Last active
July 20, 2021 03:43
-
-
Save iso2022jp/6da2133a96a90a06801f27b660292542 to your computer and use it in GitHub Desktop.
BodyPix を getUserMedia に注入してみる
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
'use strict' | |
;(async () => { | |
const handleSelectImage = (input, select) => { | |
input.addEventListener('change', e => { | |
const files = [...input.files] | |
const image = files.filter(f => f.type.startsWith('image/')) | |
if (image.length) { | |
const file = image[0] | |
e.preventDefault() | |
select(file) | |
input.value = '' | |
} | |
}) | |
} | |
const getImageItem = transfer => { | |
const items = [...transfer.items] | |
const image = items.filter(i => i.type.startsWith('image/')) | |
return image.length > 0 ? image[0] : null | |
} | |
const handleDropImage = (scope, condition, drag, drop) => { | |
scope.addEventListener('dragenter', e => { | |
if (condition()) { | |
e.preventDefault() | |
e.stopPropagation() | |
drag(true) | |
} | |
}) | |
scope.addEventListener('dragleave', e => { | |
if (condition()) { | |
e.preventDefault() | |
e.stopPropagation() | |
drag(false) | |
} | |
}) | |
scope.addEventListener('dragover', e => { | |
if (condition()) { | |
e.preventDefault() | |
e.stopPropagation() | |
e.dataTransfer.effectAllowed = 'copy' | |
e.dataTransfer.dropEffect = getImageItem(e.dataTransfer) ? 'copy' : 'none' | |
} | |
}) | |
scope.addEventListener('drop', e => { | |
if (condition()) { | |
e.preventDefault() | |
e.stopPropagation() | |
const item = getImageItem(e.dataTransfer) | |
if (item) { | |
drag(false) | |
drop(item.getAsFile()) | |
} | |
} | |
}) | |
} | |
const handlePasteImage = (condition, paste) => { | |
document.addEventListener('paste', e => { | |
if (condition()) { | |
const item = getImageItem(e.clipboardData) | |
if (item) { | |
paste(item.getAsFile()) | |
} | |
} | |
}) | |
} | |
const movable = (target, grip) => { | |
let state = { | |
move: false, | |
} | |
grip.addEventListener('mousedown', e => { | |
e.stopPropagation() | |
const bounds = target.getBoundingClientRect() | |
const dx = bounds.left - e.clientX | |
const dy = bounds.top - e.clientY | |
state = { | |
move: true, | |
dx, | |
dy, | |
} | |
e.preventDefault() | |
}) | |
grip.addEventListener('mouseup', e => { | |
e.stopPropagation() | |
state = { | |
move: false, | |
} | |
e.preventDefault() | |
}) | |
grip.addEventListener('mousemove', e => { | |
e.stopPropagation() | |
if (!state.move) { | |
return | |
} | |
const x = e.clientX + state.dx | |
const y = e.clientY + state.dy | |
target.style.setProperty('left', x + 'px', 'important') | |
target.style.setProperty('top', y + 'px', 'important') | |
target.style.setProperty('right', 'auto', 'important') | |
target.style.setProperty('bottom', 'auto', 'important') | |
e.preventDefault() | |
}) | |
grip.addEventListener('pointerdown', e => { | |
e.target.setPointerCapture?.(e.pointerId) | |
}, {passive: true, capture: true}) | |
grip.addEventListener('pointerup', e => { | |
e.target.releasePointerCapture?.(e.pointerId) | |
}, {passive: true, capture: true}) | |
} | |
// | |
const loadBodyPix = async () => { | |
// https://github.com/tensorflow/tfjs-models/tree/master/body-pix | |
const injectScript = (url, detector, initializer = null) => { | |
if (detector?.()) { | |
console.info(`bodypix-injector: {url} loaded.`) | |
return Promise.resolve() | |
} | |
return new Promise((resolve, reject) => { | |
const script = document.createElement('script') | |
script.addEventListener('load', e => resolve(script)) | |
script.addEventListener('error', e => reject(script)) | |
// script.async = true | |
initializer?.(script) | |
document.head.appendChild(script) | |
script.src = url | |
}) | |
} | |
