []
if (rawRes) {
for (var i = 0; i < rawRes.length; i++) {
let getScores = rawRes[i].slice(4)
@@ -248,14 +236,6 @@ async function videoFrameDetect (vidData) {
}
}
imageCtx.clearRect(0,0,imCanvas.width,imCanvas.height)
for (var 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
imageCtx.globalAlpha = coord[2]
imageCtx.drawImage(target, pointX, pointY, 20, 20)
}
}
tf.dispose(input)
tf.dispose(res)
@@ -264,6 +244,5 @@ async function videoFrameDetect (vidData) {
console.log(e)
}
console.timeEnd('frame-process')
await tf.nextFrame();
}
return {cds: rawCoords, mW: modelWidth, mH: modelHeight}
}

View File

@@ -1,3 +1,5 @@
import { f7 } from 'framework7-vue'
export default {
methods: {
async openCamera(imContain) {
@@ -38,6 +40,51 @@ export default {
const tempCtx = tempCVS.getContext('2d')
tempCtx.drawImage(vidViewer, 0, 0)
this.getImage(tempCVS.toDataURL())
},
async videoFrameDetect (vidData) {
const vidWorker = new SharedWorker('../js/detect-worker.js',{type: 'module'})
vidWorker.port.onmessage = (eVid) => {
self = this
if (eVid.data.error) {
console.log(eVid.data.message)
f7.dialog.alert(`ALVINN AI model error: ${eVid.data.message}`)
} else if (this.videoAvailable) {
createImageBitmap(vidData).then(imVideoFrame => {
vidWorker.port.postMessage({call: 'videoFrame', image: imVideoFrame}, [imVideoFrame])
})
if (eVid.data.coords) {
imageCtx.clearRect(0,0,imCanvas.width,imCanvas.height)
for (var coord of eVid.data.coords) {
let pointX = (imCanvas.width - imgWidth) / 2 + (coord[0] / eVid.data.modelWidth) * imgWidth - 10
let pointY = (imCanvas.height - imgHeight) / 2 + (coord[1] / eVid.data.modelHeight) * imgHeight - 10
console.debug(`cx: ${pointX}, cy: ${pointY}`)
imageCtx.globalAlpha = coord[2]
imageCtx.drawImage(target, pointX, pointY, 20, 20)
}
}
}
}
vidWorker.port.postMessage({call: 'loadModel', weights: this.miniLocation, preload: true})
const imCanvas = this.$refs.image_cvs
const imageCtx = imCanvas.getContext("2d")
const target = this.$refs.target_image
var imgWidth
var imgHeight
f7.utils.nextFrame(() => {
imCanvas.width = imCanvas.clientWidth
imCanvas.height = imCanvas.clientHeight
imageCtx.clearRect(0,0,imCanvas.width,imCanvas.height)
const imgAspect = vidData.width / vidData.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
}
})
}
}
}

View File

@@ -172,65 +172,5 @@ 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)
const [modelWidth, modelHeight] = model.inputs[0].shape.slice(1, 3)
const imCanvas = this.$refs.image_cvs
const imageCtx = imCanvas.getContext("2d")
const target = this.$refs.target_image
await tf.nextFrame();
imCanvas.width = imCanvas.clientWidth
imCanvas.height = imCanvas.clientHeight
imageCtx.clearRect(0,0,imCanvas.width,imCanvas.height)
var imgWidth
var imgHeight
const imgAspect = vidData.width / vidData.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
}
while (this.videoAvailable) {
console.time('frame-process')
try {
const input = tf.tidy(() => {
return tf.image.resizeBilinear(tf.browser.fromPixels(vidData), [modelWidth, modelHeight]).div(255.0).expandDims(0)
})
const res = model.predict(input)
const rawRes = tf.transpose(res,[0,2,1]).arraySync()[0]
let rawCoords = []
if (rawRes) {
for (var 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)
foundTarget.push(Math.max(...getScores))
rawCoords.push(foundTarget)
}
}
imageCtx.clearRect(0,0,imCanvas.width,imCanvas.height)
for (var 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
imageCtx.globalAlpha = coord[2]
imageCtx.drawImage(target, pointX, pointY, 20, 20)
}
}
tf.dispose(input)
tf.dispose(res)
tf.dispose(rawRes)
} catch (e) {
console.log(e)
}
console.timeEnd('frame-process')
await tf.nextFrame();
}
}
}
}