await injectScript('https://cdn.jsdelivr.net/npm/@tensorflow/[email protected]', () => window.tf) | |
await injectScript('https://cdn.jsdelivr.net/npm/@tensorflow-models/[email protected]', () => window.bodyPix) | |
const net = await bodyPix.load({ | |
// architecture: 'MobileNetV1', // ResNet50 | |
// outputStride: 16, | |
// multiplier: 0.75, | |
// quantBytes: 2 | |
}); | |
console.info('bodypix-injector: BodyPix model loaded.') | |
return net | |
} | |
const createControlPanel = selectImageFile => { | |
const render = () => { | |
return ` | |
<style> | |
@import 'https://cdn.jsdelivr.net/npm/[email protected]/dist/css/bootstrap.min.css'; | |
.bodypix-injector { | |
font-family: system-ui, -apple-system, "Segoe UI", Roboto, "Helvetica Neue", Arial, "Noto Sans", "Liberation Sans", sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol", "Noto Color Emoji"; | |
font-size: 1rem; | |
font-weight: 400; | |
line-height: 1.5; | |
color: #212529; | |
background-color: #fff; | |
-webkit-text-size-adjust: 100%; | |
-webkit-tap-highlight-color: transparent | |
} | |
.form-range { | |
margin-top: .375rem; | |
margin-bottom: .375rem; | |
} | |
.form-control-color { | |
border: 0; | |
} | |
.dropping { | |
2px solid blue; | |
} | |
.dropping * { | |
pointer-events: none; | |
} | |
</style> | |
<aside class="bodypix-injector"> | |
<a href="#modeless" data-toggle="modeless" title="Configure BodyPix" class="btn btn-outline-primary"> | |
<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" fill="currentColor" class="bi bi-person-lines-fill" viewBox="0 0 16 16"> | |
<path d="M6 8a3 3 0 1 0 0-6 3 3 0 0 0 0 6zm-5 6s-1 0-1-1 1-4 6-4 6 3 6 4-1 1-1 1H1zM11 3.5a.5.5 0 0 1 .5-.5h4a.5.5 0 0 1 0 1h-4a.5.5 0 0 1-.5-.5zm.5 2.5a.5.5 0 0 0 0 1h4a.5.5 0 0 0 0-1h-4zm2 3a.5.5 0 0 0 0 1h2a.5.5 0 0 0 0-1h-2zm0 3a.5.5 0 0 0 0 1h2a.5.5 0 0 0 0-1h-2z"/> | |
</svg> | |
</a> | |
<div id="modeless" class="position-fixed d-none" role="dialog" style="width: 500px; left: 1rem; bottom: 3rem"> | |
<div class="modal-dialog modal-lg" style="margin: 0"> | |
<div class="modal-content"> | |
<div class="modal-header"> | |
<h3>BodyPix injector</h3> | |
<button type="button" data-dismiss="modeless" class="btn-close" aria-label="Close"></button> | |
</div> | |
<div class="modal-body"> | |
<form id="configuration" onsubmit="return false"> | |
<fieldset> | |
<div class="row"> | |
<h4 class="col-4 fw-normal">Effect</h4> | |
<div class="col-8"> | |
<div class="form-check form-check-inline"> | |
<input class="form-check-input" type="radio" name="effect" id="effect-bokeh" value="bokeh" checked> | |
<label class="form-check-label" for="effect-bokeh">Bokeh</label> | |
</div> | |
<div class="form-check form-check-inline"> | |
<input class="form-check-input" type="radio" name="effect" id="effect-mask" value="mask"> | |
<label class="form-check-label" for="effect-mask">Image</label> | |
</div> | |
<div class="form-check form-check-inline"> | |
<input class="form-check-input" type="radio" name="effect" id="effect-off" value="off"> | |
<label class="form-check-label" for="effect-off">Off</label> | |
</div> | |
</div> | |
</div> | |
</fieldset> | |
<hr> | |
<fieldset> | |
<legend>Bokeh effect</legend> | |
<div class="row"> | |
<label class="col-4 col-form-label" for="bokeh-edge-blur">Edge blur</label> | |
<div class="col-8"> | |
<input type="range" class="form-range" id="bokeh-edge-blur" min="1" max="20" value="3" placeholder="Edge blur"> | |
</div> | |
</div> | |
<div class="row"> | |
<label class="col-4 col-form-label" for="bodypix-bokeh-injector-bokeh-background-blur">Background blur</label> | |
<div class="col-8"> | |
<input type="range" class="form-range" id="bokeh-background-blur" min="0" max="20" value="3" placeholder="Background blur"> | |
</div> | |
</div> | |
</fieldset> | |
<hr> | |
<fieldset> | |
<legend>Image effect</legend> | |
<div class="row"> | |
<label class="col-4 col-form-label" for="image-background-image-picker">Background image</label> | |
<div class="col-8"> | |
<div class="position-relative d-inline-block align-middle form-control form-control-color"> | |
<img id="image-background-image" class="position-absolute top-50 start-50 translate-middle border rounded" style="max-width: 2.25rem; max-height: 2.25rem" alt="" title="Current image"> | |
</div> | |
<input type="file" accept="image/*" class="d-none form-control" id="image-background-image-picker" placeholder="Background image"> | |
<button class="btn btn-sm btn-outline-secondary" type="button" id="pick-image">Select</button> | |
<button class="btn btn-sm btn-outline-secondary" type="button" id="clear-image">Clear</button> | |
</div> | |
</div> | |
<div class="row"> | |
<label class="col-4 col-form-label" for="image-background-color">Background color</label> | |
<div class="col-8"> | |
<input type="color" class="form-control form-control-color" id="image-background-color" value="#e0e0e0" placeholder="Background color"> | |
</div> | |
</div> | |
<div class="row"> | |
<label class="col-4 col-form-label" for="image-edge-blur">Edge blur</label> | |
<div class="col-8"> | |
<input type="range" class="form-range" id="image-edge-blur" min="1" max="20" value="3" placeholder="Edge blur"> | |
</div> | |
</div> | |
<div class="row"> | |
<label class="col-4 col-form-label" for="bodypix-bokeh-injector-image-background-blur">Background blur</label> | |
<div class="col-8"> | |
<input type="range" class="form-range" id="image-background-blur" min="0" max="20" value="3" placeholder="Background blur"> | |
</div> | |
</div> | |
</fieldset> | |
<hr> | |
<fieldset> | |
<legend>Default camera</legend> | |
<div class="row"> | |
<label class="col-4 col-form-label" for="default-camera">Default camera</label> | |
<div class="col-8"> | |
<div class="input-group"> | |
<select class="form-select d-none" id="default-camera" placeholder="Default camera"> | |
<option value="">Auto</option> | |
</select> | |
<button class="btn btn-outline-secondary" type="button" id="query-devices">Select</button> | |
</div> | |
</div> | |
</div> | |
</fieldset> | |
<hr> | |
<details> | |
<summary>More tweaks</summary> | |
<fieldset> | |
<legend>Person segmentation</legend> | |
<div class="row"> | |
<label class="col-4 col-form-label" for="segmentation-internal-resolution">Internal resolution</label> | |
<div class="col-8"> | |
<input type="range" class="form-range" id="segmentation-internal-resolution" min="0.25" max="1.0" value="0.5" step="0.25" placeholder="Internal resolution"> | |
</div> | |
</div> | |
<div class="row"> | |
<label class="col-4 col-form-label" for="segmentation-segmentation-threshold">Segmentation threshold</label> | |
<div class="col-8"> | |
<input type="range" class="form-range" id="segmentation-segmentation-threshold" min="0.0" max="1.0" value="0.7" step="0.01" placeholder="Segmentation threshold"> | |
</div> | |
</div> | |
<div class="row"> | |
<label class="col-4 col-form-label" for="segmentation-max-detections">Max detections</label> | |
<div class="col-8"> | |
<input type="range" class="form-range" id="segmentation-max-detections" min="1" max="50" value="10" placeholder="Max detections"> | |
</div> | |
</div> | |
<div class="row"> | |
<label class="col-4 col-form-label" for="segmentation-score-threshold">Score threshold</label> | |
<div class="col-8"> | |
<input type="range" class="form-range" id="segmentation-score-threshold" min="0.0" max="1.0" value="0.3" step="0.01" placeholder="Score threshold"> | |
</div> | |
</div> | |
<div class="row"> | |
<label class="col-4 col-form-label" for="segmentation-nms-radius">Non-maximum suppression Radius</label> | |
<div class="col-8"> | |
<input type="range" class="form-range" id="segmentation-nms-radius" min="1" max="200" value="20" placeholder="Non-maximum suppression"> | |
</div> | |
</div> | |
</fieldset> | |
</details> | |
</form> | |
</div> | |
<div class="modal-footer"> | |
<a class="me-auto" href="https://blog.tensorflow.org/2019/11/updated-bodypix-2.html">BodyPix</a> | |
<!-- <button type="button" id="test" class="btn btn-outline-danger me-auto">Test</a>--> | |
<button type="reset" form="configuration" class="btn btn-outline-secondary">Reset</a> | |
<button type="button" data-dismiss="modeless" class="btn btn-outline-primary">Close</a> | |
</div> | |
</div> | |
</div> | |
</div> | |
</aside> | |
` | |
} | |
const panel = document.createElement('div') | |
panel.className = 'bodypix-injector' | |
panel.style.position = 'fixed' | |
panel.style.left = '16px' | |
panel.style.bottom = '16px' | |
const shadow = panel.attachShadow({mode: 'open'}) | |
shadow.innerHTML = render() | |
const enableModelessInvokers = () => { | |
const modeless = shadow.querySelector('#modeless') | |
shadow.querySelectorAll('[data-dismiss=modeless]').forEach(e => { | |
e.addEventListener('click', e => { | |
modeless.classList.add('d-none') | |
e.preventDefault() | |
}) | |
}) | |
shadow.querySelectorAll('[data-toggle=modeless]').forEach(e => { | |
e.addEventListener('click', e => { | |
modeless.classList.toggle('d-none') | |
e.preventDefault() | |
}) | |
}) | |
shadow.querySelectorAll('input[type=range]').forEach(e => { | |
e.title = e.value | |
e.addEventListener('input', e => { | |
e.currentTarget.title = e.currentTarget.value | |
}) | |
}) | |
} | |
const enableDeviceList = () => { | |
// device list | |
const deviceList = shadow.querySelector('#default-camera') | |
const deviceLister = shadow.querySelector('#query-devices') | |
const group = key => (groups, e) => { | |
const k = key(e) | |
return {...groups, [k]: [...(groups[k] || []), e]} | |
} | |
const listDevices = async () => { | |
const devices = await navigator.mediaDevices.enumerateDevices() | |
const videos = devices.filter(d => d.kind === 'videoinput') | |
if (videos.length === 0 || videos[0].deviceId === '') { | |
// query permission | |
const stream = await navigator.mediaDevices.getUserMedia({video: true}) | |
stream.getTracks().forEach(t => t.stop()) | |
return listDevices() | |
} | |
const el = (name, attrs = {}, content = null) => { | |
const e = document.createElement(name) | |
Object.entries(attrs).forEach(([name, value]) => e.setAttribute(name, value)) | |
if (content !== null) { | |
e.append(content) | |
} | |
return e | |
} | |
const groups = videos.reduce(group(d => d.groupId), {}) | |
const options = Object.entries(groups).map(([g, list]) => { | |
if (list.length > 1) { | |
return el('optgroup', {'data-group': g}, list.map(d => el('option', {value: d.deviceId}, d.label))) | |
} else { | |
return el('option', {'data-group': g, value: list[0].deviceId}, list[0].label) | |
} | |
}) | |
deviceList.innerHTML = '' | |
deviceList.append(el('option', {value: ''}, 'Auto'), ...options) | |
deviceList.classList.remove('d-none') | |
deviceLister.textContent = 'Reload' | |
} | |
deviceLister.addEventListener('click', e => { | |
listDevices() | |
}) | |
} | |
const enableImagePicker = () => { | |
const modeless = shadow.querySelector('#modeless') | |
const visible = () => !modeless.classList.contains('d-none') | |
const showDragging = active => { | |
modeless.classList[active ? 'add' : 'remove']('dropping') | |
} | |
const picker = shadow.querySelector('#image-background-image-picker') | |
// select button | |
shadow.querySelector('#pick-image').addEventListener('click', e => { | |
picker.click() | |
}) | |
// clear button | |
shadow.querySelector('#clear-image').addEventListener('click', e => { | |
selectImageFile(null) | |
}) | |
// support file selector | |
handleSelectImage(picker, selectImageFile) | |
// support file drop during dialog shown | |
handleDropImage(modeless, visible, showDragging, selectImageFile) | |
// support paste operation during dialog shown | |
handlePasteImage(visible, selectImageFile) | |
} | |
enableModelessInvokers() | |
enableDeviceList() | |
enableImagePicker() | |
const modeless = shadow.querySelector('#modeless') | |
movable(modeless, modeless.querySelector('.modal-header')) | |
document.body.append(panel) | |
return shadow | |
} | |
let currentBackgroundImageUrl = null | |
let currentBackgroundImage = null | |
const changeBackgroundImageFile = file => { | |
currentBackgroundImageUrl && URL.revokeObjectURL(currentBackgroundImageUrl) | |
currentBackgroundImageUrl = file ? URL.createObjectURL(file) : null | |
if (currentBackgroundImageUrl) { | |
const image = new Image() | |
image.crossOrigin = 'anonymous' | |
image.onload = e => { | |
currentBackgroundImage = image | |
} | |
image.src = currentBackgroundImageUrl | |
imageBackgroundImage.src = currentBackgroundImageUrl // preview | |
} else { | |
currentBackgroundImage = null | |
imageBackgroundImage.src = null // preview | |
} | |
} | |
const getBackgroundImage = () => { | |
return currentBackgroundImage | |
} | |
const panel = createControlPanel(changeBackgroundImageFile) | |
const effectBokeh = panel.querySelector('#effect-bokeh') | |
const effectMask = panel.querySelector('#effect-mask') | |
const effectOff = panel.querySelector('#effect-off') | |
const imageBackgroundImage = panel.querySelector('#image-background-image') | |
const imageBackgroundImagePicker = panel.querySelector('#image-background-image-picker') | |
const imageBackgroundColor = panel.querySelector('#image-background-color') | |
const imageEdgeBlur = panel.querySelector('#image-edge-blur') | |
const imageBackgroundBlur = panel.querySelector('#image-background-blur') | |
const bokehEdgeBlur = panel.querySelector('#bokeh-edge-blur') | |
const bokehBackgroundBlur = panel.querySelector('#bokeh-background-blur') | |
const segmentationInternalResolution = panel.querySelector('#segmentation-internal-resolution') | |
const segmentationSegmentationThreshold = panel.querySelector('#segmentation-segmentation-threshold') | |
const segmentationMaxDetections = panel.querySelector('#segmentation-max-detections') | |
const segmentationScoreThreshold = panel.querySelector('#segmentation-score-threshold') | |
const segmentationNmsRadius = panel.querySelector('#segmentation-nms-radius') | |
const defaultCamera = panel.querySelector('#default-camera') | |
// | |
// | |
// | |
const collectImageOptions = () => { | |
return { | |
edgeBlurAmount: +imageEdgeBlur.value, | |
backgroundBlurAmount: +imageBackgroundBlur.value, | |
} | |
} | |
const collectBokehOptions = () => { | |
return { | |
edgeBlurAmount: +bokehEdgeBlur.value, | |
backgroundBlurAmount: +bokehBackgroundBlur.value, | |
} | |
} | |
const collectSegmentationOptions = () => { | |
return { | |
internalResolution: +segmentationInternalResolution.value, | |
segmentationThreshold: +segmentationSegmentationThreshold.value, | |
maxDetections: +segmentationMaxDetections.value, | |
scoreThreshold: +segmentationScoreThreshold.value, | |
nmsRadius: +segmentationNmsRadius.value, | |
} | |
} | |
const offscreens = {} | |
const prepareOffscreen = (name, size) => { | |
const canvas = offscreens[name] || (offscreens[name] = document.createElement('canvas')) | |
canvas.width = size.width | |
canvas.height = size.height | |
return canvas | |
} | |
const blur = (name, image, amount) => { | |
const canvas = prepareOffscreen('name', image) | |
const g = canvas.getContext('2d') | |
g.save() | |
g.clearRect(0, 0, canvas.width, canvas.height) | |
g.filter = `blur(${amount}px)` | |
g.drawImage(image, 0, 0, canvas.width, canvas.height) | |
g.restore() | |
return canvas | |
} | |
const net = await loadBodyPix() | |
const copyFrame = async (source, destination) => { | |
const g = destination.getContext('2d') | |
g.save() | |
g.drawImage(source, 0, 0, destination.width, destination.height) | |
g.restore() | |
} | |
const bokehFrame = async (source, destination) => { | |
const segmentation = await net.segmentPerson(source, collectSegmentationOptions()) | |
const flipHorizontal = false | |
const options = collectBokehOptions() | |
bodyPix.drawBokehEffect(destination, source, segmentation, options.backgroundBlurAmount, options.edgeBlurAmount, flipHorizontal) | |
} | |
const imageFrame = async (source, destination) => { | |
const offscreen = prepareOffscreen('offscreen', destination) | |
const g = offscreen.getContext('2d') | |
g.save() | |
// 元の絵を先に描画(セグメンテーションとの時差防止) | |
g.drawImage(source, 0, 0) | |
const segmentation = await net.segmentPerson(source, collectSegmentationOptions()) | |
const flipHorizontal = false | |
const options = collectImageOptions() | |
const mask = bodyPix.toMask(segmentation, {r: 0, g: 0, b: 0, a: 255}, {r: 0, g: 0, b: 0, a: 0}) | |
const width = destination.width | |
const height = destination.height | |
// create blur mask | |
// mask を canvas に展開 | |
const maskCanvas = prepareOffscreen('mask', destination) | |
maskCanvas.getContext('2d').putImageData(mask, 0, 0) | |
// mask の境界をぼかして描画 | |
const clipCanvas = blur('blur', maskCanvas, options.edgeBlurAmount) | |
// 人物周辺以外を落とし | |
g.globalCompositeOperation = 'destination-in' | |
g.drawImage(clipCanvas, 0, 0) | |
// 背景をぼかして描画 | |
try { | |
g.globalCompositeOperation = 'destination-over' | |
g.filter = `blur(${options.backgroundBlurAmount}px)` | |
const image = getBackgroundImage() | |
if (image?.complete) { | |
g.drawImage(image, 0, 0, width, height) | |
} else { | |
g.fillStyle = imageBackgroundColor.value | |
g.fillRect(0, 0, width, height) | |
} | |
} catch { | |
// CORS ? | |
g.fillStyle = imageBackgroundColor.value | |
g.fillRect(0, 0, width, height) | |
} | |
g.restore() | |
// 転送 | |
destination.getContext('2d').drawImage(offscreen, 0, 0) | |
} | |
const effectFrame = async (source, destination) => { | |
if (effectOff.checked) { | |
await copyFrame(source, destination) | |
return | |
} | |
if (effectBokeh.checked) { | |
await bokehFrame(source, destination) | |
return | |
} | |
if (effectMask.checked) { | |
await imageFrame(source, destination) | |
return | |
} | |
// ? | |
await copyFrame(source, destination) | |
} | |
const createTrackProcessor = () => { | |
const panel = document.createElement('div') | |
panel.className = 'processor' | |
panel.style.position = 'fixed' | |
panel.style.left = '48px' | |
panel.style.bottom = '16px' | |
panel.innerHTML = ` | |
<div style="display: none"> | |
<canvas class="processor-input"></canvas> | |
<canvas class="processor-output"></canvas> | |
</div> | |
` | |
document.body.append(panel) | |
return panel | |
} | |
let activeTrack = null | |
const effectTrack = input => { | |
if (activeTrack) { | |
activeTrack.stop() | |
activeTrack = null | |
} | |
console.info('bodypix-injector: setup track: %o', input) | |
const panel = createTrackProcessor() | |
const framerate = input.getSettings().frameRate | |
const width = input.getSettings().width | |
const height = input.getSettings().height | |
const capture = new ImageCapture(input) | |
const inputCanvas = panel.querySelector('.processor-input') | |
inputCanvas.width = width | |
inputCanvas.height = height | |
const outputCanvas = panel.querySelector('.processor-output') | |
outputCanvas.width = width | |
outputCanvas.height = height | |
const inputContext = inputCanvas.getContext('bitmaprenderer') // 2d | |
const stream = outputCanvas.captureStream() // auto framerate | |
const output = stream.getVideoTracks()[0] | |
let timer = null | |
const dispose = () => { | |
timer && clearInterval(timer) | |
panel.remove() | |
} | |
let running = false | |
const processFrame = async () => { | |
if (input.readyState !== 'live') { | |
dispose() | |
return | |
} | |
if (output.readyState !== 'live') { | |
dispose() | |
return | |
} | |
if (input.muted) { | |
return | |
} | |
if (running) { | |
console.info('bodypix-injector: Waiting for previous frame completion, skipped.') | |
return | |
} | |
const started = Date.now() | |
try { | |
running = true | |
const bitmap = await capture.grabFrame() | |
inputContext.transferFromImageBitmap(bitmap) | |
await effectFrame(inputCanvas, outputCanvas) | |
running = false | |
console.debug('bodypix-injector: process frame in %o ms', Date.now() - started) | |
} catch (e) { | |
console.info('bodypix-injector: grabFrame rejected %o', e) | |
} | |
} | |
const resume = () => { | |
timer && clearInterval(timer) | |
timer = setInterval(processFrame, 1000 / framerate) | |
} | |
const pause = () => { | |
timer && clearInterval(timer) | |
timer = null | |
} | |
input.addEventListener('ended', e => { | |
console.warn('bodypix-injector: Track ended') | |
dispose() | |
}) | |
input.addEventListener('mute', e => { | |
console.warn('bodypix-injector: Track muted') | |
pause() | |
}) | |
input.addEventListener('unmute', e => { | |
console.warn('bodypix-injector: Track unmuted') | |
resume() | |
}) | |
output.addEventListener('ended', e => { | |
console.warn('bodypix-injector: Output track ended') | |
dispose() | |
}) | |
resume() | |
activeTrack = output | |
return output | |
} | |
const effectStream = input => { | |
// audio -> as-is | |
// video -> effect | |
const output = new MediaStream() | |
input.getVideoTracks().forEach(t => output.addTrack(effectTrack(t))) | |
input.getAudioTracks().forEach(t => output.addTrack(t)) | |
return output | |
} | |
const injectGetUserMedia = () => { | |
const gum = navigator.mediaDevices.getUserMedia | |
navigator.mediaDevices.getUserMedia = async constraints => { | |
console.info('bodypix-injector: navigator.mediaDevices.getUserMedia called with constraint %o.', constraints) | |
const video = constraints?.video | |
if (!video || video === false) { | |
// no video requested, do default | |
return await gum.call(navigator.mediaDevices, constraints) | |
} | |
// default camera changed | |
if (!video.deviceId && defaultCamera.value) { | |
console.info('bodypix-injector: Video device not specified, Set deviceId constraint to %o', defaultCamera.value) | |
if (video === true) { | |
constraints = {video: {deviceId: defaultCamera.value}} | |
} else { | |
video.deviceId = defaultCamera.value | |
} | |
} | |
const stream = await gum.call(navigator.mediaDevices, constraints) | |
return effectStream(stream) | |
} | |
} | |
injectGetUserMedia() | |
// panel.querySelector('#test').addEventListener('click', async e => { | |
// | |
// const stream = await navigator.mediaDevices.getUserMedia({ | |
// audio: true, | |
// video: true, | |
// }) | |
// | |
// }) | |
})(); |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
script 要素でホストする場合 | |
<script defer src="body-pix-injector.js"></script> | |
あらゆるサイトでテストしてみる場合 Developer Console でこの Gist を即時実行 | |
fetch('https://gist.githubusercontent.com/iso2022jp/6da2133a96a90a06801f27b660292542/raw/fc2f8636e694b4e9b079641f5409b7c1f5f467c8/body-pix-injector.js').then(r => r.text()).then(eval) |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment